Ajorlo, M and Abdullah, Ramdzani and Mohd Hanif, Ahmad Husni and Abd Halim, Mohd Ridzwan and Yusoff, Mohd. Kamil (2009) A model-based approach for mapping rangelands covers using Landsat TM image data. Caspian Journal of Enviromental Science , 7 (1). pp. 1-7. ISSN 1735-3033
Full text not available from this repository.
Official URL: http://research.guilan.ac.ir/cjes/.papers/1291.pdf
Empirical models are important tools for relating field-measured biophysical variables to remotely sensed data. Regression analysis has been a popular empirical method of linking these two types of data to estimate variables such as biomass, percent vegetation canopy cover, and bare soil. This study was conducted in a semi-arid rangeland ecosystem of Qazvin province, Iran. This paper presents the development of a regression model for predicting rangeland biophysical variables using the original image data of Landsat TM nonthermal bands. The biophysical variables of interest within the rangeland ecosystem were percent vegetation canopy cover, bare soil extent, and stone and gravel which their correlations were analyzed in relation to Landsat TM original data. The results of applying stepwise multiple regression showed that there is a significant correlation between Landsat TM band 2 reflectance values and biophysical variables. The developed models were applied to Landsat TM band 2 and relevant maps were generated. We concluded that such problems as an inexact location of field samples on the image, small size of samples, vegetation heterogeneity may significantly affect the modeling of real rangeland Landsat TM data relationships.
|Keyword:||Biophysical variables; Empirical model; Multiple regression; Rangeland.|
|Subject:||Rangelands - Maps.|
|Subject:||Rangelands - Remote sensing.|
|Faculty or Institute:||Faculty of Agriculture|
|Publisher:||The University of Guilan, Printed in I.R. Iran|
|Deposited By:||Norhazura Hamzah|
|Deposited On:||08 Dec 2011 07:44|
|Last Modified:||08 Dec 2011 07:44|
Repository Staff Only: Edit item detail
Document Download Statistics
This item has been downloaded for since 08 Dec 2011 07:44.