{ "title" : "", "description" : "", "author" : "", "targetLoudness" : -18.0, "shouldApplyLoudnessNormalization" : true, "videoFormatFrameRate" : 30, "audioFormatSampleRate" : 44100, "width" : 1920.0, "height" : 1080.0, "version" : "3.0", "editRate" : 30, "authoringClientName" : { "name" : "Camtasia", "platform" : "Windows", "version" : "19.0" }, "sourceBin" : [ { "id" : 1, "src" : "C:\\Users\\Kees\\Downloads\\Webinar - HT-Mapping.mp4", "rect" : [0, 0, 1920, 1080], "lastMod" : "20220812T092059", "sourceTracks" : [ { "range" : [0, 32334063616], "type" : 0, "editRate" : 10000000, "trackRect" : [0, 0, 1920, 1080], "sampleRate" : "1000/33", "bitDepth" : 24, "numChannels" : 0, "integratedLUFS" : 100.0, "peakLevel" : -1.0, "metaData" : "" }, { "range" : [0, 32334063616], "type" : 2, "editRate" : 10000000, "trackRect" : [0, 0, 0, 0], "sampleRate" : 44100, "bitDepth" : 16, "numChannels" : 2, "integratedLUFS" : -25.7368684911907, "peakLevel" : 0.881147503852844, "metaData" : "" } ], "metadata" : { "timeAdded" : "20220812T095120.955426" } } ], "timeline" : { "id" : 2, "sceneTrack" : { "scenes" : [ { "duration" : 3233.4, "title" : "", "type" : "", "csml" : { "tracks" : [ { "trackIndex" : 0, "medias" : [ { "id" : 3, "_type" : "UnifiedMedia", "video" : { "id" : 4, "_type" : "VMFile", "src" : 1, "trackNumber" : 0, "attributes" : { "ident" : "Webinar - HT-Mapping" }, "effects" : [ ], "start" : 0, "duration" : 97002, "mediaStart" : 0, "mediaDuration" : 97002, "scalar" : 1, "animationTracks" : { } }, "audio" : { "id" : 5, "_type" : "AMFile", "src" : 1, "trackNumber" : 1, "attributes" : { "ident" : "", "gain" : 1.0, "mixToMono" : false }, "channelNumber" : "0,1", "effects" : [ ], "start" : 0, "duration" : 97002, "mediaStart" : 0, "mediaDuration" : 97002, "scalar" : 1, "animationTracks" : { } } , "start" : 0, "duration" : 97002, "mediaStart" : 0, "mediaDuration" : 97002, "scalar" : 1, "metadata" : { "clipSpeedAttribute" : false } } ] }, { "trackIndex" : 1, "medias" : [ { "id" : 6, "_type" : "Caption", "allowTrimOut" : 1, "maxMediaDuration" : 9.22337e+18, "parameters" : { "captionData" : { "type" : "caption", "keyframes" : [ { "endTime" : -9999999, "time" : -9999999, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 2131, "time" : 2131, "value" : { "text" : "Today we will have a Webinar that presents 4 topics.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 2253, "time" : 2253, "value" : { "text" : "As a fifth topic, your Questions as typed in the Q&A-box, will be addressed.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 2412, "time" : 2412, "value" : { "text" : "First, the basics of mapping Agro-EcoSystems will be presented, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 2553, "time" : 2553, "value" : { "text" : "after which I will show the strengths of using the dimension ‘time’ for mapping and monitoring Agro-EcoSystems.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 2798, "time" : 2798, "value" : { "text" : "Then, a series of maps derived from NDVI data-cubes will be presented,", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 2956, "time" : 2956, "value" : { "text" : "followed by more details on data sources, pre-processing, visualization, and interpretation. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 3186, "time" : 3186, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 3284, "time" : 3284, "value" : { "text" : "Section-1. Hyper-Temporal RS gives you a rich data-cube that can be interpreted", "textAttributes" : [{"name":"fontWeight","rangeEnd":11,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 3461, "time" : 3461, "value" : { "text" : "to provide information on what is growing where, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 3566, "time" : 3566, "value" : { "text" : "when it is growing, how it is performing, and when/how it is changing.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 3762, "time" : 3762, "value" : { "text" : "This information is essential: ...", "textAttributes" : [{"name":"fontWeight","rangeEnd":30,"rangeStart":0,"value":700,"valueType":"int"},{"name":"fontWeight","rangeEnd":34,"rangeStart":30,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 3870, "time" : 3870, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 4040, "time" : 4040, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 4241, "time" : 4241, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 4448, "time" : 4448, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 4663, "time" : 4663, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 4803, "time" : 4803, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 4964, "time" : 4964, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 5139, "time" : 5139, "value" : { "text" : "The Index", "textAttributes" : [{"name":"fontItalic","rangeEnd":9,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 5191, "time" : 5191, "value" : { "text" : "NDVI is the most widely used and possibly most successful ‘spectral difference’ index.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 5475, "time" : 5475, "value" : { "text" : "Which is the ratio of: the difference of the near infrared and red reflection, over their sum.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 5712, "time" : 5712, "value" : { "text" : "We see in the left figure that the green line, which represents vegetation ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 5886, "time" : 5886, "value" : { "text" : "[factually, it represents the amount of active chlorophyl present], ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 6002, "time" : 6002, "value" : { "text" : "absorbs most light in the visual red band and reflects most light in the \r\nNear Infra Red [NIR] band.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 6262, "time" : 6262, "value" : { "text" : "By comparing both bands, we can thus measure the amount of active chlorophyl.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 6444, "time" : 6444, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 6689, "time" : 6689, "value" : { "text" : "An NDVI data-cube", "textAttributes" : [{"name":"fontItalic","rangeEnd":17,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 6811, "time" : 6811, "value" : { "text" : "A data-cube can be presented as a movie.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 6917, "time" : 6917, "value" : { "text" : "The long-term median statistics (or: climatology) of actual (cleaned) NDVI-data are presented in the left figure. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 7195, "time" : 7195, "value" : { "text" : "The movie consists of 36 sequential images, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 7356, "time" : 7356, "value" : { "text" : "each representing a specific dekad, which is a 10-day period.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 7530, "time" : 7530, "value" : { "text" : "The figure displays a high and dense amount of vegetation in orange/red, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 7699, "time" : 7699, "value" : { "text" : "and bare-soil (no vegetation) as dark-blue/black. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 7806, "time" : 7806, "value" : { "text" : "In between light to dark-green colours are used. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 7938, "time" : 7938, "value" : { "text" : "The movie clearly shows spatial-temporal changes in vegetation phenology. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 8135, "time" : 8135, "value" : { "text" : "These are caused by climate differences, soil/terrain/landform differences, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 8333, "time" : 8333, "value" : { "text" : "land use differences, etc.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 8433, "time" : 8433, "value" : { "text" : "All differences are reflected through land cover (read: NDVI) differences.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 8637, "time" : 8637, "value" : { "text" : "Because of these differences, a specific land use, for instance: ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 8792, "time" : 8792, "value" : { "text" : "cropping of common wheat, can be mapped. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 8886, "time" : 8886, "value" : { "text" : "In the right figure, an example of such a map is presented. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 9060, "time" : 9060, "value" : { "text" : "The “common-wheat crop-intensity map” is produced on the basis of this movie, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 9205, "time" : 9205, "value" : { "text" : "on available agricultural statistics (by administrative areas), ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 9334, "time" : 9334, "value" : { "text" : "on field-observations (the Copernicus-Lucas data), ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 9449, "time" : 9449, "value" : { "text" : "and the EU-Corine map (based on a 30m TM-imagery interpretation). ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 9647, "time" : 9647, "value" : { "text" : "Thus, satellite imagery and tabular data can be fully integrated and transformed into maps ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 9894, "time" : 9894, "value" : { "text" : "containing information of importance.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 10001, "time" : 10001, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 10290, "time" : 10290, "value" : { "text" : "Let us recapture:", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 10364, "time" : 10364, "value" : { "text" : "Land Cover (NDVI) relates, amongst others, to:", "textAttributes" : [{"name":"fontItalic","rangeEnd":46,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 10496, "time" : 10496, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 11598, "time" : 11598, "value" : { "text" : "Since many of the above have a strong temporal behaviour, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 11733, "time" : 11733, "value" : { "text" : "also the NDVI varies over time. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 11835, "time" : 11835, "value" : { "text" : "Often, clear crop growing periods (seasonality) can be recognized ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 12018, "time" : 12018, "value" : { "text" : "through plotting NDVI over time; see the top-right figure, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 12179, "time" : 12179, "value" : { "text" : "which displays a specific NDVI-Profile.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 12316, "time" : 12316, "value" : { "text" : "Such NDVI-profiles may differ over years because crop-performance will differ ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 12529, "time" : 12529, "value" : { "text" : "due to the severity of adverse growing conditions (=perils).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 12698, "time" : 12698, "value" : { "text" : "The bottom-right figure displays such annual (seasonal) differences. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 12870, "time" : 12870, "value" : { "text" : "Extreme heat, combined with drought, caused severe crop-failure during the 2010 season; ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 13098, "time" : 13098, "value" : { "text" : "2003 however delivered a bumper crop. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 13227, "time" : 13227, "value" : { "text" : "If perils hit a relatively large agricultural area, it often leads to severe price hikes followed by unrest.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 13521, "time" : 13521, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 13786, "time" : 13786, "value" : { "text" : "Section-2 will zoom-in on differences in behaviour of individual pixels, ", "textAttributes" : [{"name":"fontWeight","rangeEnd":10,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 13954, "time" : 13954, "value" : { "text" : "but also of specific areas, over time.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 14083, "time" : 14083, "value" : { "text" : "Comparing NDVI-profiles between pixels, between areas, and between seasons (years) ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 14259, "time" : 14259, "value" : { "text" : "provides useful information on the actual land cover present, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 14392, "time" : 14392, "value" : { "text" : "of the variability of the vegetation performance, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 14500, "time" : 14500, "value" : { "text" : "and of gradual to abrupt changes in land cover.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 14631, "time" : 14631, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 14833, "time" : 14833, "value" : { "text" : "Visual inspection of NDVI time-series by pixel", "textAttributes" : [{"name":"fontItalic","rangeEnd":46,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 14978, "time" : 14978, "value" : { "text" : "The shown visual inspection of 3 individual pixels clearly shows that land cover of the 3 pixels truly differs.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 15229, "time" : 15229, "value" : { "text" : "The shown NDVI-Profiles (DN-values) cover the period 2000-2013", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 15418, "time" : 15418, "value" : { "text" : "(13 years of MODIS-Terra imagery).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 15534, "time" : 15534, "value" : { "text" : "- The red-line displays a continuously high NDVI-amount (DN-values) that indicates an evergreen situation. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 15808, "time" : 15808, "value" : { "text" : "Factually, the pixel is located in the Mau Forest National reserve of Kenya, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 15961, "time" : 15961, "value" : { "text" : "which consists predominantly of a dense forest complex which includes dense bamboo patches.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 16164, "time" : 16164, "value" : { "text" : "- The dark-green line displays clear seasonality with 2 peaks annually indicating 2 crop-growing seasons. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 16469, "time" : 16469, "value" : { "text" : "The respective landscape is dominated by arable fields with dispersed some trees", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 16672, "time" : 16672, "value" : { "text" : "- The light-green line displays a 1-season per year NDVI-profile, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 16823, "time" : 16823, "value" : { "text" : "with relatively low NDVI-values indicating sparse vegetation. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 16964, "time" : 16964, "value" : { "text" : "On the respective Google-Earth image, a bare-landscape is shown; ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 17105, "time" : 17105, "value" : { "text" : "likely, seasonal vegetation (short grasses) dominate the specific area.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 17308, "time" : 17308, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 17454, "time" : 17454, "value" : { "text" : "Each pixel will have its own ‘history’", "textAttributes" : [{"name":"fontItalic","rangeEnd":42,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 17747, "time" : 17747, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 18567, "time" : 18567, "value" : { "text" : "…and, each pixel will have its own ‘variability’", "textAttributes" : [{"name":"fontItalic","rangeEnd":54,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 18786, "time" : 18786, "value" : { "text" : "", "textAttributes" : [{"name":"fontWeight","rangeEnd":0,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 19838, "time" : 19838, "value" : { "text" : "Each area will have its own ‘variability’", "textAttributes" : [{"name":"fontItalic","rangeEnd":45,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 20059, "time" : 20059, "value" : { "text" : "Plotting on top of each-other all 13 annual NDVI-Profiles (DN-values), ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 20227, "time" : 20227, "value" : { "text" : "representing whole areas in and around the Masai Mara Park in Kenya, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 20376, "time" : 20376, "value" : { "text" : "displays how reliable the seasonality of the respective areas are. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 20582, "time" : 20582, "value" : { "text" : "Inspect: \r\n- If there are shifts in timing of seasons causing early or late season starts and/or season ends, and", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 20828, "time" : 20828, "value" : { "text" : "Inspect:\r\n- If complete absence of seasons do occur.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 20969, "time" : 20969, "value" : { "text" : "Where area 48, in general, is dryer and with less vegetation than area 35, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 21182, "time" : 21182, "value" : { "text" : "both areas only confirm that from April to June a clear ‘wet’ season occurs. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 21387, "time" : 21387, "value" : { "text" : "The remainder of the year can remain completely dry or can experience another early or late wet season (with every option in-between).