Google Street View (GSV) was used for urban land use classification, together with airborne light detection and ranging (LiDAR) data and high resolution orthoimagery, by a parcel-based method. In this data article, we present the input raw GSV images, intermediate products of GSV images, and final urban land use classification data that are related to our research article "Parcel-based urban la...

With the rapid advances in sensors of remote sensing satellites, a large number of high-resolution images (HRIs) can be accessed every day. Land use classification using high-resolution images has become increasingly important as it can help to overcome the problems of haphazard, deteriorating environmental quality, loss of prime agricultural lands, and destruction of important wetlands, and so...

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...

The main purpose of this study was to assess the effect of ecosystem classification systems at various scales on environmental parameters using remote sensing techniques. The processes included applying hybrid classification to generate a land-use map of northern Taiwan using Landsat-5 image in 1995; using the DTM and the SEBAL model to calculate 16 environmental parameters to compare the diffe...

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...

The growth of cities represents huge problems for modern societies. Monitoring, analysing and modelling the urban dynamic call for detailed mapping of urban land-use. Traditionally, urban land-use mapping is based on orthophotos and satellite images, but deriving land-use from remote-sensing alone is not satisfactory. The Danish Building & Dwelling Register is a database containing detailed inf...

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...

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...