To provide a quantitative spatial analysis of the riverscape (open-water bodies and their surrounding areas) of the Western Amazonian lowlands using a consistent surface of remotely sensed imagery. Taking into account the essential significance of fluvial environments for the Amazonian biota, we propose that an enhanced understanding of the Amazonian riverscape will provide new insight for biogeographical studies in the region and contribute to the understanding of these megadiverse tropical lowlands.

The objective of this paper is to exploit the potential application of an evidential belief function model to landslide susceptibility mapping at Kuala Lumpur city and surrounding areas using geographic information system (GIS). At first, a landslide inventory map was prepared using aerial photographs, high resolution satellite images and field survey. A total 220 landslides were mapped and an inventory map was prepared. Then the landslide inventory was randomly split into a testing dataset 70% (153 landslides) and remaining 30% (67 landslides) data was used for validation purpose.

Land cover classification using remotely sensed data requires robust classification methods for the accurate mapping of complex land cover area of different categories. In this regard, support vector machines (SVMs) have recently received increasing attention. However, small number of training samples remains a bottleneck to design suitable supervised classifiers. On the other hand, adequate number of unlabeled data is available in remote sensing images which can be employed as additional source of information about margins.

The patterns of urban sprawl over a 20-year period presented in the study indicate unplanned development in the urban agglomerations of Ranchi, Jamshedpur and Dhanbad. The visual interpretation of Landsat (1986, 1991, 1996 and 2001) and IRS-P6 (2005) was used to map land use/land cover and analyse urban sprawl. The saturation of urban areas within municipal limits, along with pressure from the growing population, resulted in the densification of the core urban areas within Dhanbad and Jamshedpur.

Flood regulation is a widely valued and studied service provided by watersheds. Flood regulation benefits people directly by decreasing the socio-economic costs of flooding and indirectly by its positive impacts on cultural (e.g., fishing) and provisioning (e.g., water supply) ecosystem services. Like other regulating ecosystem services (e.g., pollination, water purification), flood regulation is often enhanced or replaced by technology, but the relative efficacy of natural versus technological features in controlling floods has scarcely been examined.

Population of two cities in Pakistan has already crossed the 10-million figure and for the rest of the areas in the country populations are also increasing rapidly. Urbanization has boosted the use of energy in the cities and so is greenhouse gas (GHG) emissions but the ground situation as to the extent, vulnerability, past trends and future scenarios are not unveiled for the cities of Pakistan. Dearth of data in Pakistan is a huge hindrance to the investigation of energy use and actual GHG emissions.

1. For north temperate lakes, the well-studied empirical relationship between phosphorus (as measured by total phosphorus, TP), the most commonly limiting nutrient and algal biomass (as measured by chlorophyll a, CHL) has been found to vary across a wide range of landscape settings. Variation in the parameters of these TP-CHL regressions has been attributed to such lake variables as nitrogen/phosphorus ratios, organic carbon and alkalinity, all of which are strongly related to catchment characteristics (e.g. natural land cover and human land use).

This study aims to assess CO₂ levels in China, based on the dry air column-averaged mixing ratios of CO₂ measured by the Scanning Imaging Absorption spectrometer for Atmospheric CartograpHY (SCIAMACHY) instrument on board ENVISAT and emission inventories. A land cover and statistical data set, the Regional emission inventory in Asia (REAS), was also used in this study. The results show that the spatial variations of the CO₂ concentration in the whole of China are obvious, and with clear seasonal fluctuation during 2003–2005.

While crop rotation patterns can be complex with multiple crops rotated over several years, the most common rotation practice in the Central United States is biannual rotation between corn and soybeans. We analyzed the changes in crop rotation patterns from 2003 to 2010 using the Cropland Data Layer (CDL), which provides remotely sensed land cover layers for agricultural crops in the Central United States.

Monitoring land-cover change is often done by simple overlay of two classified maps from different dates. However, such analysis tends to overestimate the rate of change. Main error sources are the mis-registration between classified maps and their thematic accuracies. This study proposes a change detection method with morphological post-processing to improve change detection accuracy in comparison with traditional post-classification by taking into account these error sources.

In Malaysia, areas under oil palm plantations have increased dramatically since the early twentieth century and have resulted in multiple conversions of land change. This paper presents a spatial and temporal model for simulation of oil palm expansion in the Kuala Langat district, Malaysia. The model is an integration of cellular automata (CA), multi-criteria evaluation (MCE), and Markov chain (MC) analysis while MCE provides transition rules of CA iterations and MC analysis assigns a transition probability to each single pixel at the time steps.

The objective of this paper was to quantify long-term land use and land cover changes (LULCC) and to identify the spatial determinants of locations of most systematic transitions for the period 1957–2009 in the Jedeb watershed, Upper Blue Nile Basin. Black and white aerial photographs of 1957 and Landsat imageries of 1972 (MSS), 1986 (TM), 1994 (TM) and 2009 (TM) were used to derive ten land use and land cover classes by integrated use of Remote Sensing (RS) and Geographic Information System (GIS).