Ammar Rafiee Emam; Gholamreza Zehtabian; Amir Houshang Ehsani
Volume 11, Issue 3 , August 2019, , Pages 323-342
Saiedeh Nateghi; Ahmad Nohegar; Amir Houshang Ehsani; Omolbanin Bazrafshan
Volume 24, Issue 4 , January 2018, , Pages 778-790
Abstract
The monitoring of vegetation changes has a fundamental role in planning and management of environment. There are various methods to determine the changes in a region using satellite images that each has advantages and limitations. The use of vegetation indices is one of the methods to detect the changes. ...
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The monitoring of vegetation changes has a fundamental role in planning and management of environment. There are various methods to determine the changes in a region using satellite images that each has advantages and limitations. The use of vegetation indices is one of the methods to detect the changes. The aim of this study was to evaluate four vegetation indices including NDVI, SAVI, RVI and WAVI. This research was performed in Qeshm Island using Landsat images during 2001 and 2014. In this research, ETM+ and OLI data were used. After calculating each indicator, 100 sample training points were used to assess the accuracy of indicators by ENVI.5.3. Four classes including bare land, mangrove forests, agriculture and water were classified. Based on Dlapyan & Smith method, the product accuracy and user accuracy for each class were evaluated. The results showed that the SAVI index with the highest kappa coefficient, 0.93 in 2014 and 0.83 in 2001, had the best results and WAVI index with the lowest kappa coefficient, 0.43 in 2001 and 0.81 in 2014, had the weakest results. To evaluate the changes, crosstab method was used .The results showed that during 13 years the area of mangrove forests and agricultural lands and natural vegetation of Qeshm Island increased up to 21% and 60%, respectively.
Saeedeh Nateghi; ahmad Nohegar; Amir Houshang Ehsani; Omolbanin Bazrafshan
Volume 23, Issue 2 , September 2016, , Pages 416-404
Abstract
Monitoring the land use and land cover change detection is one of the most important issues in the field of planning and management. Change Vector Analysis technique is one of the common methods to detect the changes. This method is based on radiometric changes between two time series satellite data ...
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Monitoring the land use and land cover change detection is one of the most important issues in the field of planning and management. Change Vector Analysis technique is one of the common methods to detect the changes. This method is based on radiometric changes between two time series satellite data and threshold level method. For this purpose, the satellite images of Landsat ETM + (2001) and OLI (2014) were used for the Qeshm Island. The FLAASH method was used to perform atmospheric correction. Then, the vegetation indices (NDVI، WAVI، RVI, SAVI و BI) were calculated and the correlation between indices was evaluated. The results showed that the SAVI index with a correlation coefficient of 95% in 2014 and 92% in 2001 had a high correlation with BI index; therefore, the SAVI index provides better results in studying the vegetation changes in arid and semi-arid regions. The results also showed that during the study period (2001-2014), 150 km² of the lands around and between the mangrove forests were submerged, and at the same time, the area of mangrove forests decreased to 30.63 km², mostly occurring in the margins of Qeshm mangrove forests and the eastern shores of Khamir Port. As well, the area of agricultural lands and vegetation of the island decreased about 8.2 km² in central, eastern, and southeastern island.
Mehdi Jafari; Gholam Reza Zehtabian; Amir Houshang Ehsani
Volume 20, Issue 1 , June 2013, , Pages 72-87
Abstract
Today, remote sensing data can provide the latest information for the study of land cover and land uses These images are of utmost importance due to the providing updated information, variety of forms and the possibility of processing for making land use maps. Determining the location of each land use ...
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Today, remote sensing data can provide the latest information for the study of land cover and land uses These images are of utmost importance due to the providing updated information, variety of forms and the possibility of processing for making land use maps. Determining the location of each land use together with land cover helps managers in making decisions. Also, the current status of the land cover can be studied by using land use maps at different levels. In order to evaluate the ability of multitemporal satellite data of TM and ETM + in land use classification and the effect of the thermal band on increasing the accuracy of the land use maps, Landsat TM digital data relating to the September 27, 1990 and Landsat ETM + digital data of 10 July 2002 from Kashan were analyzed. Initial studies were performed on images in terms of the presence of geometric errors. In order to prepare the images for digital processing, improved operation and image enhancement were applied on the images. Ground truth map was prepared in the same stage. Then, the supervised classification of satellite images with algorithms and different approaches including a variety of bands were tested and the accuracy of each of the methods and approaches were investigated. The results showed that the highest Kappa accuracy in both Landsat TM and ETM + with all the bands were 86.34 and 83.21, respectively. While the elimination of the thermal band decreases the accuracy to 82.46 and 79.93 % The results of this study showed that using thermal bonding caused an increase of 4 percent in Kappa accuracy, and the highest accuracy was occurred in the classes of clay plains, flood plains, mountains and puffy salt lands. Therefore, despite the lower spectral resolution, the use of thermal bonding is recommended in such studies.