bush patterns in Somalia from a global mapping perspective. ... A strong boost to identifying tiger bush areas in Somalia and in other parts of the world has.
Preliminary results about mapping and geomorphological correlation of tiger bush (Brousse tigrée) in Somalia, from a remote sensing and GIS analysis perspective paolo paron, andrew s. goudie
Abstract is study contributes to the identification, description and preliminary understanding of tiger bush patterns in Somalia from a global mapping perspective. It attempts some correlations between their location and other geomorphological parameters of the landscape. e mapping and correlation process has been carried out using GIS and Image Analysis so ware. No field checks were performed due to lack of security and the difficult logistic conditions of the country. A strong boost to identifying tiger bush areas in Somalia and in other parts of the world has been given by the recently released Google Earth tool. is allowed the identification of areas of tiger bush over other nine countries where they seem never to have been reported previously. In addition, a new map of the distribution of tiger bush in Somalia has been achieved and a new area of tiger bush presence is outlined in the southern part of the country. key words: tiger bush, Somalia, geo-ecology, Google Earth, global mapping.
1. Introduction Tiger bush (brousse tigrée) gives rise to a landscape formed by alternating vegetated (grass, shrubs or trees) and bare land, arranged in different patterns that can be classified as: banded, fuzzy, dashed or dotted, and spotted depending on two main factors: slope gradient and mean annual rainfall (d’Herbes et al. 2001; Valentin 1999). Other parameters like soil composition and distance between vegetated bands and bare soil interbands (wavelength), have also been advocated as being responsible for the different patterns (see Table 1, from Valentin et al. (1999)). !e main controls on distribution are a low annual rainfall, gentle slopes and crusting soils. !ese factors tend to favour the development of sheet overland flow, which is believed to play a prime role in the establishment of banded vegetation (Valentin 2004). Tiger bush is mostly present in arid and semi-arid regions of the world. Using global mapping tools like Google Earth®, that provide both visual interpretation of satellite images and a terrain model (based on SRTM and thus coherent with the one used in our research), it is possible to attempt a global distribution map of tiger
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paolo paron — andrew s. goudie Table 1 Different band types in relations to mean rainfall and slope gradient (from Valentin et al. 1999).
Fig. 1 Location map of tiger bush patterns obtained by analyzing satellite images through the Google Earth tool. The dark grey tone highlights the countries with the new localities while the light grey tone highlights the countries with already known sites of tiger bush.
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bush (Fig. 1). !is has allowed us to identify some new locations around the world: Bolivia, Iran, Iraq, Kazakhstan, Madagascar, Namibia, Turkmenistan, Yemen, and Zambia. Photo keys of different tiger bush patterns coming from some of the most striking locations found using the global mapping facilities around the world are shown in Fig. 2. Here the pin indicates the mean geographical position in terms of latitude and longitude of the areas identified on the basis of the remote sensing analysis. Different patterns can be easily distinguished in the literature. Some of the very first studies of tiger bush were conducted in the former Somaliland Protectorate (now Northern Somalia) in the 1940s–1960s (Gillet 1941; MacFayden 1950; Gilliland 1952; Greenwood 1957; Boaler and Hodge 1962, 1964; Hemming 1965) together with the first stages of the application of aerial photography to its investigation. Starting from this research much attention has been devoted to this topic in different parts of the world. During the last 70 years most of the studies carried out can be grouped into three thematic and temporal steps (d’Herbes et al. 2001): − observation/description (1940s–60s); − experimental studies (1970s–80s); − modelling (1990s–the present). !is last modelling phase has involved multidisciplinary approaches that include mathematical-thermodynamic (e.g. !iéry et al. 1995; Lefever and Lejeune 1997; Couteron and Lejeune 2001; Lejeune et al. 2004; Meron et al. 2004; Rietkerk et al. 2002 and 2004; Sherrat 2005), ecological (e.g. Leprun 1999; Tongway and Ludwig 2001; Montana et al. 2001; Mauchamp et al. 2001; !iery et al. 2001; Dunkerley and Brown 2002), hydrologic (e.g. Bryan and Brun 1999; Ludwig et al. 1999; Galle et al. 2001; Greene et al. 2001), and anthropic/land management (Wu et al. 2000; Freudenberger and Hiernaux 2001; Noble et al. 2001) theories and experiments. Because of all these different approaches and geographical areas of investigation, tiger bush has been named in a variety of ways: Tiger bush, vegetation stripes, vegetation arcs, vegetation ripples, spotted patterns, vegetation bands, banded vegetation pattern, two-phase mosaic, brusse tigrée, mulga, and self-organized patchiness. Most field research about tiger bush has been very subject specific and local. Only the more recent modelling takes into account examples coming from different regions. No detailed maps at a national or regional level exist for any country where tiger bush is located. As regards Somalia, the great majority of the available data concern the vegetational aspects and its distribution in relation to soil types and rainfall (MacFayden 1950; Greenwood 1957; Boaler and Hodge 1962 and 1964; Hemming 1965 and 1966). !e gemorphological-related information regarding Somalia’s tiger bush that can be extracted from the literature of the 1950s and 1960s is summarized in Table 2. !e only specifically geomorphological approaches in tiger bush studies have been those of Zonnenveld (1999) and Wakelin-King (1999) relating to Northern Nigeria and Australia respectively. !e first one was a study directed at a land unit reconnaissance survey. It used the banded vegetation pattern as distinctive of differ-
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paolo paron — andrew s. goudie Table 2 A synthesis of geomorphological-related information derived from the studies on tiger bush in Somalia of the 50s and 60s. Author/s
Location of the study area
Patterns/types
Description
MacFayden 1950
British Somaliland: Haud 119,000 km2; 1,430–290 m a.s.l. Sawl Haud 21,000 km2; 1,370–915 m a.s.l.
