The field of soil spectroscopy involves global research in measuring soil reflectance across the VIS–NIR–SWIR region. Diverse soil spectral libraries (SSLs) have emerged, but challenges arise in merging or comparing SSLs due to variations in measurement conditions. With the rise of hyperspectral technology, the need for consolidated SSLs on a global scale has become crucial. In response, the IEEE-Standards Association Working Group P4005 was formed in 2021, uniting over 50 experts globally. This collaborative effort aims to establish a common protocol for laboratory and field spectral reflectance measurements that will enable users to develop standardized SSL. The focus currently is placed into five subgroups that focus on providing standards and protocols for measuring in VIS-NIR-SWIR, data archiving, cross calibration, and field operations, with in. The ongoing 48-month project aims to provide a protocol and a set of tools and algorithms that will enable the development of inter-compatible SSLs.

This study evaluates the potential of EnMAP spaceborne imaging spectroscopy for mapping and monitoring topsoil properties in two diverse Mediterranean agricultural regions. The research employs state of the art linear and nonlinear machine learning techniques, spectral transformations, and pre-processing methods to analyze EnMAP data quality in comparison to in-situ measurements. The findings demonstrate promising accuracy levels in estimating key soil properties, highlighting the potential of EnMAP imagery for global soil property mapping and monitoring applications.

Ice-free areas in Antarctica contain fragile ecosystems and are hotspots of biodiversity due to a concentration of flora and fauna. As these areas are often isolated and with difficult access, using hyperspectral satellite-borne data and remote sensing techniques presents great advantages for characterizing and monitoring their extension and surface cover characteristics. The objective of this work was to map key soil properties related to the Adélie penguin colony and associated flora and fauna of Seabee Hook at Cape Hallett using EnMAP data. Initial mapping results of extractable phosphorous (P), total organic carbon (TOC) and total nitrogen (TN) were obtained, and the distribution could be related to the intense activities of the penguin colony that comes to breed in the study area.

The Environmental Mapping and Analysis Program (EnMAP) is a new spaceborne German hyperspectral satellite mission, whose primary goal is to generate accurate information on the state and evolution of the Earth´s ecosystems. The core themes of EnMAP are monitoring environmental changes, ecosystem responses to human activities, and management of natural resources such as soils and minerals. EnMAP started on 1stApril 2022 and is now in operational phase since over six months, with strong expectations regarding data quality and impact on soil research. In this paper, we aim to demonstrate in a few case studies the observed current capabilities for EnMAP with regard to soil mapping based on different test sites and methodologies. Key soil properties could be derived and spatially mapped in agricultural test sites in semi-arid and temperate zones such as Soil Organic Carbon (SOC) content important for soil health and carbon sequestration, texture (clay content) important for soil fertility, and carbonate content. Additionally, we test different standard and state-of-the art methodologies, including new scenarios for time-series of hyperspectral remote sensing data for improved soil products.

Ice-free areas within the Antarctic Peninsula region are of particular interest due to their rich terrestrial biodiversity. They are often small extensions in isolated areas and the use of visible near infrared reflectance is an ideal tool for characterizing and monitoring their extension and surface covers. The objective of this work was to use reflectance spectroscopy to determine the distribution of terrestrial land surface covers at Cierva Point. A site specific spectral library containing 86 reference spectra was compiled. As a result, a selection of image-derived spectra from multispectral satellite data were easily labeled using the reference spectra. A preliminary distribution has distinguished seven different basic surface covers over the study area.

Soils are an essential factor contributing to agricultural production of rainfed crops such as barley and triticale cereals. Inadequate land management is endangering soil quality and productivity, and in turn crop quality and productivity are affected. In this paper, hyperspectral VNIR-SWIR airborne data (0.4-2.5 µm) is used to analyze spatial differences in vegetation vitality related to soil degradation status in a Mediterranean agricultural area of central Spain. Specifically, biophysical indices such as the leaf area index (LAI) are spatially derived from the remote sensing data and discussed regarding the land degradation status. The results of this study illustrated the potential of hyperspectral remote sensing in the context of crop and land resource monitoring.

