Title

Accuracy of Land Cover Maps Derived From Remotely Sensed Data

Authors

Daniel Unger, Arthur Temple College of Forestry and Agriculture, Stephen F. Austin State UniversityFollow
Bonnie Brown, Arthur Temple College of Forestry and Agriculture, Stephen F. Austin State University
I-Kuai Hung, Arthur Temple College of Forestry and Agriculture, Stephen F. Austin State UniversityFollow
Yanli Zhang, Arthur Temple College of Forestry and Agriculture, Stephen F. Austin State UniversityFollow

Document Type

Presentation

Publication Date

3-27-2012

Abstract

Accurate knowledge of land cover and land cover change is essential for a wide range of objectives. Since the 1970's, remotely sensed data have been used increasingly as a means to classify and characterize the earth's land use and land cover. This project compares the accuracy of results of classifying data from mid-level to very high spatial resolutions (Landsat ETM+, SPOT 4, ASTER, SPOT 5, QuickBird). Data from all of these sensors were classified for both urban and rural settings. The project examines accuracy levels between spatial and spectral resolution.

Comments

OBJECTIVES Compare the accuracy of classified maps between satellites of varying spatial and spectral resolutions. Data include 30 meter (Landsat ETM +), 20 meter (SPOT 4), 15 meter (ASTER VNIR), 10 meter (SPOT 5), and 2.44 meters (QuickBird). Two tested hypotheses are:

1 H0 - Spatial resolution of remotely sensed data does not affect the accuracy of classified maps. 2 H0 - Spectral resolution of remotely sensed images does not affect the accuracy of classified maps.

Repository Citation

Unger, Daniel; Brown, Bonnie; Hung, I-Kuai; and Zhang, Yanli, "Accuracy of Land Cover Maps Derived From Remotely Sensed Data" (2012). Faculty Publications. 4.
https://scholarworks.sfasu.edu/spatialsci/4