1 pattern (tiger skin) 2 types: with or without water lanes within
A band of vegetation forming arcs onto air photographs. Arcs are invariably oriented so that their cord form a 90° angle with the direction of drainage, they are convex upslope. Desert or bare soil between arcs
Greenwood 1957
British Somaliland: Haud Sawl Haud
Can be convex up-slope (shallow valley-like waterways, low hilly topography) or down slope (low ridges) or can be straight lines (on plains)
Grass is more frequent where clay soils exist, trees and bush more frequent where sandy soils are present.
Boaler & Hodge 1962
Somaliland. South-east of Hargeysa. The area is on and to the north of Ban Tuyo and extend westwards to the Go-Gub and Kah area.
They concentrate on MacFayden’s “water lanes”. Two types (veg stripes and lanes) both normal to the vegetation arc cord and with their long axis parallel to the direction of greatest slope
Stripes are straight or very gently curved and continuous for several miles. Lanes are smaller and parallel. Both lanes and stripes are adjacent to areas of vegetation arcs and the two types of pattern merge together.
Boaler & Hodge 1964
Northern Somalia. Study area is: Ban Sila, 30 km S of Hargeysa; Jerin, 30 km W of Burao (Burco); Aric-Aric, Kah, Go-Gub, all 30 km SE of Hargeysa. Other regions are: Kalahari, Kenya, Tanzania, Iraq, Syrian desert, West Africa-River Niger, Arabia-Jedda region, Australia.
One main type formed of grass, shrub and tree.
The arcs are bands of vegetation separated by nearly bare ground and with the uphill edge lying very nearly parallel to the contour line. They are U shaped with arc ends towards downhill. The change from the vegetated arc to bare ground is quite sharp on the uphill edge and less evident downhill for the presence of scattered plants and often dead plants. Arcs can be divided in three zones: front, the narrow zone present at the uphill edge; body or arc, is the main part of the arc; bare, is the the ground between arcs.
Hemming 1965
Somaliland: 2.4 km NW of Baran, 29 km SW of Las Anod
3 types of arcs: i) arcs of tree and grass along contour lines; ii) parallel stripes along the greatest slope; iii) much smaller, occurs in areas marked as “watercourses with no definite stream bed”
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Relation to climate
Relation to slope
Relation to bedrock/soils
Measurements/ morphometry
2 seasons: Gu rains in April–June Karan and Dhair in Sept–Nov. Maximum in May and October Haud: rainfall 127–432 mm and max of 762 mm Sawl Haud: no data SW Monsoon (kharif): May to Sept. NE Monsoon: Oct to May
Haud: mainly plains Sawl Haud: flat + slightly tilted Average slope is of 1 : 400
Rhythmic interval of a single sequence of arcs and desert is about 158 m (70–276). Transverse width of arcs ranged from 20 to 36 m (10–76); that of intervening desert 70–146 m (25–146); lateral extent of single arcs is on av. 0.5–1.0 km (up to 2)
The original spacing of arcs depends upon velocity of water flow and thus on slope, and also on the volume of material transported. A break in slope causes the sedimentation of clay and thus not allows the formation of a vegetation arc
Experiment on a gently inclined board: arcs form convex up-slope when water velocity is low; they are down-slope when water velocity and flow increase.
Rainfall: about 250 mm falling in early and late summer (May and September) varying widely from year to year
Flat plain. Slopes of 1 : 350, 1 : 190 – 1 : 240
The plain is made of alluvium. Some limestone hills 60 m height. Soils are deep (more than 2–5 m); soil surface largely bare and smooth. Soils differ between stripes and lanes for sand/clay content and texture and salts. Soils of the bare lanes are lighter textured and have a deeper topsoil than the adjoining vegetation stripe soil. Soluble salts are leached to a greater deep in the lanes.
Stripes can be long one or more miles; wide 90–180 m in the bush and 70 m in the grass. Lanes are 45 m wide in the bush and slightly wider than the stripes in the grass.
