This study investigated whether the current lateral boundary for estuaries in South Africa, i.e. the estuarine functional zone (EFZ), includes all estuarine habitats. The EFZ covers 173 930 ha in 304 estuaries/outlets nationally. Field surveys and analysis of available aerial images showed that 82 (12 956.70 ha) of these estuaries (26%) had estuarine habitats occurring outside of this boundary. As a result of mapping scale, the National Vegetation Map does not represent habitats that are associated with small estuaries (approximately 50% of South Africa's estuaries).

To assess the potential of high-resolution satellite data for land-cover monitoring in the Greater Horn of Africa, we used a regular sampling grid of 170 sites (each measuring 20 km × 20 km) located at the confluence of the latitudes and meridians across the study area. For each of these sites, Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) satellite data were acquired for the years 1990 and 2000. A dot grid visual interpretation was used to assess land-cover change between the two dates in each of the sites.

Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth’s radiative budget. While global climate studies can leverage albedo datasets from MODIS, VIIRS, and other coarse-resolution sensors, many applications in heterogeneous environments can benefit from higher-resolution albedo products derived from Landsat.

While the decrease in flow is obvious in the Kikuletwa River, the mechanism leading to the decrease is unclear. We assessed the influence of vegetation cover change on dry season flow in the Kikuletwa River. The combined cover of closed and open forests decreased by 68% while closed and open forests decreased by 56% and 64% respectively. Land under agroforestry decreased by 25%, while that under annual crops increased by 41%. Grasslands increased by 116% and riverine vegetation decreased by 53%.

This study presents a predictive modelling technique to map population distribution and abundance for rural areas in Africa. Prediction models were created using a generalized regression analysis and spatial prediction (GRASP) method that uses the generalized additive model (GAM) regression technique. Dwelling unit presence–absence was mapped from airborne images covering 98 km² (30% of the study area) and used as a response variable. Remote-sensing-based (reflectance, texture and land cover) and geospatial (topography, climate and distance) data were used as predictors.

Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared.

This paper assesses strategic water availability and use under different development pathways on a basin scale using remote sensing (RS), geographical information systems (GIS) and a spatial water budget model (SWBM). The SWBM was applied to the Upper Ing Basin in northern Thailand to investigate the spatial and temporal variations in the location of streams and water yields from different parts of the basin. The base simulation was carried out for the years 1998–2007 using a DEM and actual land-use data at 100-m resolution.

Texture in high resolution satellite images requires substantial improvement in the conventional segmentation algorithms. The use of wavelet packet transforms for texture analysis and image classification of high spatial resolution LISS IV imagery provide more details about the urban areas. This paper analyses the performance of a combination of Wavelet Packet Statistical Features (WPSFs) and Wavelet Packet Co-occurrence Features (WPCFs) for the classification of LISS IV images. The classification accuracy per pixel is improved in this paper by varying the window size.

A desirable feature of a global sampling design for estimating forest cover change based on satellite imagery is the ability to adapt the design to obtain precise regional estimates, where a region may be a country, state, province, or conservation area. A sampling design stratified by an auxiliary variable correlated with forest cover change has this adaptability. A global stratified random sample can be augmented by additional sample units within a region selected by the same stratified protocol and the resulting sample constitutes a stratified random sample of the region.

The Mississippi River Delta Plain has experienced substantial wetland loss from subsidence, erosion, and sea level rise, threatening coastal communities and the ecosystems that support them. The Atchafalaya River, the largest distributary of the Mississippi River, has one of the few prograding delta features along the ~200-km deltaic coastline. Understanding changes in the Atchafalaya River Delta complex (ARDC) development has critical implications for future prediction and management strategy for the Mississippi River Delta Plain.

Urbanization effects on ecosystem functions are both important and complex, characterized by scale multiplicity, spatial heterogeneity, and intensive human disturbances. Integrating the hierarchical structure of urban landscape pattern with ecosystem processes through simulation modeling can facilitate our understanding of human–environment interactions in urban environment.

The diurnal land surface temperature (LST) variation is a primary characteristic of the effects of urbanization. However, no study to date has focused on changes in diurnal LST variation in urban environments. This paper investigates the effects of urbanization on landscape pattern and diurnal LST variation of Taipei City, using MODIS thermal images and SPOT multispectral remote sensing images over the 1994–2010 period. Supervised land-cover classifications were conducted to investigate decadal land-cover changes within the study area.