Land capability classification of Vernazza catchment, Cinque Terre National Park, Italy

Abruzzo National Park: land of dreams.

Application of remote sensing and geographical information system in mapping land cover of the national park

The study was conducted with the objective of mapping landscape cover of Nechsar National park in Ethiopia to produce spatially accurate and timely information on land use and changing pattern. Monitoring provides the planners and decision-makers with required information about the current state of its development and the nature of changes that have occurred. Remote sensing and Geographical Inf...

Change detection and classification of land cover at Hustai National Park in Mongolia

Land cover types of Hustai National Park (HNP) in Mongolia, a hotspot area with rare species, were classified and their temporal changes were evaluated using Landsat MSS TM/ETM data between 1994 and 2000. Maximum-likelihood classification analysis showed an overall accuracy of 88.0% and 85.0% for the 1994 and 2000 images, respectively. Kappa coefficients associated with the classification were ...

The Politics of Land Use in the Korup National Park

Recently, the call to combine land change science (LCS) and political ecology (PE) in the study of human-environment interactions has been widely discussed by scientists from both subfields of geography. In this paper, we use a hybrid ecology framework to examine the effects of conservation policies on the environment and the livelihood of the people of the Korup National Park (KNP). Using tech...

Clustering Approach on Land Use Land Cover Classification of Landsat TM Over Ulu Kinta Catchment

Providing accurate land use/ land cover (LULC), as an important component in remote sensing, have been a point of concern which subjected to many studies. Researchers have made great efforts in developing superior classification approaches and techniques which can lead to classification accurateness. This study was sought to investiagte LULC over Ulu Kinta Catchment in multispectral Landsat TM ...