Semi-arid and tropical climate. Rain: 125–300 mm. They concentrate in early and late summer. Climate regime: monsoonal with long winter drought and north-east wind. In the rest of the year south-west winds.Evaporation: 1,885 mm per year, 200 mm in July. (See table 1)
They occur in plains and in very broad valleys and in some narrower flat-bottomed valleys.Along the line of greatest slope there is often a step-like profile with a slight reduction in the degree (or a rise) of slope at the front and a steeper slope at the lower side.The slope values vary from 1 : 140 to 1 : 450 with an av. of 1 : 240. (See table 2)
All the soils examined have a thin surface crust, a friable A horizon, and a compact B horizon of heavier texture. The processes that soils undergo during run-off is described (crust brakes under rain splashes, it is sufficiently impermeable to allow water not to infiltrate). The amount of clay increases with depth. The salts are more concentrated under grass arcs than bare grounds. Several potholes are present.
The arcs vary in width from 15 to 70 m with a vertical interval of 0.06 to 0.41 m. The vertical interval generally increase with width. Rhythmic interval ranges from 45–256 m and corresponding vertical intervals are of 0.19–1.16 m. No apparent connection between rhythmic interval and slope.
Rainfall: less than 150 mm The area is a plain with (deduced). At Las Anod the a maximum slope of 1 : 166 rain is 122 mm, concentrated in April–May (44 %) and October–November (33 %) Average mean monthly maximum T is 33 °C (Sept), average mean monthly minimum is 13 °C (Jan). Average diurnal range throughout the year is 13.3 °C. Extreme absolute T range is 36.9 °C.
The fine wind-borne materials is caught by belts of vegetations. The bare ground results in a stone mantle with coarse sand. Soil is less alkaline under grass arcs. No soil structure difference between inside and outside the arcs. More physical rather than chemical weathering products. **Calcareous pinkish-beige gritty clay soil with 7–11 % of small stones until 23 cm from the ground. Below the stones become more numerous and bigger. ** There is no great difference between the clay content of soils under arcs and between them. That could be the case if the arcs have been depleted by overgrazing.
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a)
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Fig. 2a–f Examples of how tiger bush appears from a satellite images viewed at different scales (highest reported in miles on the lower right corner of each frame) from Google Earth. a), b) Australia; c), d), e) Somalia; f) Sudan.
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g)
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Fig. 2g–l Examples of how tiger bush appears from a satellite images viewed at different scales (highest reported in miles on the lower right corner of each frame) from Google Earth. g) Sudan; h), i), j) Saudi Arabia; k), l) Syria–Iraq.
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m)
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Fig. 2m–p Examples of how tiger bush appears from a satellite images viewed at different scales (highest reported in miles on the lower right corner of each frame) from Google Earth. m) Syria–Iraq–Jordan; n) Ethiopia.
ent surface hydrologic conditions and specifically on sheet erosion surfaces that had levelled a palaeodune landscape. !e difference here found was due to a difference in silt content of the soils developed from the sand dune lithology. Wakelin-King, on the other hand, studied the distribution of tiger bush within the context of Cenozoic mapping in Australia. He proposed the mapping of banded vegetation as a distinctive marker of sheetflow processes over gentle slopes, given that these units are wide enough to be represented on geological maps and that they are quite difficult to define in gently sloping areas if any other geomorphic element is present. Starting from a remote sensing and a global mapping perspective we have characterized the geomorphology of the tiger bush landscapes in Somalia, analyzing the different aspects of the physical environment, and trying to find out their inter-relationships. In this way we would like to contribute to filling the gap between the several local field observations and the very few global perspectives, thereby providing a continuum between different scales of investigation (Seghieri and Dunkerley 2001). !is study did not involve a field check due to the impossibility to travel in Somalia because of lack of security.
