The urban heat island effect poses a challenge in several cities, and may affect human and ecosystem health. It was proven that relatively small urban conglomerations in mid-latitudes, such as the case study region of Rostock, have undergone a considerable effect recently, noticeable particularly in the warm season. Due to climatic changes, these effects are expected to alter in intensity and/or frequency. This was investigated using a model that focuses on interactions between land use and surface temperatures and on specific air conditions in cities.

CONTEXT: Expansion of bioenergy production is part of a global effort to reduce greenhouse gas emissions and mitigate climate change. Dedicated biomass crops will compete with other land uses as most high quality arable land is already used for agriculture, urban development, and biodiversity conservation. OBJECTIVE: First, we explore the trade-offs between converting land enrolled in the U.S. Conservation Reserve Program (CRP) to switchgrass for biofuel production or preserving it for biodiversity.

Modern ecological models often account for the influence of the surrounding environment by using landscape pattern indices (LPIs) as measures of landscape structure. Ideally, the landscape samples from which these LPIs are extracted should be centered on the locations where the response variable was measured. However, in situations where this is not possible due to a lack of adequate full-coverage landcover data, the question arises as to what degree this circumstance creates a bias in the value of the LPIs, thereby obscuring their relation with the response variable.

Land use is a key driver of global environmental change. Unless major shifts in consumptive behaviours occur, land-based production will have to increase drastically to meet future demands for food and other commodities. One approach to better understand the drivers and impacts of agricultural intensification is the identification of global, archetypical patterns of land systems. Current approaches focus on broad-scale representations of dominant land cover with limited consideration of land-use intensity.

Wetlands provide vital ecosystem services such as water purification, flood control, and climate moderation among others, which enhance environmental quality, promote public health, and contribute to risk reduction. The biggest threat to wetlands is posed by human activities which transform wetlands, often for short-term consumptive benefits. This paper aimed to classify and map recent land cover and provide a multi-temporal analysis of changes from 2002 to 2014 in the Nakivubo wetland through which wastewater from Kampala city drains to Lake Victoria in Uganda.

The present study compares the effectiveness of two common preclassification change detection (CD) methods that use two-dimensional data space of spectral-textural (S-T) change information. The methods are principal component analysis (PCA) and change vector analysis (CVA) in the Gorgan Township area, Golestn Province, Iran. A series of texture-based information was calculated mainly to separate those land use/land cover (LULC) conversions that are spectrally indistinguishable and also to provide a basis for automatic classification of S-T data space.

We examined the utility of nutrient criteria derived solely from total phosphorus (TP) concentrations in streams (regression models and percentile distributions) and evaluated their ecological relevance to diatom and algal biomass responses. We used a variety of statistics to characterize ecological responses and to develop concentration-based nutrient criteria (derived from ecological effects) for streams in Connecticut, USA, where urbanization is the primary cause of watershed alteration.

A complete, spatially explicit dataset illustrating the 21st century mining footprint for the conterminous United States does not exist. To address this need, we developed a semi‐automated procedure to map the country's mining footprint (30‐m pixel) and establish a baseline to monitor changes in mine extent over time. The process uses mine seed points derived from the U.S. Energy Information Administration (EIA), U.S.

Ashfall and pyroclastic flows from the large eruption of June 1991 destroyed much of the vegetation on the flanks of Mt. Pinatubo. Subsequent vegetation recovery has helped stabilize slopes and reduce debris flow hazard. In this project, visible and near-infrared (VNIR) satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (ASTER) captured at a similar time of year in 2001, 2004 and 2008 were used to quantify vegetation recovery within 22 upland watersheds on the mountain, 10–16 years after the eruption took place.

A number of classification techniques to generate land cover maps from satellite imagery have been proposed but supervised classification with manual selection and delineation of training samples (TSs) continues to be the preferred technique. The current practices of field visits and manual delineation of TSs by visual recognition are highly demanding on both resources and time, with limited utility.

Oil exploration and production activities (OEPA) and other extractive endeavors can create large-scale and permanent landscape alterations through the establishment of infrastructure features such as roads, well pads, pipelines and production facilities. These structures can lead to or increase landscape fragmentation and degradation, reduce biodiversity, disrupt important ecosystem services and attract informal settlements that further alter the landscape, deplete area resources and lead to social conflict.

Coyotes (Canis latrans) have expanded to live in urban areas with limited natural habitat. A year long coyote howl survey combined with geospatial information systems (GIS) was applied to locate populations within a metropolitan region, to determine the habitats where coyotes most frequently occur, and to estimate group sizes within this urbanized region. Surveys were conducted along the perimeters of natural areas and urban-residential communities.