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A spatio-temporal urban expansion modeling a case study Teheran metropolis, Iran
10-19Views:127During the past decades, urban growth has been accelerating with the massive immigration of population to cities. Urban population in the world was estimated as 2.9 billion in 2000 and predicted to reach 5.0 billion in 2030. Rapid urbanization and population growth have been a common phenomenon, especially in the developing countries such as Iran. Rapid population growth, environmental changes and improper land use planning practices in the past decades have resulted in environmental deterioration, haphazard landscape development and stress on the ecosystem structure, housing shortages, insufficient infrastructure, and increasing urban climatological and ecological problems. In this study, urban sprawl assessment was implemented using Shannon entropy and then, Artificial Neural Network (ANN) has been adopted for modeling urban growth. Our case study is Tehran Metropolis, capital of Iran. Landsat imageries acquired in 1988, 1999 and 2010 are used. According to the results of sprawl assessment for this city, this city has experienced sprawl between 1988 to 2010. Dataset include distance to roads, distance to green spaces, distance to developed area, slope, number of urban cells in a 3 by 3 neighborhood, distance to fault and elevation. Relative operating characteristic (ROC) method have been used to evaluate the accuracy and performance of the model. The obtained ROC equal to 0.8366.
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Case study for estimation of the amount of contaminants stored in soil in an industrial area
1-11Views:294One of the main sources of contaminants in the soil is industrial activity which has become one of the major environmental problems of the last few decades. The development of geoinformatics as well as the introduction of standards and regulations has led to a decreased risk of soil contamination and the cost-effective optimization of remediation activities. Based on the above, the aim of our study is to demonstrate the geoinformation processing of the remediation performed in an industrial area located in the Great Hungarian Plain, with special regard to the estimation of the amount and spread of the contaminants accumulated in the soil. In order to reveal the lithological and hydrogeological properties of the investigated area and the environmental status of the underground areas, we performed a large number of shallow land drillings (115). During the field sampling, 1000–1500 grams of samples were collected from the drill bit and were processed in an accredited laboratory. Based on the concentration and volume models created it can be concluded that with the estimations performed via modeling, we were able to locate the most critical areas from the standpoint of contamination. It was revealed that the focal point of the contaminants accumulated in the soil was in the central part of the investigated area. Furthermore, the model demonstrated the effect of lithological factors, since contaminants tend to accumulate more heavily in cohesive soils compared to porous rocks. The extent of contaminant concentration in the aquifer increased with decreasing depth; however, after reaching the floor clay the extent of contaminant concentration began to decrease. The lithological layer closest to the surface contained the most contaminants.
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Urban vegetation classification with high-resolution PlanetScope and SkySat multispectral imagery
66-75Views:608In this study two high-resolution satellite imagery, the PlanetScope, and SkySat were compared based on their classification capabilities of urban vegetation. During the research, we applied Random Forest and Support Vector Machine classification methods at a study area, center of Rome, Italy. We performed the classifications based on the spectral bands, then we involved the NDVI index, too. We evaluated the classification performance of the classifiers using different sets of input data with ROC curves and AUC values. Additional statistical analyses were applied to reveal the correlation structure of the satellite bands and the NDVI and General Linear Modeling to evaluate the AUC of different models. Although different classification methods did not result in significantly differing outcomes (AUC values between 0.96 and 0.99), SVM’s performance was better. The contribution of NDVI resulted in significantly higher AUC values. SkySat’s bands provided slightly better input data related to PlanetScope but the difference was minimal (~3%); accordingly, both satellites ensured excellent classification results.
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High water level observations along the upper course of the Olt River (Romania) from a hydrological modelling aspect
10-19Views:209Along its upper course, the Olt River (Romania) flows through several settlements, which are endangered by flooding. The multiannual water flow at Tomești station, the first hydrometric station along the Olt River, is 1.51 m3 /s, but in case of extreme events the river flow reached even 41.8 m3 /s. The aim of this study is to analyze the flood events along the upper course of the Olt River (section between Tomești and Cârța settlements) by using the HEC-RAS and the HEC-GeoRAS hydrological modeling software programs. The river cross section model showed how the main channel narrowed (characteristic to some locations) which can be considered as one of the causes of a possible overflow.
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Estimating soil loss from a watershed in Western Deccan, India, using Revised Universal Soil Loss Equation
13-25Views:396USLE (Universal Soil Loss Equation) is the original and the most widely accepted soil loss estimation technique till date which has evolved from a design tool for conservation planning to a research methodology all across the globe. The equation has been revised and modified over the years and became a foundation for several new soil loss models developed all around the world. The equation has been revised as RUSLE by Renard et al. (1991) and is computed in GIS environment. The Revised equation is landuse independent which makes it a useful technique to apply in a variety of environment. The present paper is an attempt to estimate soil loss from a semi-arid watershed in Western Deccan, India by employing RUSLE. The region is a rocky terrain and sediments are restricted to only a few localities. The result indicates that the region is at the threshold of soil tolerance limit.
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Preliminary analysis of red mud spill based on aerial imagery, Hungary
47-57Views:155One of the largest industrial spills in Europe occurred in the village of Kolontár (Hungary) on October 4, 2010. The primary objective of the hyperspectral remote sensing mission was to monitor that is necessary in order to estimate the environmental damage, the precise size of the polluted area, the rating of substance concentration in the mud, and the overall condition of the flooded district as soon as possible. The secondary objective was to provide geodetic data necessary for the high-resolution visual information from the data of an additional Lidar survey, and for the coherent modeling of the event. For quick assessment and remediation purposes, it was deemed important to estimate the thickness of the red mud, particularly the areas where it was deposited in a thick layer. The results showed that some of the existing tools can be easily modified and implemented to get the most out of the available advanced remote sensing data.