In this work we begin by performing a Principal Component Analysis (PCA) on NDVI computed over clear-sky pixels from VEGETATION data. Two techniques (i.e. ISODATA and Fuzzy Clustering) are applied to the two retained Principal Components and used to produce a land cover map over Portugal. Quality of performed classifications is assessed based on a confusion matrix, using as reference the Corine...

Detection of urban objects in very high resolution (VHR) satellite imagery is challenging due to the similarities in the spectral and textural characteristics of urban land cover classes. Therefore, additional information such as elevation data is required for a proper classification. In this study, instead of LiDAR data, elevation information generated from satellite stereo images is used to a...

Accurate representation of actual terrestrial surface types at regional to global scales is an important element for many applications. Based on National Aeronautics and Space Administration Moderate Resolution Imaging Spectroradiometer land cover algorithms, a global surface-type product from observations of the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Pola...

in this research, the applicability of geographic information system (gis) and remote sensing (rs) techniques was tested to assess soil erosion risk with the icona erosion model. this study was carried out in the tange bostanak area because of its variety of diverse landforms, land uses and land covers. the erosion risk assessment phase of this model consists of seven steps that mainly use slop...

Transformation of land use-land cover change occurs due to the numbers and activities of people. Urban growth modeling has attracted authentic attention because it helps to comprehend the mechanisms of land use change and thus helps relevant policies made. This study applied logistic regression to model urban growth in the Ahvaz Metropolitan Area of Khuzestan province in IDRISI Selva software a...

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...