A ca. 1980 national-scale land-cover classification based on aerial photo interpretation was combined with 2000 AVHRR satellite imagery to derive land cover and land-cover change information for forest, urban, and agriculture categories over a seven-state region in the U.S. To derive useful land-cover change data using a heterogeneous dataset and to validate our results, we a) stratified the cl...

Medium-scale land cover maps are traditionally created on the basis of a single cloud-free satellite scene, leaving information present in other scenes unused. Using 1309 field observations and 20 cloudand error-affected Landsat scenes covering Zanzibar Island, this study demonstrates that the use of multiple scenes can both allow complete coverage of the study area in the absence of cloud-free...

Detailed and precise information of land-use and land-cover (LULC) in rural area is essential for land-use planning, environment and energy management. The confusion in mapping residential and industrial areas brings problems in energy management, environmental management and sustainable land use development. However, they remain ambiguous in the former rural LULC mapping, and this insufficient...

Despite being inside a protected area, Lake Sumidouro has been impacted by the anthropogenic occupation of the surrounding area since the 1970's, compromising the ecological integrity of the lake and the sustainable use of natural resources. This study examined the current trophic classification of the lake and developed methods for improving it through an integrated analysis of morphometric an...

In this paper, the author evaluates the results of applying two evolving classification techniques, decision trees (DT) and artificial neural networks’ back-propagation (ANN-BP), to obtain land cover and land use classes from Quickbird XS data combined with spatial metrics, in a selected urban zone in Bogota, Colombia. In order to improve the quality of the land cover classification, additional...

This thesis describes the study of Artificial Neural Network (ANN) based techniques for the classification of aerial images for various types of land-use. In this study both gray-scale and multispectral aerial images were used in land-use classification. Three approaches were used for the preparation of the data as inputs to the ANN, including histograms of the pixel intensities, textural param...