Spatial and temporal variability in extreme rainfall, and its interactions with land cover and the drainage network, is an important driver of flood response. “Design storms,” which are commonly used for flood risk assessment, however, are assumed to be uniform in space and either uniform or highly idealized in time. The impacts of these and other commonly-made assumptions are rarely considered, and their impacts on flood risk estimates are poorly understood.

Shoreline changes along the south Gujarat coast has been analyzed by using USGS Digital Shoreline Analysis System (DSAS) version 4.3. Multi-temporal satellite images pertaining to 1972, 1990, 2001 and 2011 were used to extract the shoreline. The High water line (HTL) is considered as shoreline and visual interpretation of satellite imageries has been carried out to demarcate the HTL based on various geomorphology and land use & land cover features. The present study used the Linear Regression Method (LRR) to calculate shoreline change rate.

This study examined the separate and combined impacts of future changes in climate and land use/land cover (LULC) on streamflow in the Hoeya River Basin, South Korea, using the representative concentration pathway (RCP) 4.5 and 8.5 scenarios of the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). First, a LULC change model was developed using RCP 4.5 and RCP 8.5 storylines and logistic regression.

Environmental heterogeneity is regarded as one of the most important factors governing species richness gradients. An increase in available niche space, provision of refuges and opportunities for isolation and divergent adaptation are thought to enhance species coexistence, persistence and diversification. However, the extent and generality of positive heterogeneity–richness relationships are still debated. Apart from widespread evidence supporting positive relationships, negative and hump‐shaped relationships have also been reported.

Studies of the modern relationship between pollen, vegetation and land-use are essential to infer past human impact on vegetation from pollen records. Nevertheless, such investigations are relatively few in China. We present here a study of pollen assemblages from sediment samples collected from irrigation pools in the Tuoliang and Qipanshan catchments in northern China.

Alteration in climatic pattern has resulted to a steady decline in quality of life and the environment, especially in and around urbanized areas. These areas are faced with increasing surface temperature arising mostly from human activities and other natural sources; hence land surface temperature has become an important variable in global climate change studies. In this paper, Landsat TM/ETM imagery acquired between 1997 and 2013 were used to extract ground brightness temperature and land use/land cover change in Kuala Lumpur metropolis.

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.