River Indus flood mapping from Chashma barrage to Sukkur through satellite images and ER Mapper
This paper aims to integrate Satellite Remote Sensing (SRS), Geographic Information System (GIS) and Digital Image Processing (DIP) techniques for the identification of flood affected areas and flood damage assessment along the Indus River as a result of flood in the year 2005 due to abrupt snow melt in the northern areas of Pakistan. Snow melt in northern areas of Pakistan was the main cause of flooding in the year 2005, using ER Mapper Image Processing software, study of temporal changes of snow cover has also been carried out by calculating the snow cover area in the month of February for different years i.e. 2004, 2005 and 2006 using Moderate Resolution Imaging Spectro-radiometer (MODIS) onboard Aqua and TERRA satellites data. This showed that snow covered areas for the mentioned years were 56203, 67853 and 58642 sq km respectively. Calculations also reveal that the snowfall was maximum in the year 2005. Using satellite images of MODIS for May and July 2005 covering the area along the Indus from Chashma to Sukkur Barrage showed that this flood had caused huge damage in many cities of Punjab and Sindh provinces. Using images pertaining to pre and post-flooding periods, the evaluated flooded area between Chashma Barrage and Sukkur Barrage comes out to be approximately 6428 sq km (excluding the normal flow area which is 1359 sq km).
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Evaluation of land sensitivity to desertification
Today one of the crisis ecological affecting the world is the phenomenon of desertification. We require a proper understanding of causes and processes of desertification to control the huge phenomenon on the global and regional situation. Desertification is more related to social and anthropogenic issues than natural causes and it becomes more important over the time. Human effects on desertification could be classified as direct and indirect factors. We used ICD method to estimate and assessment of desertification in 456 km2 of Koohdasht basin lands. This method was introduced in 1995 by Ekhtesasi and Mohajer , checking human and environment factors that contributing to desertification of the area, at the end will be introduced the intensity of desertification. The first we collect the data of area then we used ILWIS software to separate the facies in basin and value the parameters of ICD method, we attain the intensity of desertification for each facies and whole basin. The analysis indicated that 35.2 % of land in basin located in low class, 31.99 in medium class, 32.7% had high class and the total area is located in medium class. As well as recognized the most importance factor is human activity.
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Morphometric Analysis of Kangshabati-Darkeswar Interfluves Area in West Bengal, India using ASTER DEM and GIS Techniques
The aim of the study is to delineate the morphometric characteristics of Kangshabati-Darkeswar Interfluves Area using remote sensing and GIS technology. 10 km2 grids were elaborate to delineate the relief characteristics using Advance Space Thermal Emission and Radiometer (ASTER) data. Drainage networks were automatically extracted from digital aster elevation models. Second order local polynomial (LP) interpolation technique was used to estimate the surface characteristics of the study area using ArcGIS 9.3. The absolute elevation of the study region is extended between 4.0 – 949.29 m with an average elevation of 484.50m. The highest relative relief resulted 833.69m, whereas the average ruggedness index of the study area is recorded as 0.09 per 10 km2 area. The average drainage density of the study area was computed 0.73 /sq. km and the highest drainage intensity are recorded as 9.58/10 km2 grid area. The average length of overland flow of the study area was 2.56/10 km2 grid areas. The result of the study highlights an about the spatial distribution of relief and hydrological characteristics which may provide the knowledge to devise and accomplish an appropriate plan to progress agriculture and others allied activities. Hence, from the study, it can be concluded that remote sensing data (ASTER –DEM) coupled with GIS techniques prove to be a competent tool in morphometric analysis and the data can be used for basin or interfluves area management and other hydrological studies in future.
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Cover change analysis of mangrove forest and surrounding land cover of Mtwapa creek, Kenya
Cover change study was carried out within and adjacent to peri-urban mangroves of Mtwapa in Kilifi County using medium resolution Landsat (1990; 2000), SPOT (2009) imageries and a mangrove species vector map of 1992. The objective of the study was to assess the temporal mangrove cover change with respect to the immediate land cover changes surrounding the creek. Between 1992 and 2009 Mangrove forest cover saw a loss of 21%. Land-cover from 1990 to 2009 revealed high rate of upland deforestation (3.85% yr-1) and an increase in agricultural land (13.9% yr-1). There is need for reforestation and conservation of the remaining patches of upland forests as well as establishment of riparian zones to enhance soil retention to minimize sedimentation.
