Quantitative Assessment of Desertification Using Landsat Data on a Regional Scale – A Case Study in the Ordos Plateau, China

Desertification is a serious threat to the ecological environment and social economy in our world and there is a pressing need to develop a reasonable and reproducible method to assess it at different scales. In this paper, the Ordos Plateau in China was selected as the research region and a quantitative method for desertification assessment was developed by using Landsat MSS and TM/ETM+ data on a regional scale. In this method, NDVI, MSDI and land surface albedo were selected as assessment indicators of desertification to represent land surface conditions from vegetation biomass, landscape pattern and micrometeorology. Based on considering the effects of vegetation type and time of images acquired on assessment indictors, assessing rule sets were built and a decision tree approach was used to assess desertification of Ordos Plateau in 1980, 1990 and 2000. The average overall accuracy of three periods was higher than 90%. The results showed that although some local places of Ordos Plateau experienced an expanding trend of desertification, the trend of desertification of Ordos Plateau was an overall decrease in from 1980 to 2000. By analyzing the causes of desertification processes, it was found that climate change could benefit for the reversion of desertification from 1980 to 1990 at a regional scale and human activities might explain the expansion of desertification in this period; however human conservation activities were the main driving factor that induced the reversion of desertification from 1990 to 2000

ON SOME PROPERTIES OF THE JELLY COAT IN OOCYTES AND MATURE EGGS OF SEA URCHINS. A STUDY OF PHASE-DEPENDENT CHANGES OF METAPLASMIC LAYERS IN THE CELL SURFACE

Volume: 127Start Page: 132End Page: 15

AN ANALYSIS OF THE ACTION OF LITHIUM ON SEA URCHIN DEVELOPMENT

Volume: 68Start Page: 378End Page: 38

ON THE INFLUENCE OF PYOCYANINE ON THE RESPIRATION OF THE SEA URCHIN EGG

Volume: 68Start Page: 327End Page: 33

A qualitative assessment of desertification change in the Tarfaya basin (Morocco) using panchromatic data of Landsat ETM +

The purpose of the present work is to assess desertification change in the Tarfaya basin (Morocco) based on quantifying sand dunes mass change at the corridor scale using two Panchromatic bands of Landsat ETM+ and OLI with 15 m of resolution covering the study area for ten years (2005–2016). In this work, the sand dunes quantification is qualitative and is based on automatic extraction and classification of sand dunes shape using co-occurence texture filters and Support Vector Machine (SVM) classifier. The statistical results show that the area covered by sand was increased during the last ten years, which reveal that desertification becomes more intense

Designing erosion management plans in Lebanon using remote sensing, GIS and decision-tree modeling

Soil erosion by water represents a serious threat to the natural and human environment in Mediterranean countries, including Lebanon, which represents a good case study. This research deals with how to use Geographic Information Systems (GIS), remote sensing, and, more specifically, structural classification techniques and decision-tree modeling to map erosion risks and design priority management planning over a representative region of Lebanon. The structural classification organization and analysis of spatial structures (OASIS) of Landsat TM satellite imagery (30 m) was used to define landscapes that prevail in this area and their boundaries, depending on their spectral appearance. The landscape map produced was overlaid sequentially with thematic erosion factorial maps (i.e., slope gradient, drainage density, rainfall quantity, vegetal cover, soil infiltration, soil erodibility, rock infiltration and rock movement). The overlay was visual and conditional using three visual interpretation rules (dominance, unimodality and scarcity conservation), and landscape properties were produced. Rills and gullies were measured in the field, and a decision-tree regression model was developed on the landscapes to statistically explain gully occurrence. This model explained 88% of the variability in field gully measurements. The erosion risk map produced corresponds well to field observations (accuracy of 82%). The landscapes were prioritized according to anti-erosive remedial measures: preventive (Pre), protective (Pro), and restorative (Res). This approach seems useful in Lebanon, but can also serve in other countries with similar geo-environmental conditions or those lacking detailed geospatial data