The main objective of this project was to derive digital land use and land cover information from satellite remote sensing data for Connecticut, Long Island, and those watersheds contributing to Long Island Sound. In doing so, four methods of land use and land cover classification were evaluated on two test quadrangles to determine which method was best suited, in terms of time and costs balanc...

the research used the satellite image (landsat 7 etm ) within the thermal infrared sixth band (tir6) and geographic information system (gis) to determine the air pollution and its relationship with the land cover (lc) and land use (lu) of baghdad city. concentration of total suspended particles (tsp), lead (pb), carbon oxides (co, co2), and sulphur dioxide (so2) were obtained from 22 ground mea...

In the presented methodology, multitemporal Landsat images were used to develop enhanced information about complex assemblages of vegetation and patterns of seasonal land cover variability, thereby facilitating improved land use and land cover (LULC) classification of urbanized areas among sensitive environments along the Mississippi Gulf Coast. For Landsat-5 and Landsat-7 images acquired for l...

The objective of this research was to determine the best model and compare performances in terms of producing landuse maps from six supervised classification algorithms. As a result, different algorithms such as the minimum distance ofmean (MDM), Mahalanobis distance (MD), maximum likelihood (ML), artificial neural network (ANN), spectral anglemapper (SAM), and support vector machine (SVM) were...

Satellite image classification is one of the most significant applications in remote sensing. Remote sensing data obtained from different optical sensors have been commonly used to characterize and quantity land information. However, conventional optical remote sensing is limited by weather conditions. Synthetic aperture radar (SAR), with the allweather and all-time advantages, is important in ...

Due to the low information content of individual SAR images, single-band SAR data do not provide highly accurate land cover classification. However, in areas under risk where rapid land cover mapping is required, the advantages of SAR which include cloud penetration and day/night acquisition, are evident in comparison to optical data. The main research goal of this study is to fuse different fr...

land degradation is a major danger which restricting different areas of iran. systematic description of the environmentfor detection of environmental changes and the human-related causes and responses is essential in land cover changestudy. use of land cover data allow detection of where certain changes occur, what type of change, as well as how theland is changing. existing systems for classif...

The main objective of this project is to develop and test methodology using ENVISAT ASAR data for agricultural applications, with an emphasis on land use, land cover classification and rice mapping. An optimal pre-processing chain for ASAR data is first constructed to provide input data to the classification steps. Experiments at the Zhangzhou test site, Fujian province, southern China, indicat...

From the past epoch, there have been great hard work and researches are undertaken for mounting land-cover classification in data mining. Whereas the essential uses of the remotely-sensed images is for mainly land-cover classification, for the purpose of applications like monitoring the forest and agricultural areas. Through remote sensing technology an extensive diversity of digital imagery is...