2. The study area Our study area is Somalia (approx 637,657 sq. km), located in the Horn of Africa. It extends from approximately 1° 40' South of the Equator to 11° 58' North and from 40° 59' to 51° 24' East. It is bordered by Djibouti to the North-West, the Gulf of Aden to the North, the Indian Ocean to the East, Kenya to the South and SouthWest and Ethiopia to the West. It has the longest coastline of the African countries with 3,898 km (WRI, 2005). Very few authors have analysed the geomorphology of Somalia, and most studies have only been of parts of it (Pallister 1963; Daniels 1965; Coltorti and Mussi 1987;
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Abdirahim et al. 1994; Sommavilla et al. 1994, Carbone and Accordi 2000). Only one has given a nationwide description of its geomorphological characteristics (Perissotto 1978). Some useful information about the landscape at a nationwide scale are provided by the technical report of the FAO Africover Project (Rosati 1999) and some other information can be extracted from the FAO Soter datasets (FAO 1998): these are the only nationwide consistent datasets. !e analysis of the NASA SRTM (Shuttle Radar Topographic Mission) elevation data at a resolution of 90 × 90 meters allowed definition of the main topographic and morphometric features and the determination of the distribution of the elevation of the country. !e analysis of these data, together with the ones coming from photointerpretation and from geological maps of the area, allowed us also to define the main landscapes and the principal sectors in which the country can be divided. !e hypsometric curve of the whole country shows a clear deep upward concavity, indicating that areal denudational processes predominate over linear ones. From a physiographic point of view the country can be subdivided in two sectors: a northern one (northward of latitude 7° 30') and a southern one (southward of latitude 7° 30'). As shown in Figs. 3a and 3b the distribution of elevations is very different between the two sectors. According to FAO-Africover (1999) five main landscapes characterize the country: plain; dune field; hill; badland and footslope; plateau and mountain. !e hydrography of Somalia is characterized by the presence of the distal portion of the two main rivers of the Horn of Africa, that flow from the highlands of Ethiopia towards the Indian Ocean: the Jubba, which flows in Somalia for more than 700 km out of its 2,000 km of total length (considering its main tributaries), and the Webi Shabellee that extends for more than 600 km in Somalia out of its almost 1,600 km of total length. Almost all the rest of the country is dominated by ephemeral streams, called toga, tug, or wadi (Faillace 1986). !ey are dry for most of the year except during the rainy season. !ey drain following the general slope of the relief. Climatic analysis has been conducted mainly on the basis of WMO data (available at either http://igskmncnwb015.cr.usgs.gov/adds/index.php or http://iridl.ldeo. columbia.edu/docfind/databrief/ or http://geodata.grid.unep.ch/), from Weatherbase (http://www.weatherbase.com/), and from Griffith (1972). !e data used here are mean, maximum and minimum monthly temperature, and mean, maximum and minimum monthly precipitation. !e climate of Somalia is dominated by seasonal variations of the monsoon, of the Inter Tropical Convergence Zone (ITCZ) and by the vicinity to the Equator. Most of Somalia falls under the Arid (0.03 < P/Pet < 0.20, Northern sector) and Semi-arid classes (0.20 < P/Pet < 0.50, Central and Southern sectors) as defined by UNESCO (1977). According to Köppen’s classification Somalia falls into the B climate type with two subtypes: BWh for the great majority of the country, and BSh only in the very southern part. !e climate is typically bimodal with two rainy seasons, called Gu (from April to June) and Der (from October to December) and two dry ones, called respectively Jilaal (from January until April) and the Hagaa (from June to October). !is has the highest average temperatures of the year (Fig. 4a and 4b).
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Fig. 3a
Main physical elements of Somalia – elevation.
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Fig. 3b Main physical elements of Somalia – morphology (hillshade derived from SRTM 90 × 90 m, displayed in rgb colours, sun light azimuth 315° elevation 45°).
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Fig. 4a–d Main climatic characteristics of Somalia. a) Precipitation regime (expressed in mm); b) temperature regime (expressed in °C); c) ΔP (= Max P – Min P) through the year; d) ΔT (= Max T – Min T) through the year.
!e Gu and Der rains are caused by the passage of the Inter Tropical Convergence Zone (ITCZ). !is causes rain to fall in isolated storm cells, the result of which is an extremely irregular rainfall pattern. !e ITCZ also controls wind direction. From May to September, when the ITCZ is at 15° S, the wind blows from the southwest and from December to February when the ITCZ is at 15° N, the wind blows predominantly from the north-east. During the transitional periods (Tangambilis), the wind drops and becomes erratic in direction (Carbone and Accordi 2000). From the geological point of view the literature available is scattered. A general geological description of Somalia is absent, but there are detailed geological analyses of specific areas and subjects (e.g. Abbate et al. 1994; Ali Kassim et al. 2002; Cli6 et al. 2002; Fantozzi and Ali Kassim 2002). A geological map of Somalia at the scale of 1 : 1,500,000 (Abbate et al. 1994) is the most recent document on the geology of the entire country. Other geological maps investigate at a greater detail only small portions of this territory (Merla et al. 1973; Bruni et al. 1987; Abbate et al. 1994; Abdihrahman et al. 1994; Ali Kassim et al. 1994; Ethiopian Government 1996; Fantozzi et al. 2002). !e lithology of Somalia mainly consists of marine sedimentary rocks ranging from Mesozoic to Recent in age. Only two isolated crystalline pre-Cambrian basement outcrops (one in the northern part and one in the southern) occur. !e marine sedimentary cover is represented mainly by limestones and marly-limestones of the Karka and Auradu Formations in the North and of the Mudug Succession in the
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Fig. 4e Main climatic characteristics of Somalia – distribution of precipitation and temperature among the country (derived from WMO and Weatherbase data).
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Central and South parts. Several Quaternary deposits of aeolian, lacustrine, and alluvial origin outcrop along the coast and in the main alluvial valleys. A characteristic long coastal dune system is almost parallel to the Indian Ocean coastline for almost 1,300 kilometres. Isolated volcanic basaltic rocks, from Late Miocene to Pleistocene in age, outcrop along the border with Djibouti, while Proterozoic and late Cambrian basement volcanic and metamorphic terrains outcrop in the North of Somalia in a very complex structural setting, while in the south they are present in a less complex arrangement (Abbate et al. 1994). !e only nationwide datasets on Somalia vegetation are the ones provided by the FAO Soter and Africover projects. From these it is clear that most of Somalia is desert or bush. In fact only 43 % of its surface is covered by vegetation that can be grouped into three categories (according to FAO-Soter): bush (32.2 %); grassland (9.9 %); and woodland (0.9 %). A previous comprehensive study by Hemming (1965) relating to the vegetation of northern Somalia (former British Somaliland) indicates the following vegetation classes: a) coastal; b) sub-coastal; c) Acacia etbalca; d) Evergreen; e) Juniper; f) Acacia bussei; g) Haud type; and h) Gypsum, giving again a picture very close to the one from the FAO datasets, where the majority of the northern territory is arid and hyperarid.