The Antartic ice-free areas are important and often hotspots of terrestrial biodiversity. Detecting change of the extension of these areas is therefore important and easily determined with remotely sensed data. The objective was to detect changes in the ice-free areas of Byers Peninsula and Hurd Peninsula on Livingston Island in the northern Antarctic Peninsula region. The proposed approach uses the combination of the Normalized Difference Snow Index and ratio of visible and near infrared reflectance bands of pan sharpened multispectral Landsat bands taken 16 years apart. Results showed an initial approximation was acceptable, but an important validation of these extensions was necessary when glacier fronts were covered by debris and sediments. This needed field determinations and thereafter a more precise digitalizing of the actual glacier front.

Using remote sensing is an ideal solution to monitor thermal inertia over wide areas. This requires modelling it in terms of quantities derived from radiometry, usually albedo and change in surface temperature along the diurnal cycle. This allows to estimate the so-called apparent thermal inertia (ATI). The quality of a remote sensing image for estimating ATI depends on different factors. The first is radiometric noise which sets the minimum temperature difference that can be meaningfully observed. The second is spatial coregistration, which is critical for any study based on the temporal evolution of a variable. Finally, the accuracy of the estimation of albedo for a pixel in the image is essential. In this work, we analyze the quality of AHS airborne remote sensing images acquired by INTA for mapping ATI at high spatial resolution in an operational case. The results show that AHS noise enables the monitoring of ATI from temperature changes with images acquired as close in time as one hour. Spatial coregistration is below one pixel when using the same observing geometry. This figure is satisfactory for accurate mapping of temperature evolution in natural areas. Finally, albedo derived from AHS images is a good proxy of total albedo, but a correction factor depending on the soil type might be needed for high-accuracy estimations of ATI.

Ice- free areas within the Northern Antarctic Peninsula region are of interest for studying changes occurring to surface covers, including those related to glacial coverage, raised beach deposits and periglacial processes and permafrost. The objective of this work is to map the main surface covers within ice-free areas of King George Island, the largest island of the South Shetlands archipelago, using fully polarimetric RADARSAT-2 SAR data. Surface covers such as rock outcrops and glacial till, stone fields, patterned ground, and sand and gravel deposits form the most representative classes and account for 84 km2of the ice-free areas on the island. A distribution of complex geomorphological features and landforms was obtained, being some of them considered indicators of periglacial processes and presence of permafrost.

Deception Island is an active volcano in the Antarctic Peninsula region, affected by different geomorphological processes interacting to form a complex mosaic of landforms and deposits. The use of visible near infrared reflectance is an ideal tool for characterizing and monitoring surface covers and substrates. The objective of this work was to use reflectance spectroscopy to identify spectral characteristics of surface covers related to different volcanic deposits in ice-free areas of Deception Island, South-Shetland Islands. A site specific spectral library containing 220 reference spectra was compiled. Image-derived spectra from multispectral satellite data were easily labeled using the reference spectra. A preliminary distribution has distinguished five different deposit types over the entire area of Deception Island.

Active periglacial processes and landforms are common within the Northern Antarctic Peninsula region and are becoming the focus of interest for studying changes occurring to permafrost. The objective of this study was to identify and characterize glacial and periglacial surface features with fully polarimetric SAR C band RADARSAT-2 data in ice-free regions surrounding Maxwell Bay, South Shetland Islands. Extraction of polarimetric parameters, a selection of field based training sites and a supervised classification approach, were chosen to determine the spatial distribution of the different geomorphological surface features. These results show the identification of complex and relatively small scale geomorphological features such as periglacial landforms that are an important indicator of the presence of permafrost.

