Name
Title | ||
|---|---|---|
Normalizing Landsat and ASTER data using MODIS data products for forest change detection |
Abstract | ||
|---|---|---|
Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one “standard” date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IGARSS.2010.5650978 | IGARSS |
Keywords | Field | DocType |
forest disturbance index,forest change detection,optical remote sensing,image fusion,forestry,normalized images,modis,landsat data normalization,aster data normalization,modis data product,data fusion,moderate resolution images,aster,geophysical image processing,change detection,vegetation mapping,forest cover monitoring,forest,landsat,indexes,thematic mapping,indexation,reflectivity,remote sensing,satellites,forests,earth,spatial resolution,seasonality | Aster (genus),Satellite,Satellite imagery,Change detection,Image fusion,Computer science,Remote sensing,Sensor fusion,Thematic map,Image resolution | Conference |
ISSN | ISBN | Citations |
2153-6996 E-ISBN : 978-1-4244-9564-1 | 978-1-4244-9564-1 | 0 |
PageRank | References | Authors |
0.34 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Feng Gao | 1 | 287 | 40.54 |
| Jeffrey G. Masek | 2 | 287 | 41.41 |
| Robert E. Wolfe | 3 | 371 | 86.53 |
| Bin Tan | 4 | 208 | 39.58 |