In the conditions of the Republic of Belarus there was examined transformation of approaches to the estimation of the role and place of land resources in social-economic development of society. There was marked the increased understanding of land use planning problems in the context of increasing its intensity and important problem of stable development of rural areas in modern world. There were established the problems of increasing ecological-economic efficiency of land use.

In Central Asia, water is a particularly scarce and valuable good. In many ecosystems of this region, the vegetation development during the growing season is dependent on water provided by rainfall. With climate change, alterations of the seasonal distribution of precipitation patterns and a higher frequency of extreme events are expected. Vegetation dynamics are likely to respond to these changes and thus ecosystem services will be affected.

Karst rocky desertification (KRD) is a type of land degradation especially prominent in southwest China. This article analyzes the anthropogenic driving forces of KRD at two scales: rural locality and its macro socio‐economic circumstances. At the rural locality scale, the intensive human pressure on land because of a large and fast growing population and unsustainable land use are identified to be the reason for KRD. However, more radical driving forces lie in the farmers' disadvantages in social‐economic circumstances, which compel them to overuse rural land.

Wildfires increased dramatically in frequency and extent in the European Mediterranean region from the 1960s, aided by a general warming and drying trend, but driven primarily by socio-economic changes, including rural depopulation, land abandonment and afforestation with flammable species. Published research into post-wildfire hydrology and soil erosion, beginning during the 1980s in Spain, has been followed by studies in other European Mediterranean countries together with Israel and has now attained a sufficiently large critical mass to warrant a major review.

Land areas in collective ownership or use are traditionally referred to as commons. Through history, the common use and ownership has been a widespread means of regulating the use of natural resources. Changing economic conditions and technology spawned a process however where land use rights and landowner rights aggregated into the modern form of private ownership of individual farms with full management and owner rights. This process had obvious rationales in terms of production of marketable agricultural products.

This paper examines environmental disturbances related to energy development in the Orenburg region through a two-pronged approach. First, it ranks environmental performance per 25 administrative districts based on multidimensional clustering of 10 diagnostic indicators. Second, it examines land-use and land-cover (LULC) patterns in nine western administrative districts by classifying Landsat imagery and quantifying surface disturbance for the year 2001. Spatial analysis and descriptive statistics help identify the most disturbed administrative units.

We estimate a system of equation model to understand the factors that influence the loss of agricultural land to non-agricultural uses in the Southeast United States. This is done by analyzing the complex relationship between population, employment, and agricultural land density for the 1990–-2000 period. From the results, it can be noted that growth in employment over time and the expansion of residential housing have to be compromised with the agricultural sector on the use and allocation of land.
Revised version of paper added to AgEcon Search 10/06/05.

In this paper we present the generic modelling system SITE (SImulation of Terrestrial Environments), a software package to develop and apply models simulating regional land-use dynamics. The modelling system includes (i) a framework managing the model generics and (ii) code templates for the development of rule-based land-use and land-cover change (LUCC) models. SITE comprises built-in methods for e.g. map comparison, model optimization and environmental scenarios.