Crop Mapping in Stanislaus County using GIS and Remote Sensing

Ramesh Gautam, Jean Woods, Simon Eching, Mohammad Mostafavi

Land Use Section, Division of Statewide Integrated Water Management

California Department of Water Resources

Usefulness of Land Use Mapping

Quantify crop acreage based on crop types

Estimate evapotranspiration

Determine urban landscape acreage

Input for groundwater and surface water

models

Verify fields fallowed for water transfers

Map urban growth patterns

Estimate economic impacts of flooding

Why Remote Sensing Based Crop Mapping is Needed

Reduce the extent of required field mapping by identifying permanent crops

Accurately assess crop acreage

Estimate annual crop water use for the California

Water Plan

Accurately estimate evapotranspiration on a field

level

Determine the annual extent of fallowing

Verify fields fallowed for water transfers

Study Area

Stanislaus CountyArea: 1,515 sq mile

Population: 515,000

Overall Crop Mapping Strategy

All Crops

Decision Tree Based

ClassificationOrchards

Non-Orchards

LCRAS Based

Classification

Time series based

Vegetation Index

Analysis

Corn, Mixed Pasture,

Fallow, Dry Beans, Tomato, Melons

AlfalfaAutocorrelation & LIDAR

Vineyards

Classify orchards from non-orchard crops

Gray Level Co-occurrence Matrix Algorithm was used to classify orchards

Textural patterns distinguish orchards from other crops

eCognition Developer software was used to develop the algorithm

Decision Tree Classification Technique

Data Processing

Textural parameters are analyzed to evaluate the fields having coarse texture versus fine texture

First Level of Classification: Results

Recently planted orchards were classified in next level as shown in next slide

Non-orchards

Orchards

Bare land and new orchardsFarmsteads

Urban area

Poultry farms

Highways/Roads

LEGEND

How recently planted orchards have been captured in second level of classification

Non-orchards

Orchards

Bare land and new orchardsFarmsteads

Urban area

Poultry farms

Highways/Roads

LEGEND

Second Level of Classification: Results

Non-orchards

Orchards

Bare land and new orchardsFarmsteads

Urban area

Poultry farms

Highways/Roads

LEGEND

Final Classification

Mapping Orchards in Stanislaus County

Mapping Non-Orchards using Lower Colorado River Accounting

System (LCRAS)

Ground Truth Survey

Collect Crop Attributes(12% of Total Fields)

QC Ground Truth Data

Update Field Border Database

Develop Personal Geo-database of Ground-truth data in ArcGIS

Randomly Select Training Data (60%)

Perform Image Segmentation in eCognition Developer

for Training Data

Create Signatures in Erdas Imagine

Data Processing

Using eCognition Developer software, crop fields are segmented into polygons of similar spectral characteristics.

LCRAS Classification Method Cont’d…

LANDSAT-5 ImageBands 1-5 and 7

Perform Supervised Classification of Spectral

Characteristics

Identify Crops at the Field Level Based on Classification

Perform Accuracy Assessment

Re-evaluate signature sets

Identify Mislabeled Fields Based on

Ground Truth

Overall Classification ≥ 90%?

Yes

EndNo

Year 2010 Crop Map, Stanislaus County, California

Staff Time Requirements for Crop Classification

Ground Truth Survey15%

Decision Tree Based Classification of Permanent Crops

25%

LCRAS Based Classi-fication of Annual

Crops60%

Questions?