Greenrey percentage estimation using band ratio

Solo disponible en BuenasTareas
  • Páginas : 10 (2400 palabras )
  • Descarga(s) : 0
  • Publicado : 13 de septiembre de 2012
Leer documento completo
Vista previa del texto
1 Greenrey(Green Space) Percentage Estimation Using Band Ratio, NDVI From Landsat Enhanced Thematic Mapper(ETM)-2002 & An Application Of Geographic Information System(GIS) Techniques, Dezful-Andimeshk, Khuzestan South-West Iran
Saied Pirasteh (1) Syed Ahmad Ali (2) Heshmi Jamil Hussain (3) Contact Email: 1- Faculty of Engineering, Islamic Azad University of Dezful,Dezful-Iran 2-Department of Geology, Aligarh Muslim University, Aligarh, India, 3-Forest Research Institute, Dehradun, India,

Abstract Landsat-7 ETM was used to derive the greenery for the Oct-2002 in the DezfulAndimeshk, Khuzestan, southwest Iran. Dezful and Andimeshk are very hot cities in summer and dry winter with about +1 degreecentigrade. Urbanization was correlated with increasing needed of the land for settelment and it caused one of decreasing amount of greenery.In other hand decreasing of greenery makes human who stay in these area loose their comfortability. Greenery has an important role as an indicator of environmental condition in the urban areas. The percentage of the greenery was estimate and evaluated by the remotesensing methods like Band Ratio, NDVI, supervised classification and post classification . Function of vegetation in urban areas strongly controls urban air pollution, thermal environment and influence urban microclimate. Quantitative analysis about green space in Dezful-Andimeshk and its suburbs are necessary for evaluate environmental condition in greenery aspect, application of image dataanalysis, and GIS are effective for the area like Dezful-Andimeshk of the present research. Percentage obtained of greenery in selected area indicated shortage of green spaces in both the cities namely Dezful-Andimeshk from the study area. However, this study reveals that how satellite data beside GIS techniques approach eases data archiving and map. Keywords Dezful-Andimeshk’ Khuzestan’Band Ratio’NDVI,GIS

Introduction During the past millennium, human, have taken an increasingly large role in the modification of the global environment. With increasing numbers and developing technologies, man has emerged as the major most powerful, and universal instrument of environmental change in the biosphere today. Both globally and in the Iran land cover today is altered primarily by direct human use.Greenery percentage prediction has become a central component in current strategies for the Dezful-Andimesh area. Viewing the Earth from space has become essential to comprehend the cumulative influence of human activities and its natural resourcebase. Over the past two decades, data from Earth Sensing Satellites(ESS) has become important in different aspect such as monitoring, mapping ,infrastructure and environmental green open space studies. Remote Sensing and GIS are providing new tools for advanced natural resources evaluation, mapping and prediction of the greenery percentage in the study area. Several studies have been established good correlation vegetation indeces and grain yield using single data (Colwell, 1979, Barnett & Thompson, 1982, 1983, Parihar et al 1987, Alinda Medrial etal, 2001 & R. Singh et al, 2002) and remotely sensed data. Dezful city covers around 5289.166 hectars which about 1953.876 hectares of the area are urban. Andimeshk city also covers around 1544.818 hectares and 1133.820 hectares of the total area are urban. Dezful- Andimeshk cities are connected by the road and that is about 7 km. Image processing techniques employed in this study were conductedusing ER-Mapper and Environmental Visualization Images (ENVI)softwares. Both the softwares are raster based software package with advanced vector capabilities. The False Color Composit (FCC) image bands 7-4-2, Band Ratio and Normalizes Difference Vegetation Index (NDVI) images were produced using ENVI software. These two images were classified and dirctely converted

from raster to vector...
tracking img