| Full text | |
| Author(s): |
Shimabukuro, Yosio Edemir
;
Arai, Egidio
;
da Silva, Gabriel Maximo
;
Dutra, Andeise Cerqueira
;
Verola Mataveli, Guilherme Augusto
;
Duarte, Valdete
;
Martini, Paulo Roberto
;
IEEE
Total Authors: 8
|
| Document type: | Journal article |
| Source: | 2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022); v. N/A, p. 4-pg., 2022-01-01. |
| Abstract | |
This article presents a method to map the extent of forest plantation in an area located in the Sao Paulo State (Brazil). The proposed method applies the Linear Spectral Mixing Model (LSMM) to Landsat Thematic Mapper (TM) datasets to derive annually vegetation, soil and shade fraction images for local analysis. We used 30 m annual mosaics of TM images during the 1985 to 1995 time period. These fraction images have the advantage to reduce the volume of data to be analyzed highlighting the target characteristics. Then, we generated only one mosaic for each fraction images for TM dataset computing de maximum value through this period, facilitating the classification of areas occupied by forest plantation. The proposed method allowed to classify two forest plantation classes: Eucalypt and Pine. In addition, it allowed to monitor the phenological stages of Eucalypt according to its growth cycle. The results are very important for planning and management by the commercial companies and can contribute to develop an automatic method to map forest plantation areas in a regional and global scales. (AU) | |
| FAPESP's process: | 19/19371-5 - Spatial-temporal analysis of land use and land cover in the São Paulo state using remote sensing techniques |
| Grantee: | Yosio Edemir Shimabukuro |
| Support Opportunities: | Regular Research Grants |