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 21708, "time" : 21708, "value" : { "text" : "The shown unreliability in seasonality makes for this area arable agriculture rather difficult; ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 21959, "time" : 21959, "value" : { "text" : "good years will be fully mixed with years experiencing severe crop failures. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 22110, "time" : 22110, "value" : { "text" : "Semi-extensive animal husbandry with local trans-migration options is thus the best option to build ones livelihood. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 22371, "time" : 22371, "value" : { "text" : "The Masai thus got it right !", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 22464, "time" : 22464, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 22621, "time" : 22621, "value" : { "text" : "Monitoring an area through its NDVI data", "textAttributes" : [{"name":"fontItalic","rangeEnd":40,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 22744, "time" : 22744, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 23920, "time" : 23920, "value" : { "text" : "… The drop in cultivated area was caused by a major overhaul of the irrigation infrastructures upstream. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 24171, "time" : 24171, "value" : { "text" : "Thus, the shown ‘drop’ was only temporary.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 24312, "time" : 24312, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 24491, "time" : 24491, "value" : { "text" : "Monitoring an area through its NDVI data", "textAttributes" : [{"name":"fontItalic","rangeEnd":40,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 24633, "time" : 24633, "value" : { "text" : "Another example.\r\n", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 24696, "time" : 24696, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 25503, "time" : 25503, "value" : { "text" : "Section-3. The third section shows several mapping-examples, and reviews a series of aspects that relate to creating area-strata from NDVI data-cubes.", "textAttributes" : [{"name":"fontWeight","rangeEnd":10,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 25904, "time" : 25904, "value" : { "text" : "The mapping examples cover: ...", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 26000, "time" : 26000, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 26769, "time" : 26769, "value" : { "text" : "Pixels are Mixels", "textAttributes" : [{"name":"fontItalic","rangeEnd":17,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 26894, "time" : 26894, "value" : { "text" : "This example relates to wheat & barley systems in Andalusia, Spain.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 27098, "time" : 27098, "value" : { "text" : "When an NDVI data-cube is converted to a strata map, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 27230, "time" : 27230, "value" : { "text" : "and if only the key-strata with wheat and barley areas are extracted, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 27402, "time" : 27402, "value" : { "text" : "then we get the shown 7 NDVI-profiles. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 27529, "time" : 27529, "value" : { "text" : "It shows profiles of 5 wheat strata and of 2 barley strata. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 27728, "time" : 27728, "value" : { "text" : "Where barley profiles mainly differ due to the cropping intensity (22 versus 13% in average), ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 27957, "time" : 27957, "value" : { "text" : "the wheat strata differ both in wheat cropping intensities (29 to 47%), ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 28190, "time" : 28190, "value" : { "text" : "and in the presence of sunflower cropping (22 to 40%).", "textAttributes" : [{"name":"fontWeight","rangeEnd":4,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 28370, "time" : 28370, "value" : { "text" : "As an inset, a map of Andalusia, showing the overall wheat cropping intensity (area-fractions) is presented; ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 28608, "time" : 28608, "value" : { "text" : "it varies, if present, from 2 to 47%.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 28780, "time" : 28780, "value" : { "text" : "A key message of this slide is that preparing a ‘library’ of NDVI-profiles makes no sense. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 29047, "time" : 29047, "value" : { "text" : "Crop mixes vary, responses over time vary, etc. etc. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 29198, "time" : 29198, "value" : { "text" : "A profile will be very-very area-and-season specific and very specific in what mixes it represents. ", "textAttributes" : [{"name":"fontWeight","rangeEnd":85,"rangeStart":79,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 29424, "time" : 29424, "value" : { "text" : "We need thus skills to stratify a space-time cube and to relate each created strata with secondary data ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 29657, "time" : 29657, "value" : { "text" : "(or as a base to carry out fieldwork) ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 29742, "time" : 29742, "value" : { "text" : "in order to make a legend as required.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 29865, "time" : 29865, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 30004, "time" : 30004, "value" : { "text" : "Mapping at which resolution ?", "textAttributes" : [{"name":"fontItalic","rangeEnd":27,"rangeStart":0,"value":1,"valueType":"int"},{"name":"fontItalic","rangeEnd":28,"rangeStart":27,"value":1,"valueType":"int"},{"name":"fontItalic","rangeEnd":29,"rangeStart":28,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 30151, "time" : 30151, "value" : { "text" : "A general misconception is that use of higher spatial resolution data, produces better mapping opportunities. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 30359, "time" : 30359, "value" : { "text" : "However, please note that the sought-after strata must differentiate land cover & land use patterns ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 30578, "time" : 30578, "value" : { "text" : "in the space-time domain that relates best to differentiating different climate, soil, terrain, and landforms.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 30838, "time" : 30838, "value" : { "text" : "Differentiating dominant mixtures of Agro-EcoSystems happens to relate better to landscapes when using coarse resolution pixels.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 31126, "time" : 31126, "value" : { "text" : "‘Mixels’ at, for instance 100m resolution, will be less ‘generalised’ and will produce an increasing mix of land cover type combinations.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 31450, "time" : 31450, "value" : { "text" : "Note also that we mostly analyse NDVI-based data-cubes at country and regional scales. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 31685, "time" : 31685, "value" : { "text" : "Using a too fine spatial resolution of such huge areas will also defeat the effort to create generalizations at the required scale.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 32000, "time" : 32000, "value" : { "text" : "As example, for the Mekong area of Vietnam, two stratified maps are presented, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 32173, "time" : 32173, "value" : { "text" : "the left one at 1km resolution (using Spot-VGT) ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 32304, "time" : 32304, "value" : { "text" : "and the right one at 250m resolution (using MODIS-Terra.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 32475, "time" : 32475, "value" : { "text" : "The 1km map does not suffer from various inclusions (specific mixels) within mapped landscapes ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 32743, "time" : 32743, "value" : { "text" : "and provides a better generalization (as required). ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 32865, "time" : 32865, "value" : { "text" : "The right map shows a serious increase in specific mixels, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 32986, "time" : 32986, "value" : { "text" : "each with a different unique combination of land cover types. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 33115, "time" : 33115, "value" : { "text" : "As such, linear features like canals and roads, create many of these mixels. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 33277, "time" : 33277, "value" : { "text" : "They clearly interfere with the generalization effort envisaged.