This research focuses on a semi-arid, agricultural area in Central Spain near Madrid, in which airborne hyperspectral images have been obtained. Small-scale soil erosion features are exposed at the surface as a consequence of human induced soil erosion derived mainly from tillage practice. Such features are associated with different soil horizons and rock outcrops with contrasted physical and chemical characteristics. Results show that the identification and mapping of different soil surface horizons linked to soil erosion and depositional stages can be achieved over selected test sites based on the spectroscopy data at high spatial resolution. Linked with field validation data and geomorphological analyses, the spatial mapping of the soil erosion and depositional stages is consistent with the soil erosion models implemented for the region. Preliminary multiscale analyses at 3 m, 6 m, and 30 m show the effect of increasing spatial mixing in the field-of-view of the sensor due to the variability at small scale of the different soil horizons representing the surface topsoil.

In a Mediterranean semiarid area in Central Spain, with dominant rainfed agriculture, hyperspectral airborne data, supported by field spectroscopy have been obtained, allowing a spectral identification of bare soil with the corresponding erosion stages. The definition of soil erosion stages is based on a spectral characterization supported by morphological, physical and chemical features of contrasted soil surfaces as a result of soil loss. Different soil erosion stages were defined within two bare-soil sites representing the soil variability of the area, and where such stages are spatially represented. The validation of selected image derived endmebers was a key step to carry out a partial unmixing for determining soil erosion stages. A preliminary spatial distribution of advanced and intermediate erosion stages was obtained for the most representative soil types.

This paper deals with the application of ALOS microwave and Landsat optical data in the study of glacial and periglacial features as well as morphostructural features in a selected area in Livingston Island which lies in the South Shetland Islands of the northern Antarctic Peninsula region. Polar Regions are key areas in the study of the Earth System having an important role in the understanding of the dynamics, reconstruction and monitoring of global natural processes. The main objective of this work is to study and map periglacial, including permafrost, glacial and geological structures by applying an integrated remote sensing approach in one of our study sites in Livingston Island (Byers Peninsula) for which extensive ground truth information exists from various field expeditions.

The largest mercury concentration is situated in Almadén, Spain. Mining activities have dominated in the region till the closure of the mines in 2002 and alternative land use has gained importance after the mining activities ceased. The rehabilitation of areas affected by the mining are the main priority within the region. The objective is to identify and monitor abiotic and biotic characteristics of the region affected by mining activities as well as alternative human-induced activities. Multi-senor data are implemented to carry out a regional characterization. Advanced image processing procedures obtain detailed information from hyperspectral data and this information is implemented in the multispectral data to monitor the different land uses. Monitoring results show that the distribution of areas affected by mining activities is rapidly diminishing in the most recent years.

The National Park of Las Tablas de Daimiel (Central Spain) is a semi-arid wetland included in the UNESCO Man and Biosphere Reserve and Ramsar Convention in 1981 and 1982. The wetland is very important with respect to biodiversity and wildlife habitats essential for migratory movements and wintering of water fowl in the south of Europe. The work determines and monitors sensitive changes of specific wetland characteristics, related with indicators of quality and degradation. A spectral library of semi-arid wetland covers in Las Tablas is elaborated and multi-angle hyperspectral data from Proba-1/CHRIS sensor is applied. Spectral data obtained at individual viewing angles and from different acquisition dates show that significant information on wetland palustrine vegetation and water can be obtained. Spectral Angle Mapper classification has provided a distribution of sensitive characteristics related to wetland degradation and is a major support for the ongoing work.

Soils in semi-arid regions of Spain are especially susceptible to soil degradation processes due to natural as well as human-induced land use/cover changes. The result is a decline in the capacity of the soil to perform environmental regulatory functions and yield agricultural goods. A multisensor and multiscale approach is presented in this work to assess soil degradation stages. The approach consists of (1) obtaining detailed information from field and imaging spectroscopy data, soil analyses, field survey observations, topographic information and ancillary data from selected test plots of soils, (2) use this information (i.e., hyperspectral images and site specific spectral library) to derive endmembers representing soil degradation characteristics, and (3) implement high resolution information on soil types and conditions into medium resolution (multispectral) data covering a wider area. Soil degradation stages are successfully determined by relating spectral variations of the soil surface features to differences in the mineralogical composition as well as physical and chemical soil properties.

