Landscape indicators, when combined with information about environmental conditions (such as habitat potential, biodiversity, carbon and nutrient cycling, and erosion) and socioeconomic forces, can provide insights about changing ecosystem services. They also provide information about opportunities for improving natural resources management. Landscape indicators rely on data regarding land cover, land management and land functionality.

The paper gives an overview on the trends in the usage of landscape metrics as indicators for: land use changes, habitat functions (biodiversity, habitats), landscape regulating functions (fire control, microclimate control, etc.), and information functions (landscape aesthetics). We reviewed papers published in international peer-reviewed journals that are indexed by the Institute of Science Information (ISI) Web of Knowledge from 2000 to 2010. The terms “landscape metrics”, “landscape indexes” and “landscape indices” were searched.

This paper presents the conceptual design and application of a new land-change modelling framework that represents geographical, sociological, economic, and ecological aspects of a land system. The framework provides an overarching design that can be extended into specific model implementations to evaluate how policy, land-management preferences, and land-market dynamics affect (and are affected by) land-use and land-cover change patterns and subsequent carbon storage and flux.

Mapping and monitoring wetland ecosystems over large geographic areas based on remote sensing is challenging because of the spatial and spectral complexities of the inherent ecosystem dynamics. The main objective of this research was to develop and evaluate a new method for detecting and quantifying wetland changes in the Northern Gulf of Mexico (NGOM) region using multitemporal, multispectral, and multisensor remotely sensed data.

Declining urban tree canopy cover in the United States underscores the importance of elucidating factors that influence the distribution of urban trees. This is particularly relevant as most urban trees are located on private property while their canopies maintain ecosystem services that constitute public goods. Thus, municipalities establish institutions in the form of canopy cover goals and various policies to incentivize private actions to meet those goals.

The planning and management of urban forest has become increasingly important as a focus of urban environmental management. The objectives of this study were to analyze the landuse/land cover and to map functional zones of the urban forest in the upper catchment area of Addis Ababa. This study identifies five landuse/land cover types: (i) Eucalyptus–Juniperus dominated forest, (ii) mixed native forest, (iii) built-up areas, (iv) Eucalyptus plantation (v) crop/grazing lands.

Tropical mountain regions are prone to landslide hazards. Given the current land pressure with increasing occupation of steep uplands, landslide hazards are expected to increase in the near future. Understanding the factors that control landslide hazards is therefore essential. Rare event logistic regression allows us to perform a robust detection of landslide controlling factors. This technique is here applied to the tropical Andes to evaluate the impact of dynamic land cover changes on landslide occurrences. Land cover change trajectories (i.e.

Global, long-term monitoring of changes in Earth's land surface requires quantitative comparisons of satellite images acquired under widely varying atmospheric conditions. Although physically based estimates of surface reflectance (SR) ultimately provide the most accurate representation of Earth's surface properties, there has never been a globally consistent SR dataset at the spatial resolution (b1 ha) or temporal extent (~40 years) of the Landsat mission.

An illumination correction algorithm has been developed to improve the accuracy of forest change detection from Landsat-derived reflectance data. This algorithm is based on an empirical rotation model and was tested on Landsat image pairs over the Cherokee National Forest, Tennessee; Uinta–Wasatch–Cache National Forest, Utah; San Juan National Forest, Colorado; and Sinkyone Wilderness State Park, California. The illumination correction process successfully eliminated correlation between Landsat reflectance and illumination condition.

The Persian Long-tailed Desert Lizard, Mesalina watsonana , is one of the most common and most widely distributed lizards on the Iranian Plateau extending from Iran to Pakistan and Afghanistan. The species is frequently encountered in various types of habitats. We collected over 600 distributional records from available literature, museum collections, and our own field work and used bioclimatic and land cover characteristics to develop a model of potential distribution for M. watsonana . According to the model, the most important factors limiting the distribution of M.

In this work, a high resolution wind atlas for Nakhon Si Thammarat and Songkhla provinces in southern Thailand was developed using combined mesoscale, MC2, and microscale, MsMicro, modeling techniques. The model inputs consist of long-term statistical climate data, i.e. the NCEP/NCAR database, high resolution topography and land cover data. The 200 m resolution wind resource maps were validated with observed mean wind speeds from 10 met stations located along the coastlines of the territory studied.

Predictive models are frequently used to define the most suitable areas for species protection or reintroduction. Land-cover variables can be used in different ways for distribution modelling. The surface area of a set of land-cover classes is often used, each land-cover presence/absence or the distance to them from any point of the study area can be preferred; multiple types of land-cover variables may be combined to produce a single model.