Harmonized Landsat Sentinel Service

API change history

The Harmonized Landsat-Sentinel Service API produces high-resolution imagery and NDVI data for a desired area-of-interest. From NASA, the Harmonized Landsat-Sentinel-2 project is an initiative to produce a consistent, harmonized surface reflectance product from Landsat and Sentinel-2 data.

HLS Service

The Harmonized Landsat and Sentinel-2 (HLS) is a NASA initiative to produce a Virtual Constellation (VC) of surface reflectance (SR) data from the Operational Land Imager (OLI) and MultiSpectral Instrument (MSI) onboard the Landsat 8 and Sentinel-2 remote sensing satellites, respectively. The data from these satellites creates unprecedented opportunities for timely and accurate observation of Earth status and dynamics at moderate (<30 m) spatial resolution every 2-3 days.

The Ag-Analytics HLS API provides the service which a user can provide a polygon in specific formats in additional with more customized options to retrieve the dynamics of their land at various times for Landsat from 2013 and Sentinel-2 from 2015 calendar years. Additionally, this service also provides information on cloud cover, statistics, Normalized Difference Vegetation Index in addition to MSI bands information.


Harmonised Landsat Sentinel Data in Ag-Analytics FarmScope.



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Call API

Request

Request URL

Request headers

  • (optional)
    string

Request body

aoi: "{"type":"Feature","geometry":{"type":"Polygon","coordinates":[[[-79.686546,41.78304],[-79.686533,41.782839],[-79.68684,41.782599],[-79.687885,41.781732],[-79.688636,41.781147],[-79.689531,41.780429],[-79.69046,41.779711],[-79.690827,41.779434],[-79.691645,41.778854],[-79.69182,41.778718],[-79.692253,41.779078],[-79.692508,41.779297],[-79.692567,41.779379],[-79.692592,41.77945],[-79.692527,41.779657],[-79.692452,41.779944],[-79.69237,41.78057],[-79.692333,41.780677],[-79.692288,41.780767],[-79.692165,41.780895],[-79.69211,41.781027],[-79.692045,41.781272],[-79.692041,41.781472],[-79.692029,41.781608],[-79.691868,41.781904],[-79.691715,41.782199],[-79.691598,41.782405],[-79.691478,41.782805],[-79.691406,41.782924],[-79.691335,41.783033],[-79.691238,41.783129],[-79.691107,41.783202],[-79.690743,41.783236],[-79.690137,41.783291],[-79.689834,41.78332],[-79.689652,41.783311],[-79.689411,41.783273],[-79.689204,41.783264],[-79.688927,41.783261],[-79.688676,41.783284],[-79.688382,41.783281],[-79.688288,41.783267],[-79.688038,41.783238],[-79.687969,41.783218],[-79.687822,41.783216],[-79.687597,41.783226],[-79.687424,41.783224],[-79.687262,41.783145],[-79.687082,41.783065],[-79.686857,41.783063],[-79.686546,41.78304]]]},"properties":{"OBJECTID":22751350,"CALCACRES":32.43000031,"CALCACRES2":null},"id":22751350}"

aoi=%7B%22type%22%3A%22Feature%22%2C%22geometry%22%3A%7B%22type%22%3A%22Polygon%22%2C%22coordinates%22%3A%5B%5B%5B-93.531133%2C42.209365%5D%2C%5B-93.531193%2C42.216571%5D%2C%5B-93.521469%2C42.216616%5D%2C%5B-93.521532%2C42.209364%5D%2C%5B-93.525625%2C42.209368%5D%2C%5B-93.525637%2C42.21082%5D%2C%5B-93.527329%2C42.210813%5D%2C%5B-93.527317%2C42.20936%5D%2C%5B-93.531133%2C42.209365%5D%5D%5D%7D%2C%22properties%22%3A%7B%22OBJECTID%22%3A3352084%2C%22CALCACRES%22%3A152.63000488%2C%22CALCACRES2%22%3Anull%7D%2C%22id%22%3A3352084%7D&Band=%5B'NDVI'%5D&Enddate=7%2F31%2F2019&Startdate=7%2F25%2F2019&legendtype=Relative&satellite=Landsat

