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The goal of this study is to develop remote sensing desertification indicators for drylands, in particular using the capabilities of imaging spectroscopy (hyperspectral imagery) to derive soil and vegetation specific properties linked to land degradation status. The Cabo de Gata-Nijar Natural Park in SE Spain presents a still-preserved semiarid Mediterranean ecosystem that has undergone several changes in landscape patterns and vegetation cover due to human activity. Previous studies have revealed that traditional land uses, particularly grazing, favoured in the Park the transition from tall arid brush to tall grass steppe. In the past ~40 years, tall grass steppes and arid garrigues increased while crop field decreased, and tall arid brushes decreased but then recovered after the area was declared a Natural Park in 1987. Presently, major risk is observed from a potential effect of exponential tourism and agricultural growth. A monitoring program has been recently established in the Park. Several land degradation parcels presenting variable levels of soil development and biological activity were defined in summer 2003 in agricultural lands, calcareous and volcanic areas, covering the park spatial dynamics. Intensive field spectral campaigns took place in Summer 2003 and May 2004 to monitor inter-annual changes, and assess the landscape spectral variability in spatial and temporal dimension, from the dry to the green season. Up to total 1200 field spectra were acquired over ~120 targets each year in the land degradation parcels. The targets were chosen to encompass the whole range of rocks, soils, lichens, and vegetation that can be observed in the park. Simultaneously, acquisition of hyperspectral images was performed with the HyMap sensor. This paper presents preliminary results from mainly the field spectral campaigns. Identifying sources of variability in the spectra, in relation with the ecosystem dynamics, will allow the definition of spectral indicators of change that can be used directly to derive the desertification status of a land.

The goal of this study is to develop remote sensing desertification indicators for drylands, in particular using the capabilities of imaging spectroscopy (hyperspectral imagery) to derive soil and vegetation specific properties linked to land degradation status. The Cabo de Gata-Nijar Natural Park in SE Spain presents a still-preserved semiarid Mediterranean ecosystem that has undergone several changes in landscape patterns and vegetation cover due to human activity. Previous studies have revealed that traditional land uses, particularly grazing, favoured in the Park the transition from tall arid brush to tall grass steppe. In the past ~40 years, tall grass steppes and arid garrigues increased while crop field decreased, and tall arid brushes decreased but then recovered after the area was declared a Natural Park in 1987. Presently, major risk is observed from a potential effect of exponential tourism and agricultural growth. A monitoring program has been recently established in the Park. Several land degradation parcels presenting variable levels of soil development and biological activity were defined in summer 2003 in agricultural lands, calcareous and volcanic areas, covering the park spatial dynamics. Intensive field spectral campaigns took place in Summer 2003 and May 2004 to monitor inter-annual changes, and assess the landscape spectral variability in spatial and temporal dimension, from the dry to the green season. Up to total 1200 field spectra were acquired over ~120 targets each year in the land degradation parcels. The targets were chosen to encompass the whole range of rocks, soils, lichens, and vegetation that can be observed in the park. Simultaneously, acquisition of hyperspectral images was performed with the HyMap sensor. This paper presents preliminary results from mainly the field spectral campaigns. Identifying sources of variability in the spectra, in relation with the ecosystem dynamics, will allow the definition of spectral indicators of change that can be used directly to derive the desertification status of a land.

