Vahed Kiyani; Afshin Alizade Shaabani; Aliakbar Nazari Samani
Abstract
Nowadays, remote sensing images are able to provide the latest information for studying land coverage and land uses, and the value and usability of produced maps depend on their accuracy. Hence, the purpose of this study was to evaluate the classification accuracy of LISS-III sensor's image of IRS-P6 ...
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Nowadays, remote sensing images are able to provide the latest information for studying land coverage and land uses, and the value and usability of produced maps depend on their accuracy. Hence, the purpose of this study was to evaluate the classification accuracy of LISS-III sensor's image of IRS-P6 satellite using the Google Earth's database in order to provide a map of land coverage and land uses. Therefore, the QUICKBIRD satellite imagery provided by Google Earth's software was used to determine both educational samples and to evaluate the classification. The studied area is Taleghan city in the Alborz province which is located in the watershed of Taleghan. In this research before determining the educational samples to verify the accuracy of the Google Earth's image, linear digital layers (roads and channels) with terrestrial coordinates were used which obtained an RMSE of 0.77.
In the next step, after determining the educational samples, the mentioned satellite image was classified into 5 categories of garden, agriculture. Pasture, lake and no coverage based on a supervised classification and with maximum probability algorithm using software ENVI 4/2 which obtained a classification KAPPA coefficient of 0.85 and an overall accuracy of 91/4.
The results of this study indicated that Google Earth's software images have a high spatial accuracy in order to evaluate the classification accuracy in some regions and also the use of ecological features such as the slope of the area, hydrologic network and… increase this accuracy. Finally, it is suggested that Google Earth's satellite imagery to be used to evaluate the accuracy of the satellite image classification and even visual interpretation of land coverage and land use.
Nasrin Nikandish; Seyyed Farzad Hosseynizadeh Arani
Volume 22, Issue 87 , November 2013, , Pages 81-86
Abstract
Analyzing landslide and risk management are among the important responsibilities of managers. The present study explores different features of landslide using Google earth satellite images and Geographic Information system. Case study includes landslide zone in Chahar Takhte which is located in Ardal, ...
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Analyzing landslide and risk management are among the important responsibilities of managers. The present study explores different features of landslide using Google earth satellite images and Geographic Information system. Case study includes landslide zone in Chahar Takhte which is located in Ardal, Chahar Mahal va Bakhtiary province. Data was collected from Google earth and digital elevation model. Maps of landslide zone, land use, topographic and landslide development were produced based on the obtained images. Results indicate that the sliding mass is located near one of Karun tributaries, and undercutting by this tributary is one of the main reasons for the occurrence of landslide. The toe of this mass discharges sediments into the river. Rotational landslide happen in alluvium, colluvium and skirts with a less than 20 degree slope, while cliffs and toe have steep slope. Other reasons for the occurrence and development of landslide includes water drainage in Naqan city, roads and irrigated agriculture. 53 percent of flows are drained in south and south west directions. Main cliff in the landslide zone is located near grade IV and V water flows. Agricultural lands, roads and even Naqan face the threat of landslide zone development.