Crop Data Layers¶
Crop Land Data Layers, also known as CDLs, are published by USDA and provide estimates of historical crops cover.
In [25]:
import requests
import json
import time
from pandas.io.json import json_normalize
import requests, zipfile, io
import geopandas as gpd
%matplotlib inline
import pandas as pd
API Details¶
Request URL:https://ag-analytics.azure-api.net/CroplandDataLayers/get[?year][&inputShape][&env:outSR]
Request parameters
year Year of desired result.
inputShape (ESRI Polygon shape): The shape information for field in esriGeometryPolygon format. Standard open source JavaScript front-end libraries (e.g., Leaflet) can be used to structure the shape
env:outSR (optional) Output Spatial Reference. Return features in the specified spatial reference by supplying specific wkid (eg. 4326).
In order to get Ocp-Apim-Subscription-Key, please click on this link https://analytics.ag/Session/SignInToAPIPayment
Request Parameters¶
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year=2016
inputShape={"geometryType":"esriGeometryPolygon","features":[{"geometry":{"rings":[[[-89.045774,43.730605],[-89.04577,43.730488],[-89.045722,43.729998],[-89.045789,43.729653],[-89.045661,43.72961],[-89.045635,43.729782],[-89.045644,43.730045],[-89.045653,43.730308],[-89.045651,43.730607],[-89.041228,43.730676],[-89.041171,43.728908],[-89.041111,43.727076],[-89.042892,43.727044],[-89.044665,43.727018],[-89.046178,43.726999],[-89.046237,43.730597],[-89.045774,43.730605]]],"spatialReference":{"wkid":4326}}}]}
env=4326
f="json"
headers={'Ocp-Apim-Subscription-Key': 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'}
API Function¶
In [27]:
def get_crop_data_layers(year,inputShape,env,headers,f):
try:
url = "https://ag-analytics.azure-api.net/CroplandDataLayers/get?year={}&inputShape={}&env:outSR={}&f={}".format(year,inputShape,env,f)
response = (requests.get(url,headers=headers).text)
print(response)
response_json = json.loads(response)
time.sleep(0.5)
return response_json
except Exception as e:
raise e
Calling API Function¶
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crop_layer=get_crop_data_layers(year,inputShape,env,headers,f)
Displaying Map¶
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#saving the respons eof api in geojson format
file=open('./jsonfiles/cropdatalayers.json','w')
file.write(json.dumps(crop_layer['results'][0]["value"]))
file.close()
# Helper functions for creating shapefiles
def post_converttogeojson(requestbody):
try:
url = "https://ogre.adc4gis.com/convert"
response = (requests.post(url,files=requestbody).text)
return response
except Exception as e:
raise e
def post_converttoshapefile(requestbody):
try:
url = "https://ogre.adc4gis.com/convertJson"
response = (requests.post(url,data=requestbody))
z = zipfile.ZipFile(io.BytesIO(response.content))
z.extractall("./shapefiles/")
time.sleep(0.5)
return response
except Exception as e:
raise e
In [30]:
requestbody={'upload':open('./jsonfiles/cropdatalayers.json','rb')}
# Function call to convert json to geojson
cropdata_geojson=post_converttogeojson(requestbody)
requestbody={'json':cropdata_geojson,'skipFailures':"on"}
#function call to creatr shapefile from geojson
post_converttoshapefile(requestbody)
# Reading a shapefile and displaying the map
gdf = gpd.read_file('./shapefiles/OGRGeoJSON.shp')
grid_code_mappings=pd.read_csv("cropnames_gridcodes_mappings.csv")
grid_code_mappings.set_index('Code',inplace=True)
gdf['CropName']=gdf['GRIDCODE'].map(grid_code_mappings.to_dict()['CropName'])
gdf.plot(column='CropName', cmap=None,figsize=(10, 10),legend=True)
gdf.head()
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