-
Notifications
You must be signed in to change notification settings - Fork 1
/
Collect.py
426 lines (376 loc) · 15.8 KB
/
Collect.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
# -*- coding: utf-8 -*-
"""
WaterSat
author: Tim Martijn Hessels
Created on Sun Sep 15 18:40:44 2019
"""
import requests, json, time
import pandas as pd
import os
import urllib
import datetime
from pyproj import Proj, transform
def WAPOR(output_folder, Startdate, Enddate, latlim, lonlim, auth_token, Parameter, Area = None, Version = "2"):
time_steps = Parameter.split("_")[-1]
level = Parameter.split("_")[0]
# Find the time frequency of the parameter
if time_steps == "A":
freq = "AS"
if time_steps == "M":
freq = "MS"
if time_steps == "D":
freq = "MS"
# Find LEVEL type
if level == "L3":
Parameter_first_part = "_".join(Parameter.split("_")[0:-1])
Parameter = "_".join([Parameter_first_part, "{AREA}", Parameter.split("_")[-1]])
Version = "1" # LEVEL 3 is only available in Version 1 dataset
# Define dates
Dates = pd.date_range(Startdate, Enddate, freq = freq)
if time_steps == "D":
for Date in Dates:
if Date == Dates[0]:
Dates_end = [pd.Timestamp(datetime.datetime(Date.year, Date.month, 1)), pd.Timestamp(datetime.datetime(Date.year, Date.month, 11)), pd.Timestamp(datetime.datetime(Date.year, Date.month, 21))]
else:
Dates_end.append(pd.Timestamp(datetime.datetime(Date.year, Date.month, 1)))
Dates_end.append(pd.Timestamp(datetime.datetime(Date.year, Date.month, 11)))
Dates_end.append(pd.Timestamp(datetime.datetime(Date.year, Date.month, 21)))
else:
Dates_end = Dates
# Define server
url = 'https://io.apps.fao.org/gismgr/api/v1/query'
# Login into WAPOR
sign_in= 'https://io.apps.fao.org/gismgr/api/v1/iam/sign-in'
resp_vp=requests.post(sign_in,headers={'X-GISMGR-API-KEY':auth_token})
resp_vp = resp_vp.json()
token = resp_vp['response']['accessToken']
# Set header type
header = {"Authorization": "Bearer " + token,
"Content-type": "application/json;charset=UTF-8",
"Accept": "application/json"
}
# Get constant variables for payload
measure = VariablesInfo.measures[Parameter]
dimension = VariablesInfo.dimensions[Parameter]
version = VariablesInfo.versions[Version]
output_folder_para = os.path.join(output_folder, Parameter.format(AREA = Area))
if not os.path.exists(output_folder_para):
os.makedirs(output_folder_para)
if Parameter.split("_")[0] == "L1":
latlim[0] = latlim[0] - 0.1
latlim[1] = latlim[1] + 0.1
lonlim[0] = lonlim[0] - 0.1
lonlim[1] = lonlim[1] + 0.1
if level == "L3":
Projection = LEVEL3.Projection[Area]
inProj = Proj(init='epsg:4326')
outProj = Proj(init='epsg:%d' %Projection)
Projection = Projection
lonlim[0], latlim[1] = transform(inProj, outProj, lonlim[0], latlim[1])
lonlim[1], latlim[0] = transform(inProj, outProj, lonlim[1], latlim[0])
else:
Projection = 4326
if level == "L3":
Parameter = Parameter.format(AREA = Area)
# Loop over the dates
for Date_end in Dates_end:
