Use of remote sensing and GIS in mapping the environmental sensitivity areas for desertification of Egyptian territory

Use of remote sensing and GIS in mapping the environmental sensitivity areas for desertification of Egyptian territory A. Gad and I. Lotfy National Authority for Remote Sensing and Space Sciences, Egypt Received: 25 January 2008 – Accepted: 6 May 2008 – Published: 4 June 2008 Correspondence to: A. Gad (abdallagad@gmail.com) Published by Copernicus Publications on behalf of the European Geosciences Union.


Introduction
Desertification is the consequence of a set of important processes, which are active in arid and semi-arid environment, where water is the main limiting factor of land use performance in ecosystems (Batterbury and Warren, 2001).In the context of the EC MEDLUS (Mediterranean Desertification and Land Use, a distinction has been made between degradation processes in European Mediterranean environments and the more arid areas.Physical loss of soil by water erosion, and associated loss of soil nutrient status are identified as the dominant problems in the European Mediterranean region.However, Wind erosion and salinisation problems are most often in the arid Mediterranean areas (Glantz, 1977;Quintanilla, 1981;Zonn, 1981).
Environmental systems are generally in a state of dynamic equilibrium with external driving forces.Small changes in the driving forces, such as climate or imposed land use tend to be accommodated partially by a small change in the equilibrium and partially by being absorbed or buffered by the system.Desertification of an area will proceed if certain land components are brought beyond specific threshold, beyond which further change produces irreversible change (Tucker et al., 1991;Nicholson et al., 1998).For example, climate change cannot bring a piece of land to a desertified state by itself, but it may modify the critical thresholds, so that the system can no longer maintain its equilibrium (Williams and Balling, 1996).Environmentally Sensitive Areas (ESA's) to desertification around the Mediterranean region exhibit different sensitivity status Introduction

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Full to desertification for various reasons.For example there are areas presenting high sensitivity to low rainfall and extreme events due to low vegetation cover, low resistance of vegetation to drought, steep slopes and highly erodable parent material (Ferrara et al., 1999).Land degradation processes involve two interlocking, complex systems: the natural ecosystem and the human social system (WMO, 2005).Natural forces, through periodic stresses of extreme and persistent climatic events, and human use and abuse of sensitive and vulnerable dry land ecosystems, often act in unison, creating feedback processes.Interactions between the two systems determine the severity of the degradation process.Inclusion of climate, vegetation, and land use into desertification assessment is reviewed by Gad (2008).The Universal Soil Loss Equation (USLE) was developed in the mid-1960s for understanding soil erosion for agricultural applications.In 1985, it was updated and renamed the Revised Universal Soil Loss Equation (RUSLE) to incorporate the large amount of information that had accumulated since the original equation was developed and to address land use applications besides agriculture.The RUSLE is derived from the theory of soil erosion and from more than 10 000 plotyears of data from natural rainfall plots and numerous rainfall simulations.
The RUSLE states that: Where A is the soil loss per year (t/ha/year); R represents the rainfall-runoff erosivity factor; K is the soil erodibilty factor; L represents the slope length; S is the slope steepness; C represents the cover management, and P denotes the supporting practices factor.These factors illustrate the interaction of various climatic, geological, and human factors, and that smart land management practices can minimize soil erosion and even land degradation.
Desertification indicators are those, which indicate the potential risk of desertification while there still time and scope for remedial action.Regional indicators should be based on available international source materials, including remotely sensed images, topographic data (maps or DEM's), climate, soil and geologic data (Woodcock et al., 1994;Pax-Lenney et al., 1996).At the scale ranging 1:25 000 to 1:1 000 000 the impact of socio-economic drivers is expressed mainly through pattern of land use.Each regional indicator or group of associated indicators should be focused on a single desertification process.The various types of ESA's to desertification can be distinguished and mapped by using certain key indicators for assessing the land capability to withstand further degradation, or the land suitability for supporting specific types of land use.The key indicators for defining ESA's to desertification, which can be used at regional or national level, can be divided into four broad categories defining the qualities of soil, climate, vegetation, and land management (Kosmas et al., 1999).This approach includes parameters, which can easily be found in existing soil, vegetation and climate reports.

