•  
  •  
 

Creative Commons License

Creative Commons Attribution-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-No Derivative Works 3.0 License.

Abstract

The use of Change Vector Analysis (CVA) combined with the Tasselled Cap tranform (TCT) is a powerful remote sensing tool to monitor forests and vegetated areas, but its application to arid and semiarid environment is not straightforward.

This question is tackled through the calculation of a new set of TCT coefficients using R and GRASS-GIS for SPOT and Landsat satellites, then applied and tested in change detection analysis on a short (seasonal) and a long (decades) temporal scale.

Results show that the combined procedure is an effective method to detect changes in desert environment. Furthermore, the new TCT allows the use of this combined procedure for studies in arid and semi-arid regions, eliminating the doubts on its compatibility with the area of study.

Further development is the creation of a new GRASS-GIS module to performe CVA, thus enabling the simple usage of this technique, until now not available in most common software.

DOI

https://doi.org/10.7275/R51V5C55

Share

COinS
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.