1. Introduction
Desertification is a form of land degradation in arid, semiarid and dry sub-humid regions caused by a combination of various factors, such as climatic variations and human activities [
1]. Over 3.6 million hectares of world surfaces are affected by this phenomenon [
2]. One of the manifestations of desertification is the loss of total or partial agricultural and grazing lands. Moreover, desertification negatively influences biophysical and socioeconomic processes in various spatial and temporal scales [
3].
Desertification is a common environmental threat that affects a large part of Morocco. About 93% of Moroccan surface is classified as arid, semi-arid and Saharan, wherein 90% is affected by the phenomenon [
4]. The aridity of climate, vulnerability to soil erosion, human pressure and overexploitation of natural resources in rural areas are the main driving forces of desertification in Morocco [
5]. The Tafilalet and Draa Valleys, which are located in the south-eastern part of Morocco, are mostly affected by desertification caused by soil and water salinities, sand dune encroachment, water erosion, migration and severe climate conditions [
6]. The main characteristics of the Draa Valley include water and soil salinities, scarcity and variability of precipitation, intense evaporation and inadequate human activities. These characteristics result in low vegetation coverage, thereby contributing to the deterioration of an already fragile ecosystem.
For the past three decades, remote sensing data were popularly used for the monitoring and assessment of ecosystems and natural hazards, such as desertification [
7,
8,
9]. Remote sensing offers precise data, quick update and abundant information [
10] that can be exploited to combat and mitigate the effect of desertification in arid and semiarid areas. Several remote sensing satellites, such as Landsat and a satellite for the observation of the earth, were used to map and understand the origins of the desertification process at local or regional scales [
11,
12,
13].
On the basis of surveys and experimental data, specific indices have been developed to monitor and assess desertification in the arid and the semiarid regions. Desertification hazards can be mapped based on remotely sensed images using traditional classification methods [
14], spectral mixture analysis (SMA) [
15] or spectral indices [
2]. Some studies proposed that the normalized difference vegetation index (NDVI)–albedo feature space can be used to extract desertification on the basis of the negative relationship between vegetation coverage and surface albedo [
16] or the hybrid method combined with the SMA and spectral indices through the use of vegetation fraction and albedo feature space [
15].
The tasselled cap transformation (TCT) tool is used for landscaping, environmental threat mapping, estimating biomass, agricultural studies and identifying areas that exhibit desertification [
17,
18]. Tasselled cap is an orthogonal transformation for the reduction of interpretability of the multispectral image to return three thematic indices: (1) Brightness, which is sensitive to soil backgrounds and bright soils; (2) greenness, which is used to discriminate vegetation coverage; and (3) wetness, which provides information about water and soil moisture and vegetation conditions [
19].
Some researchers established a relationship between desertification and the increase in bright soil or surface albedo [
20]. Soils with sand and bright soil texture dry rapidly compared with soils with clay texture that conserve surface moisture [
2]. Decrease in soil moisture reduces the water availability of vegetation, thereby leading to the desertification of landscapes.
However, some studies monitored desertification by establishing a quantitative relationship between biophysical indices and the degrees of desertification (albedo, vegetation, soil) [
15,
16,
21]. These models cannot affine the extraction of the low and high desertification grades of lands. This deficiency encourages us to develop a new quantitative relationship to extract different degrees of desertification in the context of arid oasis areas with a high discrimination among different land cover classes with a risk of desertification.
The objectives of this study are: (1) To map the desertification degrees in the Middle Draa Valley (MDV) and (2) to identify a pixel-based relationship among the different biophysical indices (NDVI, greenness, wetness, surface albedo, brightness) that contribute to the desertification process. The applied methodology is based on the comparison of the regression analyses of three index combinations (NDVI–albedo, Tasselled Cap brightness [TCB], greenness [TCG] and wetness [TCW]). A desertification degree index (DDI) is calculated based on the results of regression analysis and is further used to extract the desertification degrees. The final desertification degree map is classified into five grades. The results are validated based on ground data and high-resolution images. The present study is one of the first studies that adopted a remote sensing-based approach for the desertification in the oases of Morocco. The developed model can be easily reproduced and applied to other arid lands using multispectral images and can easily achieve the automatic identification of desertification.