# Set the required time period
if time_steps == "D":
Start_day_payload = Date_end.day
End_year_payload = Date_end.year
if Start_day_payload == 21:
End_day_payload = 1
End_month_payload = Date_end.month + 1
if End_month_payload == 13:
End_month_payload = 1
End_year_payload += 1
else:
End_day_payload = Start_day_payload + 10
End_month_payload = Date_end.month
if time_steps == "M":
Start_day_payload = Date_end.day
End_day_payload = 1
End_month_payload = Date_end.month + 1
End_year_payload = Date_end.year
if End_month_payload == 13:
End_month_payload = 1
End_year_payload += 1
if time_steps == "A":
Start_day_payload = Date_end.day
End_day_payload = 1
End_month_payload = 1
End_year_payload = Date_end.year + 1
file_name_temp = os.path.join(output_folder_para, "%s_WAPOR_%s_%s.%02d.%02d.tif" %(Parameter, dimension, Date_end.year, Date_end.month, Start_day_payload))
if not os.path.exists(file_name_temp):
# Create payload file
payload = Create_Payload_JSON(Parameter, Date_end, Start_day_payload, End_year_payload, End_month_payload, End_day_payload, latlim, lonlim, version, dimension, measure, Projection)
success = 0
no_succes = 0
while success == 0 and no_succes<10:
try:
# Collect the date by using the payload file
response = requests.post(url, data=json.dumps(payload), headers=header)
response.raise_for_status()
response_json = response.json()
result = response_json['response']
job_url = result['links'][0]['href']
# output filename
print("Try to create %s" %file_name_temp)
time.sleep(10)
job_response = requests.get(job_url, headers=header)
if job_response.status_code == 200:
while job_response.json()['response']['status'] == 'RUNNING':
time.sleep(30)
job_response = requests.get(job_url, headers=header)
if job_response.json()['response']['status'] == 'COMPLETED':
job_result = job_response.json()['response']['output']['downloadUrl']
urllib.request.urlretrieve(job_result, file_name_temp)
print("Created %s succesfully!!!" %file_name_temp)
success = 1
else:
print("ERROR: Was not able to create output")
else:
print("ERROR: Was not able to connect to WAPOR server")
except:
success = 0
no_succes +=1
if no_succes == 10:
print("ERROR: already tried 10 times, and no connection with server. Please run code again")
return()
def Create_Payload_JSON(Parameter, Date_end, Start_day_payload, End_year_payload, End_month_payload, End_day_payload, latlim, lonlim, version, dimension, measure, Projection):
payload = {
"type": "CropRaster",
"params": {
"properties": {
"outputFileName": "%s_clipped.tif" %Parameter,
"cutline": True,
"tiled": True,
"compressed": True,
"overviews": True
},
"cube": {
"code": Parameter,
"workspaceCode": version,
"language": "en"
},
"dimensions": [
{
"code": dimension,
"values": [
"[%d-%02d-%02d,%d-%02d-%02d)" %(Date_end.year, Date_end.month, Start_day_payload, End_year_payload, End_month_payload, End_day_payload)
]
}
],
"measures": [
measure
],
"shape": {
