Over the last few decades, many researchers have produced landslide susceptibility maps using different techniques including the probability method (frequency ratio), the analytical hierarchy process (AHP), bivariate, multivariate, logistics regression, fuzzy logic and artificial neural network In addition, a number of parameters such as lithology, slope, aspect, land cover, elevation, distance to stream, drainage density, distance to lineament, seismicity, and distance to road are recommended to analyze the mechanism of landslides.

Based on the fact that streamwater quality reflects landscape conditions, the objectives of this study were: to investigate nitrogen (N), carbon (C), and major ion concentrations in six streams crossing minimally disturbed Atlantic Forest areas, with similar geomorphological characteristics; to determine N and C fluxes in one of these pristine streams (Indaiá); and assess the impact of human activity on the biogeochemistry of two other streams in the same region, crossing urbanized areas.

Priorities for the management of lowland rural floodplains in many parts of Europe have changed from a focus on agricultural production towards multi-functional landscapes that provide a range of environmental, social and economic benefits to society. This paper uses an ecosystem services framework to explore alternative management scenarios with different objectives (production, biodiversity, floodwater storage, agri-environment and income) for two rural floodplains in England. Each scenario featured different types of land cover and hydrological management.

Optimization techniques are often used in remote sensing retrieval of surface or atmospheric parameters. Nevertheless, different algorithms may exhibit different performances for the same optimization problem. Comparison of some classic optimization approaches in this article aims to select the best method for retrieving aerosol opacity, or even for other parameters, from remotely sensed data. Eight frequently used optimization algorithms were evaluated using both simulated data and actual AATSR (advanced along track scanning radiometer) data.

Even though considerable parts of the global tropical forests are located in Africa, reliable data on African forest resources is limited. While this is widely recognized for tropical moist forests, it also holds for tropical dry forests. To partially fill the gap a forest inventory was carried out in Burkina Faso, West Africa. In this paper we present a methodological approach and sample based estimates of the tree and forest resources including estimates of (1) land cover classes, (2) species composition, and (3) above ground tree carbon stocks.

Since the 1950s, with national policy changes and socio-economic development, the habitat of the giant pandas has altered accordingly. This can also be inferred from the population changes of the giant pandas as reported in three national surveys. Thus, monitoring the changes in giant panda habitat and then taking appropriate action would be a valuable contribution to giant panda protection. In this paper, using existing habitats and potential habitats of the giant pandas as the study area, multitemporal remotely sensed data from the three national surveys are used as the data source.

Multiple classifier systems (MCS) are attracting increasing interest in the field of pattern recognition and machine learning. Recently, MCS are also being introduced in the remote sensing field where the importance of classifier diversity for image classification problems has not been examined.

Erosion is one of the most important natural hazard phenomena in the world, and it poses a significant threat to Turkey in terms of land degredation and desertification. To cope with this problem, we must determine which areas are erosion-prone. Many studies have been carried out and different models and methods have been used to this end. In this study, we used a logistic regression to prepare an erosion susceptibility map for the Ayvalık region in Balıkesir (NW Turkey).

To better assess the impacts of conservation buffers and grasslands on water quality at large spatial scales, development and integration of novel approaches are crucial to ensure that these land management practices are functioning properly and meeting their original goals. Recent developments in remote sensing technology have greatly enriched the availability of geospatial data that can be used in hydrological modeling to assess the potential hydrological response of conservation practices over larger areas.

Whilst exposure to air pollution is linked to a wide range of adverse health outcomes, assessing levels of this exposure has remained a challenge. This study reports a modeling approach for the estimation of weekly levels of ambient black smoke (BS) at residential postcodes across Northeast England (2055km²) over a 12 year period (1985–1996). A two-stage modeling strategy was developed using monitoring data on BS together with a range of covariates including data on traffic, population density, industrial activity, land cover (remote sensing), and meteorology.

The productivity of semi-arid rangelands on the Arabian Peninsula is spatially and temporally highly variable, and increasing grazing pressure as well as the likely effects of climatic change further threatens vegetation resources. Using the Al Jabal al Akhdar mountains in northern Oman as an example, our objectives were to analyse the availability and spatial distribution of aboveground net primary production (ANPP) and the extent and causes of vegetation changes during the last decades with a remote sensing approach.

CO₂ consumption by chemical weathering is an integral part of the boundless carbon cycle, whose spatial patterns and controlling factors on continental scale are still not fully understood. A dataset of 338 river catchments throughout North America was used to empirically identify predictors of bicarbonate fluxes by chemical weathering and interpret the underlying controlling factors. Detailed analysis of major ion ratios enables distinction of the contributions of silicate and carbonate weathering and thus quantifying CO₂ consumption.