Land is becoming a scarce natural resource due to the burgeoning population growth and urbanization. Essentially, detecting changes in land surface is significant for understanding and assessing human impacts on the environment. Nowadays, land use change detection using remote sensing data provides quantitative and timely information for management and evaluation of natural resources. This stud...

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...

This paper explores the use of ALOS (Advanced Land Observing Satellite) PALSARL-band (Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. Transformed divergence was used to identify potential textural images which were calculated with the gray-level co-occurrence matrix method. The standard deviation of selected...

An ever increasing population associated with various other factors has put tremendous pressure on the environment and its respective resources. Hence it has become necessary to study the human interactions with its surrounding environment to facilitate sustainable developmental plans. Land use and land cover is the most dominant factor to study these interactions. Remote Sensing technology has...

Using satellite imagery for the study of Earth's resources is attended by manyresearchers. In fact, the various phenomena have different spectral response inelectromagnetic radiation. One major application of satellite data is the classification ofland cover. In recent years, a number of classification algorithms have been developed forclassification of remote sensing data. One of the most nota...

Urban land cover classification using remote sensing data is quite challenging due to spectrally and spatially complex urban features. The present study describes the potential use of hyperspectral data for urban land cover classification and its comparison with multispectral data. EO-1 Hyperion data of October 05, 2012 covering parts of Bengaluru city was analyzed for land cover classification...

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...

Land use mapping is one of the major applications of remote sensing. While most studies focus on the advanced remote sensing thematic classification algorithms for land use mapping, the scale factor in remote sensing data classification was less recognized. Previous studies showed that while the multi-scale characteristics exist in the remotely sensed data for land use classification, some clas...

classifying remote sensing imageries to obtain reliable and accurate landuse/cover (luc) information still remains a challenge that depends on many factors suchas complexity of landscape especially in arid region. the aim of this paper is to extractreliable luc information from land sat imageries of the pishkouh watershed of centralarid region, iran. the classical maximum likelihood classifier ...

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon fo...