3. Data and Methodology !e methodology of this research has followed two main steps: 1. !e Mapping process: visual and multispectral interpretation of satellite images to derive a map of the occurrence of tiger bush for the whole of Somalia; 2. GIS analysis: pre-elaboration of the available digital data (climate, vegetation, soil, geology, landform data, etc.) and spatial analysis to find the correlations between tiger bush distribution and these datasets. !e mapping process has involved a visual interpretation of satellite imagery a6er appropriate spectral combination and enhancement. !e scale at which this interpretation was performed is 1 : 100,000. !e analysis has been based on public, freely available, remote sensed data. From the NASA Applied Science Directorate (https://zulu.ssc.nasa.gov/mrsid/) data portal, ten Landsat 7 ETM+ mosaicked and enhanced, with false colour composite RGB-742 were downloaded. !e pixel resolution of these datasets is 14.25 meters and they are stretched using a contrast stretch k known as LOCAL (Locally Optimized Continuously Adjusted Look-up-tables) stretch (EarthSat). !is stretch uses multiple, locally collected histograms, to create a radiometrically seamless blend of contrast adjustment across areas of potentially extreme contrast ranges. From the Global Land Cover Facility – Earth Science Data Interface (http:// glcfapp.umiacs.umd.edu:8080/esdi/index.jsp) data portal it was possible to download all the bands of the Landsat7 ETM+ sensor covering the Somalia area. !e single band Landsat 7 ETM+ data have been used to create the following false colour
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composites (fcc) (Drury 2003; http://rst.gsfc.nasa.gov/; http://www.crisp.nus.edu. sg/~research/tutorial/rsmain.htm): − 742-RGB (reclassified to a pixel resolution of 15 × 15 meters), mainly used for geomorphological and geological analysis; − 432-RGB (with a pixel resolution of 30 × 30 meters) mainly used for vegetation analysis; − 321-RGB (with a pixel resolution of 30 × 30 meters), also called “true color”, used for visual interpretation; − 4-Grayscale (with a pixel resolution of 30 × 30 meters), Very Near Infra Red (VNIR) band used for the validation of vegetation identification on other bands; − Normalized Difference Vegetation Index (NDVI), was used for selected sites where the identification of the vegetation was less clear from the analysis of the other band composite. !e good quality of the original data, both in terms of absence of cloud cover and in good colour contrast, allowed us also to distinguish between different types of patterns of tiger bush vegetation, according to the literature. A major contribution to identifying tiger bush areas in Somalia as well as in other parts of the world has been given by the recently released Google Earth® tool. !is has been useful both for performing a multitemporal analysis over the same area and in conducting a quick and scientifically valid comparison of different tiger bush environments over the entire world. !rough this new tool it was possible to identify the new areas of tiger bush environment shown in Fig. 1. For the analysis of morphology and other landform-related parameters (slope, aspect, curvature, etc) data coming from the Shuttle Radar Topographic Mission (NASA-SRTM) have been of great impact. !e data covering Somalia were downloaded from http://esip.umiacs.umd.edu/index.shtml. !e SRTM data have a horizontal spatial resolution of 90 × 90 meters and an absolute vertical accuracy of 16 meters (and a relative one of 6 meters) (Falorni et al. 2005). In order to derive the best information from the DEM dataset, they have been implemented following the procedure of Sijmons et al. (2005) from ITC. !is allows one to obtain a seamless and geometrically corrected dataset for the elevation of a given region. In the GIS analysis a spatial analysis was performed, combining the newly obtained map with data providing national coverage and relating to geomorphology (landscapes and landform), lithology, climate, etc. !ree main datasets were available: two coming from FAO (SOTER and AFRICOVER Projects) and one coming from the World Meteorological Organization network of meteorological stations, integrated with data coming from the Weatherbase repository. As regards the other two datasets, they were provided in a digital format suitable for being used in a GIS so6ware (shape or Arcinfo file formats). Specifically they were the following two: SOTER (SOil and TERrain of East Africa): this project was mainly designed for the production of soil databases, at the scale of 1 : 1,000,000. It includes, as well, many other types of information such as geology, landscape, slope, surface form,
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vegetation, soil depth, soil texture, parent material and soil type. !e scale of Soter is much more smaller than the one used in the present research, nevertheless it represents the only consistent data available on soils for Somalia. AFRICOVER (Africa Land Cover Project): this project was mainly designed for the production of landcover at the scale of 1 : 200,000. However, it contains landform and lithology datasets. !is dataset has a scale that is quite far from the one used in the present study, but still it is the best known consistent dataset on Somalia.
