Image classification is a complex process that may be affected by many factors. This paper
examines current practices, problems, and prospects of image classification. The emphasis …

Natural and anthropogenic processes at the Earth's surface operate at a range of spatial and
temporal scales. Different scales of observation are required to match the spatial scales of …

Abstract Land Use/Land Cover change detection is an inspiring, interesting task to be
performed worldwide. The real-time satellite data of the earth's surface and its different …

Feature selection is a key task in remote sensing data processing, particularly in case of
classification from hyperspectral images. A logistic regression (LR) model may be used to …

Urban Remote Sensing The second edition of Urban Remote Sensing is a state-of-the-art
review of the latest progress in the subject. The text examines how evolving innovations in …

Digital image classification is generally performed to produce land cover maps from remote
sensing data, particularly for large areas. The performance of image classifiers that utilize …

This paper examines the subpixel analysis of Landsat ETM/sup+/data to estimate the
percent cover of impervious surface, lawn, and woody tree cover in typical urban/suburban …

With urbanization as a global phenomenon, there is a need for data and information about
these terrains. Urban remote sensing techniques provide critical physical input and …

Although soft classification analyses can reduce problems such as those associated with
mixed pixels that impact negatively on conventional hard classifications their accuracy is …

The segmentation and classification of high-resolution satellite images (HRSI) are useful
approaches to extract information. In recent times, roads and buildings have been classified …