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 33436, "time" : 33436, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 33596, "time" : 33596, "value" : { "text" : "Mapping the gradient between a desert and continental humid areas", "textAttributes" : [{"name":"fontItalic","rangeEnd":65,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 33803, "time" : 33803, "value" : { "text" : "Stratifying, for instance an NDVI data-cube of Mongolia, creates a series of strata that follow a beautiful gradient: ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 34066, "time" : 34066, "value" : { "text" : "from desert and steppe to continental humid (severe cold winters and warm/hot summers).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 34267, "time" : 34267, "value" : { "text" : "Capturing such gradients is simply impossible without the use of an NDVI-based spatial-temporal data-cube.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 34562, "time" : 34562, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 34714, "time" : 34714, "value" : { "text" : "A down-hill gradient", "textAttributes" : [{"name":"fontItalic","rangeEnd":18,"rangeStart":0,"value":1,"valueType":"int"},{"name":"fontItalic","rangeEnd":20,"rangeStart":18,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 34821, "time" : 34821, "value" : { "text" : "Another nice example to map a gradient occurs in Java, Indonesia. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 34966, "time" : 34966, "value" : { "text" : "The white arrow points to an area East of Jakarta. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 35089, "time" : 35089, "value" : { "text" : "In the whole area cropping occurs during two seasons annually. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 35232, "time" : 35232, "value" : { "text" : "The timing of each season gets delayed when one moves to the North, or better: when one moves downhill towards the Java Sea. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 35518, "time" : 35518, "value" : { "text" : "This specific gradient is divided into 4 strata, but it could have been divided into more strata, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 35718, "time" : 35718, "value" : { "text" : "each with a ‘narrower’ temporal window regarding the start and end dates of each season.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 35910, "time" : 35910, "value" : { "text" : "Exactly, because of the existence of many criss-crossing gradients all over the globe, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 36075, "time" : 36075, "value" : { "text" : "it becomes impossible to specify “how many strata to differentiate”. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 36209, "time" : 36209, "value" : { "text" : "It is as difficult as to state that there just x-shades of grey (between white and black). ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 36438, "time" : 36438, "value" : { "text" : "Just consider that you aim to create a map (for monitoring) which must contain a certain level of ‘generalization’. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 36668, "time" : 36668, "value" : { "text" : "Only the expert (you) can decide on the required level (pending on your objectives).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 36874, "time" : 36874, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 37051, "time" : 37051, "value" : { "text" : "Base-Line Mapping", "textAttributes" : [{"name":"fontItalic","rangeEnd":17,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 37211, "time" : 37211, "value" : { "text" : "Base-line mapping, through an NDVI-based space-time data-cube, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 37380, "time" : 37380, "value" : { "text" : "at country or regional level,", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 37453, "time" : 37453, "value" : { "text" : "is meant to differentiate areas that are clearly different regarding land use and land cover.", "textAttributes" : [{"name":"fontWeight","rangeEnd":93,"rangeStart":74,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 37661, "time" : 37661, "value" : { "text" : "The created strata or map-units must be relatively homogeneous within regarding the land cover mixes present, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 37942, "time" : 37942, "value" : { "text" : "and rather heterogeneous between the strata. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 38038, "time" : 38038, "value" : { "text" : "A base-line map can be used, amongst others, for:", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 38175, "time" : 38175, "value" : { "text" : "- To adopt the strata as a first-level survey sample scheme (i.e. stratified sampling), ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 38360, "time" : 38360, "value" : { "text" : "e.g. for Area Frame Sampling (AFS) to collect data that relate to land cover (biodiversity) and/or to land use (agricultural statistics),", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 38713, "time" : 38713, "value" : { "text" : "- For developing a subsequent monitoring scheme to detect changes in land cover and land use,", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 38924, "time" : 38924, "value" : { "text" : "- For subsequent mapping individual strata at higher spatial scales through use of high resolution earth observation imagery,", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 39178, "time" : 39178, "value" : { "text" : "- To use the created NDVI-profiles by strata for subsequent monitoring the performance of those strata as required e.g. for early warning or for insurance schemes", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 39572, "time" : 39572, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 39734, "time" : 39734, "value" : { "text" : "Note that mapped ”forests” of Korea (top-right figure with the green lines) ", "textAttributes" : [{"name":"fontWeight","rangeEnd":5,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 39949, "time" : 39949, "value" : { "text" : "differentiates a clear gradient capturing differences in forest-densities (as average for a 1km pixel).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 40237, "time" : 40237, "value" : { "text" : "Note also that the ‘dent’ in the green NDVI-profiles reflects the fact that during the ‘long’ growing season of trees,", "textAttributes" : [{"name":"fontWeight","rangeEnd":5,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 40520, "time" : 40520, "value" : { "text" : "haze and clouds influenced (dented) the NDVI-readings. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 40649, "time" : 40649, "value" : { "text" : "The ‘dent’ is thus an artifact specific for the forests and the prevailing weather conditions.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 40830, "time" : 40830, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 41065, "time" : 41065, "value" : { "text" : "A second example of a base-line map concerns Pakistan.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 41246, "time" : 41246, "value" : { "text" : "Using 11 years of MODIS NDVI-imagery at 250m resolution,", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 41412, "time" : 41412, "value" : { "text" : "80 different clusters were created.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 41537, "time" : 41537, "value" : { "text" : "Subsequently, the NDVI-profiles of the 80 clusters were grouped into 13 major-groups. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 41766, "time" : 41766, "value" : { "text" : "The map shows that the colour scheme of the Agro-Ecosystems map of Pakistan follows the 13 colours used for plotting the NDVI-profiles (legend).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 42109, "time" : 42109, "value" : { "text" : "This map clearly reflects (i) an altitude gradient (up North),", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 42321, "time" : 42321, "value" : { "text" : "(ii) Irrigated areas versus Barani (rainfed) areas, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 42485, "time" : 42485, "value" : { "text" : "(iii) the performance of the two cropping seasons per year.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 42651, "time" : 42651, "value" : { "text" : "From ‘purple’ to ‘red’, to ‘blue’, the performance of the first season was best, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 42806, "time" : 42806, "value" : { "text" : "then both seasons performed equally, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 42864, "time" : 42864, "value" : { "text" : "and more South (downstream) the 2nd season performed best.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 43037, "time" : 43037, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 43220, "time" : 43220, "value" : { "text" : "The 3rd Base-Line map concerns a specific land use: ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 43379, "time" : 43379, "value" : { "text" : "rice-cropping in India and Pakistan.