4. Tiger bush patterns in Somalia and their spatial correlation As a result of this methodology a new map of the distribution of tiger bush in Somalia, at the scale of 1 : 100,000, has been achieved, showing a new area of tiger bush in the southern part of the country. !is product was the basis for the further GIS elaborations that allowed us to compare the tiger bush distribution with other parameters. !ree different patterns of tiger bush have been distinguished worldwide in the literature (Valentin 1999; d’Herbes et al. 2001) and are used here: arcs, lines, and dots. For each of them, two different categories have been added that give rise to the following six patterns: arcs; degraded arcs; lines; degraded lines; dots; and degraded dots. !e degraded patterns are given by a discontinuous distribution of the dominant pattern, even though it is still possible, from a remote sensing point of view, to identify the original geometrical vegetational arrangement; the presence of degraded patterns implies also a degradation of the vegetational cover within the stripes (!iery et al. 1995; Chappell et al. 1999; Ludwig et al. 1999; Valentin et al. 1999). In fact only five of these patterns have been identified, as the degraded dots class is not present in Somalia. !e resulting map (Fig. 5) depicts the distribution of the five classes of tiger bush in Somalia. !e map indicates the following: 1. three main areas of tiger bush occurrence are easily distinguished: two in the north of the country (areas A and B on the map) and one in the south (area C on the map); 2. the wider and more continuous areas are distributed in the north (areas A and B); 3. some spotted occurrence of tiger bush are also present in the North eastern, North western and the very South parts of the country. 4. the great majority of the tiger bush in Somalia is of the banded or arc pattern type (see also next section); It is important to notice that tiger bush occupies almost 10 % of the total surface of Somalia (63,637 sq km out of a total of 637,657 sq. km). !e physical setting of tiger bush can vary between different sites. It is found at elevations that vary from 1,763 m a.s.l. to less than 200 m a.s.l. and with slope angles that can vary from almost flat to more than 15°. Areas A and B are at the highest el-
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Fig. 5 Tiger bush map for Somalia. The grey colours identify the five different types of tiger bush. The capital letters A, B and C identify the main areas of presence of tiger bush (see text for details).
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paolo paron — andrew s. goudie
a)
b) Fig. 6a–b Examples of different types of tiger bush, as they appear on the Landsat false colour composite frames. a) arcs type with water lanes, in northern Somalia, developed on the bottom of small and flat valleys, A area; b) arcs type with differences in band/interband ratio and in width of the band between the ones developed on the flat plateau surface and the ones on the bottom of dried rivers, B area.
preliminary results about mapping and geomorphological correlation
c)
d) Fig. 6c–d Examples of different types of tiger bush, as they appear on the Landsat false colour composite frames. c) degraded arc type developed on a pediment surface, north of a ridge made by gypsiferous rocks, B area; d) degraded line type, developed on an alluvial plain, C area.
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e) Fig. 6e Examples of different types of tiger bush, as they appear on the Landsat false colour composite frames. e) arcs and degraded arcs types developed on both gently sloping surfaces and flat bottom small valleys of both sides of the Shabelle river valley in its middle tract, C area.
evations while area C has a lower altitude. !e tiger bush in Somalia can be found on a number of different geomorphological settings. !e two most frequent landscapes are represented by plateau or almost flat areas. !ese two are found mainly in areas A and B, while in area C some interfluves and gentle sloping flanks are also covered by tiger bush. On plateaux the tiger bush can be found both on flat plains and on the bottoms of dry river beds. !is gives rise to a different spacing of the bands: closely spaced and thicker bands occur in river bottoms, while more widely spaced and thinner ones occur on flat areas. When they occur on gentle sloping flanks they are mainly inside the dry river beds and so are of the thick and dense type. In all three areas the general convexity of the arcs is upward or at least very close to being parallel to the contour lines. Inside the dry river beds the convexity is much more accentuated than on the flat areas where it usually passes to degraded arcs if the slope is very low. If “water lines” (sensu MacFayden 1950) are present (mainly in area A) they tend to be straight and have an average length between 10 and 20 km. In Fig. 6a to 6e some Landsat 7 ETM+ photo key examples of striking tiger bush features and environments in Somalia are presented. !e clearest ones are the most widespread and are of the arc type. Line and dot types are much more infrequent. From a spatial analysis point of view some geo-correlations have been performed between the location of tiger bush and 18 other parameters coming from different sources, at different scales and resolutions, and of different digital formats (vectors,
