Nest survival is a critical factor affecting avian demographics, and can be influenced by nesting chronology, fine scale nest-site selection and broad-scale landscape characteristics. We modeled the relative influences of nest age, temporal variation in nest success and habitat-related covariates at two spatial scales (nest-site and patch scale) on daily nest survival during incubation for eastern wild turkeys Meleagris gallopavo silvestris in a mixed-use landscape. Daily survival rate of turkey nests during incubation increased as percent understory cover (vegetation

Extracting information about saline soils from remote sensing data is useful, particularly given the environmental significance and changing nature of these areas in arid environments. One interesting case study to consider is the delta oasis of the Weigan and Kuqa rivers, China, which was studied using a Landsat Enhanced Thematic Mapper Plus (ETM+) image collected in August 2001. In recent years, decision tree classifiers have been successfully used for land cover classification from remote sensing data.

Arid regions in Asia are commonly characterized by rapidly growing populations with limited land resources and varying rainfall frequencies under climatic change. Despite being one of the most important environmental challenges in Asia, the changing aridity in this region, particularly due to large-scale land cover change, has not been well documented. In this study, we used rainfall data and a new land heterogeneity index to identify recent trend in land cover changes in the Asian arid regions.

Many production landscapes are complex human-environment systems operating at various spatio-temporal scales and provide a variety of ecosystem goods and services (EGS) vital to human well-being. EGS change over space and time as a result of changing patterns of land use or changes in the composition and structure of different vegetation types. Spatio-temporal assessment of EGS can provide valuable information on the consequences of changing land use and land cover for EGS and helps to deal with this complexity.

Ecological risk assessments are used by policy makers and regulatory agencies for balancing and comparing ecological risks associated with environmental hazards. An approach for regional—scale ecological risk assessment is described and demonstrated by modeling environmental risks associated with elevated ozone in a forested region. The demonstration illustrates (1) how a regional—scale risk assessment might be done, (2) the importance of spatial characteristics in considering regional—scale risk, and (3) the necessity of considering terrestrial and aquatic linkages.

Assessments of ecosystem services (ES) and biodiversity (hereafter ecological parameters) provide a comprehensive view of the links between landscapes, ecosystem functioning and human well‐being. The investigation of consistent associations between ecological parameters, called bundles, and of their links to landscape composition and structure is essential to inform management and policy, yet it is still in its infancy.

This paper presents findings of a land-use and land-cover (LULC) change mapping exercise conducted in Freetown, Sierra Leone. Nine LULC classes were mapped from multi-temporal Landsat data of 1974, 1986 and 2000. Special attention was given to the growth or otherwise of agricultural land in relation to other LULC classes. Conversion of one land-use/-cover type to the other was identified, and its effects discussed. Major conversions occurred between agricultural lands, grasslands, evergreen forest, built-up areas and barren land.

Analysis of land-cover change in the seasonal tropical forests of the Southern Yucatán, Mexico presents a number of significant challenges for the fine-scale land-cover information required of land-change science. Subtle variation in mature forest types across the regional ecocline is compounded by vegetation transitions following agricultural land uses. Such complex mapping environments require innovation in multispectral classification methodologies. This research presents an application of a step-wise maximum likelihood/In-Process Classification Assessment (IPCA) procedure.

Integrating social demands into landscape management has been proven difficult because of a lack of suitable measures. In order to address this issue this article describes the development of the Index of Function Suitability (IFS). This offers an integrated conceptual tool for incorporating social demands into landscape management. The IFS links preferences to land cover spatial patterns as it uses quantitative indicators for gauging differences between the preferred landscape patterns by users, for a certain activity related to an amenity function (e.g.

Two-thirds of the total area of Taiwan is mountainous terrain, which is the main groundwater recharge source of the plains region. This study assesses groundwater recharge and exploitative potential zone in the central division of the mountain areas of Taiwan (the middle reaches of the Jhuoshuei River Basin). Basic information from remote sensing and a satellite phantom is collected to set up the basic data maps using elevation, Formosa-II images, the Normalized Difference Vegetation Index, drainage distribution, slope, aspect ratio, lineament distribution, and land cover.

There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on farm-groups. These entities are defined according to variables such as altitude, economic size and type of farming (referring to land uses).

CONTEXT: Green infrastructure may improve water quality and mitigate flooding in forest-urban watersheds, but reliably quantifying all benefits is challenging because most land cover maps depend on moderate- to low-resolution data. Complex and spatially heterogeneous landscapes that typify forest-urban watersheds are not fully represented with these types of data. Hence important questions concerning how green infrastructure influences water quality and quantity at different spatial scales remain unanswered.