Ammar Rafiee Emam; Gholamreza Zehtabian; Amir Houshang Ehsani
Volume 11, Issue 3 , August 2019, , Pages 323-342
Akbar Fakhireh; Ahmad Pahlevanravi; Mahmoud Najafi zilaee; Mohsen Moradzadeh; Soheila Nouri
Volume 19, Issue 3 , December 2012, , Pages 457-468
Abstract
Detailed studies of vegetation in desert areas are almost difficult due to the limitations and conditions of these areas. Remote sensing technology with numerous capabilities can be used as an efficient method in these areas. This study was aimed to determine an appropriate vegetation index to assess ...
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Detailed studies of vegetation in desert areas are almost difficult due to the limitations and conditions of these areas. Remote sensing technology with numerous capabilities can be used as an efficient method in these areas. This study was aimed to determine an appropriate vegetation index to assess vegetation changes in the desert area of West Karkheh over a period of 18 years using satellite images of TM (1991) and ASTER (2008). After measuring the canopy cover, geometric and atmospheric corrections, different methods of detection and classification were applied on the images with maximum likelihood method. Results showed that PVI2 index was the best indicator to produce vegetation changes map during the study. So based on this index, final map of desertification was produced in the three classes with no changes and rehabilitation. The results showed that canopy cover increased up to 17.5% of the total area during the study period due to the implementation of desertification projects in some parts of the region and combined cultivation. These changes were classified in two classes of rehabilitation (69.8%) and desertification (30.2%).
Saleh Arekhi; yaghoub Niyazi
Volume 17, Issue 1 , September 2010, , Pages 74-93
Abstract
Presently, unplanned changes of land use have become a major problem. Most land use changes occur without a clear and logical planning with little attention to their environment impacts.Since that landuse change occurring over large areas, remote sensing technology is an essential and useful tool for ...
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Presently, unplanned changes of land use have become a major problem. Most land use changes occur without a clear and logical planning with little attention to their environment impacts.Since that landuse change occurring over large areas, remote sensing technology is an essential and useful tool for landuse change detection. In this study,after applying geometric and radiometric correction on landsat images of TM(1988) and ETM+(2001) ,five techniques of change detection have been used in 80470 hectare in the region of Daresher,Ilam province. These change detection techniques included Image regression, NDVI differencing, Principal component analysis (PCA(, Tasselled cap (KT) and post-classification comparison. In all these techniques, following standarizing maps,change direction has been determined.The accuracy of the results obtained by each technique was evaluated by comparison with post-classification method through Kappa coefficient calculation. According to the results, NDVI differencing and PC2 differencing showed the largest accuracy with Kappa coefficients of 0.667 and 0.655, respectively.However, Different change detection algorithms have their own merits and no single approach is optimal and applicable to all cases. In practice, several change detection techniques should be used to implement change detection, whose results are then compared to identify the best approach through visual or quantitative assessment.
Seyed Alireza Mousavi; Mahdi farahpour; Maryam Shokri; Karim Solaimani; Mahmood Godarzi
Volume 13, Issue 3 , February 2006, , Pages 186-200
Abstract
Landsat 7 ETM+ satellite data of 2002 versus vegetation cover map of 1976 were used to: 1- assess the capability of satellite data to prepare vegetation cover classes map and 2- study the vegetation changes trend in an area of about 26858.6 ha in Lar Dam Basin. Field Sample spots were defined after accomplishing ...
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Landsat 7 ETM+ satellite data of 2002 versus vegetation cover map of 1976 were used to: 1- assess the capability of satellite data to prepare vegetation cover classes map and 2- study the vegetation changes trend in an area of about 26858.6 ha in Lar Dam Basin. Field Sample spots were defined after accomplishing necessary corrections of satellite images. Suitable band compositions were selected by considering the Optimum Index Factor (OIF), correlation matrix, Principal Components Analysis (PCA) and 2-dimensional diagram analysis. These compositions were classified using Maximum Likelihood, Minimum Distance and Box Classifier algorithms and then Majority Filter was used. Accuracy of resulted maps was evaluated by pixel to pixel method. Then Overall Accuracy Coefficient and Kappa Index were calculated. The map resulted from classification of band composition 123457 through Maximum Likelihood and Majority Filter was selected as the vegetation cover map of 2002. Vegetation cover map of 1976 prepared by Asgari-khah (1977) via field survey was used as "vegetation cover classes" map of that year. Then the changes happened in each class were assessed by operation of cross function on the mentioned maps. Due to complexity of initial classes, more homogenous classes were merged resorting to more detectable maps having only four classes. Overall Accuracy Coefficient of final map was promoted by using these classes. Then the changes happened during 1976-2002 were detected. The results showed that 28.55% of total area which was covered by rangeland vegetation types in 1976, is unchanged, 14.03% is dropped into lower and 57.42% into higher classes. The map of vegetation cover changes was produced, finally.