Responses

200 OK

Representations

[
  {
    "band": "NIR",
    "download_url": "downloads/result_raster_20190719_163615_1374.tif",
    "features": [
      {
        "attributes": {
          "CellSize": [
            1E-05,
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          ],
          "CoordinateSystem": "GEOGCS[\"WGS 84\",DATUM[\"WGS_1984\",SPHEROID[\"WGS 84\",6378137,298.257223563,AUTHORITY[\"EPSG\",\"7030\"]],AUTHORITY[\"EPSG\",\"6326\"]],PRIMEM[\"Greenwich\",0,AUTHORITY[\"EPSG\",\"8901\"]],UNIT[\"degree\",0.0174532925199433,AUTHORITY[\"EPSG\",\"9122\"]],AUTHORITY[\"EPSG\",\"4326\"]]",
          "Extent": "-87.91751032820102, 40.14826234941817, -87.91357032820102, 40.15643234941817",
          "Legend": [
            {
              "Area": "40.4 %",
              "Count": 129095,
              "CountAllPixels": 319546,
              "Max": 2504.07814534505,
              "Mean": 2238.03986612956,
              "Min": 1972.00158691406,
              "color": "#ff66ff"
            },
            {
              "Area": "12.58 %",
              "Count": 40196,
              "CountAllPixels": 319546,
              "Max": 3036.15470377604,
              "Mean": 2770.11642456055,
              "Min": 2504.07814534505,
              "color": "#ff00ff"
            },
            {
              "Area": "12.41 %",
              "Count": 39652,
              "CountAllPixels": 319546,
              "Max": 3568.23126220703,
              "Mean": 3302.19298299154,
              "Min": 3036.15470377604,
              "color": "#6666ff"
            },
            {
              "Area": "11.61 %",
              "Count": 37106,
              "CountAllPixels": 319546,
              "Max": 4100.30782063802,
              "Mean": 3834.26954142253,
              "Min": 3568.23126220703,
              "color": "#0000ff"
            },
            {
              "Area": "15.11 %",
              "Count": 48285,
              "CountAllPixels": 319546,
              "Max": 4632.38437906901,
              "Mean": 4366.34609985352,
              "Min": 4100.30782063802,
              "color": "#ff6666"
            },
            {
              "Area": "7.89 %",
              "Count": 25212,
              "CountAllPixels": 319546,
              "Max": 5164.4609375,
              "Mean": 4898.42265828451,
              "Min": 4632.38437906901,
              "color": "#ff0000"
            }
          ],
          "Matrix": [
            817,
            394
          ],
          "Max": 5164.4609375,
          "Mean": 3128.27420852874,
          "Min": 1972.00158691406,
          "Percentile5": 2036.31546020508,
          "Percentile95": 4768.91760253906,
          "pngb64": "data:image/png;base64, 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"
        }
      }
    ],
    "flattened_raster": "Error: not possible calculate flattened raster",
    "tiledate": "2019-06-26T00:00:00.0000000+00:00",
    "tilenames": [
      "L309/HLS.L30.T16TDK.2019177.v1.4_05.tif"
    ]
  },
  {
    "band": "Red",
    "download_url": "downloads/result_raster_20190719_163615_9237.tif",
    "features": [
      {
        "attributes": {
          "CellSize": [
            1E-05,
            -1E-05
          ],
          "CoordinateSystem": "GEOGCS[\"WGS 84\",DATUM[\"WGS_1984\",SPHEROID[\"WGS 84\",6378137,298.257223563,AUTHORITY[\"EPSG\",\"7030\"]],AUTHORITY[\"EPSG\",\"6326\"]],PRIMEM[\"Greenwich\",0,AUTHORITY[\"EPSG\",\"8901\"]],UNIT[\"degree\",0.0174532925199433,AUTHORITY[\"EPSG\",\"9122\"]],AUTHORITY[\"EPSG\",\"4326\"]]",
          "Extent": "-87.91751032820102, 40.14826234941817, -87.91357032820102, 40.15643234941817",
          "Legend": [
            {
              "Area": "43.72 %",
              "Count": 139712,
              "CountAllPixels": 319546,
              "Max": 1187.03823852539,
              "Mean": 901.299850463867,
              "Min": 615.561462402344,
              "color": "#ffcccc"
            },
            {
              "Area": "16.03 %",
              "Count": 51217,
              "CountAllPixels": 319546,
              "Max": 1758.51501464844,
              "Mean": 1472.77662658691,
              "Min": 1187.03823852539,
              "color": "#ff9999"
            },
            {
              "Area": "10.26 %",
              "Count": 32793,
              "CountAllPixels": 319546,
              "Max": 2329.99179077148,
              "Mean": 2044.25340270996,
              "Min": 1758.51501464844,
              "color": "#ff6666"
            },
            {
              "Area": "13.34 %",
              "Count": 42634,
              "CountAllPixels": 319546,
              "Max": 2901.46856689453,
              "Mean": 2615.73017883301,
              "Min": 2329.99179077148,
              "color": "#ff3333"
            },
            {
              "Area": "10.96 %",
              "Count": 35023,
              "CountAllPixels": 319546,
              "Max": 3472.94534301758,
              "Mean": 3187.20695495605,
              "Min": 2901.46856689453,
              "color": "#ff6666"
            },
            {
              "Area": "5.69 %",
              "Count": 18167,
              "CountAllPixels": 319546,
              "Max": 4044.42211914063,
              "Mean": 3758.6837310791,
              "Min": 3472.94534301758,
              "color": "#ff0000"
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          ],
          "Matrix": [
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            394
          ],
          "Max": 4044.42211914063,
          "Mean": 1744.29493687106,
          "Min": 615.561462402344,
          "Percentile5": 699.947814941406,
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"
        }
      }
    ],
    "flattened_raster": "Error: not possible calculate flattened raster",
    "tiledate": "2019-06-26T00:00:00.0000000+00:00",
    "tilenames": [
      "L309/HLS.L30.T16TDK.2019177.v1.4_04.tif"
    ]
  },
  {
    "band": "NDVI",
    "download_url": "downloads/result_raster_20190719_163615_8965.tif",
    "features": [
      {
        "attributes": {
          "CellSize": [
            1E-05,
            -1E-05
          ],
          "CoordinateSystem": "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\",\"4326\"]]",
          "Extent": "-87.91751032820102, 40.14826234941817, -87.91357032820102, 40.15643234941817",
          "Legend": [
            {
              "Area": "16.41 %",
              "Count": 52814,
              "CountAllPixels": 321898,
              "Max": 0.190133181028347,
              "Mean": 0.155879547496601,
              "Min": 0.121625913964854,
              "color": "#ff0000"
            },
            {
              "Area": "16.81 %",
              "Count": 54112,
              "CountAllPixels": 321898,
              "Max": 0.258640448091841,
              "Mean": 0.224386814560094,
              "Min": 0.190133181028347,
              "color": "#ff6666"
            },
            {
              "Area": "11.3 %",
              "Count": 36390,
              "CountAllPixels": 321898,
              "Max": 0.327147715155334,
              "Mean": 0.292894081623587,
              "Min": 0.258640448091841,
              "color": "#ffff66"
            },
            {
              "Area": "20.23 %",
              "Count": 65126,
              "CountAllPixels": 321898,
              "Max": 0.395654982218827,
              "Mean": 0.361401348687081,
              "Min": 0.327147715155334,
              "color": "#ffff00"
            },
            {
              "Area": "24.3 %",
              "Count": 78236,
              "CountAllPixels": 321898,
              "Max": 0.46416224928232,
              "Mean": 0.429908615750574,
              "Min": 0.395654982218827,
              "color": "#66ff66"
            },
            {
              "Area": "10.21 %",
              "Count": 32868,
              "CountAllPixels": 321898,
              "Max": 0.532669516345814,
              "Mean": 0.498415882814067,
              "Min": 0.46416224928232,
              "color": "#00ff00"
            }
          ],
          "Matrix": [
            817,
            394
          ],
          "Max": 0.532669516345814,
          "Mean": 0.326934527835111,
          "Min": 0.121625913964854,
          "Percentile5": 0.149247766626636,
          "Percentile95": 0.487226303880616,
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"
        }
      }
    ],
    "flattened_raster": "Error: not possible calculate flattened raster",
    "tiledate": "2019-06-26T00:00:00.0000000+00:00",
    "tilenames": [
      [
        "/home/aganalyticshls/AgAnalyticsMain/HLSserviceapp/server/downloads/result_raster_20190719_163615_1374.tif",
        5
      ],
      [
        "/home/aganalyticshls/AgAnalyticsMain/HLSserviceapp/server/downloads/result_raster_20190719_163615_9237.tif",
        4
      ]
    ]
  }
]

