A COMPARATIVE STUDY OF ALGORITHMS FOR LAND COVER CHANGE
A COMPARATIVE STUDY OF ALGORITHMS FOR LAND COVER CHANGE
SHYAM BORIAH*, VARUN MITHAL*, ASHISH GARG*, VIPIN KUMAR*, MICHAEL STEINBACH*,
CHRIS POTTER**, AND STEVE KLOOSTER***
Abstract. Ecosystem-related observations from remote sensors on satellites offer huge potential
for understanding the location and extent of global land cover change. This paper presents a
comparative study of three time series based algorithms for detecting changes in land cover. The
techniques are evaluated quantitatively using forest fire ground truth from the state of California
for 2000–2009. On relatively high quality data sets, all three schemes perform reasonably well,
but their ability to handle noise and natural variability in the vegetation data differs dramatically.
In particular, one of the algorithms significantly outperforms the other two since it accounts for
variability in the time series.
Complete Metadata
| bureauCode |
[ "026:00" ] |
|---|---|
| identifier | DASHLINK_236 |
| issued | 2010-10-13 |
| landingPage | https://c3.nasa.gov/dashlink/resources/236/ |
| programCode |
[ "026:029" ] |