Saline wetlands in the semiarid environment of Central Spain are fragile and highly dynamic ecosystems that are affected by degradation processes as a result of anthropological influences. An increase in agricultural production has led to the development of large-scale irrigation schemes with overexploitation of groundwater, and with consequent effects on the complex hydrology and associated land use. In this work, data from field, hyperspectral airborne, and multispectral satellite sensors are used in order to determine changes of wetland characteristics over time. The spectra of surface components (soil, vegetation, and salt crusts) were selected from the hyperspectral data and identified as endmembers using a site-specific spectral library. The spectral information contained in these endmembers was extrapolated to a temporal series of broadband multispectral imagery on which spectral unmixing analysis was performed in order to detect changes in the wetland over time. Results showed that the selected wetland components have undergone important changes in both their total area as well as their spatial distribution. These changes are mainly associated with the anthropogenic impact; however, natural influences due to seasonal fluctuations may coincide with the overall changes, although this in general is difficult to determine. Water regulation and agricultural practices directly influence the salinity of the soils and therefore the nature of the hygrophytic vegetation.

Sensitive ecosystems such as wetlands in a semi-arid environment of Central Spain are important indicators of environmental quality and biodiversity for an area dominated by human induced activities. These areas support an important ecological function for the variety of natural plant species as well as migrating and wintering waterfowl. The wetland areas are classified as saline and sub saline due to climatic and lithological conditions. However, rapid land use changes where natural and semi-natural vegetation is substituted for intensive agricultural cultivation, over exploitation of ground water, drying and artificial drainage of wetlands as well as altering and channeling of rivers; and introducing waste disposal have severely affected the wetlands and their natural functions. The objective of this study is to determine abiotic and biotic land surface changes within semi-arid wetland and surrounding upland areas using reflective spectroscopial field, hyperspectral and multispectral data. This is carried out with intensive field work on test plots obtaining soil samples, determining vegetation types and the related spectroscopial information from a hyper saline wetland and from an anthropogenic affected floodplain including surrounding upland areas. The information obtained from the field forms the basis to identify and compare the hyperspectral (DAIS 7915) and multispectral (Landsat TM, ETM+and ASTER) data from various sensors. Image processing is performed with the DAIS 7915 data (acquired on 29 June 2000) using a minimum noise fraction transformation followed by a pixel purity index analysis. Applying multi dimensional scatter plots, image derived end members for the different surface cover components are determined and compared with field derived end members. A pool of field and image derived end members is created and selected end members with high-resolution information are spectrally resampled to multispectral Landsat TM (17 June 1987), ETM+(28 June 2000), and ASTER (2 June 2002) data. In order to determine and monitor the changes of selected surface cover components, an unconstrained linear spectral unmixing model is applied to the multispectral data and individual fraction maps representing the spatial distribution of the different surface covers are generated. A change detection analysis is made from the resulting end member fraction maps obtained for the different dates (1987, 2000, 2002). The results show that a detailed methodology is required in order to determine surface cover changes for wetlands in semi-arid areas. The interpretation and statistical analysis of spectroscopial field data together with soil analysis form the basis to differentiate slight compositional changes of land surface covers within the wetland and upland areas. A high correlation is shown between spectral absorption features and soil analysis representing the mineralogy of gypsum, calcite and phyllosilicates, and soil properties such as iron oxide content, electrical conductivity and soil colour. The moisture influence is naturally a dominant feature in the wetland areas and serves to distinguish the drier areas leading to the upland soils. DAIS image-derived end members determine a series of surface components, which successfully delineates the wetland areas and differentiates the areas affected by human induced activities. Synthesizing and extrapolating high-resolution information to medium-resolution data has improved the resulting fraction maps obtained for selective surface cover components related to wetland and upland areas. The surface cover changes are particularly apparent in the areas where agricultural activities are pushing back the extension of the wetland areas where soils have lower salinity levels. This approach can therefore be extrapolated to similar medium-resolution data covering thus larger regional and temporal scales