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 43475, "time" : 43475, "value" : { "text" : "The rice-systems are differentiated based on ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 43597, "time" : 43597, "value" : { "text" : "(i) the water management system, and ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 43688, "time" : 43688, "value" : { "text" : "(ii) differences in crop calendars practiced.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 43811, "time" : 43811, "value" : { "text" : "The latter differences were nicely captured through the respective area-specific NDVI-profiles.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 44023, "time" : 44023, "value" : { "text" : "A small selection of these profiles is shown; ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 44144, "time" : 44144, "value" : { "text" : "note specifically the ‘sudden dip’ in NDVI at the start of a growing season ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 44305, "time" : 44305, "value" : { "text" : "as caused by flooding of the concerned paddies.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 44447, "time" : 44447, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 44614, "time" : 44614, "value" : { "text" : "The last base-line mapping example concerns an effort by IWMI-staff, Colombo, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 44829, "time" : 44829, "value" : { "text" : "to map the global cropping areas of five major crops. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 44951, "time" : 44951, "value" : { "text" : "They are: wheat, rice, maize, barley and soybeans. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 45133, "time" : 45133, "value" : { "text" : "Also in this case, the authors made ample use of differentiating NDVI-profiles.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 45394, "time" : 45394, "value" : { "text" : "Using the link provided at the bottom of the map will play a video by ESA titled “Changing Lands”. ", "textAttributes" : [{"name":"fontWeight","rangeEnd":98,"rangeStart":84,"value":700,"valueType":"int"},{"name":"fontItalic","rangeEnd":98,"rangeStart":84,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 45666, "time" : 45666, "value" : { "text" : "This video further illustrates the strength to map actual land cover and to monitor actual land cover", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 45936, "time" : 45936, "value" : { "text" : "through the use of remotely sensed imagery ‘over time’.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 46080, "time" : 46080, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 54675, "time" : 54675, "value" : { "text" : "Topic-4. Our 4th topic will present a series of examples to illustrate: ", "textAttributes" : [{"name":"fontWeight","rangeEnd":9,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 54887, "time" : 54887, "value" : { "text" : "acquisition, pre-processing, visualization, analysis and interpretation, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 55074, "time" : 55074, "value" : { "text" : "of Hyper-Temporal NDVI-based data-cubes.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 55240, "time" : 55240, "value" : { "text" : "But first, let us list some typical characteristics of Hyper-Temporal (HT) NDVI-catalogues. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 55438, "time" : 55438, "value" : { "text" : "They are: ...", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 55482, "time" : 55482, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 57065, "time" : 57065, "value" : { "text" : "Maximum Value Composites (=MVCs)\r\n", "textAttributes" : [{"name":"fontItalic","rangeEnd":32,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 57310, "time" : 57310, "value" : { "text" : "MVC means: The ‘best’ pixel-specific, daily, NDVI-value of a given period is used ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 57570, "time" : 57570, "value" : { "text" : "to represent that specific period. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 57673, "time" : 57673, "value" : { "text" : "This follows the logic that haze and clouds ‘allways’ reduce the actual NDVI-value ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 57901, "time" : 57901, "value" : { "text" : "which leads to a lower ‘recorded’ NDVI-value. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 58011, "time" : 58011, "value" : { "text" : "As it happens, the highest recorded NDVI-value in a given period ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 58169, "time" : 58169, "value" : { "text" : "thus suffered least from haze and cloud contamination (of course assuming that during the given period,", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 58387, "time" : 58387, "value" : { "text" : "the NDVI remained relatively static).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 58485, "time" : 58485, "value" : { "text" : "Since during a 10-day period, the ‘greenness’ of vegetation is not supposed to fluctuate heavily, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 58718, "time" : 58718, "value" : { "text" : "use of a 10-day MVC-period is very common. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 58853, "time" : 58853, "value" : { "text" : "16-day and monthly composites already (partially) defeat the purpose of creating a Hyper-Temporal NDVI-based data-cube.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 59196, "time" : 59196, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 59413, "time" : 59413, "value" : { "text" : "The very best 10-daily MVC NDVI-series, as made available by the Copernicus Global Land Service (CGLS), are:", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 59751, "time" : 59751, "value" : { "text" : "For the period 1 Jan.’1999 – 30 June 2020: The 1km SPOT-VGT & Proba-V catalogue (version 3; final version!), and", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 60116, "time" : 60116, "value" : { "text" : "For the period 1 July 2020 – present: The 300m Sentinel-3 OLCI-based catalogue (version 2).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 60381, "time" : 60381, "value" : { "text" : "Both series are fully cross-calibrated (BRDF-adjusted), and carry a guarantee that they will be continued till at least 2040.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 60801, "time" : 60801, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 60973, "time" : 60973, "value" : { "text" : "Why a BRDF-adjusted NDVI ?", "textAttributes" : [{"name":"fontItalic","rangeEnd":24,"rangeStart":0,"value":1,"valueType":"int"},{"name":"fontItalic","rangeEnd":26,"rangeStart":24,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 61189, "time" : 61189, "value" : { "text" : "The overpass times of the various platforms used, differed and varied.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 61385, "time" : 61385, "value" : { "text" : "See for instance the ‘drifting’ of Proba-V in the figure on: “The evolution of local overpass time at nadir”.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 61650, "time" : 61650, "value" : { "text" : "In addition, the viewing angle of the overpassing satellite to the specific ‘pixel’ varies between image rows & columns, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 61934, "time" : 61934, "value" : { "text" : "and pending calendar dates, to make it worse, also the sun follows an annual North-South cycle.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 62139, "time" : 62139, "value" : { "text" : "This all impacts on absorption-reflection aspects of VIS and NIR light. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 62372, "time" : 62372, "value" : { "text" : "It also impacts on the shade pattern thrown by objects ‘catching’ the sunlight. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 62544, "time" : 62544, "value" : { "text" : "To make it worse, also the slope and slope-position of the surveyed ‘pixel’ matters.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 62729, "time" : 62729, "value" : { "text" : "All the above is adjusted by the data-provider using a Bidirectional_Reflectance_Distribution_Function (BRDF). ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 63066, "time" : 63066, "value" : { "text" : "The bottom-right figure shows the results of the BRDF exercise, while the top-right figure shows the considerable mismatch between catalogues when a BRDF-adjustments is omitted.