Record Details

Soil Surface Salinity Prediction Using ASTER Data: Comparing Statistical and Geostatistical Models

OAR@ICRISAT

View Archive Info
 
 
Field Value
 
Relation http://oar.icrisat.org/8342/
http://www.insipub.com/ajbas/2010/457-467.pdf
 
Title Soil Surface Salinity Prediction Using ASTER Data: Comparing Statistical and Geostatistical Models
 
Creator Tajgardan, T
Ayoubi, S
Shataee, S
Sahrawat, K L
 
Subject Soil Science
Agriculture-Farming, Production, Technology, Economics
 
Description This study was conducted to evaluate the performance of univariate spatial (ordinary
kriging- OK), hybrid/multivariate geostatistical methods (regression-kriging- RK, Co-kriging- CK) with
multivariate linear regression (MLR) in incorporation with ASTER data in order to predict the spatial
variability of surface soil salinity in an arid area in northern Iran. The primary attributes were obtained
from grid soil sampling with nested-systematic pattern of 169 samples and the secondary information
extracted from spectral data of ASTER satellite images. The principal component analysis, NDVI and
some suitable ratioing bands were applied to generate new arithmetic bands. According to validation
based RMSE and ME calculated by a validation data set, the predictions for soil salinity were found
to be the best and varied in the following order: RK ASTERmultivariate > REG ASTERmultivariate > Co-kriging
ASTER> kriging. Overall, this comparative study demonstrated that RK approach was a better predicator
than other selected methods to predict spatial variability of soil salinity. The overall results confirmed
that using ancillary variables such as remotely sensed data, the accuracy of spatial prediction can
further improved.
 
Publisher INSInet Publication
 
Date 2010
 
Type Article
PeerReviewed
 
Format application/pdf
 
Language en
 
Rights —
 
Identifier http://oar.icrisat.org/8342/1/AustJBasicAppSci_4_3_457-467_2010.pdf
Tajgardan, T and Ayoubi, S and Shataee, S and Sahrawat, K L (2010) Soil Surface Salinity Prediction Using ASTER Data: Comparing Statistical and Geostatistical Models. Australian Journal of Basic and Applied Sciences, 4 (3). pp. 457-467. ISSN 1991-8178