Parcel-based classification of high-resolution images is one of the most reliable alternatives for the automatic updating of land cover/land use geospatial databases. Each parcel can be characterized by means of a set of features extracted from the image, its outline, the contextual relationships with its neighbours, etc. Qualitative information about the former land use contained in the geospa...

Spatial Database is a collection of spatially referenced data that acts as a model of reality. Geographical Information System includes spatial data which is either in raster or vector form and data derived from remote sensors are increasingly utilized as source for GIS. Spatial data is the core part of the Geographical Information System. Data mining techniques are studied to discover knowledg...

Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development [1]. Detection of such changes may help decision makers and planners to understand the factors in land use and land cover changes in order to take effective and useful measures. Remote sensing and GIS techniques ...

New aerial cameras and new advanced geoprocessing tools improve the generation of urban land cover maps. Elevations can be derived from stereo pairs with high density, positional accuracy, and efficiency. The combination of multispectral high-resolution imagery and high-density elevations enable a unique method for the automatic generation of urban land cover maps. In the present paper, imagery...

For the successful tree establishment, an evaluation of land suitability is necessary.In this paper, we demonstrate how to implement fuzzy classification of land suitability in aGIS environment for afforestation with Juglans regia in Gharnaveh Watershed of GolestanProvince in Iran. Juglans regia is one of the most important agro-forestry species in manyrural parts of Iran. Relevant criteria for...

The main aim of this research is to find optimum segmentation parameters for extracting different land cover classes. A relatively new segmentation approach, multiresolution segmentation, is being examined using two data sets (Landsat and IRS). Keywordsmultiresolution segmentation; object-based classification; land-cover classification

Remote sensing in urban areas has been a challenger for quite some time due to their complexity and fragment with combination of man-made features and natural features. High-resolution satellite images and airborne laser altimetry data offered potential possibilities for feature extraction and spatial modelling in urban areas. Land use classification of urban areas may become possible by exploi...

The aim of this work was to develop airborne laser scanning (ALS) based forest inventory for practical forest management by applying novel horizontal metrics and multiple data sources. In particular, this work examined classification of forest land attributes (study I), prediction of species-specific stand attributes (study II) and detection of spatial pattern of trees (study III) and need for ...

[1] This paper presents an ARTMAP neural network approach for burn detection in Moderate Resolution Imaging Spectroradiometer (MODIS) data using two methods: discrete and continuous classifications. The study area covers the states of Idaho and Montana in the United States, where extensive fire events took place during the months of July and August in the year 2000. The proposed approach differ...

Accurate land cover classification information is a critical variable for many applications. This study presents a method to classify land cover using the fusion data of airborne discrete return LiDAR (Light Detection and Ranging) and CASI (Compact Airborne Spectrographic Imager) hyperspectral data. Four LiDAR-derived images (DTM, DSM, nDSM, and intensity) and CASI data (48 bands) with 1 m spat...