In this notebook we'll have a look at how to download WaPOR v3 data using FAO's GISMGR 2.0 API for a specific region (for a notebook on downloading WaPOR v2 data, go here). Let's get started by importing the modules we are going to use.
import os
import sys
import ilwis
import requests
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from osgeo import gdal, gdalconst
from IPython.display import HTML
import warnings
warnings.filterwarnings('ignore')
gdal connector: ilwis3 connector: Organizing data:
The WaPOR v3 variables are stored in mapsets, which in turn contain rasters that contain the data for a particular date or period.
We can get an overview of the available mapsets by requesting the following url (note that you can also open this url in your browser):
base_url = f"https://data.apps.fao.org/gismgr/api/v2/catalog/workspaces/WAPOR-3/mapsets"
Next we create a function that requests the url and returns some of the information thats returned.
def collect_responses(url, info = ["code"]):
data = {"links": [{"rel": "next", "href": url}]}
output = list()
while "next" in [x["rel"] for x in data["links"]]:
url_ = [x["href"] for x in data["links"] if x["rel"] == "next"][0]
response = requests.get(url_)
response.raise_for_status()
data = response.json()["response"]
if isinstance(info, list):
output += [tuple(x.get(y) for y in info) for x in data["items"]]
else:
output += data["items"]
if isinstance(info, list):
output = sorted(output)
return output
Then we run the function on the url we defined above.
#retrieve information on all collections
all_mapsets = collect_responses(base_url, info = ["code", "caption"])
all_mapsets
[('L1-AETI-A', 'Actual EvapoTranspiration and Interception (Annual)'), ('L1-AETI-D', 'Actual EvapoTranspiration and Interception (Dekadal)'), ('L1-AETI-M', 'Actual EvapoTranspiration and Interception (Monthly)'), ('L1-E-A', 'Evaporation (Annual)'), ('L1-E-D', 'Evaporation (Dekadal)'), ('L1-I-A', 'Interception (Annual)'), ('L1-I-D', 'Interception (Dekadal)'), ('L1-NPP-D', 'Net Primary Production (Dekadal)'), ('L1-NPP-M', 'Net Primary Production (Monthly)'), ('L1-RSM-D', 'Relative Soil Moisture (Dekadal)'), ('L1-T-A', 'Transpiration (Annual)'), ('L1-T-D', 'Transpiration (Dekadal)'), ('L2-AETI-A', 'Actual EvapoTranspiration and Interception (Annual)'), ('L2-AETI-D', 'Actual EvapoTranspiration and Interception (Dekadal)'), ('L2-AETI-M', 'Actual EvapoTranspiration and Interception (Monthly)'), ('L2-E-A', 'Evaporation (Annual)'), ('L2-E-D', 'Evaporation (Dekadal)'), ('L2-I-A', 'Interception (Annual)'), ('L2-I-D', 'Interception (Dekadal)'), ('L2-NPP-D', 'Net Primary Production (Dekadal)'), ('L2-NPP-M', 'Net Primary Production (Monthly)'), ('L2-RSM-D', 'Relative Soil Moisture (Dekadal)'), ('L2-T-A', 'Transpiration (Annual)'), ('L2-T-D', 'Transpiration (Dekadal)')]
The variable all_mapsets now contains a list with all the available mapset codes and a accompanying description. Let's choose one of the codes, add it to the base_url and see what's returned.
