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Validating gap-filling of Landsat ETM+ satellite images in the Golestan Province,Iran 总被引：2，自引：0，他引：2
M. Mohammdy H. R. Moradi H. Zeinivand A. J. A. M. Temme H. R. Pourghasemi H. Alizadeh 《Arabian Journal of Geosciences》2014,7(9):3633-3638
The Landsat series of satellites provides a valuable data source for land surface mapping and monitoring. Unfortunately, the scan line corrector (SLC) of the Landsat7 Enhanced Thematic Mapper plus (ETM+) sensor failed on May 13, 2003. This problem resulted in about 22 % of the pixels per scene not being scanned and has seriously limited the scientific applications of ETM+ data. A number of methods have been developed to fill the gaps in the incorrect images. Most of these methods have problems in heterogeneous landscapes. We applied and validated a simple and effective gap-fill algorithm developed by the US Geological Survey to a study area in the Golestan Province in the north of Iran. This algorithm operates under the assumption that the same-class neighboring pixels around the unscanned pixels have similar spectral characteristics, and that these neighboring and unscanned pixels share patterns of spectral differences between dates. For validation, unsupervised land use classification was performed on both gap-filled SLC-off data and the original “sound” data set. Classification results and accuracies were very comparable. 相似文献
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H. R. Pourghasemi H. R. Moradi S. M. Fatemi Aghda C. Gokceoglu B. Pradhan 《Arabian Journal of Geosciences》2014,7(5):1857-1878
The aim of this study is to produce landslide susceptibility mapping by probabilistic likelihood ratio (PLR) and spatial multi-criteria evaluation (SMCE) models based on geographic information system (GIS) in the north of Tehran metropolitan, Iran. The landslide locations in the study area were identified by interpretation of aerial photographs, satellite images, and field surveys. In order to generate the necessary factors for the SMCE approach, remote sensing and GIS integrated techniques were applied in the study area. Conditioning factors such as slope degree, slope aspect, altitude, plan curvature, profile curvature, surface area ratio, topographic position index, topographic wetness index, stream power index, slope length, lithology, land use, normalized difference vegetation index, distance from faults, distance from rivers, distance from roads, and drainage density are used for landslide susceptibility mapping. Of 528 landslide locations, 70 % were used in landslide susceptibility mapping, and the remaining 30 % were used for validation of the maps. Using the above conditioning factors, landslide susceptibility was calculated using SMCE and PLR models, and the results were plotted in ILWIS-GIS. Finally, the two landslide susceptibility maps were validated using receiver operating characteristic curves and seed cell area index methods. The validation results showed that area under the curve for SMCE and PLR models is 76.16 and 80.98 %, respectively. The results obtained in this study also showed that the probabilistic likelihood ratio model performed slightly better than the spatial multi-criteria evaluation. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose. 相似文献
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Mohammady Majid Moradi Hamid Reza Zeinivand Hossein Temme A.J.A.M. Yazdani Mohammad Reza Pourghasemi Hamid Reza 《Theoretical and Applied Climatology》2018,133(1-2):459-471
Theoretical and Applied Climatology - Land use change is an important determinant of hydrological processes and is known to affect hydrological parameters such as runoff volume, flood frequency,... 相似文献
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Soil organic carbon (SOC) is an important aspect of soil quality and plays an imperative role in soil productivity in the agriculture ecosystems. The present study was applied to estimate the SOC stock using space-borne satellite data (Landsat 4–5 Thematic Mapper [TM]) and ground verification in the Medinipur Block, Paschim Medinipur District and West Bengal in India. In total, 50 soil samples were collected randomly from the region according to field surveys using a hand-held Global Positioning System (GPS) unit to estimate the surface SOC concentrations in the laboratory. Bare soil index (BSI) and normalized difference vegetation ndex (NDVI) were explored from TM data. The satellite data-derived indices were used to estimate spatial distribution of SOC using multivariate regression model. The regression analysis was performed to determine the relationship between SOC and spectral indices (NDVI and BSI) and compared the observed SOC (field measure) to predict SOC (estimated from satellite images). Goodness fit test was performed to determine the significance of the relationship between observed and predicted SOC at p ≤ 0.05 level. The results of regression analysis between observed SOC and NDVI values showed significant relationship (R2 = 0.54; p < 0.0075). A significant statistical relationship (r = ?0.72) was also observed between SOC and BSI. Finally, our model showed nearly 71% of the variance of SOC distribution could be explained by SOC and NDVI values. The information from this study has advanced our understanding of the ongoing ecological development that affects SOC dissemination and might be valuable for effective soil management. 相似文献
