Remotely sensed data has potential value for vegetation change detection and mapping in arid/semi-arid environments, which can be used and analysed to extract information relevant to the understanding of useful information for the study of desert environments and desertification monitoring, assessment and mapping. In Libya, the vast agricultural development which occurred during the last decades was accompanied by desertification ofdifferent areas. Desertification varied in type and degree according to the geographical site, irregularity of rainfall and the prevalence of strong wind which significantly affects the stability of the fragile ecosystem. The potential of this study was to offer answers to the understanding of desertification indicators and has identified criteria for desertification assessment and the creation of land degradation maps using remote sensing data and a geographic information system (GIS). The indicators which mainly impact the study area are wind erosion, vegetation degradation, salinization, and deterioration of water resources etc. Landsat TM imagery has been used as a source of data to monitor land cover and its change over large areas.In this study, multi-temporal Landsat TM imagery has been used in order to map land cover and their changes during five-year intervals from 1988 to 2000. This was achieved by using a soil adjusted vegetation index formula to detect vegetation Thealgorithm classification technique has been used to map vegetation cover, Eolian Mapping (EM) vegetation of various densities, by used the Soil Adjusted Vegetation Index (SA VI) images: TM 1988, TM 1992, TM 1996 and TM 2000. The results of this technique show areas that have vulnerability to wind erosion susceptibility. and change detection algorithm has been used to calculate the vegetation changes in theperiod from 1988 to 2000. This is therefore one land degradation factor that can be created from remotely sensed data. The analysis clearly demonstrates a net decrease in vegetation cover. This situation exemplifies the deterioration of the naturalvegetation cover. The information derived from remotely sensed data has beenintegrated in a GIS to identify relevant factors for developing a spatial model for desertification assessment and mapping. A Geographic Information System was used to combine and interpret a range of parameters (land cover, soil type, topography,climate, etc.).This This study presents an efficient methodology to delineate the land degradation factors in study area, in a GIS environment. In this study have used one of the multi-criteria decision-making techniques, Analytical Hierarchical Process (AHP) which provides a systematic approach for assessing and integrating the impact of various factors,involving several levels. The methodology has been present for computing a composite index of land degradation factors derived from topographical, land cover, soil type and climate data. All data are finally integrated in a GIS environment to prepare a final desertification map. This land degradation factors computed from AHP method not only considers susceptibility of each area to emphasize thevulnerability of land to erosion but also takes into account the factors that are related to desertification.

Desertification, even though not a new problem, in recent years has become one of the major global threats widely recognized not only by research community but also by public interest. Traditionally, the term desert is typically used to refer to vast areas of sand dune spreading over thousands miles such as in the Sahara Desert, Africa. However, in the new concept of desertification as a degradation process, today we are facing a new trend of desertification in the sub-humid regions with an accelerating rate because of deforestation, poor agricultural land use practice and overgrazing. Mapping desertification in sub-humid areas, however, is difficult due to cloud cover, poor geo- database infrastructure and limited investment. Current desertification mapping techniques are primarily developed for arid regions and are inappropriate for sub-humid areas, both in terms of scale and ecosystem characterization. There is an obvious need for new monitoring approaches developed specifically for sub-humid areas, which utilize readily available Earth observation systems in a cost effective solution. The goal of this study is to develop an imagery-based mapping method that can be used to monitor desertification in sub-humid areas of Vietnam, which is transferable to areas with similar conditions in South East Asia. Specific objectives are: 1) to characterise the desertification process in sub- humid areas from a remote sensing perspective, 2) to develop a method for desertification mapping which combines advantages of several types of satellite imagery, thus overcoming the limitations in spatial, temporal and spectral resolution of individual satellite image systems, 3) to test and evaluate the new desertification mapping method in the coastal lowlands of Vietnam. In the first step, characterising the desertification, field surveys were conducted in the coastal lowland of Vietnam to understand the background of land processes: vegetation fluctuation in savannah landscape, land use patterns and human activities, land form and soil properties. Archived remote sensing data including Landsat, ASTER, MODIS, MERIS, and different types of SAR imagery were used to investigate the spatial and spectral responses of desertification surfaces. Through this step a set of remote sensing imagery most suitable for sub-humid desertification was selected. Next, different parameters extracted from remote sensing data and their relationships with desertification features were examined. Soil temperature and vegetation index were selected as the components required to develop the Vegetation Temperature Angle Index (VTAI) algorithm. These two parameters have strong relationships with the thermal dynamics of land processes and vegetation moisture stress, thus providing a simple yet robust representation of desertification land spectrum. The methods to extract these parameters are mature and have led to standard products being available from data providers, therefore making the implementation of the mapping method simple and comparable between geographic regions. In addition a method for rapid soil moisture estimation from SAR images was investigated. Soil moisture represents a direct and measurable indicator of dryness and therefore provides an additional dimension to verify the desertification index algorithm. The Vegetation Temperature Angle Index (VTAI), and soil moisture estimation method are evaluated in the coastal lowland of Vietnam using data from ASTER and MODIS, and ENVISAT ASAR imagery. In particular, the efficiency of the VT AI index in detecting the vegetation condition and soil water availability was investigated. The results indicate that the VT AI index is simple to construct and capable of discriminating different variation in vegetation and soil, effectively identifying vegetation stress, and is able to separate inactive vegetation from bare soil. At the same time, soil moisture estimation from SAR images can be used to verify the desertification index, and to provide a weather-independent monitoring method. The VTAI and soil moisture estimation was combined into the Vegetation Temperature Angle and Moisture (VT AMI) index. The new combined index showed improved performance compared to VT AI and produced reliable results across a wider range of land cover and surface conditions. A desertification risk class map of the study area was produced from the VT AMI index. From the results of the testing project, the elements required for effective monitoring and management of sub-humid desertification are discussed in terms of optimal remote sensing imagery and land process characteristics, in order to identify areas at risk of desertification.

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Οι βόρειες πλαγιές του Παναχαϊκού όρους στη Β. Πελοπόννησο καλύπτονται από Πλειο - Πλειστοκαινικά λιμναία, θαλάσσια/λιμνοθαλάσσια και ποτάμια ιζήματα. Στα ιζήματα αυτά αναπτύσσονται οι γεωμορφές τύπου badlands, που θεωρούνται από τις πιο κλασικές διαβρωσιγενείς γεωμορφές. Η παρουσία των γεωμορφών αυτών είναι αρκετά διαδεδομένη στα Πλειο-Πλειστοκαινικά αργιλικά ιζήματα της περιοχής μελέτης, πλην όμως οι χαρακτήρες τους διαφοροποιούνται από αυτούς των κλασικών badlands. / The northern slopes of Panachaikon mountain in North Peloponnese are covered with Plio - Pleistocene lacustrine, marine / lagoon and river sediments . In these sediments are developed characteristic landforms called badlands, which are considered the most classic erosional landforms. The presence of these landforms are quite common in the Plio - Pleistocene clay sediments of the study area.