Soils are often considered as just thin layers of surficial unconsolidated material; however, they are a vital component of an ecosystem influencing every landscape. Given that, the soil monitoring for any changing conditions is a topic of great interest, in order to better understand their potential effects on productivity. A key element of sustainable soil function is Soil Quality (SQ), that involves physical, biological, and chemical attributes merged together. SQ can be defined as the capacity of a soil-specific property to sustain the productivity of plants and animals, within the limits of the ecosystem (natural or managed), while maintaining or improving the quality of water and air, and supporting human health and habitation. In this field, the capability of VIS-NIR-SWIR and imaging spectroscopy of monitoring the effects of land use and for identifying hotspots of soil degradation at a regional scale has been recently demonstrated.

 In the framework of the ASI supported research projects called SAP4PRISMA, it has been demonstrated the capability of PRISMA Hyperspectral data to evaluate land degradation vulnerability in still productive areas affected by different processes of alteration/disturbance involving soil and vegetation, considering soil erosion, vegetation stress and landscape fragmentation, which are crucial topics for evaluating the health state of ecosystems. Soil erosion has been evaluated by the Grain Size Index, that is able to capture increases in the sandy component of soil mainly ascribable to current transporting effects of runoff caused by erosion processes. Such index can indicate possible stress situations due to anomalous climatic conditions, water deficit, land use/cover changes, plant diseases, etc. Landscape fragmentation is connected to the evaluation of ecological stability of natural ecosystems.

 Soil moisture plays a key role in the water cycle and its assessment is of great importance in forecasting changes in the water balance of a region. It has both a spatially and a temporally variability due to factors such as soil type, soil horizon, soil texture features like soil organic carbon or clay contents. At the regional and local scales, Soil Moisture Content (SMC) has an impact on erosion (which leads to soil and organic matter losses) since it directly influences infiltration rates and runoff values, soil contamination, crusting, soil compaction and salinity. Accurate estimation of SMC with a high spatial resolution would improve the characterization of soil texture but also the growth of the vegetation and its biodiversity. To improve the performance of SMC retrieval, it is fundamental to consider also factors influencing surface reflectance, such as roughness and texture, organic matter content, vegetation cover and mineral composition. Among texture parameters, one of the most important is the clay content (CC). It has been observed that the properties of water retention of clay soil depend on the clay mass, the organization of the granulometry and finally the CC. A recent study demonstrated the potential of hyperspectral imagers to estimate SMC over bare soil, and proposed a method to take into account the CC of the soil to improve the estimation of the SMC.

Probably one of the most important application of hyperspectral data from the operational perspective is that related to the assessment of soil contamination caused by chronic or accidental pollution from metal mining. Furthermore, imaging spectroscopy can be used to detect oil discharges on the Earth surface, which has both environmental concern and economical fallouts. Indeed, crude oil can be detected by hyperspectral sensors operating in the visible/near-infrared spectral bands, such as that of PRISMA. A phenomenon known as ‘micro-leakage’ yields hydrocarbon components in the surface soil and water; the detection of these micro-leakages, that can be achieved thanks to the fine PRISMA resolution, is extremely useful being an indicator of the probability of an oil or gas reservoir.

Hyperspectral satellite image (Hyperion) acquired in Maccarese (Rome) and estimated soil variables maps concerning soil moisture, clay and soil organic carbon (SOC).

 

Thus, as discussed above, PRISMA mission can provide crucial contribution to the following domains:

·         Evaluation of soil moisture

·         Detection and monitoring of pollutants on soil

·         Evaluation of soil degradation (soil erosion, land use, stability of ecosystems, stress status)

·         Extraction of soil properties

·         Detection and accurate location of oil and gas micro-leaks

·         Extraction of index related to the presence of hydrocarbons

·         Providing relative oil concentration

 

 

References

 

[1]     Estimation of Soil Moisture Content from the Spectral Reflectance of Bare Soils in the 0.4–2.5 μm Domain. S. Fabre, X. Briottet, A. Lesaignoux. Sensors (Basel). 2015 Feb; 15(2): 3262–3281.

[2]     Improvement of Soil Moisture Retrieval from Hyperspectral VNIR-SWIR Data Using Clay Content Information: From Laboratory to Field Experiments. Oltra-Carrio, F. Baup, S. Fabre, R. Fieuzal, X. Briottet. Remote Sens. 2015, 7, 3184-3205

[3]     Hyperspectral Analysis of Soil Nitrogen, Carbon, Carbonate, and Organic Matter Using Regression Trees. S. Gmur, D. Vogt, D. Zabowski, L.M. Moskal. Sensors (Basel). 2012; 12(8): 10639–10658.

[4]     Mapping the Spectral Soil Quality Index (SSQI) Using Airborne Imaging Spectroscopy. T. Paz-Kagan, E. Zaady, C. Salbach, A. Schmidt, A. Lausch, S. Zacharias, G. Notesco, E. Ben-Dor, A. Karnieli. Remote Sens. 2015, 7, 15748-15781.

[5]     Environmental products overview of the Italian Huperspectral PRISMA Mission: The SAP4PRISMA Project. S. Pignatti et al., IGARSS 2015