| タイトル |
-
en
Random Forest classification of crop type using multi-temporal TerraSAR-X dual-polarimetric data
|
| 作成者 |
|
| アクセス権 |
open access |
| 主題 |
-
Other
en
crop
-
Other
en
gamma nought
-
Other
en
multi-temporal classification approach
-
Other
en
TerraSAR-X
-
NDC
519
|
| 内容注記 |
-
Abstract
en
The classification maps are required for the management and the estimation of agricultural disaster compensation; however, those techniques have yet to be established. Some supervised learning models may allow accurate classification. In this study, the Random Forest (RF) classifier and the classification and regression tree (CART) were applied to evaluate the potential of multi-temporal TerraSAR-X dualpolarimetric data, on the StripMap mode, for the classification of crop type. Furthermore, comparisons of the two algorithms and polarizations were carried out. In the study area, beans, beet, grasslands, maize, potato and winter wheat were cultivated, and these crop types were classified using the data set acquired in 2009. The classification results of RF were superior to those of CART, and the overall accuracies were 0.91–0.93.
|
| 出版者 |
en
Taylor&Francis
|
| 日付 |
|
| 言語 |
|
| 資源タイプ |
journal article |
| 出版タイプ |
AM |
| 資源識別子 |
HDL
http://hdl.handle.net/2115/57984
|
| 関連 |
-
isVersionOf
DOI
https://doi.org/10.1080/2150704X.2014.889863
|
| 収録誌情報 |
-
-
PISSN
2150-704X
-
EISSN
2150-7058
-
en
Remote Sensing Letters
-
巻5
号2
開始ページ157
終了ページ164
|
| ファイル |
|
| コンテンツ更新日時 |
2023-07-26 |