preliminary results about mapping and geomorphological correlation
rasters, and tables) as summarized in Table 3. !e aim of this analysis was to find out which are the most representative physical environmental characteristics of tiger bush sites in Somalia. A great part of the analysis was devoted to the pre-elaboration of all the different data formats in order to obtain consistent datasets to be overlaid by the vector polygons of tiger bush previously mapped. !e main so6ware tools here used have been Spatial Analyst and 3D Analyst of the ArcGIS-ArcInfo package. Table 3 List of parameters used for the GIS analysis and for correlations with the distribution of tiger bush patterns. N°
Parameter
Source
Scale/spatial resolution
Original data type
1
Landscape
FAO- SOTER (Soil and Terrain Database for North-Eastern Africa), 1998
1 : 1,000,000
Vector
2
Landforms
FAO-Africover, 2003
1 : 200,000
Vector
3
Geology
FAO-Soil and Terrain Database for NorthEastern Africa, 1998
1 : 1,000,000
Vector
4
Lithology
FAO-Africover, 2003
1 : 200,000
Vector
5
Slope
FAO-Soil and Terrain Database for NorthEastern Africa, 1998
1 : 1,000,000
Vector
6
Slope
NASA-SRTM (Shuttle Radar Topographic Mission), 2000
90 × 90 meters
Raster
7
Surface Form
FAO-Soil and Terrain Database for NorthEastern Africa, 1998
1 : 1,000,000
Vector
8
Vegetation
FAO-Soil and Terrain Database for NorthEastern Africa, 1998
1 : 1,000,000
Vector
9
Soil Depth
FAO-Soil and Terrain Database for NorthEastern Africa, 1998
1 : 1,000,000
Vector
10
Soil Texture
FAO-Soil and Terrain Database for NorthEastern Africa, 1998
1 : 1,000,000
Vector
11
Parent Material
FAO-Soil and Terrain Database for NorthEastern Africa, 1998
1 : 1,000,000
Vector
12
FAO Soil Classification
FAO-Soil and Terrain Database for NorthEastern Africa, 1998
1 : 1,000,000
Vector
13
Elevation
NASA-SRTM (Shuttle Radar Topographic Mission), 2000
90 × 90 meters
Raster
14
Aspect
NASA-SRTM (Shuttle Radar Topographic Mission), 2000
90 × 90 meters
Raster
15
Mean annual Temperature
WMO (World Meteorological Organization) and Weatherbase
—
Table
16
Total annual Precipitation
WMO (World Meteorological Organization) and Weatherbase
—
Table
17
Mean minimum Temperature
WMO (World Meteorological Organization) and Weatherbase
—
Table
18
Mean maximum Precipitation
WMO (World Meteorological Organization) and Weatherbase
—
Table
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paolo paron — andrew s. goudie Table 4 Areas covered by different tiger bush patterns within the Somalia territory (as absolute values in sq km and as percentage of the total tiger bush area). Pattern
Absolute area (sq km)
Relative area %*
Arcs
40,309
63 %
Arcs, degraded
22,571
35 %
83
0%
Dots Lines
466
1%
Lines, degraded
208
0%
63,637
100 %
TOTAL
* the area percentage is intended over the overall tiger bush area
Every parameter listed in Table 3 (column Parameter) has a further subdivision into classes, defined by the different authors. Table 4 clearly shows that the 98 % of the tiger bush pattern is formed by arcs and degraded arcs (63 % of arcs and 35 % of degraded arcs). !is means that the arc pattern, taken as a whole, can be considered as the main typology of tiger bush patterns in Somalia. !e following Table 5 and diagrams show the results of the spatial elaborations conducted so far. It account for all five patterns of tiger bush vs. each class of the parameter considered. Table 5 is related to the vector/vector spatial analysis while the diagrams of Fig. 7 are related to the raster/vector spatial analysis. As concerns the data coming as tables or spreadsheets (mainly climatic data) they have been analysed considering the three main areas of tiger bush distribution and the results are presented in Table 6.
a)
b)
Fig. 7a–c Correlation between the raster datasets vs tiger bush areas. All the raster datasets come from NASA – SRTM. a) Slope classes of tiger bush. In this chart the value of 0° (representing the 95.65%) is not computed. b) Elevation classes of tiger bush. c) Aspect classes of tiger bush.