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Landslide Hazard assessment around Tehri Reservoir in the lesser Himalayas using Geoinformatics
The role of reservoir in causing landslides and also in reactivating old landslides due to difference in hydraulic action has been very common around the world. The present study is an attempt to divide the area around tehri reservoir into various landslide susceptible zones. The result obtained after superimposing the active landslide and lanslideslide hazard zonation shows that there is strong correlation between these slides with high and very high landslides hazard zone area. On the whole it is clear that the density of landslides increases from very low to very high class. The quantative analysis of the data shows that more than 80% of the total landslide area existed in moderate and high hazard zone classified area. In spite of the scarcity of the data the hazard zonation assessment is helpful to mask out the area highly vulnerable to landslide which in turn is helpful for short-term and long-term plan before initiating any sort of development activities in the tehri rim area. Keywords: Landslide, Susceptible, vulnerable, Superimposing, Hazard Zonation.
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Estimating of Land Surface Emissivity from Landsat-8 Satellite Data Based on NDVI
As an intrinsic property of natural materials, land surface emissivity (LSE) is an important surface parameter and surface emissivity estimation is a significant factor for the land surface temperature estimation from remotely sensed data. Public domain data are available from the newly operational Landsat-8 Thermal Infrared Sensor (TIRS). Vegetation coverage has a significant influence on the LSE distribution. In this study, emissivity values of bands 10 and 11 have been calculated based on the Normalized Difference Vegetation Index (NDVI) method. The NDVI thresholds values have been determined to separate the bare soil, fully vegetated and mixed areas. Then using a regression relation, the values of emissivity of the bare soil samples and mixed area have been derived. A constant value of emissivity is also used for the fully vegetated area.
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The influence of the plant coverage on the desertification status in Jarghooye region of Isfahan using IMDPA model
The issue of plant coverage, destroying it and the resulting influence on desertification process has long been taken into consideration by the scholars and researchers of different fields of study specially natural resources and agriculture. In many areas of the world, human being has played the main role, intentionally or unintentionally, in desertification or speeding up the rate of it. It has been accepted that proper and effective plant coverage slows down the rate of desertification to a great extent in an area susceptible for desertification and also it makes the condition conducive for changing the ecosystems into a better form. The current study has been done with the objective of determining the quantitative influence of the plant coverage in Jarghooye area on desertification in this region that is one of the most susceptible areas of the country. In this study, Iranian Model of Desertification Potential Assessment (IMDPA) was applied. This model is one of the valuable models for determining the level of desertification in different areas of Iran. The results of this study shows that the coverage exploitation index with the numeral value of 3.18 is in sever class and has the most influence on the indices studied in the region. Generally the plant coverage index of this area with the numeral value of 1.99 is indicator of the average influence on desertification process in Jarghooye region.
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Bio-Diversity Characterizations using Remote Sensing & GIS Techniques: A Case Study of Dalma Wild Life Sanctuary, East Singhbhum
Tropical forests are more diverse than the other terrestrial ecosystems by possessing greater number of life forms. It is widely accepted that the identification and prioritization of important centers of biodiversity are necessary at both the national and the global scale for conservation action. Indian subcontinent, with diverse bio-climatic regions supports one of the richest flora and fauna. The increased human pressure and consequent effects on the landform and land use changes has a profound effect on the present vegetation and the biodiversity. The present study is one of the important parts of Gangetic plains whose flora is unique to India because of the tropical drier and occasionally humid climate, it provides the information on the present status of biodiversity of the forests of Dalma in Jharkhand state through analyses of phyto-sociology and remote sensing data, as to their structure and compositional variations correlated with topography, fragmentation and threats operating, which may be useful for planning and monitoring sustainable management of forests and conservation of biodiversity. The objective of the present study is to present initial information of vegetation through the application of RS and GIS techniques along with a phytosociological analysis of the forests for their diversity and it’s based on three major approaches i.e. Remote Sensing, GIS and Ecology.
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