Land cover classification of Landsat images is one of the most important applications developed from Earth observation satellites. The last four decades were marked by different developments in land cover classification methods of Landsat images. This paper reviews the developments in land cover classification methods for Landsat images from the 1970s to date and highlights key ways to optimize...

Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised c...

For researching properties of HJ-1A CCD camera multispectral data in performance on extraction of land features information, this paper selected the east area of NiLeke forest farm in the western Tianshan mountain as the study area, and analyzed different accuracies for HJ-1A CCD data in identifying forest land categories using various classification methods. Firstly, maximumlikelihood classifi...

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...

This paper proposes a two-layer Conditional Random Field model for simultaneous classification of land cover and land use. Both classification tasks are integrated into a unified graphical model, which is reasonable due to the fact that land cover and land use exhibit strong contextual dependencies. In the CRF, we distinguish a land cover layer and a land use layer. Both layers differ with resp...

YUAN, HUI. Development and Evaluation of Advanced Classification Systems using Remotely Sensed Data for Accurate Land-Use/Land-Cover Mapping. (Under the direction of Dr. Siamak Khorram.) Our general objective in this research was to design, develop, implement, and evaluate advanced classification approaches for more accurate land-use/land-cover mapping using remotely sensed data. The overall re...

land cover is one of basic data layers in geographic information system for physical planning and environmentalmonitoring. digital image classification is generally performed to produce land cover maps from remote sensing data,particularly for large areas. in the present study the multispectral image from irs liss-iii image along with ancillary datasuch as vegetation indices, principal componen...

Mapping land cover change is an important problem for the scientific community as well as policy makers. Traditionally, bi-temporal classification of satellite data is used to identify areas of land cover change. However, these classification products often have errors due to classifier inaccuracy or poor data, which poses significant issues when using them for land cover change detection. In t...

An artificial neural network is a system based on the operation of biological neural networks, in other words, is an emulation of biological neural system. Artificial Neural Networks or simply Neural Networks are powerful general purpose computing tools. They have become popular in the analysis of remotely sensed data, particularly in classification or feature extraction from image data more ac...

SUMMARY One of the main parameter for urban heat island mapping is the land cover information. Satellite data were used to map the land cover over the study area, CyberJaya. Remotely sensed data were processed using pixel based and object based image processing techniques. Most traditional classification approaches are based exclusively on the digital number of the pixel itself. Thereby only th...