 |
| Titel |
MODIS 250m burned area mapping based on an algorithm using change point detection and Markov random fields. |
| VerfasserIn |
Bernardo Mota, José Pereira, Manuel Campagnolo, Rebeca Killick |
| Konferenz |
EGU General Assembly 2013
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250080159
|
|
|
|
|
|
| Zusammenfassung |
| Area burned in tropical savannas of Brazil was mapped using MODIS-AQUA daily 250m
resolution imagery by adapting one of the European Space Agency fire_CCI project burned
area algorithms, based on change point detection and Markov random fields. The study area
covers 1,44 Mkm2 and was performed with data from 2005. The daily 1000 m image quality
layer was used for cloud and cloud shadow screening. The algorithm addresses each pixel as
a time series and detects changes in the statistical properties of NIR reflectance values, to
identify potential burning dates. The first step of the algorithm is robust filtering, to exclude
outlier observations, followed by application of the Pruned Exact Linear Time (PELT) change
point detection technique. Near-infrared (NIR) spectral reflectance changes between time
segments, and post change NIR reflectance values are combined into a fire likelihood
score. Change points corresponding to an increase in reflectance are dismissed as
potential burn events, as are those occurring outside of a pre-defined fire season. In the
last step of the algorithm, monthly burned area probability maps and detection
date maps are converted to dichotomous (burned-unburned maps) using Markov
random fields, which take into account both spatial and temporal relations in the
potential burned area maps. A preliminary assessment of our results is performed by
comparison with data from the MODIS 1km active fires and the 500m burned area
products, taking into account differences in spatial resolution between the two sensors. |
|
|
|
|
|
|