Sample project: establishing a global forest monitoring capability using multi-resolution and multi-temporal remotely sensed data sets
The NASA LCLUC Program: an interdisciplinary approach to studying land-cover and land-use change
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Abstract
Quantifying rates of forest-cover change is important for improved carbon accounting and climate change modeling, management of forestry and agricultural resources, and biodiversity monitoring. A practical solution to examining trends in forest cover change at global scale is to employ remotely sensed data. Satellite-based monitoring of forest cover can be implemented consistently across large regions at annual and inter-annual intervals. This research extends previous research on global forest-cover dynamics and land-cover change estimation to establish a robust, operational forest monitoring and assessment system. The approach integrates both MODIS and Landsat data to provide timely biome-scale forest change estimation. This is achieved by using annual MODIS change indicator maps to stratify biomes into low, medium and high change categories. Landsat image pairs can then be sampled within these strata and analyzed for estimating area of forest cleared.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Sample project: establishing a global forest monitoring capability using multi-resolution and multi-temporal remotely sensed data sets |
| Series title | The NASA LCLUC Program: an interdisciplinary approach to studying land-cover and land-use change |
| Year Published | 2009 |
| Language | English |
| Publisher | University of Maryland |
| Publisher location | College Park |
| Contributing office(s) | Earth Resources Observation and Science (EROS) Center |
| Description | 1 p. |
| Larger Work Type | Report |
| Larger Work Subtype | Other Report |
| Larger Work Title | The NASA LCLUC Program: an interdisciplinary approach to studying land-cover and land-use change |
| First page | 3 |
| Last page | 3 |
| Google Analytic Metrics | Metrics page |