Land cover change in any ecosystem vary in space and time. The study analyzed spatial-temporal land cover change to predict forest degradation pressure points in Eastern Mau Forest Reserve. The study objectives were to determine types and amount of spatial-temporal land cover change; land cover change drivers and; forest resources use sustainability. The study used mixed sample survey design involving purposive sampling of spatial data and cluster sampling of forest resource use data. Primary data included ground control points, field validation data and forest resource use data.

Yangon, the former capital of Myanmar, is the major economic areas of the country. Also, the urban areas have significantly increased. However, Yangon has problems with disasters such as flood and earthquake. To support disaster risk management in Yangon, Myanmar, the estimation of urban expansion is required to understand the mechanism of urban expansion and predict urban areas in the future. This research proposed a methodology to develop urban expansion modeling based the dynamic statistical model using Landsat Time-Series and GeoEye Images.

Land cover objects are reflected in a set of georeferential data and are constantly changing. These changes can be accurately examined by computer and interactive information systems. One of the main advantages of computer information systems is the fact that their maps can be constantly improved and updated. The update of georeferential data was conducted in a selected area using the ArcGIS software.

This study is the first to assess land subsidence in the Kathmandu Valley, Nepal. Land subsidence simulations were based on a fully calibrated groundwater (GW) flow model developed using a coupled surface–subsurface modelling system. Subsidence is predicted to occur as a result of deep aquifer compaction due to excessive GW abstraction. The north and north-east areas at the periphery of the GW basin are hotspots for this subsidence. The estimated subsidence is most sensitive to changes in land cover within the recharge areas.

Microbiological and enzymatic research has been conducted in the field experiment modeling different supply of Luvisol sandy loam soil with exchangeable magnesium (71, 84, 137, 172, 181 and 243 mg/kg) and even exchangeable acidity. It’s established that within the diapason of 70–170 Mg2+ content in soil and with NPK-fertilization it’s observed the increase of soil microbial biomass, metabolic activity of microbial communities, intensity of the main microbiological processes which regulate soil fertility – ammonification, carbonhydrates mineralization and plant residues humification.

application on the productivity of crop rotation and agrochemical characteristics of sod-podzol sandy soil. The influence of byproducts ploughing and mineral fertilizer doses on the crop rotation productivity and agrochemical indicators of sod-podzol sandy loam soil is studied. It is established that autumn application of a compensatory dose of nitrogen to the straw did not ensure the increased productivity of crop rotation.

Nowadays evaluation of intake of nutritive substances, especially potassium from organic fertilizers, with atmospheric precipitation and analysis of their losses in environment appears very perspective direction of scientific research. Migration of potassium depends on several factors such as soil composition, climatic conditions, cultivars, quantity of applied mineral fertilizers etc.

Modern technologies of information collection and processing appear the necessary means for the development of agricultural producing in the country. National soil information systems have been created in many countries all over the world. In the conditions of the Republic of Belarus there has been created a program-information complex aimed on concentration and systematization of information concerned to utilization of soil resources in agricultural practice.

Here we propose an accurate and robust method for large-area land-use and land-cover (LULC) mapping using multi-temporal optical data. The conventional method for LULC classification usually uses time-series data at regular intervals to consider the seasonality of LULC. However, high-resolution optical data have considerable seasonal biases, making it difficult to use time-series data.

Application of the satellite remote sensing techniques to wildlife research began from discernment of the individual animal and/or evaluation of animal behavior from the photography experiments. Satellite remote sensing to wildlife research at the present has applied for the purpose of evaluating the animal habitat. Trends in satellite remote sensing for wildlife are evaluating the index of wildlife habitat and estimating relationship with an environmental variables and animal distribution.