IMPROVED IN-SEASON CROP CLASSIFICATION PERFORMANCE USING ENSEMBLE LEARNING TECHNIQUE: A CASE STUDY OF LEKODA INSURANCE UNIT, UJJAIN, MADHYA PRADESH
The classification of agricultural crop types is an important application of remote sensing. With the improvement in spatial, temporal and spectral resolution of satellite data, a complete seasonal crop growth profile and separability between different crop classes can be studied by using ensemble-l...
Збережено в:
| Автори: | , , , |
|---|---|
| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Copernicus Publications
2019-07-01
|
| Серія: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Онлайн доступ: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W6/477/2019/isprs-archives-XLII-3-W6-477-2019.pdf |
| Теги: |
Немає тегів, Будьте першим, хто поставить тег для цього запису!
|