Desertification Extraction Based on a Microwave Backscattering Contribution Decomposition Model at the Dry Bottom of the Aral Sea

The fine particles produced during the desertification process provide a rich material source for sand and dust activities. Accurately locating the desertified areas is a prerequisite for human intervention in sand and dust activities. In arid and semi-arid regions, due to very sparse vegetation coverage, the microwave surface scattering model is very suitable for describing the variation of topsoil property during the process of desertification. However, the microwave backscattering coefficient (MBC) trend of the soil during the desertification process is still unclear now. Moreover, the MBC of a resolution unit usually involves the contribution of soil and vegetation. These problems seriously limit the application of microwave remote sensing technology in desertification identification. In this paper, we studied the soil MBC change trend during the desertification process and proposed a microwave backscattering contribution decomposition (MBCD) model to estimate the soil MBC of a resolution unit. Furthermore, a simple microwave backscattering threshold (SMSBT) model was established to describe the severity of desertification. The MBCD and SMSBT models were verified qualitatively through landscape photos of sampling points from a field survey in November 2018. The results showed that the MBC would gradually decline with the deepening degree of desertification. The MBCD model and the corresponding least squares method can be used to estimate the soil MBC accurately, and the SMSBT model can accurately distinguish different degrees of desertification. The results of desertification classification showed that more than 68% of the dry bottom of the Aral Sea is suffering from different degrees of desertification.

ON A COMPARATIVE LANDSCAPE STUDIES OF DELTAS UNDER DESERTIFICATION PROCESS WITH LANDSCAPE PATTERTNS STRUCTURAL METRICS

The report disputes some possibilities of landscape patterns structural metrics fot comparative studies of structural and functional affinity for intra-continental arid deltas, such us Aral Sea basin and Caspian plains. We suggest using optical indexes (NDVI, SAVI et al.) as a input layer for the statistical image processing and landscape metrics extracting.

Use of Vegetation Cover Index (ICV) to Identify Susceptible Areas to Desertification Process in the Municipalities of Betânia, Floresta and Itacuruba, Pernambuco, Brazil

Climate change in Brazil has led to an increase in temperature and changes in the distribution of climatic extremes, such as droughts, droughts, floods and floods. This is potentialized when it comes to the semi-arid Northeast. Environmental studies related to this theme are in constant development. For this, the geotechnologies are of great importance for the environmental studies, since they allow the acquisition and analysis of information of use of the ground, vegetal cover and phenomena of the nature. In the present work, the Vegetation Cover Index was studied using remote sensing and geoprocessing techniques through the digital processing of images acquired in the years 2000 to 2015 of the LANDSAT satellites of three municipalities of Pernambuco to observe the vegetation cover in the said temporal space with the degraded areas possibly resulting from the desertification process in the region. Thus, it was found that the municipalities of Betânia and Itacuruba have very high vulnerability (0.75 and 1, respectively). On the other hand, the municipality of Floresta presented a high vulnerability of ICV (0.5), as the vegetation deficit influences hydrological dynamics, soil protection, climatic stability and thermal influence, corroborating the desertification process.