Name
Title | ||
|---|---|---|
Large-scale crop mapping from multi-source optical satellite imageries using machine learning with discrete grids |
Abstract | ||
|---|---|---|
•Enhancing the space–time coverage with multi-source optical satellite data.•Automatic feature selection using machine learning improves the mapping accuracy.•Discrete grids technology improves the efficiency of large-scale data computing.•A comprehensive application case proves the advantages of the proposed scheme. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.jag.2021.102485 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | DocType | Volume |
Crop Mapping,Large-Scale,Remote Sensing,Machine Learning,Discrete Grids | Journal | 103 |
ISSN | Citations | PageRank |
1569-8432 | 2 | 0.43 |
References | Authors | |
0 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuai Yan | 1 | 2 | 0.77 |
| xiaochuang yao | 2 | 19 | 6.44 |
| De Hai Zhu | 3 | 102 | 23.81 |
| Diyou Liu | 4 | 2 | 0.43 |
| lin zhang | 5 | 2 | 2.80 |
| Guojiang Yu | 6 | 2 | 0.77 |
| Bingbo Gao | 7 | 2 | 0.43 |
| Jianyu Yang | 8 | 429 | 78.51 |
| Wenju Yun | 9 | 30 | 5.09 |