2. Study Area
The study area is a part of the MDV situated in the central-southern part of Morocco. The study area is located in the middle of the 6° west meridian and below the 30° north parallel. The Draa Wadi (typical ephemeral river), which feeds from the Mansour Eddahbi dam, crosses the MDV. The study site includes four successive oases from Ternata to M’Hamid (
Figure 1). The MDV is characterized by an arid climate, whereas the oases are marked by hot and humid microclimates promoted by the stratified management favouring diversified cultivation. The MDV is characterized by an arid climate with annual precipitation varying between 54 mm (in the Ktaoua oasis) and 64 mm (in the Ternata oasis). The precipitation pattern is irregular and has long periods of droughts. Temperatures range from −1 °C to 7 °C in winter and more than 48 °C in summer [
22], whereas evaporation is high and reaches 3000 mm/year.
The hydrological system depends on the extent of water runoff in the High Atlas mountain chain, which is located north of Ouarzazate City [
23]. However, the scarce surface water supply in the MDV results in high dependence on groundwater pumping, which increased from 2000 pumps in 1977 in the six oases to 10,000 in 2011 [
24]. The Mansour Eddahbi Dam, which was constructed in 1972, is at risk from severe siltation. This area has a higher level of limited stocks than the increase rate of demand, especially for unsustainable crops, such as watermelon cultivation that expanded from a little over 100 ha in 2010 to more than 2400 ha in 2014 in the MDV. Of the total amount of exploitable water resources, 96.66% is allocated to agriculture, 2.70% to domestic use, 0.28% to tourism and 0.36% to economic activities [
24]. Farms practice traditional production methods, including three levels of vegetation management: Palm trees (
Phoenix dactylifera), fruit trees and crops. Major crops in the oases include barley, wheat, date palms, alfalfa, maize and henna.
From 1994 to 2014, the number of residents in the study area increased from 12,800 to 15,395 [
25]. In terms of socioeconomic factors, the Draa area is plagued by poverty, which has caused a migration of young people to the northern part of the country. The main economic sectors are agriculture and tourism.
Precipitation in the MDV is characterized by a binary pattern, either a succession of years of drought or exceptional rainy years. This acute variability of precipitation resulted in the desertification of the oasis palm in the early years of the last century, including the death of 780,783 palm trees in 1975. Major activities, such as overgrazing in pastoral lands and the endorsement of new inadequate cultivation in the context of the arid area that needs high quantities of water, contributed to desertification.
In recent years, the study area encountered several environmental problems, such as water shortage, water and soil salinities, sand dune encroachments, overgrazing and overexploitation of groundwater for agricultural activities [
25]. The climate pattern is characterized by a high temperature that encourages evaporation; low precipitation affects water availability and desertification of the ecosystem [
6,
26,
27]. Only a few studies were conducted in the study area, which inspired us to conduct this study.
5. Discussion
5.1. The Cap Tasselled Transformation Features and the Desertification Asessment
TCT was adopted to retrieve the indicators of TCW and TCB related to the soil witness and brightness and acquire the relative relationship of vegetation, water bodies and bright soils with the desertification process. On the basis of the correlation analysis of the indicators of soil moisture and other indicators, a desertification degree model was constructed in a TCW–TCW feature space to construct a map of different desertification grades of lands in the Middle Draa Valley. Based on the TCT, the proposed method and feature space classification take full benefit for the monitoring of the status in an arid ecosystem. The index, which is an easy, powerful, simple, quick, and efficient method, can be implemented using different satellites and sensors and different scales of study (local, regional) to facilitate quantitative assessment and monitoring of desertification grades in arid and semiarid areas.
Crist et al. (1986) reported similar result, which was a highly negative correlation between TCW and TCB, and made a comment that the TCW can have a more relevant datum for soil and vegetation management purpose [
43]. The finding of this research also corroborated that the TCW can be used as a valuable indicator of the vegetation and environment assessment in arid and semi-arid areas.
Similar to previous studies [
15,
16,
21], the NDVI–α model could not present a good discrimination between water bodies, dark bare soil and other features of land cover. The NDVI and surface albedo values are low for water and dark bare soil. The relationship between NDVI and surface albedo does not meet Equation (7); this finding means that the ‘
I’ values of water bodies (corresponding to the non-desertification class) and dark soil are distributed more widely [
16]. The dark soils, which represent the soils rich in organic matter, can be classified as low desertified lands. Furthermore, the integration of the wetness instead of the NDVI index in the 2D feature space provides a high discrimination of the different grades of land desertification.