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Eskandari Saeedeh Amiri Mahdis Sãdhasivam Nitheshnirmal Pourghasemi Hamid Reza 《Natural Hazards》2020,104(1):305-327
Natural Hazards - The forest fire hazard mapping using the accurate models in the fire-prone areas has particular importance to predict the future fire occurrence and allocate the resources for... 相似文献
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Application of frequency ratio,statistical index,and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya 总被引：12，自引：1，他引：11
Amar Deep Regmi Krishna Chandra Devkota Kohki Yoshida Biswajeet Pradhan Hamid Reza Pourghasemi Takashi Kumamoto Aykut Akgun 《Arabian Journal of Geosciences》2014,7(2):725-742
The Mugling–Narayanghat road section falls within the Lesser Himalaya and Siwalik zones of Central Nepal Himalaya and is highly deformed by the presence of numerous faults and folds. Over the years, this road section and its surrounding area have experienced repeated landslide activities. For that reason, landslide susceptibility zonation is essential for roadside slope disaster management and for planning further development activities. The main goal of this study was to investigate the application of the frequency ratio (FR), statistical index (SI), and weights-of-evidence (WoE) approaches for landslide susceptibility mapping of this road section and its surrounding area. For this purpose, the input layers of the landslide conditioning factors were prepared in the first stage. A landslide inventory map was prepared using earlier reports, aerial photographs interpretation, and multiple field surveys. A total of 438 landslide locations were detected. Out these, 295 (67 %) landslides were randomly selected as training data for the modeling using FR, SI, and WoE models and the remaining 143 (33 %) were used for the validation purposes. The landslide conditioning factors considered for the study area are slope gradient, slope aspect, plan curvature, altitude, stream power index, topographic wetness index, lithology, land use, distance from faults, distance from rivers, and distance from highway. The results were validated using area under the curve (AUC) analysis. From the analysis, it is seen that the FR model with a success rate of 76.8 % and predictive accuracy of 75.4 % performs better than WoE (success rate, 75.6 %; predictive accuracy, 74.9 %) and SI (success rate, 75.5 %; predictive accuracy, 74.6 %) models. Overall, all the models showed almost similar results. The resultant susceptibility maps can be useful for general land use planning. 相似文献
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AbstractThe main objective of this study is to investigate and monitor the landuse and morphological changes in the floodplain part of the Talar River, northern parts of Iran. In the present study, the aerial photographs have been used to produce landuse maps of the floodplain for three periods including 1968, 1994, and 2013. The quantitative analysis of the produced landuse maps showed that the floodplain has undergone substantial landuse changes. Moreover, the sediment bar and the beach area have been decreased about 97 and 90%, respectively, during the 45-year period. Substantial increases of 192 and 622% have been observed for orchards and residential areas, respectively. On the other hand, not only the forest and riparian vegetation were decreased but also the average width of river was decreased about 25.5 m. In addition, flow length of the study reach increased about 8 m. The RNCI was about ?0.7 m per year indicating sedimentation process. During the period of 1968–2013, Caspian Sea has retreated about 150 m and the delta of Talar River was changed. This study showed that morphological actions during first 26 years (1968–1994) were the stable and last 19 years had the change period, especially sedimentation (bar). 相似文献
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Ali Haghizadeh Davoud Davoudi Moghaddam Hamid Reza Pourghasemi 《Journal of Earth System Science》2017,126(8):109
Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster–Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran. The research was done using 11 groundwater conditioning factors and 496 spring positions. Based on the ground water potential maps (GPMs) of SI and DST methods, 24.22% and 23.74% of the study area is covered by poor zone of groundwater potential, and 43.93% and 36.3% of Broujerd region is covered by good and very good potential zones, respectively. The validation of outcomes displayed that area under the curve (AUC) of SI and DST techniques are 81.23% and 79.41%, respectively, which shows SI method has slightly a better performance than the DST technique. Therefore, SI and DST methods are advantageous to analyze groundwater capacity and scrutinize the complicated relation between groundwater occurrence and groundwater conditioning factors, which permits investigation of both systemic and stochastic uncertainty. Finally, it can be realized that these techniques are very beneficial for groundwater potential analyzing and can be practical for water-resource management experts. 相似文献