Driven principally by government regulation and societal expectations, mining companies around the world are seeking to mitigate the environmental impacts of mining through mined land rehabilitation programs. The ultimate goal of rehabilitation is to establish an acceptable and sustainable post-mining land use. Mining companies worldwide face the challenge of specifying just what a sustainable post-mining land use will be.

Scholars of pastoralism often refer to changes of pastoral land tenure as ‘encroachment.’ The New Zealand case of pastoral land tenure reform suggests that this is incorrect for several reasons. First it takes the point of view of the pastoralist, which introduces unnecessary bias. Second, it assumes that all changes in land tenure are situations in which the state, or another powerful agent, takes land away from the less powerful pastoralists.

Timber harvest often results in accelerated soil erosion and subsequent elevated fine (

Intense anthropogenic exploitation has altered distribution of forest resources. This change was analyzed using visual interpretation of satellite data of 1979, 1999 and 2009. Field and interactive social surveys were conducted to identify spatial trends in forest degradation and data were mapped on forest cover and land use maps. Perceptions of villagers were compiled in a pictorial representation to understand changes in forest resource distribution in central Himalaya from 1970 to 2010. Forested areas were subject to degradation and isolation due to loss of connecting forest stands.

In the present study, Remote Sensing Technique and GIS tools were used to prepare landslide susceptibility map of Shiv-khola watershed, one of the landslide prone part of Darjiling Himalaya, based on 9 landslide inducing parameters like lithology, slope gradient, slope aspect, slope curvature, drainage density, upslope contributing area, land use and land cover, road contributing area and settlement density applying Analytical Hierarchy Approach (AHA). In this approach, quantification of the factors was executed on priority basis by pair-wise comparison of the factors.

Agriculture and forestry play an important role in emitting and storing greenhouse gases. For an efficient and cost-effective climate policy it is therefore important to explicitly include land use, land use change, and forestry (LULUCF) in economy-climate models. This paper gives an overview and assessment of existing approaches to include land use, land-use change, and forestry into climate-economy models or to link economy-climate models to land-use models.

The wild boar is the target species selected for developing a GIS model of potential habitat for big game species, mainly using many GIS layers and kilometric abundance indices (KAI). We identify and weight environmental factors that determine the suitability for wild boar populations in a Mediterranean region, highly influenced by urban and agro-forestry activities. Marina Baja region (Spain) is selected to make a regional analysis. In the GIS modelling process, a suitability value is assigned to each pixel, which represents the habitat preference of the species.

The remaining Atlantic Forest fragments are structurally isolated by a matrix of pastures, plantations, or urban areas, and most remnants are small (

Today, GIS is used in many areas. One of the most important using area is agriculture and it provides great advantages in this area.

CBS günümüzde birçok alanda kullanılmaktadır. En önemli kullanım alanlarından biri de tarımdır ve bu alanda büyük kolaylıklar sağlamaktadır. CBS ile tarımsal taşınmazların değerlemesinde ortaya çıkan problemler önemli ölçüde çözülebilmektedir.

Development of accurate classification methods for rapidly changing catchments like that of Lake Basaka is fundamental to better understanding the catchment dynamics, which were not addressed in previous studies. Thus, the aim of this study was to map the decadal land use/cover (LUC) regimes of the Lake Basaka catchment, utilizing time series of LANDSAT images and to analyse the changes that occurred at different time periods. Both unsupervised and supervised image classification systems were utilized in Earth Resources Data Analysis System (ERDAS) Imagine (9.1).