Mato Grosso has emerged as the Brazilian state with the highest deforestation rate, and with the most dynamic changes in vegetation and land cover. In this article, we focus on the following two main objectives: (i) to quantitatively assess the extent of vegetation change over the past two decades for more accurate eco-climatic impact analysis; and (ii) to clarify the causes to the changes in this state, with special focus to agro-pastoral activities and roads networks.

Adult coho salmon Oncorhynchus kisutch return each autumn to freshwater spawning habitats throughout western North America. The migration coincides with increasing seasonal rainfall, which in turn increases storm water run‐off, particularly in urban watersheds with extensive impervious land cover. Previous field assessments in urban stream networks have shown that adult coho are dying prematurely at high rates (>50%).

Perennial coolwater streams (maximum daily mean water temperature 20.7–24.6°C; 90th percentile annual exceedence flow≥0.0283m³/s) are common in the Laurentian Great Lakes region of North America, including the state of Wisconsin, but they lack specific and effective bioassessment tools.

Socioecological theory, developed through the study of urban environments, has recently led to a proliferation of research focusing on comparative analyses of cities. This research emphasis has been concentrated in the more developed countries of the Northern Hemisphere (often referred to as the “Global North”), yet urbanization is now occurring mostly in the developing world, with the fastest rates of growth in sub‐Saharan Africa.

Large-scale land conversion for agriculture in Brazilian Amazonia is occurring at persistently high rates. Basin-wide net land use and land cover changes imply substantially different situations between distinct regions and states due to different agricultural policies. This research used eight landscape metrics to quantify and investigate the spatial patterns of cattle pasture and cropland throughout the states of Pará, Mato Grosso, Rondônia, and Amazonas.

Intensification of human activities has caused drastic losses in semi-natural habitats, resulting as well in declining connectivity between remaining fragments. Successful future restoration should therefore increase both habitat area and connectivity. The first steps in a framework for doing so are addressed here, which involve the mapping of past habitat change.

We apply a linear regression mixed effects model to explore the influence of landscape factors on nitrate-N concentrations in a coastal watershed of Portugal. Landscape composition and configuration metrics, together with variables assessing the physical characteristics of the study area, were used. The analysis was performed using seasonal data from the years 2001 and 2006. The seasonal influence was included as a random effect to account for temporal correlations. Together, the fixed and the random factors explain 78% of the variance, whereas the fixed factors alone explain 10%.

This research investigated the effects of climate and land cover change on variation in sagebrush ecosystems. We combined information of multi-year sagebrush distribution derived from multitemporal remote sensing imagery and climate data to study the variation patterns of sagebrush ecosystems under different potential disturbances. We found that less than 40% of sagebrush ecosystem changes involved abrupt changes directly caused by landscape transformations and over 60% of the variations involved gradual changes directly related to climatic perturbations.

Cropland fires are an important source of black carbon (BC) emissions. Previous research has suggested that springtime cropland burning in Eastern Europe, more specifically Russia, is a main contributor of BC in the Arctic atmosphere, acting as a short-lived climate forcer strongly influencing snow-ice albedo and radiation transmission.

Recent land cover change estimates show overall decline of tropical forests at the regional and global scales caused by multiple social, cultural and economic factors. There is an overall concern on the prevailing land use practices, such as shifting cultivation and extraction of forest materials as agents of forests losses, but also new, emerging land uses are threatening tropical forests. Understanding of the long-term development and driving forces of forest changes are needed, especially at local levels where many decisions on forest policies and land uses are made.

Super-resolution mapping (SRM) is a process that provides land-cover spatial distribution with a spatial resolution finer than the size of a remotely sensed image pixel. Usually, the fraction images generated from soft classifiers are used as constraints in SRM, making the accurate estimation of fraction images an important task in SRM. Supervised fuzzy c-means (sFCM), which belongs to the fuzzy-set technology commonly applied for unmixing mixed pixels, is capable of providing accurate estimates of fraction images used for SRM.

Chennai city the capital of Tamil Nadu is located in southeastern India. Its average population growth rate is 25% per decade, which recurrently alters the city's land-cover particularly the receding green-cover distressed the city's self-renewal capacity, in terms of groundwater recharge, pollution sequestration and microclimatic amelioration. This has been appraised by means of a GIS model. This model was developed using three sets of green-cover associated parameters, namely air quality amelioration, hydrological process regulation and microclimatic amelioration.