A COMPARATIVE STUDY OF ALGORITHMS FOR LAND COVER CHANGE

Description

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.

Resources

Name Format Description Link
Paper 14 .pdf PDF A COMPARATIVE STUDY OF ALGORITHMS FOR LAND COVER CHANGE Open resource
View documentation related to this dataset HTML Includes a user's guide, supplemental documents like ATBDs and academic papers, How Tos, FAQs, etc. Open resource
This dataset's landing page HTML Provides access to data, documentation, tools, citation information, support, and other resources. Open resource
Download this dataset HTML Direct download via HTTPS protocol. Open resource
Download this dataset HTML Search and filter data files using a map-based interface Open resource
Google Scholar search results HTML Search results for publications that cite this dataset by its DOI. Open resource
Download this dataset through Earthdata Search HTML NASA's newest search and order tool for subsetting, reprojecting, and reformatting data. Open resource

Tags

Topics

Categories