"crs": "EPSG:%d" %Projection,
"type": "Polygon",
"coordinates": [
[
[
lonlim[0],
latlim[1]
],
[
lonlim[1],
latlim[1]
],
[
lonlim[1],
latlim[0]
],
[
lonlim[0],
latlim[0]
],
[
lonlim[0],
latlim[1]
]
]
]
}
}
}
return(payload)
class VariablesInfo:
"""
This class contains the information about the WAPOR variables
"""
descriptions = {'L1_GBWP_A': 'Gross Biomass Water Productivity',
'L1_NBWP_A': 'Net Biomass Water Productivity',
'L1_AETI_A': 'Actual EvapoTranspiration and Interception (Annual)',
'L1_AETI_M': 'Actual EvapoTranspiration and Interception (Monthly)',
'L1_AETI_D': 'Actual EvapoTranspiration and Interception (Dekadal)',
'L1_T_A': 'Transpiration (Annual)',
'L1_E_A': 'Evaporation (Annual)',
'L1_I_A': 'Interception (Annual)',
'L1_T_D': 'Transpiration (Dekadal)',
'L1_E_D': 'Evaporation (Dekadal)',
'L1_I_D': 'Interception (Dekadal)',
'L1_NPP_D': 'Net Primary Production',
'L1_TBP_A': 'Total Biomass Production (Annual)',
'L1_LCC_A': 'Land Cover Classification',
'L1_RET_A': 'Reference EvapoTranspiration (Annual)',
'L1_PCP_A': 'Precipitation (Annual)',
'L1_RET_M': 'Reference EvapoTranspiration (Monthly)',
'L1_PCP_M': 'Precipitation (Monthly)',
'L1_RET_D': 'Reference EvapoTranspiration (Dekadal)',
'L1_PCP_D': 'Precipitation (Dekadal)',
'L1_RET_E': 'Reference EvapoTranspiration (Daily)',
'L1_PCP_E': 'Precipitation (Daily)',
'L1_QUAL_NDVI_D': 'Quality of Normalized Difference Vegetation Index (Dekadal)',
'L1_QUAL_LST_D': 'Quality Land Surface Temperature (Dekadal)',
# 'L2_GBWP_S': 'Gross Biomass Water Productivity (Seasonal)',
'L2_AETI_A': 'Actual EvapoTranspiration and Interception (Annual)',
'L2_AETI_M': 'Actual EvapoTranspiration and Interception (Monthly)',
'L2_AETI_D': 'Actual EvapoTranspiration and Interception (Dekadal)',
'L2_T_A': 'Transpiration (Annual)',
'L2_E_A': 'Evaporation (Annual)',
'L2_I_A': 'Interception (Annual)',
'L2_T_D': 'Transpiration (Dekadal)',
'L2_E_D': 'Evaporation (Dekadal)',
'L2_I_D': 'Interception (Dekadal)',
'L2_NPP_D': 'Net Primary Production',
#'L2_TBP_S': 'Total Biomass Production (Seasonal)',
'L2_LCC_A': 'Land Cover Classification',
#'L2_PHE_S': 'Phenology (Seasonal)',
'L2_QUAL_NDVI_D': 'Quality of Normalized Difference Vegetation Index (Dekadal)',
'L2_QUAL_LST_D': 'Quality Land Surface Temperature (Dekadal)',
'L3_AETI_A': 'Actual EvapoTranspiration and Interception (Annual)',
'L3_AETI_M': 'Actual EvapoTranspiration and Interception (Monthly)',
'L3_AETI_D': 'Actual EvapoTranspiration and Interception (Dekadal)',
'L3_T_A': 'Transpiration (Annual)',
'L3_E_A': 'Evaporation (Annual)',
'L3_I_A': 'Interception (Annual)',
'L3_T_D': 'Transpiration (Dekadal)',
'L3_E_D': 'Evaporation (Dekadal)',
'L3_I_D': 'Interception (Dekadal)',
'L3_NPP_D': 'Net Primary Production',
'L3_QUAL_NDVI_D': 'Quality of Normalized Difference Vegetation Index (Dekadal)',
'L3_QUAL_LST_D': 'Quality Land Surface Temperature (Dekadal)',
'L3_LCC_A': 'Land Cover Classification'}
