Name
Title | ||
|---|---|---|
Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using a random forest classifier on the Google Earth Engine Cloud |
Abstract | ||
|---|---|---|
•Highest resolution (30-m) Landsat-derived cropland product for Southeast and Northeast Asia.•Unique cropland mapping methods involving petabyte scale computing in cloud.•Random forest machine learning algorithm applied over very large area.•Overall accuracy of 88.6% and producer’s accuracy of 81.6% over entire area.•Public availability of 30-m cropland product, algorithm, codes and reference data. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.jag.2018.11.014 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | Field | DocType |
Southeast Asia,Northeast Asia,Croplands,Food security,Water security,Landsat | Hydrology,Download,Natural disaster,Agriculture,Random forest,Geography,Land cover,Agricultural productivity,Cartography,Cloud computing,Food security | Journal |
Volume | ISSN | Citations |
81 | 0303-2434 | 2 |
PageRank | References | Authors |
0.41 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adam J. Oliphant | 1 | 2 | 0.41 |
| Prasad S. Thenkabail | 2 | 210 | 30.03 |
| Pardhasaradhi Teluguntla | 3 | 2 | 0.41 |
| Jun Xiong | 4 | 149 | 16.30 |
| Murali K. Gumma | 5 | 99 | 15.47 |
| russell g congalton | 6 | 75 | 9.35 |
| kamini yadav | 7 | 65 | 5.54 |