#retrieve listing of all L2-AETI-D (Dekadal Actual EvapoTranspiration and Interception) data in the collection
mapset_code = "L2-AETI-D"
mapset_url = f"{base_url}/{mapset_code}/rasters"
all_rasters = collect_responses(mapset_url, info = ["code", "downloadUrl"])
all_rasters
[('WAPOR-3.L2-AETI-D.2018-01-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2018-01-D1.tif'), ('WAPOR-3.L2-AETI-D.2018-01-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2018-01-D2.tif'), ('WAPOR-3.L2-AETI-D.2018-01-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2018-01-D3.tif'), ('WAPOR-3.L2-AETI-D.2018-02-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2018-02-D1.tif'), ('WAPOR-3.L2-AETI-D.2018-02-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2018-02-D2.tif'), ('WAPOR-3.L2-AETI-D.2018-02-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2018-02-D3.tif'), ('WAPOR-3.L2-AETI-D.2018-03-D1', 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'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-01-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-01-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-01-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-01-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-01-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-02-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-02-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-02-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-02-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-02-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-02-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-03-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-03-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-03-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-03-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-03-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-03-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-04-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-04-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-04-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-04-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-04-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-04-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-05-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-05-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-05-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-05-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-05-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-05-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-06-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-06-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-06-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-06-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-06-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-06-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-07-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-07-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-07-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-07-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-07-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-07-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-08-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-08-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-08-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-08-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-08-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-08-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-09-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-09-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-09-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-09-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-09-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-09-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-10-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-10-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-10-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-10-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-10-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-10-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-11-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-11-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-11-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-11-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-11-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-11-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-12-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-12-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-12-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-12-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-12-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-12-D3.tif')]
#select your year of interest
year = '2022'
#create listing only for selected year
all_rasters = [raster for raster in all_rasters if raster[0].split('.')[-1].split('-')[0] == year]
all_rasters
[('WAPOR-3.L2-AETI-D.2022-01-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-01-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-01-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-01-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-01-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-01-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-02-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-02-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-02-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-02-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-02-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-02-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-03-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-03-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-03-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-03-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-03-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-03-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-04-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-04-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-04-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-04-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-04-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-04-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-05-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-05-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-05-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-05-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-05-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-05-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-06-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-06-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-06-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-06-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-06-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-06-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-07-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-07-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-07-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-07-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-07-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-07-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-08-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-08-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-08-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-08-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-08-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-08-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-09-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-09-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-09-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-09-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-09-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-09-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-10-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-10-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-10-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-10-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-10-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-10-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-11-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-11-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-11-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-11-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-11-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-11-D3.tif'), ('WAPOR-3.L2-AETI-D.2022-12-D1', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-12-D1.tif'), ('WAPOR-3.L2-AETI-D.2022-12-D2', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-12-D2.tif'), ('WAPOR-3.L2-AETI-D.2022-12-D3', 'https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-12-D3.tif')]
We now have a list with all the available rasters in this mapset, including direct links to the geotif files. You can now simply click on the link, or copy and paste these links in your browser and download the data.
If you are only interested in data for a specific region however, the next part of this notebook explains how to download a subset of a geotif using gdal.
work_dir = os.getcwd()+'/WaPOR_Data/V3'
print("current dir is: %s" % (os.getcwd()))
print("current working directory is:",work_dir)
if os.path.isdir(work_dir):
print("Folder exists")
else:
print("Folder doesn't exists")
os.mkdir(work_dir)
current dir is: /home/eoafrica/surface_flood current working directory is: /home/eoafrica/surface_flood/WaPOR_Data/V3 Folder exists
cd_folder = os.getcwd() #check current directory folder
print(cd_folder)
/home/eoafrica/surface_flood
Using the Python implementation of gdal_translate we can download a part of a file (the command line version would work as well ofcourse). We start by choosing a specific url from the list of urls we've found above, define a bounding-box, which bands (this particular file has only 1 band so it's an easy choice) of the Geotiff we want to have and where we want to store the downloaded file.
tif_url = all_rasters[0] [1]#from tuple select URL
print(tif_url)
bounding_box = [32.378, -18.699, 34.758, -20.941] # left, top, right, bottom
bands = [1] #, selected band within layer
output_filepath = work_dir + '/' + 'Buzi_'+ year + '_01_01_V3.mpr'
https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-01-D1.tif
Then we pass these variables to gdal.TranslateOptions (you can check out what other options are available by running help (gdal.TranslateOptions), e.g. you can also create an ILWIS file instead of a GeoTIFF).
translate_options = gdal.TranslateOptions(projWin=bounding_box, format='ILWIS', bandList=bands, unscale = True, outputType=gdalconst.GDT_Float64)
Next we can run gdal.Translate
.