measures = {'L1_GBWP_A': 'WPR',
'L1_NBWP_A': 'WPR',
'L1_AETI_A': 'WATER_MM',
'L1_AETI_M': 'WATER_MM',
'L1_AETI_D': 'WATER_MM',
'L1_T_A': 'WATER_MM',
'L1_E_A': 'WATER_MM',
'L1_I_A': 'WATER_MM',
'L1_T_D': 'WATER_MM',
'L1_E_D': 'WATER_MM',
'L1_I_D': 'WATER_MM',
'L1_NPP_D': 'NPP',
'L1_TBP_A': 'LPR',
'L1_LCC_A': 'LCC',
'L1_RET_A': 'WATER_MM',
'L1_PCP_A': 'WATER_MM',
'L1_RET_M': 'WATER_MM',
'L1_PCP_M': 'WATER_MM',
'L1_RET_D': 'WATER_MM',
'L1_PCP_D': 'WATER_MM',
'L1_RET_E': 'WATER_MM',
'L1_PCP_E': 'WATER_MM',
'L1_QUAL_NDVI_D': 'N_DEKADS',
'L1_QUAL_LST_D': 'N_DAYS',
# 'L2_GBWP_S': 'WPR',
'L2_AETI_A': 'WATER_MM',
'L2_AETI_M': 'WATER_MM',
'L2_AETI_D': 'WATER_MM',
'L2_T_A': 'WATER_MM',
'L2_E_A': 'WATER_MM',
'L2_I_A': 'WATER_MM',
'L2_T_D': 'WATER_MM',
'L2_E_D': 'WATER_MM',
'L2_I_D': 'WATER_MM',
'L2_NPP_D': 'NPP',
# 'L2_TBP_S': 'LPR',
'L2_LCC_A': 'LCC',
# 'L2_PHE_S': 'PHE',
'L2_QUAL_NDVI_D': 'N_DEKADS',
'L2_QUAL_LST_D': 'N_DAYS',
'L3_AETI_{AREA}_A': 'WATER_MM',
'L3_AETI_{AREA}_M': 'WATER_MM',
'L3_AETI_{AREA}_D': 'WATER_MM',
'L3_T_{AREA}_A': 'WATER_MM',
'L3_E_{AREA}_A': 'WATER_MM',
'L3_I_{AREA}_A': 'WATER_MM',
'L3_T_{AREA}_D': 'WATER_MM',
'L3_E_{AREA}_D': 'WATER_MM',
'L3_I_{AREA}_D': 'WATER_MM',
'L3_NPP_{AREA}_D': 'NPP',
'L3_QUAL_NDVI_{AREA}_D': 'N_DEKADS',
'L3_QUAL_LST_{AREA}_D': 'N_DAYS',
'L3_LCC_{AREA}_A': 'LCC'}
dimensions = {'L1_GBWP_A': 'YEAR',
'L1_NBWP_A': 'YEAR',
'L1_AETI_A': 'YEAR',
'L1_AETI_M': 'MONTH',
'L1_AETI_D': 'DEKAD',
'L1_T_A': 'YEAR',
'L1_E_A': 'YEAR',
'L1_I_A': 'YEAR',
'L1_T_D': 'DEKAD',
'L1_E_D': 'DEKAD',
'L1_I_D': 'DEKAD',
'L1_NPP_D': 'DEKAD',
'L1_TBP_A': 'YEAR',
'L1_LCC_A': 'YEAR',
'L1_RET_A': 'YEAR',
'L1_PCP_A': 'YEAR',
'L1_RET_M': 'MONTH',
'L1_PCP_M': 'MONTH',
'L1_RET_D': 'DEKAD',
'L1_PCP_D': 'DEKAD',
'L1_RET_E': 'DAY',
'L1_PCP_E': 'DAY',
'L1_QUAL_NDVI_D': 'DEKAD',
'L1_QUAL_LST_D': 'DEKAD',
# 'L2_GBWP_S': 'SEASON',
'L2_AETI_A': 'YEAR',
'L2_AETI_M': 'MONTH',
'L2_AETI_D': 'DEKAD',
'L2_T_A': 'YEAR',
'L2_E_A': 'YEAR',
'L2_I_A': 'YEAR',
'L2_T_D': 'DEKAD',
'L2_E_D': 'DEKAD',
'L2_I_D': 'DEKAD',
'L2_NPP_D': 'DEKAD',
# 'L2_TBP_S': 'SEASON',
'L2_LCC_A': 'YEAR',
# 'L2_PHE_S': 'SEASON',
'L2_QUAL_NDVI_D': 'DEKAD',
'L2_QUAL_LST_D': 'DEKAD',
'L3_AETI_{AREA}_A': 'YEAR',
'L3_AETI_{AREA}_M': 'MONTH',
'L3_AETI_{AREA}_D': 'DEKAD',
'L3_T_{AREA}_A': 'YEAR',
'L3_E_{AREA}_A': 'YEAR',
'L3_I_{AREA}_A': 'YEAR',
'L3_T_{AREA}_D': 'DEKAD',
'L3_E_{AREA}_D': 'DEKAD',
'L3_I_{AREA}_D': 'DEKAD',
'L3_NPP_{AREA}_D': 'DEKAD',
'L3_QUAL_NDVI_{AREA}_D': 'DEKAD',
'L3_QUAL_LST_{AREA}_D': 'DEKAD',
'L3_LCC_{AREA}_A': 'YEAR'}
versions = {'1': 'WAPOR',
'2': 'WAPOR_2'}
class LEVEL3:
"""
This class contains the information of the areas in LEVEL 3
"""
Area = {'AWA': 'Awash, Ethiopia',
'BKA': 'Bekaa, Lebanon',
'KOG': 'Koga, Ethiopia',
'ODN': 'Office du Niger, Mali',
'ZAN': 'Zankalon, Egypt'}
Projection = {'AWA': 32637,
'BKA': 32636,
'KOG': 32637,
'ODN': 32630,
'ZAN': 32636}