Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine
Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used to estimate agricultural productivity as well as degree of disturbance on food security from natural disasters and political conflict. However, existing cropland extent maps over large areas (e.g., Country, region, continent, world) are derived from coarse resolution imagery (250 m to 1 km pixels) and have many limitations such as missing fragmented and\or small farms with mixed signatures from different crop types and\or farming practices that can be, confused with other land cover. As a result, the coarse resolution maps have limited useflness in areas where fields are small (
Citation Information
| Publication Year | 2019 |
|---|---|
| Title | Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine |
| DOI | 10.1016/j.jag.2018.11.014 |
| Authors | Adam Oliphant, Prasad Thenkabail, Pardhasaradhi Teluguntla, Jun Xiong, Murali Gumma, Russell Congalton, Kamini Yadav |
| Publication Type | Article |
| Publication Subtype | Journal Article |
| Series Title | International Journal of Applied Earth Observation and Geoinformation |
| Index ID | 70203561 |
| Record Source | USGS Publications Warehouse |
| USGS Organization | Western Geographic Science Center |