⚠️ You'll see that we have to add a small string (
"/vsicurl/"
) in front of the URL we've found earlier, this is to tellgdal
that we are not dealing with a normal local file, but with a file somewhere on a server (see here for more info).
ds = gdal.Translate(output_filepath, f"/vsicurl/{tif_url}", options = translate_options)
That should finish in a couple of seconds, finally we can quickly create a simple plot to see if the data was really downloaded.
band = ds.GetRasterBand(1)
print(band.DataType) #returns index number 7, meaning gdal data type = Float64
array = band.ReadAsArray()
print('minimum value:',array.min(), 'maximum value:',array.max())
plt.imshow(array, vmin=0 , vmax=7, cmap ='jet');
7 minimum value: -1e+308 maximum value: 6.800000000000001
Get further meta data information on selected window, pixelsize and projection
geotransform = ds.GetGeoTransform()
print(geotransform)
print()
projection = ds.GetProjection()
print(projection)
print(ds.RasterXSize, ds.RasterYSize)
(32.3779296875, 0.0009765625, 0.0, -18.6982421875, 0.0, -0.0009765625) GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] 2437 2296
#bounding_box = [32.378, -18.699, 34.758, -20.941] # left, top, right, bottom - was already defined before
bands = [1] #, selected band within layer
year = all_rasters[0][0].split('.')[-1].split('-')[0]
output_filepath = work_dir + '/' + 'Buzi_' + year + '_V3.mpl'
translate_options = gdal.TranslateOptions(projWin=bounding_box, format='MEM', bandList=bands)
datasets = []
print('processing')
for raster in all_rasters:
tif_url = raster[1] #from tuple select URL
print(tif_url)
ds = gdal.Translate('', f"/vsicurl/{tif_url}", options = translate_options)
datasets.append(ds)
print('Writing to disk')
driver = gdal.GetDriverByName('ILWIS')
dataset_out = driver.Create(output_filepath, datasets[0].RasterXSize, datasets[0].RasterYSize, len(datasets), datasets[0].GetRasterBand(1).DataType)
dataset_out.SetGeoTransform(geotransform)
dataset_out.SetProjection(projection)
for bandnr in range(len(datasets)):
print(all_rasters[bandnr][0])
out_band = dataset_out.GetRasterBand(bandnr+1).WriteArray(datasets[bandnr].GetRasterBand(1).ReadAsArray())
dataset_out.FlushCache()
dataset_out = None
print('Done!')
processing https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-01-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-01-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-01-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-02-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-02-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-02-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-03-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-03-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-03-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-04-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-04-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-04-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-05-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-05-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-05-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-06-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-06-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-06-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-07-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-07-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-07-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-08-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-08-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-08-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-09-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-09-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-09-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-10-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-10-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-10-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-11-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-11-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-11-D3.