Hyperspectral images were acquired along the Front Range Urban Corridor in Colorado to determine the feasibility of identification and mapping of expansive clay soils with two, high-SNR imaging spectrometers. Swelling soils are a major geologic hazard, and cause extensive damage world-wide every year. The cost of postconstruction mitigation and standard engineering soil tests for creation of regional maps are immense. Smectite is the clay mineral group that has the greatest swelling potential and is responsible for most of the severe swelling soil damage observed in Colorado. Data sets were acquired from 1997 to 1999 with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Hyperspectral Mapper (HyMap). Using a matched filtering algorithm, maps of exposed clay material were produced, despite a strong vegetation cover. Among those exposures, spectral discrimination and identification of variable clay mineralogy such as smectite, smectite/illite, and kaolinite, in decreasing order of swelling potential hazard, was possible. The comparison of the results from the two sensors showed that higher spatial resolution provided purer image endmembers in more heterogeneous sites, but did not exhibit more endmembers and did not identify new natural outcrops that a lower spatial resolution data set would miss in a homogeneous terrain. However, an increase in the signal-to-noise ratio (SNR) of the instrument by pixel summation made possible the identification of low reflectance exposures. This work demonstrates that, using recent instruments and well-established methodologies, imaging spectrometry can be of practical help for the detection and mapping of expansive clays.

This study examines the extent to which mineralogy and swelling potential can be correlated in the expansive clays and shales along the Colorado Front Range Urban Corridor. 182 undisturbed samples were collected from 20 sites from Boulder to Pueblo. Sites were selected in Cretaceous shales, including the Pierre Shale, that have been uplifted into steeply dipping strata near the foothills of the Rocky Mountains, and that are well known to be hazardous to residential and light commercial developments in this region. For each sample, mineralogy was determined by x-ray diffraction and swelling potential was obtained from moisture content (w), suction (h), and clod volume (V) measurements in terms of the suction potential (dh/dw) and suction-compression index (dV/dh) parameters used in the classification scheme McKeen proposed in 1992. Swelling potentials were also obtained on more limited suites of samples with conventional and labor-intensive schemes including Seed and Chen's schemes based on tests for grain-size distribution and Atterberg limits, and with swell-consolidation measurements in response to saturation, consolidation, and rebound in an oedometer. The results show the percent total smectite provides a useful index of the swelling potential concept defined by Seed and correlates reasonably well with the swelling potential indices developed by Seed, Chen, and McKeen. However, the percent total smectite does not correlate well with conventional swell-consolidation test indices. The causes for this lack of correlation appear to be placement and environmental factors such as the initial moisture content, stress history, and surcharge loading that are beyond the scope of Seed's swell potential concept and Seed, Chen, and McKeen's swelling potential indices.

SAND proposes a space-borne imaging spectrometer (hyperspectral) mission measuring bio-geochemical/bio-geophysical variables to determine land degradation processes in semi-arid geographical areas. Arid and semi-arid lands cover approximately one third of the continental surface of the Earth. They include the deserts and their semi-arid and sub-humid dry margins, and the subtropical Mediterranean latitudes. The semi-arid ecosystems provide important land resources for adapted agricultural production and grazing systems. The importance of thoroughly monitoring the state of the environment in areas considered at risk, in the context of global climatic change and worldwide desertification dynamics, has long been recognised. These facts have led to the ratification of the UN Convention to Combat Desertification (UNCCD) by almost 200 nations worldwide. This agreement emphasises the need to assess land degradation and desertification processes. The status of dryland systems is controlled to a large extent by a fragile equilibrium between soil, vegetation and water resources. Precipitation rates are generally low and rainfall events are known to be irregular and of high intensity. Natural ecosystems and traditional land use practices have largely adapted to these conditions over time, and thus, assure an optimum use of available resources. Dryland degradation may be triggered by (global) climatic change and/or human mismanagement. While the former may result in longer and more frequent drought events, the latter one mainly consists of inappropriate land use practices. Both may induce changes in surface properties, impacting the type and density of the vegetation cover. Many of these changes can be detected remotely by measuring the spectral characteristics of the land surfaces. Accordingly, a high-spectral resolution remote sensing system such as the proposed SAND substantially increases these detection capabilities. This paper presents a sensor concept providing global coverage at a reasonable spatial and very high spectral resolution for a quantitative derivation of land surface variables. This includes vegetation parameters and soil-related information such as foliage chemistry, water content, fractional cover, chemical composition, organic matter content and information about the lithological background for selected targets.