Information on plant adaptation can be very useful in agrobiodiversity studies. Ecogeographical land characterization (ELC) maps constitute a new tool in this direction with great potential. To assess the usefulness of this approach, an ELC map of Spain was created through multivariate methods. Its performance to characterize plant habitat preferences was compared with existing ecological regions and land cover maps. Collecting sites and seed weight from eight plant species were used to test the ELC map. Categories from each map were assigned to accessions using collecting sites.

Accurate monitoring of irrigated paddy field area and irrigation timing are of a great concern in agricultural water management due to the substantial consumption of fresh water when irrigating paddy fields. Spectral threshold methods (Xiao et al., 2005) have been widely applied to detect irrigated paddy fields and irrigation timing using Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI). These methods applied constant additive threshold values (T) to LSWI and compared it to EVI to detect the irrigated paddy fields.

This paper proposes a simplified approach to mapping soil capability, as defined by the Canada Land Inventory (CLI), based on the hypothesis that the primary determinants of soil capability may be surrogated by Normalized Difference Vegetation Index (NDVI) derived from Earth Observation (EO) data integrated with other biophysical information. A case study in which a Decision Tree classification method with a boosting algorithm was used in spatially locating individual soil capability classes as estimated in the complex symbol of the CLI database was conducted in Saskatchewan Canada.

The Great Plains of the United States has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes.

Following the clearance of indigenous forest (~1880s to 1920s) for pastoral use, actively eroding gullies had by the late 1950s become a pervasive form of erosion occupying 0.7% of the 7468km² of pastoral hill country within the East Coast Region, North Island, New Zealand. Commencing in the early 1960s the primary strategy used to stabilise gully and other associated forms of erosion on degraded pastoral hill country was to establish exotic forest.

A remote-sensing and geographical information sysytem (GIS)-based quantitative methodology for landslide-susceptibility zonation is described in a stepwise manner with its application in the Igo River Basin in the West Siang District of Arunachal Pradesh, Eastern Himalaya, India. Parameters such as geology, physiography, slope angle, slope length, slope aspect, slope type, generic landforms, lineament distance, road distance, drainage distance, altitudinal zones and land cover are used for landslide-susceptibility zonation.

In this paper, the potential of superresolution (SR) image reconstruction methods for sub-pixel land-cover mapping in dense urban areas is studied. A multiple endmember approach (MESMA) is used for unmixing both original hyperspectral CHRIS/Proba and SR enhanced CHRIS/Proba data. Validation based on high resolution orthophotos (25cm) shows that land-cover fraction maps generated from SR-enhanced CHRIS/Proba data (9m) have a lower overall fractional error compared to the land-cover fractions produced from the original CHRIS data (18m), when validating both results at the 18m resolution.

The potential and limitations of the hyperspectral remote sensing MIVIS sensor (Multispectral Infrared Visible Imaging Spectrometer) in classifying heterogeneous landscapes are explored in this study. In order to quantify the discriminant information derived from selected MIVIS subsets we classified a monitored scenario by progressively increasing the feature space dimensionality.

Considering the potential of shaded coffee plantations mixed with natural vegetation for promoting biodiversity conservation, this project assessed the utility of multi-date Landsat Thematic Mapper (TM) satellite imagery for the characterization of natural vegetation versus coffee plantations in western El Salvador. For assembling a multi-temporal Landsat TM data set, we applied a regression analysis model to remove cloud cover and cloud shadows. Then, through a hybrid classification approach, a nine-class land use/land cover (LULC) map was generated.

A Compound Specific Stable Isotope (CSSI) sediment tracing approach is evaluated for the first time in an agricultural catchment setting against established geochemical fingerprinting techniques. The work demonstrates that novel CSSI techniques have the potential to provide important support for soil resource management policies and inform sediment risk assessment for the protection of aquatic habitats and water resources.

Spatial Data Infrastructures (SDIs) provide access to geospatial data and operations through interoperable Web services. These data and operations can be chained to set up specialized geospatial business processes, and these processes can give support to different applications. End users can benefit from these applications, while experts can integrate the Web services in their own business processes and developments.

The commonly used discretization approaches for distributed hydrological models can be broadly categorized into four types, based on the nature of the discrete components: Regular Mesh, Triangular Irregular Networks (TINs), Representative Elementary Watershed (REWs) and Hydrologic Response Units (HRUs). In this paper, a new discretization approach for landforms that have similar hydrologic properties is developed and discussed here for the Integrated Hydrologic Model (IHM), a combining simulation of surface and groundwater processes, accounting for the interaction between the systems.