In this study, a new classification algorithm in which only the selected pixels have been attempted to be classified (selected pixels classification: SPC) has been introduced and compared with the well known supervised classification methods such as maximum likelihood, minimum distance, nearest neighbour and condensed nearest neighbour. To examine the algorithm. Landsat Thematic Mapper (TM) data have been used to classify the crop cover in the selected region. It is clearly demonstrated that the SPC method has the higher accuracy with comparable CPU times
Land use land cover (LULC) classification is a valuable asset for resource managers; in many fields ...
Remote sensing measurements provide an accurate and timeous record of the landscape components. This...
Satellite image classification is crucial in various applications such as urban planning, environmen...
In this study, land cover types in Zonguldak test area were analysed on the basis of the classificat...
Two supervised classification methods, the maximum likelihood and ellipsoid classification methods [...
Abstract Classification is the technique by which real world objectsland covers are identified withi...
Obtaining reliable and accurate crop classification and land cover map based on satellite data, in p...
Although a large number of new image classification algorithms have been developed, they are rarely ...
Accurate agricultural land use (LU) map is essential for many agro-environmental applications. With ...
Pixel-based and object-based classifications are two commonly used approaches in extracting land cov...
Landscape fragmentation is quite dominant in Mediterranean regions and poses significant problems in...
Land use classification is an important part of many remote-sensing applications. A lot of research ...
Recognizing different types of crops trough satellite imagery is an important application of Digital...
Paddy rice area estimation via remote sensing techniques has been well established in recent years. ...
In this study, Kwali Council Area located on the western part of the Federal Capital Territory, Abuj...
Land use land cover (LULC) classification is a valuable asset for resource managers; in many fields ...
Remote sensing measurements provide an accurate and timeous record of the landscape components. This...
Satellite image classification is crucial in various applications such as urban planning, environmen...
In this study, land cover types in Zonguldak test area were analysed on the basis of the classificat...
Two supervised classification methods, the maximum likelihood and ellipsoid classification methods [...
Abstract Classification is the technique by which real world objectsland covers are identified withi...
Obtaining reliable and accurate crop classification and land cover map based on satellite data, in p...
Although a large number of new image classification algorithms have been developed, they are rarely ...
Accurate agricultural land use (LU) map is essential for many agro-environmental applications. With ...
Pixel-based and object-based classifications are two commonly used approaches in extracting land cov...
Landscape fragmentation is quite dominant in Mediterranean regions and poses significant problems in...
Land use classification is an important part of many remote-sensing applications. A lot of research ...
Recognizing different types of crops trough satellite imagery is an important application of Digital...
Paddy rice area estimation via remote sensing techniques has been well established in recent years. ...
In this study, Kwali Council Area located on the western part of the Federal Capital Territory, Abuj...
Land use land cover (LULC) classification is a valuable asset for resource managers; in many fields ...
Remote sensing measurements provide an accurate and timeous record of the landscape components. This...
Satellite image classification is crucial in various applications such as urban planning, environmen...