A standard methodology is needed to recognize potentially suitable areas for sustainable bioenergy crop production. This facilitates better identification of promising crops and cropping systems, logistical and economic studies, and work needed to meet regulatory criteria. A possible approach is built upon three layers of internationally available spatial data: (1) degrading and abandoned areas, (2) potentially suitable land cover classes, (3) exclusion zones such as nature reserves and areas of high biodiversity.

The rapid urbanization of the world has significant ecological consequences that shape global biodiversity patterns. The plant communities now common in urban centers may represent new habitats with unique dynamics and the potential for highly modified ecological services. This study, joining extensive spatial and floristic data sets, examined current distribution patterns of non-native and native woody plant species in the New York metropolitan region, USA.

Dry subtropical regions, originally hosting xerophytic vegetation, are currently characterized by diverse land cover/use patterns. Using existing biophysical and socio-economic databases, we explored how human contexts influenced land cover, vegetation composition and agricultural production in five distant regions. On average, cultivated areas represented a minor proportion (

Airborne Laser Swath Mapping instrument technology and subsequent algorithm advances have made it possible over the last few years to map the Earth's surface and land cover at unprecedented resolution. The ability of Airborne Laser Swath Mapping technology to densely sample ground elevations beneath forest canopies is particularly important because forested watersheds have traditionally been difficult to study with remote sensing techniques.

The effects of urban sprawl, at the expense of green natural areas, and the increasing anthropogenic pressure on these areas, lead to significant changes in land cover composition and structure. One of the threats and hazardous aspects of the urban sprawl is the disposal of construction site waste (CW) at the cities’ fringes and by the roadsides. The analysis of vegetation community structure over space and time in such areas may contribute to the understanding of community dynamics at the urban fringe following modern human intervention.

Recognition of geomorphic features, such as landslide scarps, is the first key step for landslide risk assessment and mitigation. Geomorphic features can be identified from high-resolution digital elevation model (DEM). Light Detection and Ranging (LiDAR) is a useful tool to collect high-density point elevation data from ground surfaces. LiDAR ground points are used to generate high-resolution DEMs. However, LiDAR sample sizes and interpolation methods are critical parameters for DEM estimation under various land cover types.

BACKGROUND: Southeast Asia presents a high diversity of Anopheles. Environmental requirements differ for each species and should be clarified because of their influence on malaria transmission potential. Monitoring projects collect vast quantities of entomological data over the whole region and could bring valuable information to malaria control staff but collections are not always standardized and are thus difficult to analyze.

We analysed spectral and textural attributes from the Advanced Land Imager (ALI)/EO-1 for land-cover mapping and inspected their correlation with biophysical parameters of primary and secondary forests from Eastern Amazon. An artificial neural network (ANN) technique selected the most relevant spectral/textural attributes, which were combined for classification of the ALI scene. From the ANN land-cover map, areas classified as primary forest (PF), initial (SS1), intermediate (SS2) and advanced (SS3) stages of secondary succession were studied.

A major challenge in modeling the carbon dynamics of vegetation communities is the proper parameterization and calibration of eco-physiological variables that are critical determinants of the ecosystem process-based model behavior. In this study, we improved and calibrated a biochemical process-based WxBGC model by using in situ AmeriFlux eddy covariance tower observations. We simulated carbon dynamics of fire-dominated forests at tower sites and upscaled the tower site-based simulations to regional scale for the New Jersey Pinelands using LANDSAT-ETM land cover and DAYMET climate data.

Conversion of land for agriculture has led to the channelisation of headwater streams and reduced water quality. Resident fish populations are expected to be challenged under such conditions and may experience declines that lead to a loss of neutral genetic variation. However, species‐specific responses to recent ecological changes in stream condition and/or range expansion following glacial retreat can also influence the pattern of genetic variation found within and among contemporary populations.

In this study, a data-driven weights of evidence (WOE) technique was used to demarcate groundwater potential zones at northeastern Missan and Wasit governorates, Iraq using geographic information system (GIS) platform. In the first step, borehole location inventory map consisting of 143 with relatively high yield (>8 L/s) was prepared. Then, eight influencing groundwater factors, namely altitude, slope, geology, land use/land cover, distance to roads, distance to faults, aquifer type, and depth of wells were prepared and integrated into spatial database.

Urban sprawl along the Mediterranean coast is characterized by single-family houses and domestic gardens. Many new residences are secondary homes for socio-demographically diverse tourists. We explore the differences between the residence types in terms of their garden structures and plant compositions using socioeconomic and legacy attributes. Outdoor areas of 245 primary and secondary homes were investigated to determine plant compositions, land cover and household characteristics. Then, the outdoor land cover was compared between the two residence types.