HYPSOS (HYPerspectral Stereo Observing System, patented) is a novel remote sensing instrument able to extract the spectral information from the two channels of a pushbroom stereo camera; thus it simultaneously provides 4D information, spatial and spectral, of the observed features. HYPSOS has been designed to be a compact instrument, compatible with small satellite applications, to be suitable both for planetary exploration as well for terrestrial environmental monitoring. An instrument with such global capabilities, both in terms of scientific return and needed resources, is optimal for fully characterizing the observed surface of investigation. HYPSOS optical design couples a pair of folding mirrors to a modified three mirror anastigmat telescope for collecting the light beams from the optical paths of the two stereo channels; then, on the telescope focal plane, there is the entrance slit of an imaging spectrograph, which selects and disperses the light from the two stereo channels on a bidimensional detector. With this optical design, the two stereo channels share the large majority of the optical elements: this allowed to realize a very compact instrument, which needs much less resources than an equivalent system composed by a stereo camera and a spectrometer. To check HYPSOS actual performance, we realized an instrument prototype to be operated in a laboratory environment. The laboratory setup is representative of a possible flight configuration: the light diffused by a surface target is collimated on the HYPSOS channel entrance apertures, and the target is moved with respect to the instrument to reproduce the in-flight pushbroom acquisition mode. Here we describe HYPSOS and the ground support equipment used to characterize the instrument, and show the preliminary results of the instrument alignment activities.
In the Wadi Biskra arid and semiarid areas, sustainable development is restricted by land degradation processes such as secondary salinization of soils. Being an important high-quality date production region of Algeria, this area needs continuous monitoring of desertification indicators, hence highly exposed to climate-related risks. Given the limited access to field data, appropriate methods were assessed for the identification and change detection of salt-affected areas, involving image interpretation and automated classifications employing Landsat imagery, ancillary and multisource ground truth data. First, a visual photointerpretation study of the land cover and land use classes was undergone according to acknowledged methodologies. Second, two automated classification approaches were developed: a customized decision tree classification (DTC) and an unsupervised one applied to the principal components of Knepper ratios composite. Five indices were employed in the DTC construction, among which also is a salinity index. The diachronic analysis was undergone for the 1984 to 2015 images (including seasonal approach), being supported by the interpreted land cover/land use map for error estimation. Considering also biophysical and socioeconomic data, comprehensive results are discussed. One of the most important aspects that emerged was that the accelerated expansion of agricultural land in the last three decades has led and continues to contribute to a secondary salinization of soils.
In the Wadi Biskra arid and semi-arid area, sustainable development is limited by land degradation, such as secondary salinization of soils. As an important high quality date production region of Algeria, it needs continuous monitoring of desertification indicators, since the bio-physical setting defines it as highly exposed to climate-related risks. For this particular study, for which little ground truth data was possible to acquire, we set up an assessment of appropriate methods for the identification and change detection of salt-affected areas, involving image interpretation and processing techniques employing Landsat imagery. After a first phase consisting of a visual interpretation study of the land cover types, two automated classification approaches were proposed and applied for this specific study: decision tree classification and principal components analysis (PCA) of Knepper ratios. Five of the indices employed in the Decision Tree construction were set up within the current study, among which we propose a salinity index (SMI) for the extraction of highly saline areas. The results of the 1984 to 2014 diachronic analysis of salt – affected areas variation were supported by the interpreted land cover map for accuracy estimation. Connecting the outputs with auxiliary bio-physical and socio-economic data, comprehensive results are discussed, which were indispensable for the understanding of land degradation dynamics and vulnerability to desertification. One aspect that emerged was the fact that the expansion of agricultural land in the last three decades may have led and continue to contribute to a secondary salinization of soils. This study is part of the WADIS-MAR Demonstration Project, funded by the European Commission through the Sustainable Water Integrated Management (SWIM) Program (www.wadismar.eu).
This paper introduces the development of a web- platform for sharing of environmental data in the framework of EvK2 – CNR Committee SHARE Project (Stations at High Altitude for Research on the Environment). This system intends to meet the requirement of access to the complex information concerning the acquisition of climate data at high altitude and to the data themselves. The tool that is being studied and developing proposes an environment for the research, dedicated mainly to high-altitude studies, allowing researchers to access the wealth of resources that are acquired by the climatologic stations. With regards to remote sensing data processing, the system gives the opportunity to free access to the data relevant either for atmospheric corrections or ground data calibrations. Moreover, into SHARE GeoNetwork, a specific topic is dedicated to the description of the new technologies developed in the SHARE Project. The core of the system is the catalogue of metadata based on GeoNetwork open source application, proposed on the principles of Free and Open Source Software (FOSS) and International and Open Standards for services and protocols (from ISO/TC211 and OGC). A new hierarchical structure has been implemented into SHARE for the description of metatada of the stations, sensors and measures The first release of SHARE-GeoNetwork is working from 2011 and it is accessible for public at http://geonetwork.evk2cnr.org. The integrated activity of the SHARE GeoNetwork is the implementation of the Data Base for the management of the measures acquired since 1987 by the Ev-K2 CNR Committee. These data have been ordered and stored in a coherent form by an open source database management system, Weather and Water Database (WDB), developed by the Norwegian Meteorological Institute. The geographic component of the system has been implemented and the publication of maps and georeferenced data is allowed.
Tigre Province is in northern Ethiopia between Eritrea on the north and east, and Begemdir and Wollo on the south. The area is comprised of five main physiographic units: Danakil Depression, Escarpment, Tigre and Eritrea Plateau, Semien Mountains and the Western Lowlands. The first two drain into the closed drainage basin of Dallol whilst the other three drain into the Nilo Through the Tezeke, Mareb and Barka River. Three main rock complexes build up the prospect area. The metamorphic and intrusive rocks of the Precambrian basement, the Paleozoic-Mesozoic Sediments and Tertiary Trap Volcanics, and the Young Sedimentary and Volcanic Rocks of the Danakil Depression. The only existing geological data on this area is represented by maps assembled from different sources on very large scale. Thanks to interactive computer processing, it is becoming possible to trace, on the relief as it appears on the display unit, lithological boundaries and the faults which affect them, measuring each of their geometric characteristics. Image processing coupled with pattern recognition programs has made it possible to take into consideration landscape units combining morphological, botanical and geological signatures, and more generally to quantify the morphological elements. Satellite images (Landsat TM and Spot XS) have been processed to produce thematic maps.
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