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

# paths./.post.description
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

Documentation

Github Repo

Notebook

Sample API Specifications

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

Request Parameters ▼

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 ▼

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.

Examples ▼

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”

# paths./.get.description
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

Documentation

Github Repo

Notebook

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

GET Request

Parameter | Description | Example | Request

filename

File name to download. From POST request.
Only request a single file at a time.

result_tillageraster_ 20191126 _175158_3291.tif

https://ag-analytics.azure-api.net/tillage-model/?filename=result_tillageraster_%2020191126%20_175158_3291.tif

# paths./.get.parameters[].description
File name of the file from POST TillageAI API.