c)
preliminary results about mapping and geomorphological correlation Table 5 Comparison of different geomorphological parameters vs. tiger bush. The values are expressed as absolute area (in square kilometres) and as relative values (the percentage is intended over the overall tiger bush area, considered as 100 %). Parameters
Classes
Landscape1
Plains Uplands Footslopes / Piedmont plains Plateau Plains Alluvial plains Limestones Sandstones Undifferentiated, unconsolidated sediments Limestones Undifferentiated Sand, coastal, and aeolian deposits 0–5 % (slope angle) 2–16 % 0–2 % Undulating Rolling Level Bush / Bare surface Bush / Bare surface / Grassland Bare surface / Grassland 0–50 cm 51–100 cm 101–150 cm Loam Unknown Clay loam Colluvial / Residual Colluvial Alluvial Haplic Calcisols-orthic Calcaric Cambisols-orthic Eutric Leptosols-chormic
Landform2
Lithology1
Lithology2
Slope1
Surface forms1
Vegetation2
Soil depth1
Soil texture1
Parent material1
FAO Soil classification1
1
Absolute values (sq. km) 35,236 9,100 6,783 20,923 16,119 13,456 38,808 8,694 6,398 29,878 11,181 7,344 19,872 14,725 8,451 32,540 17,246 6,940 36,270 10,589 4,161 23,113 22,340 8,229 34,406 19,187 8,808 23,048 19,712 7,820 16,744 10,914 7,569
Relative values (%) 55 % 14 % 11 % 33 % 25 % 21 % 61 % 14 % 10 % 49 % 18 % 12 % 31 % 23 % 13 % 51 % 27 % 11 % 57 % 17 % 7% 36 % 35 % 13 % 54 % 30 % 14 % 36 % 31 % 12 % 26 % 17 % 12 %
from FAO SOTER; 2 from FAO AFRICOVER
A further attempt to quantify and verify the correlations between the proposed parameters was made through a statistical analysis of the correlations. Assuming that each square kilometre could be considered as an occurrence, a statistical test (chisquare) has been conducted on the datasets that were directly available in vector format. !is sort of analysis was not carried out for the raster (slope, aspect, elevation) and climatic data. In Table 7 the results of this test are shown.
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paolo paron — andrew s. goudie Table 6 Distribution of mean annual temperature (°C), total annual rainfall, mean T min and its occurring months, mean T max and its occurring months, over the three areas with tiger bush. Area
Mean Annual Temperature
Total Annual rainfall
Mean T min
Month of mean T min
Mean T max
Month of mean T max
A
20–25 °C
200–500 mm
15–20 °C
Dec–Feb
25–30 °C
May–Aug
B
> 25 °C
50–400 mm
20–25 °C
Dec–Feb
25–30 °C
Apr–Sep
C
> 25 °C
100–400 mm
20–25 °C
Jul–Oct
25–30 °C
Dec–Jun
* datasets from WMO & Weatherbase
Table 7 Results of the chi-square test on the following 11 parameter association, considering each square kilometre as an occurrence. N° (according to table 6.1)
Parameter 1
Parameter 2
P-value
1
Landscape
Tiger bush
< 0.001
2
Landforms
Tiger bush
< 0.001
3
Geology
Tiger bush
< 0.001
4
Lithology
Tiger bush
< 0.001
5
Slope
Tiger bush
< 0.001
7
Surface Form
Tiger bush
< 0.001
8
Vegetation
Tiger bush
< 0.001
9
Soil Depth
Tiger bush
< 0.001
10
Soil Texture
Tiger bush
< 0.001
11
Parent Material
Tiger bush
< 0.001
12
FAO Soil Classification
Tiger bush
< 0.001
!ere is a highly significant statistical association between all the parameters of Table 7 (chi-square, p < 0.001 in every case). !e distribution of tiger bush over the most representative subtype of each parameter (i.e. the one with the highest percentage) appears not to be random.
5. Conclusions As a result of the present research a new map of the distribution of tiger bush in Somalia, at the scale of 1 : 100,000, has been achieved, and 5 different patterns of tiger bush have been mapped. A new area of tiger bush presence is outlined in the southern part of the country, along part of the Shabelle valley and on the rim of the Bur basement complex. A GIS based analysis of tiger bush distribution in relation to 18 parameters coming from previously published datasets (i.e. landscapes, lithology, soil, climate, etc.) has allowed quantification of the spatial relationships existing between tiger bush and its surrounding physical environment. !e majority of tiger bush is of the arc type. !is analysis, supported by the statistical test (chi-square) on the significance of the relationships, shows that tiger bush is (a) distributed on undulating plains and
preliminary results about mapping and geomorphological correlation
plateau, made in the majority of the cases of limestone and secondly on sandstone, (b) on slopes of 0 to 5 % and from 2 to 16 %, and (c) over loamy Haplic calcisols or Calcaric cambisols, with a depth between 50 and 100 cm, developed over colluvial/ residual parent materials. !e gentle slopes where tiger bush develop are oriented towards the east, east-southeast and west, and west-northwest. !e patterns exist where there is a mean rainfall varying between 50 and 500 mm per year, with a mean maximum temperature that varies between 20 and more than 25 °C. Finally, spatial analysis has provided a major contribution to the characterization of the tiger bush’s physical environment and this work also contributes to global mapping and the quantification of the interrelationships existing between different geo-ecological contexts. !e availability of an ever increasing number of datasets at medium to broad scale allows such analysis without the need for great finance.
Acknowledgements It would not have been possible to carry out this research without the help of many different persons. First of all the staff of the OUCE (Oxford University Centre for the Environment) and of the School of Geography and the Environment Library, gave the authors access to the so ware facilities and to all the references consulted. Big thanks are due to Filippo Dibari, for his general support during all the research and specifically for the help given in statistical analysis. Many thanks to Ronald Vargas Rojas for his useful revision of the manuscript. anks are also due to the FAO-Africover project for their data on Somalia and to Zoltan Balint, Laura Monaci, and Michele Downie, from the FAO-SWALIM Project for their collaborative support in the final stage of this work.
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