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 63495, "time" : 63495, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 63706, "time" : 63706, "value" : { "text" : "… more pre-processing by ‘you'", "textAttributes" : [{"name":"fontItalic","rangeEnd":33,"rangeStart":0,"value":1,"valueType":"int"},{"name":"fontItalic","rangeEnd":34,"rangeStart":33,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 63876, "time" : 63876, "value" : { "text" : "First note that in the CGLS-imagery, all DN-values above 250 are Quality Flags, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 64130, "time" : 64130, "value" : { "text" : "and when used for a pixel, that pixel has thus a ‘missing’ NDVI-value.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 64326, "time" : 64326, "value" : { "text" : "Then after the required BRDF-adjustment, and after creating the MVC, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 64506, "time" : 64506, "value" : { "text" : "the resulting NDVI-data can still be influenced by ‘rather persistent’ haze and clouds. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 64770, "time" : 64770, "value" : { "text" : "The brown-line in the shown figure, displays for a specific pixel, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 64949, "time" : 64949, "value" : { "text" : "the NDVI data-series covering 2006. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 65083, "time" : 65083, "value" : { "text" : "Many negative ‘outlyers’ and downward anomalies do occur.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 65254, "time" : 65254, "value" : { "text" : "Theoretically, the NDVI pattern, covering the specific pixel and year, would follow the dotted green line. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 65567, "time" : 65567, "value" : { "text" : "That line can partially be estimated through a function called ‘Timesat’ (by Ecklund et.al). ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 65797, "time" : 65797, "value" : { "text" : "Timesat is iterative and uses the Savitsky-Golay smoothing algorithm to interpolate between NDVI-readings. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 66053, "time" : 66053, "value" : { "text" : "If the estimated ‘smoothing’ value is higher than the actual value at time-x, then Timesat uses the higher value. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 66303, "time" : 66303, "value" : { "text" : "This process is repeated thrice with a growing temporal window. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 66444, "time" : 66444, "value" : { "text" : "It results in an estimation of the “Upper-Envelope”. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 66619, "time" : 66619, "value" : { "text" : "At the peak of the growing season, the red-line did not fully manage to approach the dotted green line; ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 66836, "time" : 66836, "value" : { "text" : "persistent haze and clouds made that impossible, and the Upper-Envelope is thus never completely perfect.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 67095, "time" : 67095, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 67262, "time" : 67262, "value" : { "text" : "The TIMESAT filter will deliver a ‘clean’ data-cube", "textAttributes" : [{"name":"fontItalic","rangeEnd":54,"rangeStart":0,"value":1,"valueType":"int"},{"name":"fontItalic","rangeEnd":55,"rangeStart":54,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 67477, "time" : 67477, "value" : { "text" : "Besides filling values for missing records and adjusting values for negative outliers and anomalies, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 67703, "time" : 67703, "value" : { "text" : "Timesat will also remove smaller ‘peaks’; see the figure. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 67869, "time" : 67869, "value" : { "text" : "This removal is achieved through a final iteration, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 67996, "time" : 67996, "value" : { "text" : "in which the actual estimate of the last Savitsky-Golay smoothing is used and not the possible ‘higher’ actual.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 68236, "time" : 68236, "value" : { "text" : "Real “Upward” NDVI-anomalies occur only seldomly. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 68402, "time" : 68402, "value" : { "text" : "We call it ‘Glint’.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 68464, "time" : 68464, "value" : { "text" : "It happens when the distance between the pixel and the sensor is very high and has a very low angle", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 68648, "time" : 68648, "value" : { "text" : "(the ‘signal’ has to pass lots of atmosphere); ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 68767, "time" : 68767, "value" : { "text" : "in addition, it only occurs when the pixel consists of snow or ice. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 68909, "time" : 68909, "value" : { "text" : "This type of anomaly thus occurs rather rarely, and should not concern us the least.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 69132, "time" : 69132, "value" : { "text" : "Once a BRDF-adjusted data-cube of MVC-values has passed the Timesat filter, we can start using that data-cube for our ‘science’.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 69545, "time" : 69545, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 69746, "time" : 69746, "value" : { "text" : "Once cleaned, do visualize the NDVI-imagery as a movie", "textAttributes" : [{"name":"fontItalic","rangeEnd":53,"rangeStart":0,"value":1,"valueType":"int"},{"name":"fontItalic","rangeEnd":54,"rangeStart":53,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 69980, "time" : 69980, "value" : { "text" : "Viewing an original cleaned data-cube is of importance, because ‘data-implosion’ through clustering or classification is not yet done. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 70252, "time" : 70252, "value" : { "text" : "Viewing the data-cube as a movie will display and show lots of specifics in which one might be interested.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 70494, "time" : 70494, "value" : { "text" : "Do take time to detect and understand features that later must also show in the analysis results.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 70715, "time" : 70715, "value" : { "text" : "The movie can be ‘sharpened’ by overlaying a semi-transparent hill-shade image (prepared from a 30m resolution SRTM).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 71046, "time" : 71046, "value" : { "text" : "Also add roads, rivers, etc. as required to identify and recognize features of the movie.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 71283, "time" : 71283, "value" : { "text" : "Shown is a ‘movie’ of Mozambique prepared through 36 images representing 36 sequential dekads (these are 10-day periods).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 71646, "time" : 71646, "value" : { "text" : "The NDVI-value of each pixel of a specific dekad-image represents the median value of all annual repeats of the cleaned NDVI-values for that dekad and pixel.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 72039, "time" : 72039, "value" : { "text" : "The shown ‘movie’ thus represents the ‘climatology’ of Mozambique: ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 72182, "time" : 72182, "value" : { "text" : "it is a cloudless representative of the average green vegetation present over time covering the past 20 years (2000-2019). ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 72435, "time" : 72435, "value" : { "text" : "It is thus the ‘best’ base-line country-level map to study present differences and monitor future changes in land cover and land use.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 72734, "time" : 72734, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 72930, "time" : 72930, "value" : { "text" : "After one has studied the movie, it is time for a computer-guided ‘data-implosion’. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 73124, "time" : 73124, "value" : { "text" : "The ‘movie’ must become a 2D-map containing map-units, and its legend must become a collection of NDVI-profiles. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 73420, "time" : 73420, "value" : { "text" : "Each NDVI-profile represents one specific map-unit of the prepared map. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 73613, "time" : 73613, "value" : { "text" : "Note that, through the clustering or classification process of a time-series of data by pixel, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 73851, "time" : 73851, "value" : { "text" : "the pixel has received a map-unit code and the pixel-data (its time-series of NDVI-values) ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 74050, "time" : 74050, "value" : { "text" : "has shifted to the legend.