TillageAI - BETA

This API is in BETA. Please contact us to demo this API, or for more information on production scale models.

Tillage Identification

The Ag-Analytics® TillageAI API predicts whether or not a provided field has been tilled. The underlying Tillage Model has trained on millions of acres of ground-truth precision data coupled with SAR data, Harmonized Landsat-Sentinel multispectral satellite data, and other data streams. Our models are highly configurable and can incorporate a wide variety of data sources. They are driven by millions of acres-years of precision ag data, which provides unparalleled ground-truth to maximize model efficacy. Please contact us for more information on custom production scale models at support@analytics.ag.


Example of Tillage Identification

 

Sample API Specifications

Please contact us to demo our tillage models. See sample API call below.

Request Parameters


Parameter Data Type Required? Default Options Description
SHAPE Geometry, file/text Yes - Geojson Desired area-of-interest, see Fig. 1 for example.
ModelType Text String No Neural Network "NN" (Neural Network)
"TREE" (Decision Tree)
Type of model to use for prediction. Default is "NN". Not necessary to specify for most cases.
TillageStartDate Text Yes - Date String
"mm/dd/yyyy"
The date that tillage began. Must be in years {2014, 2015, 2016, 2017, 2018}. For 2019,
must be more than 3 weeks prior to the current date.Ex. "04/23/2017"
ScalarVariables Dictionary Yes - - Wrapper dictionary for any variables that need to be included along with ModelType and SHAPE.
Does not have a value itself. Please see sample request for clarification.

Response Parameters


Parameter Data Type Description
feature_averages Dictionary Average value of each input used to predict tillage.
raster_filename String URL to use in GET request to retrieve predicted raster file.
rasterinfo List of Dictionaries Container for the features and metadata information for the raster.
attributes Dictionary Container for specific features regarding the tillage prediction raster.
CellSize List Size of a single cell in the raster in degrees. (0.0001, -0.0001) roughly corresponds to an 8 meter by 8
meter square on the Earth’s equator. (i.e., 0.0001 degrees ~= 8 meters)
CoordinateSystem String Information about the coordinate system being used for calculations.
Extent String Specifies the left bottom corner and right top corner in longitude and latitude respectively.
Legend List of Dictionaries List of the metadata features for the areas of the field that returned as till or no-till or both.
Area Float Specifies the number of acres that were till or no-till for a given field.
AreaPercent String Specifies a percentage of the field that returned either till or no-till. For example, if 50% of the field is “till”,
then Area is 50%.
Count Integer Number of pixels that returned as till or no-till. Used to calculate area.
CountAllPixels Integer Total number of pixels that make up the field in the predicted tillage raster.
Till String Specifies whether the given section (or entire area) of the field has been tilled. Returns “Yes” for tillage
and “No” for tillage not detected.
Value Integer Binary value for tillage detected or not. Tillage detected = 1, Tillage not detected = 0.
color String Color that can be used to display the feature when plotting in a GIS application. (Hexadecimal)
pngb64 String PNG image of the tillage raster encoded as base64. Actual raster file can be obtained with a
GET request to the service.

Parameter Examples

ModelType

“NN”

SHAPE
JSON
"{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-89.199484,40.972729],[-89.199773,40.97258],[-89.200135,40.972415],[-89.20034,40.972318],[-89.200445,40.972177],[-89.200439,40.972001]]]},\"properties\":{\"OBJECTID\":5134895,\"CALCACRES\":122.651351,\"CALCACRES2\":null},\"id\":4861522}""

TillageStartDate

“04/23/2017”



Call API

Request

Request URL

Request headers

  • (optional)
    string

Request body

{
"ModelType": "RF",
"SHAPE": "{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[ [ [-85.530165756639363, 41.003585131948597], [-85.520434643189319, 41.003807344585127], [-85.520353401853086, 40.999164864997709], [-85.523662529524572, 40.998736874798666], [-85.522491522109163, 40.997877961142841], [-85.52301570506603, 40.997135046630873], [-85.529932360326256, 40.996987366356251], [-85.530165756639363, 41.003585131948597] ] ]},\"properties\":{\"OBJECTID\":5102679,\"CALCACRES\":145.08999634,\"CALCACRES2\":null},\"id\":5102679}",
"ScalarVariables": {
"TillageStartDate": "04-23-2017"
}
}

Code samples

@ECHO OFF

curl -v -X POST "https://ag-analytics.azure-api.net/tillage-model/"
-H "Content-Type: application/json"

--data-ascii "{body}" 
using System;
using System.Net.Http.Headers;
using System.Text;
using System.Net.Http;
using System.Web;

namespace CSHttpClientSample
{
    static class Program
    {
        static void Main()
        {
            MakeRequest();
            Console.WriteLine("Hit ENTER to exit...");
            Console.ReadLine();
        }
        
        static async void MakeRequest()
        {
            var client = new HttpClient();
            var queryString = HttpUtility.ParseQueryString(string.Empty);

            // Request headers

            var uri = "https://ag-analytics.azure-api.net/tillage-model/?" + queryString;

            HttpResponseMessage response;

            // Request body
            byte[] byteData = Encoding.UTF8.GetBytes("{body}");

            using (var content = new ByteArrayContent(byteData))
            {
               content.Headers.ContentType = new MediaTypeHeaderValue("< your content type, i.e. application/json >");
               response = await client.PostAsync(uri, content);
            }

