1. Cropland mapping in South America
Global Food Security-Support Analysis m
Chandra Giri
Ying Zhong
5/21/2015

2. Workflow Continent segmentation Cropland masking
Training data selection
Random Forest classification

3. Continent segmentation
Landsat Tile 56
Landsat tiles segmentation
Ecoregion segmentation
Eco-regions of South America

4. Cropland mask
Landsat Tile 56
Giri, C., & Long, J. (2014)

5. “Cropland” definition
“All cultivated plants harvested for food, feed, and fiber, including plantation.” (Teluguntla et al. 2009)
Is pasture included as a type of cropland?

6. “Cropland” definition
Is rangeland included as a type of cropland?
Google Earth photos

7. Training sample database
Training points selection
Random sample strategy
Reference data
Google Earth – high resolution images and photos
2009 GlobCover
Time-series NDVI composite
Landsat image
Ground truth data – geo-wiki validation and geo-wiki competition

8. Training sample database
Training dataset :
Dataset A: Non-cropland: 129, Cropland: 54
Dataset B: Non-cropland: 44, Cropland: 41

9. Random Forest Classification
Tool: Google Earth Engine
Input bands:
Landsat 5 and 7, band 2, 3, 4

10. Pasture Barren Result from training dataset A:
Non-cropland: 129, Cropland: 54
Result from training dataset B:
Non-cropland: 44, Cropland: 41
Barren
Pasture

11. Classification results
Result from training dataset A
Result from training dataset B

12. Take-home message
The same training sample dataset can have different classification performance in different eco-regions.
Harvested cropland is difficult to be distinguished from barren land.

13. Thoughts Add temporal various images
Classify at eco-region segmentation level
Mosaic best

14. Thank you!