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 74132, "time" : 74132, "value" : { "text" : "Actually: each NDVI-profile in the legend represents the averaged values of all pixels classified to that specific cluster or class.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 74481, "time" : 74481, "value" : { "text" : "The produced map is an intermediate-map, ready for use during fieldwork or for integration with secondary data. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 74796, "time" : 74796, "value" : { "text" : "Note that this map can, for 100%, be reproduced at will. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 74981, "time" : 74981, "value" : { "text" : "The only influence one had is by defining the number of clusters that the 2D map must contain. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 75201, "time" : 75201, "value" : { "text" : "That represents the only ‘unknown’ when clustering (classifying) the movie. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 75375, "time" : 75375, "value" : { "text" : "Supervised classification, based a list of a-priori specified land-cover types, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 75563, "time" : 75563, "value" : { "text" : "is rather impossible to carry out, because the ‘coarse’ pixels will often contain complexes of land-cover types, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 75805, "time" : 75805, "value" : { "text" : "and one may easily overlook unique land-cover types that an unsupervised clustering algorithm like ISODATA will properly identify.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 76141, "time" : 76141, "value" : { "text" : "Note in the legend the “gradient” of NDVI-profiles. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 76289, "time" : 76289, "value" : { "text" : "Their mutual distances indicates that preparing 50 clusters ‘did the job’.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 76480, "time" : 76480, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 76647, "time" : 76647, "value" : { "text" : "Another ‘movie'", "textAttributes" : [{"name":"fontItalic","rangeEnd":16,"rangeStart":0,"value":1,"valueType":"int"},{"name":"fontItalic","rangeEnd":17,"rangeStart":16,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 76754, "time" : 76754, "value" : { "text" : "Shown now is the climatology of Luzon, The Philippines, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 76895, "time" : 76895, "value" : { "text" : "representing the period 1998-2011.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 77030, "time" : 77030, "value" : { "text" : "Using the Iterative Self-Organizing Data Analysis Technique (ISODATA), ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 77219, "time" : 77219, "value" : { "text" : "an unsupervised clustering of the Hyper-Temporal data-cube is performed.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 77400, "time" : 77400, "value" : { "text" : "Using patterns identification and classification, the ‘movie’ is ‘imploded’ to a 2D-map with 79 map-units; ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 77687, "time" : 77687, "value" : { "text" : "each map-unit is described through an NDVI-profile.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 77837, "time" : 77837, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 77993, "time" : 77993, "value" : { "text" : "Shown now are some NDVI-profiles that clearly differ and that can each be labelled using some expert knowledge and field-experience in Luzon.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 78400, "time" : 78400, "value" : { "text" : "The red line, for instance, shows 2 distinct growing periods within one year; ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 78596, "time" : 78596, "value" : { "text" : "they suggests arable-cropping. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 78687, "time" : 78687, "value" : { "text" : "Indeed, in Luzon, the ‘red’ areas happen to be cropped to irrigated rice twice annually.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 78911, "time" : 78911, "value" : { "text" : "The light- and darker-green profiles show a distinct “dry-period” ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 79101, "time" : 79101, "value" : { "text" : "and a rather long (extended) growing season, during which NDVI values are rather high. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 79308, "time" : 79308, "value" : { "text" : "Such findings relate likely to evergreen cover-types with a high density of trees and bushes.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 79533, "time" : 79533, "value" : { "text" : "Likely, the orange-line represents something in-between the red and green lines.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 79707, "time" : 79707, "value" : { "text" : "It depicts just one growing season. Likely it represents a mixel of rainfed rice and trees and/or bushes.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 79963, "time" : 79963, "value" : { "text" : "Verification through high resolution imagery and fieldwork is clearly required.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 80141, "time" : 80141, "value" : { "text" : "Gradually, through use of field data, expert knowledge, and secondary data,", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 80316, "time" : 80316, "value" : { "text" : "the legend of the intermediate map will become a legend that contains factual land cover and land use terminology.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 80546, "time" : 80546, "value" : { "text" : "The intermediate NDVI-profiles will thus disappear.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 80700, "time" : 80700, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 80855, "time" : 80855, "value" : { "text" : "Detecting past changes\r\n", "textAttributes" : [{"name":"fontItalic","rangeEnd":22,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 81035, "time" : 81035, "value" : { "text" : "In case, annual repeats are NOT generalized using their median values, and thus the movie does not represent ‘climatology’, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 81306, "time" : 81306, "value" : { "text" : "ISODATA clustering will produce a legend with NDVI-profiles covering the full time-period of the original data-cube.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 81586, "time" : 81586, "value" : { "text" : "Now, the variability between years is thus NOT removed from the dataset", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 81764, "time" : 81764, "value" : { "text" : "- This also represents a choice made by the researcher", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 81887, "time" : 81887, "value" : { "text" : "- Detecting ‘past’ changes or defining ‘past extremes’ will now be possible through studying the produced legend.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 82158, "time" : 82158, "value" : { "text" : "As example, shown are NDVI-profiles covering a 10-year period (1998-2008) and representing 3 specific irrigated rice areas in the Mekong area of Vietnam.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 82629, "time" : 82629, "value" : { "text" : "- In the blue area the extent of annual flooding in the area increased between 1998 and 2000.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 82871, "time" : 82871, "value" : { "text" : "Afterwards, a very steady sequence ensued of flooding and cropping twice a year.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 83126, "time" : 83126, "value" : { "text" : "- In the green area, the sequence of cropping and flooding was rather haphazard till early 2002.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 83342, "time" : 83342, "value" : { "text" : "Afterwards, annually, 3 crops were cultivated, with no time remaining for any serious flooding. Till 2007!", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 83658, "time" : 83658, "value" : { "text" : "Then, famers claimed to have opened the dike that was completed in 2002 and that surrounds their villages,", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 83914, "time" : 83914, "value" : { "text" : "to ‘harvest’ silt and thus to fertilize their paddies in a very natural way.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 84048, "time" : 84048, "value" : { "text" : "In was by intent and not an unforeseen disaster that created a loss of the specific crop.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 84302, "time" : 84302, "value" : { "text" : "- The brown line displays a very gradual increase in performance of the rice crop until 2003.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 84534, "time" : 84534, "value" : { "text" : "Otherwise, no shocks or abrupt changes did occur.