Oases can play a significant role in the sustainable economic development of arid and Saharan regions. The aim of this study was to map the desertification-sensitive areas in the Middle Draa Valley (MDV), which is in the southeast of Morocco. A total of 13 indices that affect desertification processes were identified and analyzed using a geographic information system. The Mediterranean desertification and land use approach; which has been widely used in the Mediterranean regions due to its simplicity; flexibility and rapid implementation strategy; was applied. All the indices were grouped into four main quality indices; i.e., soil quality; climate quality; vegetation quality and management quality indices. Each quality index was constructed by the combination of several sub-indicators. In turn; the geometric mean of the four quality index maps was used to construct a map of desertification-sensitive areas; which were classified into four classes (i.e., low; moderate; high and very high sensitivity). Results indicated that only 16.63% of the sites in the study were classified as least sensitive to desertification; and 50.34% were classified as highly and very highly sensitive areas. Findings also showed that climate and human pressure factors are the most important indicators affecting desertification sensitivity in the MDV. The framework used in this research provides suitable results and can be easily implemented in similar oasis arid areas.
Desertification is an environmental problem worldwide. Remote sensing data and technique offer substantial information for mapping and assessment of desertification. Desertification is one of the most serious forms of environmental threat in Morocco, especially in the oases in the south-eastern part of the country. This study aims to map the degree of desertification in middle Draa Valley in 2017 using a Sentinel-2 MSI (multispectral instrument) image. Firstly, three indices, namely, tasselled cap brightness (TCB), greenness (TCG) and wetness (TCW) were extracted using the tasselled cap transformation method. Secondly, other indices, such as normalized difference vegetation index (NDVI) and albedo, were retrieved. Thirdly, a linear regression analysis was performed on NDVI–albedo, TCG–TCB and TCW–TCB combinations. Results showed a higher correlation between TCW and TCB (r = −0.812) than with that of the NDVI–albedo (r = −0.50). On the basis of this analysis, a desertification degree index was developed using the TCW–TCB feature space classification. A map of desertification grades was elaborated and divided into five classes, namely, nondesertification, low, moderate, severe and extreme levels. Results indicated that only 6.20% of the study area falls under the nondesertification grade, whereas 26.92% and 32.85% fall under the severe and extreme grades, respectively. The employed method was useful for the quantitative assessment of desertification with an overall accuracy of 93.07%. This method is simple, robust, powerful, and easy to use for the management and protection of the fragile arid and semiarid lands.
During the last decades, The Middle Draa Valley (Southeast of Morocco) was subjected to various environmental problems which haves caused land degradation especially in the south of the Middle Draa (M’hamid oasis). This study aims to analyze the spatiotemporal changes of vegetation in the M’hamid oasis. Based on the Landsat images belonging to six separate periods during 1984 to 2016 and Geographical Information System (GIS) techniques, the pattern of spatiotemporal changes of vegetation cover in M’hamid oasis was analyzed based to visual interpretation and NDVI (Normalized Difference Vegetation Index) and supervised classified. For easier understanding of the causes and origins of these changes, we exploited statistical data survey from various local administrations (climatological, socio-economic data) and fieldworks. The results show that the total area of the oasis showed an oscillating decrease between 1984-1999 compared to 1999-2013 and a sharp increase after 2003 to 2007 and a moderate decrease from 2003 to 2016, with an area 3 times smaller than the initial date (loss of 22% of oasis area), correlated with a reduction of the habitants (loss of 21% between 1980 and 2016). Mass tourism, construction of the Mansour Eddahbi dam and the irregularities of the rains and the succession of years of drought led to a modification of the oasis ecosystem. Due to these climatic conditions, the oasis population are obliged to emigration thus they leave their fields which are threatened by sand encroachments, therefore accelerating the phenomenon of sand movements and consequently desertification.
The expansion of agricultural land at the cost of pastoral land is the common cause of land degradation 12 in the arid areas of developing countries, especially in Morocco. This study aims to assess and monitor 13 the transformation of pastoral land to agricultural land in the arid environment of the Feija Basin 14 (Southeast of Morocco) and to find the key drivers and the issues resulting from this transformation. 15 Spectral mixture analysis was applied to multi-temporal (1975-2017) and multi-sensor (i.e. Multi-16 spectral Scanner, Thematic Mapper, and Operational Land Imager) Landsat satellite images, from 17 which land use classifications were derived. The remote sensing data in combination with ground 18 reference data (household level), groundwater and climate statistics were used to validate and explain 19 the derived land use change maps. The results of the spatiotemporal changes in agricultural lands show 20 two pattens of changes, a middle expansion from 1975-2007, and a rapid expansion from 2008 to 2017. 21 In addition, the overall accuracy demonstrated a high accuracy of 94.4%. In 1975 and 1984, the 22 agricultural lands in Feija covered 0.17 km² and 1.32 km², respectively, compared with 20.10 km² in 23 2017. Since the adoption of the Green Morocco Plan in 2008, the number of watermelon farms and wells 24 has increased rapidly in the study area, which induced a piezometric level drawdown. The results show 25 that spectral mixture analysis yields high accuracies for agricultural lands extraction in arid dry lands 26 and accounts for mixed pixels issues. Results of this study can be used by local administrators to prepare 27 an effective environmental management plan of these fragile drylands. The proposed method can be 28 replicated in other regions to analyse land transformation in similar arid conditions.
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