Mapping burned area at relatively high spatio-temporal resolution is important to assess the causes and consequences of landscape fire in forest ecosystems. A simple algorithm, Burned Area Extraction and Dating (BAED) algorithm, was developed to automatically extract burned patches and determine approximate date of fire occurrence for each burned perimeter. Burned perimeters were extracted by a two stage approach, including determining “core burned” pixels and shape of the burned patches, from successive Landsat images. A time series model that has components of seasonality and trend was fitted from MODIS (MODerate-resolution Imaging Spectroradiometer) NDVI (Normalized Difference Vegetation Index) product. The approximate date of fire occurrence for each burned patch was assigned when the difference between the observed NDVI and the predicted NDVI from the time series model exceeded a threshold for three consecutive times. The BAED algorithm was tested in Siberian larch forest, an ecosystem with unique fire regime and considerable contribution to the global carbon balance. The results suggested that correct rate detected by BAED algorithm increases sharply when fire size < 200 ha, and then levels at 90% thereafter. The BAED provides ecologists an easy way to map burned area for assessing ecological effects of landscape fire in Landsat data poor regions.
|Number of pages||27|
|Journal||European Journal of Remote Sensing|
|State||Published - Dec 13 2016|
Bibliographical noteFunding Information:
This research was funded by National Natural Science Foundation of China (31100345 and 31470517) and CAS Pioneer Hundred Talents Program. The BAED algorithm was coded in R programming language, and available at https://github.com/liuzh811/BurnedAreaRS.git.
© 2016 by the authors; licensee Italian Society of Remote Sensing (AIT).
- Boreal forest
- Landscape ecology
- Remote sensing
ASJC Scopus subject areas
- Environmental Science (all)
- Computers in Earth Sciences
- Atmospheric Science
- Applied Mathematics