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 84694, "time" : 84694, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 84872, "time" : 84872, "value" : { "text" : "The last example will be presented through a sequence of slides. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 85089, "time" : 85089, "value" : { "text" : "It concerns mapping rice systems and their cropping calendars, in Odisha, India.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 85279, "time" : 85279, "value" : { "text" : "Step-1 shows the climatology movie, which was converted through ISODATA into a map with 100 clusters.", "textAttributes" : [{"name":"fontWeight","rangeEnd":6,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 85580, "time" : 85580, "value" : { "text" : "Step-2. Knowing that 100 clusters is rather ‘many’, the 100 NDVI-profiles were grouped into 21 distinct types of profiles. ", "textAttributes" : [{"name":"fontWeight","rangeEnd":6,"rangeStart":0,"value":700,"valueType":"int"},{"name":"fontWeight","rangeEnd":8,"rangeStart":7,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 85974, "time" : 85974, "value" : { "text" : "This was partly achieved through k-means grouping using the profile-data, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 86128, "time" : 86128, "value" : { "text" : "and partly through ‘expert-interpretation’ considering both the ‘relevant’ parts of the NDVI-Profiles and the locations of related ‘profiles’, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 86429, "time" : 86429, "value" : { "text" : "that is: ‘where’ does a profile occur (and its extent).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 86579, "time" : 86579, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 86743, "time" : 86743, "value" : { "text" : "This in-between slide shows that ‘expert-guided’ step by showing the spatial relation ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 86963, "time" : 86963, "value" : { "text" : "of 4 created NDVI-groups, each having 2 distinct growing seasons:", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 87145, "time" : 87145, "value" : { "text" : "- Groups [E-E1-I] occur closely together and they form together a gradient (see the profiles and the map)", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 87440, "time" : 87440, "value" : { "text" : "- Group J (the red area) stands spatially separate and seems unrelated to the others.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 87679, "time" : 87679, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 87820, "time" : 87820, "value" : { "text" : "Step-3 shows the NDVI-profiles of the 21 groups.", "textAttributes" : [{"name":"fontWeight","rangeEnd":6,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 88073, "time" : 88073, "value" : { "text" : "These profiles are used to identify the critical periods within one year that ISODATA used to differentiate the clusters (groups).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 88408, "time" : 88408, "value" : { "text" : "Inspection identified 4 distinct periods.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 88556, "time" : 88556, "value" : { "text" : "Knowing the 4 periods, a 2nd phase of ‘mapping’ started.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 88712, "time" : 88712, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 88899, "time" : 88899, "value" : { "text" : "Steps 4 to 6\r\n", "textAttributes" : [{"name":"fontItalic","rangeEnd":12,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 89047, "time" : 89047, "value" : { "text" : "Step 4. For the identified 4-periods, NDVI-averages from all available cloud-free medium-resolution imagery, ", "textAttributes" : [{"name":"fontWeight","rangeEnd":6,"rangeStart":0,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 89341, "time" : 89341, "value" : { "text" : "covering recent years, were extracted. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 89434, "time" : 89434, "value" : { "text" : "This delivered 4 images that contained mean NDVI-values. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 89596, "time" : 89596, "value" : { "text" : "These 4 images were then used by ISODATA to once more generate 21 classes, ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 89826, "time" : 89826, "value" : { "text" : "but now at a 30m spatial resolution.", "textAttributes" : [{"name":"fontWeight","rangeEnd":17,"rangeStart":13,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 89946, "time" : 89946, "value" : { "text" : "The super-imposed figure illustrates some results of Step-4.", "textAttributes" : [{"name":"fontWeight","rangeEnd":59,"rangeStart":53,"value":700,"valueType":"int"},{"name":"fontWeight","rangeEnd":60,"rangeStart":59,"value":700,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 90126, "time" : 90126, "value" : { "text" : "The 10 profiles shown all have just 4 datapoints each, matching the 4 earlier identified periods.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 90365, "time" : 90365, "value" : { "text" : "- Classes 11 & 15 relate to cropping during 2 seasons, where 11 occurs in the lowlands and 15 in the uplands.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 90608, "time" : 90608, "value" : { "text" : "- Classes 4, 6, 9 and 10 relate to cropping in the upland areas.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 90789, "time" : 90789, "value" : { "text" : "- Classes 5, 7, 8, and 12 relate to cropping in the lowlands.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 90968, "time" : 90968, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 91113, "time" : 91113, "value" : { "text" : "Step 5: The extent of each of the 21 classes was inspected and compared with published seasonal area statistics on rice by administrative area (Ref. EARAS).", "textAttributes" : [{"name":"fontWeight","rangeEnd":10,"rangeStart":9,"value":700,"valueType":"int"},{"name":"fontItalic","rangeEnd":8,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 91665, "time" : 91665, "value" : { "text" : "This created an improved legend containing area fractions by NDVI-class.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 91863, "time" : 91863, "value" : { "text" : "The shown table contains these area fractions as area-percentages, and does so by season, by water management system (irrigated versus rainfed), and by terrain unit (uplands versus lowlands).", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 92282, "time" : 92282, "value" : { "text" : "Besides these fractions, also the fractions of the total net area sown annually to any crop is reported.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 92552, "time" : 92552, "value" : { "text" : "Please do note that in Odisha, used season-identifiers relate to the harvesting periods of the respective crops.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 92838, "time" : 92838, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 92981, "time" : 92981, "value" : { "text" : "Step 6: The legend was further improved by matching created legend-items with published crop calendar information.", "textAttributes" : [{"name":"fontItalic","rangeEnd":7,"rangeStart":0,"value":1,"valueType":"int"}] }, "duration" : 0 }, { "endTime" : 93385, "time" : 93385, "value" : { "text" : "Note once more that the season-identifiers relate to the harvesting periods of the respective crops:", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 93644, "time" : 93644, "value" : { "text" : "- Summer rice is harvested in June and has a Crop Growing Period Length of 120 to 135 days,", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 93867, "time" : 93867, "value" : { "text" : "- Autumn rice is harvested in September, with a relatively short growing period of 80 to 100 days, and", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 94165, "time" : 94165, "value" : { "text" : "- Winter rice is harvested from October to December, with a growing period that can extend from 100 to 150 days.", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 94424, "time" : 94424, "value" : { "text" : "Finally do note, that I as author of this map, never set foot in Odisha. ", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 94637, "time" : 94637, "value" : { "text" : "Agronomic expert knowledge, great secondary data sources, and smart combination of NDVI-data in the spatial and temporal domains, did the job !", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 94967, "time" : 94967, "value" : { "text" : "", "textAttributes" : null }, "duration" : 0 }, { "endTime" : 95178, "time" : 95178, "value" : { "text" : "Section-5. This brings us to the end of the presentation. 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