We tested the effectiveness of the Purposive Selection selected using the AVHRR tiles. A random sample was also selected for comparison. The domain AVHRR cover Algorithm (PSA, described in the companion first article) to accurately estimate land cover composition over a type fractions were then corrected using TM maps for the selected tiles, following the method of Walsh and Burk large area. Th...

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...

Detailed and accurate land cover and land cover change information is needed for South America because the continent is in constant flux, experiencing some of the highest rates of land cover change and forest loss in the world. The land cover data available for the entire continent are too coarse (250 m to 1 km) for resource managers, government and non-government organizations, and Earth scien...

Given the current lack of interoperability between global and regional land cover products, efforts are underway to link the new European global land cover map (GLOBCOVER) with the existing global land cover 2000 map (GLC2000) and European CORINE mapping initiative. Since both datasets apply different mapping standards, key for a successful implementation is a thorough understanding of the hete...

Global urban expansion has created incentives to convert green spaces to urban/built-up area. Therefore, understanding the distribution and dynamics of the land-cover changes in cities is essential for better understanding of the cities’ fundamental characteristics and processes, and of the impact of changing land-cover on potential carbon storage. We present a grid square approach using multi-...

This note concerns the updating of the land cover map of the Arno River basin (9.000 km) developed in the frame of a research project aimed at landslide risk assessment. The land cover map has been produced through the analysis of panchromatic/multispectral Landsat ETM+ images and TERRA-ASTER data; those data were integrated and compared with B/W and color ortho-photos. To improve photointerpre...

The efficiency of three statistical models, AHP surface-weighted density bivariate (semi-quantitative models), stepwise multivariate regression and logistic multivariate regression models were compared in Chehel-Chai watershed in Golestan province, Iran. In current study the hazard map was prepared according to the top model of landslide hazard map. Chehel-Chai watershed is located as one of Go...

Preparation of land cover / land use maps for large areas, based on automatic classification of high-resolution satellite data is the objective of many application programmes, e.g. GSE Land Monitoring Services. The crucial point for this kind of activity is to apply optimal classification approach, which will ensure high class recognition accuracy and classification repeatability. Among differe...