Methodology
The identification of sensitive areas is based on the hypotheses of MEDALUS project model (Giordano et al., 2008).The model applies a geometrical average of some quality indexes, in order to provide sensitivity diagnosis.It assumes that each index has only a limited capacity to influence the final value of ESA index and only when several parameters have a high score, an area can be assigned to high sensitivity class.
The following three quality indices were computed; -Soil Quality Index (SQI), -Vegetation Quality Index (VQI) The methodology is based on classification of each quality index obtained as geometric mean of available environmental and anthropogenic parameters.The available parameters are quantified in relation to their influence on the desertification process Introduction

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Full assigning score to each.The scores assigned to different parameters range between 1 (best value) and 2 (worst value).The final overall ESA index is obtained as a geometrical average of the quality indexes (E.C, 1999).Figure 1 demonstrates the main flow chart of concepts and studied steps performed in the current study.The main input data for calculating these indices include a mosaic of LANDSAT ETM image, geologic map of Egypt, produced by CONOCO, 1990, climatic data derived from the Ministry of Agriculture.An image processing system (i.e.ERDAS IMAGINE 8.3) and a GIS system (i.e.Arc GIS 9) were the main tools in indices computations and ESA's mapping.

Mapping Soil Quality Index (SQI)
Soil is the dominant factor of the terrestrial ecosystems in the arid and semi arid and dry zones, particularly through its effect on biomass production.Soil quality indicators for mapping ESA's can be related to water availability and erosion resistance (Briggs et al., 1992;Basso et al., 1998).A number of four soil parameters were considered at the current investigation (i.e.parent material, soil texture, soil depth and slope gradient).
Weighting factors were assigned to each category of the considered parameters, on basis of OSS, 2004, which were adapted from Medalus project methodology (European Commission, 1999).Tables 1 to 4 demonstrate the assigned indexes for different categories of each parameter.The soil Quality Index (SQI) was calculated on basis of the following equation, and classified according to categories shown in Table 5.
(3) Vegetation quality, according to Basso et al. (2000) is assessed in terms of three aspects (i.e.erosion protection to the soils, drought resistance and plant cover).The TM satellite images mosaic covering Egypt (Fig. 2) is the main material used to map vegetation and plant cover classes.Adapted rating values for each of erosion protection, drought resistance and vegetal cover classes were adapted on basis of OSS ( 2004) as shown in Table 6.Vegetation Quality Index was calculated according the following equation, while VQI was classified on basis of the ranges indicated in Table 7.
Where: I E p index of erosion protection, I Dr index of drought resistance and Ranking of different elements is based upon the magnitude of vegetation fundamental role in erosion protection, drought resistance and soil capacity protection.The perennial cultivation provides a very high capacity to reduce the kinetic energy caused by the impact of soil erosion driving forces.Furthermore, the plant root system increases the stability of the soil, thus a value of (1) was assigned to rank each of I E p , I Dr , and I V c .Gradual relative lower capacity are provided by other vegetation classes (e.g.Halophytes, orchards, Saharan vegetation, etc.), thus relatively higher values are assigned for different sensitivity indices.

Mapping Climatic quality index (CQI)
The aim of the climatic quality index (CQI) in the current investigation is to assess the water availability to vegetation.Climatic quality is assessed by using parameters that influence water availability to plants such as the amount of rainfall, air temperature and aridity, as well as climate hazards, which might inhibit plant growth (Thornes, 1995).ArcGIS9 software was used to map ESA's to Desertification (Kosmas et al, 1999) by integrating all data concerning the soil, vegetation and climate.Different quality indices were calculated and displayed as GIS ready maps from which class areas were deduced.The Desertification Sensitivity Index (DSI) was calculated in the polygonal attribute tables linked with the geographic coverage according to the following equation; 3 Results and discussions 3.1 Soil Quality Index (SQI) The geologic map was used to deduce the nature of parent material, which is demonstrated in Figs. 3 and 4. Table 10 summarizes the areas of various parent materials classes, as deduced from the GIS system.The results show that 48% of the territory is originated from soft to friable parent material (i.e.friable sand, calcareous clay and colluviums materials).The coherent Introduction

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Full parent materials are limited in the Red Sea Mountains and southern Sinai, as these regions are mostly coherent hard crystalline Rockland.The soil depth (Fig. 5) was also evaluated on basis of both geologic map (CONCO, 1989) and soil map of Egypt (ASRT, 1982).
Table 11 shows that the soils characterized by a very shallow soil depth represent 44.2% of Egyptian territory.Those soils characterized by deep and very deep soils do not exceed more than 30% of the whole territory, located mainly in the Nile Valley and Delta and areas of sandy plains.
The soil texture was assessed on basis of the geomorphology, deduced from the ETM satellite mosaic.Table 12 and Fig. 6 show that the most sensitive coarse textured soils amount 81.5% of whole territory.The alluvial Nile Valley is exhibited by average textured soils, covering 8.25% of all soils.The colluviums (16.7%), brought by the alluvial fans and ravines, at the desert fringes, are exhibited by very light to average textured soils.The wadi soils are characterized by fine to average textured soils, covering 1.7% of all soils.The slope gradient (Fig. 7 and Table 13) was classified, on basis of topographic maps and digital elevation model (DEM).Calculating the soil quality index (Table 14 and Fig. 8) reveals that the majority of Egyptian soils (64.84%) are characterized by very low soil quality.The soils of the Nile Valley (21%) are characterized by moderate quality due to its capability to sustain soil structure and moisture.Those soils in the wadies, oases and desert fringes (13.20%) are attaining low soil quality.