        }
    }
}	
// // This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
import java.net.URI;
import org.apache.http.HttpEntity;
import org.apache.http.HttpResponse;
import org.apache.http.client.HttpClient;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.utils.URIBuilder;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;

public class JavaSample 
{
    public static void main(String[] args) 
    {
        HttpClient httpclient = HttpClients.createDefault();

        try
        {
            URIBuilder builder = new URIBuilder("https://ag-analytics.azure-api.net/tillage-model/");


            URI uri = builder.build();
            HttpPost request = new HttpPost(uri);
            request.setHeader("Content-Type", "application/json");


            // Request body
            StringEntity reqEntity = new StringEntity("{body}");
            request.setEntity(reqEntity);

            HttpResponse response = httpclient.execute(request);
            HttpEntity entity = response.getEntity();

            if (entity != null) 
            {
                System.out.println(EntityUtils.toString(entity));
            }
        }
        catch (Exception e)
        {
            System.out.println(e.getMessage());
        }
    }
}

<!DOCTYPE html>
<html>
<head>
    <title>JSSample</title>
    <script src="http://ajax.googleapis.com/ajax/libs/jquery/1.9.0/jquery.min.js"></script>
</head>
<body>

<script type="text/javascript">
    $(function() {
        var params = {
            // Request parameters
        };
      
        $.ajax({
            url: "https://ag-analytics.azure-api.net/tillage-model/?" + $.param(params),
            beforeSend: function(xhrObj){
                // Request headers
                xhrObj.setRequestHeader("Content-Type","application/json");
            },
            type: "POST",
            // Request body
            data: "{body}",
        })
        .done(function(data) {
            alert("success");
        })
        .fail(function() {
            alert("error");
        });
    });
</script>
</body>
</html>
#import <Foundation/Foundation.h>

int main(int argc, const char * argv[])
{
    NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
    
    NSString* path = @"https://ag-analytics.azure-api.net/tillage-model/";
    NSArray* array = @[
                         // Request parameters
                         @"entities=true",
                      ];
    
    NSString* string = [array componentsJoinedByString:@"&"];
    path = [path stringByAppendingFormat:@"?%@", string];

    NSLog(@"%@", path);

    NSMutableURLRequest* _request = [NSMutableURLRequest requestWithURL:[NSURL URLWithString:path]];
    [_request setHTTPMethod:@"POST"];
    // Request headers
    [_request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
    // Request body
    [_request setHTTPBody:[@"{body}" dataUsingEncoding:NSUTF8StringEncoding]];
    
    NSURLResponse *response = nil;
    NSError *error = nil;
    NSData* _connectionData = [NSURLConnection sendSynchronousRequest:_request returningResponse:&response error:&error];

    if (nil != error)
    {
        NSLog(@"Error: %@", error);
    }
    else
    {
        NSError* error = nil;
        NSMutableDictionary* json = nil;
        NSString* dataString = [[NSString alloc] initWithData:_connectionData encoding:NSUTF8StringEncoding];
        NSLog(@"%@", dataString);
        
        if (nil != _connectionData)
        {
            json = [NSJSONSerialization JSONObjectWithData:_connectionData options:NSJSONReadingMutableContainers error:&error];
        }
        
        if (error || !json)
        {
            NSLog(@"Could not parse loaded json with error:%@", error);
        }
        
        NSLog(@"%@", json);
        _connectionData = nil;
    }
    
    [pool drain];

    return 0;
}
<?php
// This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
require_once 'HTTP/Request2.php';

$request = new Http_Request2('https://ag-analytics.azure-api.net/tillage-model/');
$url = $request->getUrl();

$headers = array(
    // Request headers
    'Content-Type' => 'application/json',
);

$request->setHeader($headers);

$parameters = array(
    // Request parameters
);

$url->setQueryVariables($parameters);

$request->setMethod(HTTP_Request2::METHOD_POST);

// Request body
$request->setBody("{body}");

try
{
    $response = $request->send();
    echo $response->getBody();
}
catch (HttpException $ex)
{
    echo $ex;
}

?>
########### Python 2.7 #############
import httplib, urllib, base64

headers = {
    # Request headers
    'Content-Type': 'application/json',
}

params = urllib.urlencode({
})

try:
    conn = httplib.HTTPSConnection('ag-analytics.azure-api.net')
    conn.request("POST", "/tillage-model/?%s" % params, "{body}", headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

####################################

########### Python 3.2 #############
import http.client, urllib.request, urllib.parse, urllib.error, base64

headers = {
    # Request headers
    'Content-Type': 'application/json',
}

params = urllib.parse.urlencode({
})

try:
    conn = http.client.HTTPSConnection('ag-analytics.azure-api.net')
    conn.request("POST", "/tillage-model/?%s" % params, "{body}", headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

####################################
require 'net/http'

uri = URI('https://ag-analytics.azure-api.net/tillage-model/')


request = Net::HTTP::Post.new(uri.request_uri)
# Request headers
request['Content-Type'] = 'application/json'
# Request body
request.body = "{body}"

response = Net::HTTP.start(uri.host, uri.port, :use_ssl => uri.scheme == 'https') do |http|
    http.request(request)
end

puts response.body