Using land cover datasets derived from satellite imagery as a proxy for ecosystem services (ES) mapping and evaluation generates a series of technical problems mainly related to the resolution at which spatial data are acquired. Small sized and highly fragmented ecosystems such as wetlands, streams and rivers are particularly underestimated when coarse resolution land cover datasets are used.

Water samples were collected for determination of dissolved trace metals in 56 sampling sites throughout the upper Han River, China. Multivariate statistical analyses including correlation analysis, stepwise multiple linear regression models, and principal component and factor analysis (PCA/FA) were employed to examine the land use influences on trace metals, and a receptor model of factor analysis-multiple linear regression (FA-MLR) was used for source identification/apportionment of anthropogenic heavy metals in the surface water of the River.

Quantification of spatial and temporal heterogeneity has been given much attention in order to link ecological patterns to processes. The patch mosaic model, as an operational paradigm, has led to major advances in the field of quantitative landscape ecology. However, it is more realistic to conceptualize landscapes based on continuous rather than discrete spatial heterogeneity. While a conceptual shift has been proposed to supplement the patch mosaic model, few studies use the surface gradient model as a context.

Observation of the Earth's surface from spaceborne platforms is complicated by the various layers of the Earth's atmosphere that reflect, scatter, and attenuate electromagnetic radiation passing through them, thus influencing (upward or downward) the signal strength recorded at the sensor relative to the true quantity of radiance reflected from the observed surfaces. The magnitude and spatial distribution of atmospheric effects is non-stationary and will vary due to numerous factors.

The Hani terrace landscape located in the mountainous areas of Southwestern China has a history of 1300 years and is a classic example of human–environment harmony. This study investigates the spatial distribution and pattern characteristics of land cover in the landscape using geographical information system and remote-sensing techniques. With the synthetic consideration of both physical and cultural factors, the ecological stability of the landscape was discussed.

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.

Amounts of organic carbon in the mineral soil (SOC) and fine-root (

The bracken (Pteridium aquilinum) fern is environmentally significant due to its great abundance and swift colonisation, and its perception as a problem plant in degrading agricultural or ecologically sensitive land. Various attempts have been made to map bracken using remote sensing, but these have proved relatively unsuccessful, often apparently constrained by the lack of spatial detail associated with medium spatial resolution satellite sensors such as the Landsat series. In this study, bracken was characterised using a combination of 30m Landsat sensor imagery and 4m IKONOS imagery.

Mapping land cover and vegetation characteristics on a regional scale is critical to soil moisture retrieval using microwave remote sensing. In aircraft-based experiments such as the National Airborne Field Experiment 2006 (NAFE’06), it is challenging to provide accurate high resolution vegetation information, especially on a daily basis. A technique proposed in previous studies was adapted here to the heterogenous conditions encountered in NAFE’06, which included a hydrologically complex landscape consisting of both irrigated and dryland agriculture.

Balancing the number of grazing animals with the level of plant resources is a core issue in grazing management. Complete, full-coverage vegetation surveys are often used for this purpose, but these are expensive undertakings. We have presented a method to downscale information from regional sampling surveys by poststratification using a land cover map derived from satellite-based measures of reflectance values. This approach opens new prospects for landscape-level evaluation of productivity.

Soil moisture is an important hydrologic variable of great consequence in both natural and agricultural ecosystems. Unfortunately, it is virtually impossible to accurately assess the spatial and temporal variability of surface soil moisture using conventional, point measurement techniques. Remote sensing has the potential to provide areal estimates of soil moisture at a variety of spatial scales. This investigation evaluates the use of European Remote Sensing Satellite (ERS-2) C-band, VV polarization, synthetic aperture radar data for regional estimates of surface soil moisture.