5.2. Driving Forces of Desertification in the Middle Draa Valley
The causes of desertification of the oases in the MDV are natural and human factors. Analysis of the climatic data shows a climate characterized by a high intra-annual and intra-seasonal variability with high temperatures, especially in August. Precipitation is characterized by a binary pattern, either a succession of years of drought (1945–1947, 1979–1984, 1987, 1993–1995, 2015) or exceptional rainy years (1991, 1996, 2008 and 2014). This acute variability of precipitation generates a desertification of oasis palm and fruit trees in the early years of the last century.
The Middle Draa Valley is characterized by water salinity that causes soil salinity and the loss of soil productivity [
25]. In addition, the oases, especially the M’Hamid, are exposed to the sand dune encroachment that affects the palm trees and causes desertification [
22]. In recent years, watermelon farms have been cultivated in this area. The overexploitation of groundwater has caused the water shortage, and consequently leading to degradation and desertification of lands. Regarding the climatic conditions, the site is characterized by a low rainfall, high temperatures, and evaporation [
26]. Those severe climate conditions influence the availability of water for the vegetation growth. With the absence of vegetation coverage, the lands are exposed to water and wind erosion [
25].
The study site is also characterized by the shortage and the salinity of water, which affect the soil and contribute to desertification. The number of water motopumps increased rapidly in recent years, especially after the construction of the Mansour Eddahbi dam. This overexploitation of the groundwater implies the water level decline, which results in the desertification of lands in those regions.
The authors conducted a field study to collect water samples from the well of the study area. The measurement indicates that the average of water salinity was 2.7 g/L in Ternata, 4.36 g/L in Fezouata, 4.36 g/L in Ktaoua and 5.33 g/L in M’Hamid. These results show that water salinity increases from north to south of the MDV. This finding confirms the result of the final map of the desertification. The most desertified lands are located in the Ktaoua and M’Hamid oases.
The socioeconomic factors can contribute to the deterioration of the ecosystems in the study area. The local people cut wood in pastoral lands for domestic purposes or pottery, especially in the Fezouata oasis, due to poverty [
25]. Furthermore, anthropogenic pressure and overgrazing affect the pastoral lands, especially in the southern part of the MDV. According to the census of the Regional Centre of Agricultural Development of Ouarzazate, the number of camels in M’Hamid and Ternata oases was more than 8400 [
25]. Grazing in the pastoral lands makes vegetation sparse or absent in those areas, thereby resulting in short-term desertification through water or soil erosion.
The only choice for local residents is mass migration, because of desertification and severe climatic conditions. In the M’Hamid oasis, the number of inhabitants decreased from 8671 in 1982 to 6781 in 2014 [
22].
6. Conclusions
In this study, a desertification monitoring index was proposed based on the relationship between desertification and two indexes, such as soil moisture (TCT) and soil brightness (TCB). Then the proposed index was applied, using the Sentinel-2 image, to assess quantitively the desertification in the Middle Drâa Valley. The analysis revealed the combination TCT-TCB gives better results compared to the NDVI-albedo combination. However, the calculated index (DDI) makes full use of easy accessed of desertification using other multi-spectral remote sensing images, and it is robust, easy to achieve, accurate, efficient for desertification monitoring, and only depend on the remote sensing image itself to extract desertification grades. The DDI was applied to map quantitatively the desertification grades. The applied method produced higher accuracy (overall accuracy = 93.07 %). Moreover, the employed methodology is fast and easy to implement and efficient for the quantitative assessment of land degradation. The results of the map of the desertification revealed that over 26.92% (195.28 Km2) and 32.85% (123.62 km2) are classified under severe and extreme grades of desertification, respectively. Only 6.20% (36.94 km2) of the Middle Draa Valley are classified in the non-desertification degree class.
The most affected zones by the desertification threat are located in south of the study area especially in the Ktaoua and M’Hamid oases. Those areas are characterized by sand dune movements, soil and water salinities, and low precipitations.
The desertification map preliminarily supports local and national authorities who work for the protection of fragile landscapes. This map will facilitate the protection of valuable land resource and will also determine the region that needs intervention.
The proposed approach can be replicated and transferable in other arid and semi-arid regions, especially in North Africa, the Middle East, and Asia. These areas are generally characterized by a high desertification risk with a low vegetation coverage density. Different multi-spectral remote sensing data, such as Landsat and Sentinel-2, can be used to apply the developed index.