Pakistan is an agricultural country with an increasing interest for hydropower. Water management problems such as sedimentation and evaporation have been of high concern for surface water reservoirs for many years. Therefore, groundwater storage through subsurface dams could be promising, especially considering the monsoon rainfall and seasonal river flows in Pakistan. The paper aims to develop and test a methodology to locate suitable sites for construction of subsurface dams using spatial multi-criteria analysis (SMCA) in the northern parts of Pakistan.

Impact of anthropogenic activities has led to significant changes in riverbeds over a period of time. The objective of the study was to monitor the land use land cover (LULC) of Yamuna riverbed in Delhi and to assess the changes due to natural and anthropogenic activities. The maximum likelihood classification was carried out by using March 1977, April 1999, April 2002 and February 2009 imageries. An overall accuracy of LULC classification of 2009 imagery was around 88.6% based on ground truth data.

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.

Dams strongly impair the fluvial environment by altering downstream flows. We analysed riverscapes downstream of three dams and hypothesized that different dam types in rivers with diverse history of land-use and land cover (LULC) change have significant riparian cover differences at diverse biogeomorphic units (banks, riverbanks, islands). We performed a temporal comparison using pre-dam (1965) and post-dam (2013) high-resolution airborne imagery. A new approach was devised to correct the spatial offset between historical and contemporary imagery.

Steppe, an important belt to protect North China from dust storms, is vulnerable and has been degraded in recent decades because of climatic change and heavy grazing. In order to improve steppe management, this study presents a framework for the monitoring of grazing intensity in Xilingol steppe of middle Inner Mongolia, northern China, by integrating the CENTURY ecosystem model-based simulation and remotely sensed MODIS data-based inversion.

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.

Water resources are influenced by various factors such as weather, topography, geology, and environment. Therefore, there are many difficulties in evaluating and analyzing water resources for the future under climate change. In this paper, we consider climate, land cover and water demand as the most critical factors affecting change in future water resources. We subsequently introduce the procedures and methods employed to quantitatively evaluate the influence of each factor on the change in future water resources.

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.

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.

Natural wetland ecosystem plays an important role in global climate change due to its large amounts of stored carbon and nitrogen. The Sanjiang Plain, Northeast China, encompasses large area of natural freshwater marshy wetlands. However, the magnitude and temporal patterns of major greenhouse gases (GHGs: CO₂, CH₄ and N₂O) in this region remain far from certain. Here we used a process-based ecosystem model to examine GHGs fluxes and their underlying mechanisms in the marshland across the Sanjiang Plain over the period 1949–2008.

Landscape similarity search involves finding landscapes from among a large collection that are similar to a query landscape. An example of such collection is a large land cover map subdivided into a grid of smaller local landscapes, a query is a local landscape of interest, and the task is to find other local landscapes within a map which are perceptually similar to the query. Landscape search and the related task of pattern-based regionalization, requires a measure of similarity – a function which quantifies the level of likeness between two landscapes.

Many arid and semi‐arid landscapes around the world are affected by a shift from grassland to shrubland vegetation, presumably induced by climate warming, increasing atmospheric CO₂concentrations, and/or changing land use. This major change in vegetation cover is likely sustained by positive feedbacks with the physical environment. Recent research has focused on a feedback with microclimate, whereby cold intolerant shrubs increase the minimum nocturnal temperatures in their surroundings.