Vegetation Quality Index (VQI)
Hybrid classification of ETM images (Fig. 9) resulted in identifying a number of four vegetation classes.Each of these classes was given a score evaluating vegetation cover, erosion protection and drought resistance (Table 15).
Calculating the vegetation quality index, on basis of the previous parameters (Table 16 and Fig. 10) reveal that the 94.29% of the vegetation cover is very weak and sensitive to desertification.The good vegetation index class, which may resist desertification, represents only 3.51% of the vegetation cover.Climatic data (i.e.rainfall and evapo-transpiration) interpolation resulted in obtaining values for both parameters (Figs. 11 and 12).The climatic sensitivity index was calculated and stored in a GIS ready map (Fig. 13).Most rainfed areas are located in the northern coastal region and don't exceed 200 mm.annually.The average annual rainfall drops down to almost zero, at less than 50-150 km distance south of the Mediterranean coast.The average annual potential evapo-transpiration is relatively high in the whole country, however increases southwards.Table 17 shows the areas of climatic quality index classes.The hyper arid climatic conditions characterize 89.3% of the whole territory, while 10.7% is characterized by arid climatic conditions.

Environmentally Sensitive Areas (ESA's) to Desertification
The three previous indices were driven together for the assessment of the environmentally sensitive areas (ESA's) to desertification, on basis of the calculated Desertification Sensitivity Index (DSI).Figure 14 shows the distribution of ESA's, while Table 18 demonstrates their areas.It is clear that most of the Egyptian territories are very sensitive and sensitive to desertification; these classes exhibit 74.39 and 20.27% of the whole territory respectively.The Nile Valley region is classified as moderately sensitive area, as its moderate quality soils are protected by good quality vegetation.The oases and the interference zone between the desert area and the Nile Valley are vulnerable to high desertification sensitivity index.

Conclusions and recommendations
It can be concluded that the assessment of desertification sensitivity is rather important to plane combating actions and to improve the employment of natural resources.It can be realized that the merely quantitative aspect of desertification sensitivity demon-Introduction

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Full strates a clearer image of the risk state than descriptive approaches.Reliable priority actions can be planned better on basis of risk magnitude knowledge.Remote sensing, in addition to thematic maps, may supply valuable information concerning the soil and vegetation quality at the general scale.However, for more detailed scales, conventional field observation would be essential.The Geographic Information System (GIS) is a valuable tool to store, retrieve and manipulate the huge amount of data needed to compute and map different quality indices to desertification.
Mathematical modeling should be developed for the operational monitoring of different elements contributing in desertification sensitivity.Multi scale mapping of ESA's are needed to point out the risk magnitude and causes of degradation in problematic areas.Evaluation and validation of the assessment methodology are recommended, they should be a matter of scientific discussions.
The Egyptian territory is susceptible to very high-to-high desertification sensitivity, however the Nile Valley is moderately sensitive because of its vegetation cover.Action measures are essential for the sustainable agricultural projects located in the desert oases, wadis and interference zone.
Table 8 reveals the classification categories of climatic quality index according Introduction The Climate quality index is evaluated through the Aridity Index (AI), using the methodology developed by the Applied Meteorology Foundation "FMA" (Ren é Gommes et al., 2007) in accordance with the following formula In the current study, rainfall and evapotranspiration data on a number of 33 metrological stations, published in the Monthly weather report (The Arab Republic of Egypt ARE, 1979), were used to

Table 1 .
Classes and assigned weighting index for parent material.
Note: In case of deep Aeolian deposits over a rocky parent material, the Aeolian sediments are considered as parent material.

Table 2 .
Classes and assigned weighting index for soil depth.

Table 3 .
Classes, and assigned weighting index for soil texture.

Table 4 .
Classes, and assigned weighting index for Slope gradient.

Table 5 .
Classification of soil quality index.

Table 6 .
Classes, and assigned weighting index for different vegetation parameters.

Table 9 .
Ranges and classes of desertification sensitivity index (DSI).

Table 10 .
Nature of parent material classes of Egyptian territory and assigned scores.

Table 11 .
Distribution of soil depth classes and assigned scores in the Egyptian territory.

Table 12 .
Distribution of soil texture classes and assigned scores in the Egyptian territory.

Table 13 .
Distribution of slope classes and assigned scores in the Egyptian territory.

Table 14 .
Areas of different categories of Soil Quality Index (SQI) classes.

Table 15 .
Vegetation cover classes and assigned scores for different elements.

Table 16 .
Areas of different vegetation quality index classes.

Table 17 .
Areas of different climatic quality index classes.