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-12-D1.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-12-D2.tif https://storage.googleapis.com/fao-gismgr-wapor-3-data/DATA/WAPOR-3/MAPSET/L2-AETI-D/WAPOR-3.L2-AETI-D.2022-12-D3.tif Writing to disk WAPOR-3.L2-AETI-D.2022-01-D1 WAPOR-3.L2-AETI-D.2022-01-D2 WAPOR-3.L2-AETI-D.2022-01-D3 WAPOR-3.L2-AETI-D.2022-02-D1 WAPOR-3.L2-AETI-D.2022-02-D2 WAPOR-3.L2-AETI-D.2022-02-D3 WAPOR-3.L2-AETI-D.2022-03-D1 WAPOR-3.L2-AETI-D.2022-03-D2 WAPOR-3.L2-AETI-D.2022-03-D3 WAPOR-3.L2-AETI-D.2022-04-D1 WAPOR-3.L2-AETI-D.2022-04-D2 WAPOR-3.L2-AETI-D.2022-04-D3 WAPOR-3.L2-AETI-D.2022-05-D1 WAPOR-3.L2-AETI-D.2022-05-D2 WAPOR-3.L2-AETI-D.2022-05-D3 WAPOR-3.L2-AETI-D.2022-06-D1 WAPOR-3.L2-AETI-D.2022-06-D2 WAPOR-3.L2-AETI-D.2022-06-D3 WAPOR-3.L2-AETI-D.2022-07-D1 WAPOR-3.L2-AETI-D.2022-07-D2 WAPOR-3.L2-AETI-D.2022-07-D3 WAPOR-3.L2-AETI-D.2022-08-D1 WAPOR-3.L2-AETI-D.2022-08-D2 WAPOR-3.L2-AETI-D.2022-08-D3 WAPOR-3.L2-AETI-D.2022-09-D1 WAPOR-3.L2-AETI-D.2022-09-D2 WAPOR-3.L2-AETI-D.2022-09-D3 WAPOR-3.L2-AETI-D.2022-10-D1 WAPOR-3.L2-AETI-D.2022-10-D2 WAPOR-3.L2-AETI-D.2022-10-D3 WAPOR-3.L2-AETI-D.2022-11-D1 WAPOR-3.L2-AETI-D.2022-11-D2 WAPOR-3.L2-AETI-D.2022-11-D3 WAPOR-3.L2-AETI-D.2022-12-D1 WAPOR-3.L2-AETI-D.2022-12-D2 WAPOR-3.L2-AETI-D.2022-12-D3 Done!
work_dir = os.getcwd()+'/WaPOR_Data/V3'
#set the working directory for ILWISPy
ilwis.setWorkingCatalog(work_dir)
print(work_dir)
gdal connector: /home/eoafrica/surface_flood/WaPOR_Data/V3 ilwis3 connector: Organizing data:
band_data = ilwis.RasterCoverage ('Buzi_' + year + '_V3.mpl')
print(band_data.size())
Size(2437, 2296, 36)
#calculate statistics and display selected thresholds
stat = band_data.statistics(ilwis.PropertySets.pHISTOGRAM, 65535)
minPerc, maxPerc = stat.calcStretchRange(0.5)
print(minPerc)
print(maxPerc)
1.7450331125819503 50.940870387888936
#transform to numpy array
band_data_in = np.fromiter(iter(band_data), np.float64, band_data.size().linearSize())
band_data_2np = band_data_in.reshape((band_data.size().zsize, band_data.size().ysize, band_data.size().xsize))
#setting path for ffmpeg - to create animations
os.environ["PATH"] = '/home/eoafrica/surface_flood/software:' + os.environ["PATH"]
!chmod +x /home/eoafrica/surface_flood/software/ffmpeg #ensure the program can be executed!
#create animation of imported data
warnings.filterwarnings('ignore')
imageList = band_data_2np
fig = plt.figure(figsize=(8, 8))
ims = []
coordSys = band_data.coordinateSystem()
ax = plt.subplot(1, 1, 1)
for i in range(len(imageList)):
im = plt.imshow(imageList[i], vmin=minPerc, vmax=maxPerc, cmap='jet', animated=True)
ann = ax.annotate(f"Time step {1+i:.0f}.", (1.0, 1.01), xycoords="axes fraction", ha="right")
ims.append([im, ann])
ani = animation.ArtistAnimation(fig, ims, interval=600, blit=True, repeat=True)
plt.xticks(color='b')
plt.yticks(color='b')
plt.colorbar(shrink=0.65)
plt.grid(True, alpha = 0.5)
plt.title("animation imported data");
plt.close()
# Show the animation inline (below)
HTML(ani.to_html5_video())
# Uncomment line below to save animation as video
ani.save(work_dir+'/ani_fin.mp4', fps=2)
Select another year or another product and create an animation