Code samples

@ECHO OFF

curl -v -X POST "https://ag-analytics.azure-api.net/hls-service/"
-H "Content-Type: application/x-www-form-urlencoded"

--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/hls-service/?" + 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/hls-service/");


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


            // 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/hls-service/?" + $.param(params),
            beforeSend: function(xhrObj){
                // Request headers
                xhrObj.setRequestHeader("Content-Type","application/x-www-form-urlencoded");
            },
            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/hls-service/";
    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/x-www-form-urlencoded" 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/hls-service/');
$url = $request->getUrl();

$headers = array(
    // Request headers
    'Content-Type' => 'application/x-www-form-urlencoded',
);

$request->setHeader($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/x-www-form-urlencoded',
}

params = urllib.urlencode({
})

try:
    conn = httplib.HTTPSConnection('ag-analytics.azure-api.net')
    conn.request("POST", "/hls-service/?%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/x-www-form-urlencoded',
}

params = urllib.parse.urlencode({
})

try:
    conn = http.client.HTTPSConnection('ag-analytics.azure-api.net')
    conn.request("POST", "/hls-service/?%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/hls-service/')


request = Net::HTTP::Post.new(uri.request_uri)
# Request headers
request['Content-Type'] = 'application/x-www-form-urlencoded'
# 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