Envtl Earth Sci_artigo-480


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Envtl Earth Sci_artigo-480

  1. 1. Environ Earth SciDOI 10.1007/s12665-010-0480-z ORIGINAL ARTICLEGeo-environmental mapping using physiographic analysis:constraints on the evaluation of land instability and groundwaterpollution hazards in the Metropolitan District of Campinas, BrazilPaulo Cesar Fernandes-da-Silva • Ricardo Vedovello •Claudio Jose Ferreira • John Canning Cripps •Maria Jose Brollo • Amelia Joao FernandesReceived: 13 April 2009 / Accepted: 20 January 2010Ó Springer-Verlag 2010Abstract Geo-environmental terrain assessments and land instability and the vulnerability of groundwater toterritorial zoning are useful tools for the formulation and pollution hazards. The implementation incorporated proce-implementation of environmental management instruments dures for inferring the influences and potential implications(including policy-making, planning, and enforcement of of tectonic fractures and other discontinuities on groundstatutory regulations). They usually involve a set of proce- behaviour and local groundwater flow. Terrain attributesdures and techniques for delimitation, characterisation and such as degree of fracturing, bedrock lithology andclassification of terrain units. However, terrain assessments weathered materials were explored as indicators of groundand zoning exercises are often costly and time-consuming, properties. The paper also discusses constraints on- andparticularly when encompassing large areas, which in many limitations of- the approaches taken.cases prevent local agencies in developing countries fromproperly benefiting from such assessments. In the present Keywords Terrain units Á Satellite imagery Ápaper, a low-cost technique based on the analysis of texture Physiographic compartmentalisation Á Tectonic fracturing Áof satellite imagery was used for delimitation of terrain Inferential toolsunits. The delimited units were further analysed in two testareas situated in Southeast Brazil to provide estimates of Introduction Data about the physical environment (such as rock and soilP. C. Fernandes-da-Silva (&) Á R. Vedovello Á types, relief, vegetation and natural processes) are essentialC. J. Ferreira Á M. J. Brollo Á A. J. Fernandes to formulate and to implement successful strategies for ˜Geological Institute, Sao Paulo State Secretariat of Environment, environmental management. Such data underpin all policy- ˜Av. Miguel Stefano nr. 3900, Sao Paulo CEP 04301-903, Brazile-mail: paulo.fernandes@igeologico.sp.gov.br; making and planning instruments and enforcement regula-pfernandes_us@yahoo.co.uk tions which usually require geo-environmental terrainR. Vedovello assessment and territorial zoning in terms of advantages ande-mail: vedovello@igeologico.sp.gov.br constraints for development of different types (CulshawC. J. Ferreira et al. 1990; Zuquette et al. 2004). For regional planning ande-mail: cferreira@igeologico.sp.gov.br watershed management purposes, such assessments provideM. J. Brollo advice about the types of land use that would be acceptablee-mail: mjbrollo@igeologico.sp.gov.br in certain areas but should be precluded in others. Fur-A. J. Fernandes thermore, ranking of terrain units in terms of the likelihoode-mail: amelia@igeologico.sp.gov.br and consequences of land instability also enable the iden- tification, control and mitigation of hazards as well asJ. C. Cripps provide decision support to contingency actions and/or toDepartment of Civil and Structural Engineering, Universityof Sheffield, Mappin Street, Sheffield S1 3JD, UK engineering solutions (Cripps et al. 2002; Abella and Vane-mail: j.c.cripps@sheffield.ac.uk Westen 2008). 123
  2. 2. Environ Earth Sci According to Cendrero et al. (1979) and Bennett and This paper describes an application of the syntheticDoyle (1997) there are two main approaches to geo-envi- (integrated) approach to a geo-environmental terrainronmental terrain assessments and territorial zoning: (a) the assessment and territorial zoning exercise at a semi-regio-analytical or parametric approach; and (b) the synthetic nal scale. This is exemplified by a case study that exploresapproach, also termed integrated, landscape or physio- a low-cost technique comprising physiographic compart-graphic approach. The parametric approach deals with mentalisation based on the use of satellite imagery for theenvironmental features or components individually so that delimitation of terrain units. The resulting map is thenterrain units usually result from the intersection or carto- interpreted in terms of the potential for land instability andgraphic summation of several layers of information. Unit groundwater vulnerability in two test areas situated in thelimits do not necessarily correspond with ground features. ˜ Metropolitan District of Campinas (Sao Paulo State,In the synthetic approach, the form and spatial distribution Southeast Brazil, see Fig. 2). Key to the success of thisof ground features are analysed in an integrated manner so approach was the incorporation of procedures for inferringthat the land units or divisions correspond with landscape the presence and characteristics of geological structures,patterns that express interactions between environmental such as fractures and other discontinuities and the assess-components. ment of these in terms of the potential implications to Since the advent of airborne and orbital sensors, the ground stability and the flow of groundwater. A generalintegrated analysis is based in the first instance, on the description of the physiographic compartmentalisationinterpretation of images and air-photos. In this case, the technique and a discussion of the performance and limi-content and spatial boundaries of terrain units would tations of the approach are also provided.directly correspond with ground features. According tosome authors, such correlation and also the recurrence ofparticular landscape patterns gives rise to following The physiographic compartmentalisation techniqueadvantages: (1) facilitation of understanding by non-spe-cialists and planners (Davidson 1992; Fernandes da Silva Geo-environmental terrain assessments and territorialet al. 1997); and (2) providing of means of correlating zoning generally involve three main stages, as follows: (1)known and unknown areas, thus permitting ground condi- delimitation of terrain units; (2) characterisation of unitstions to be reasonably predicted (Finlayson 1984; Moore (e.g. in bio-geographical, engineering geological or geo-et al. 1993). Terrain units delineated using the physio- technical terms); and (3) evaluation and classification ofgraphic approach should hold a genetically linked assem- units.blage of components such as relief, rocks and soils, The first stage consists of dividing the territory into zonesindependent of their sizes. Their definition depends on with respect to a set of pre-determined physical and envi-climatic, tectonic and lithological criteria, as well as those ronmental characteristics and properties. Regions, zones orof form (Mitchell 1991). units are regarded as distinguishable entities depending upon Data collection, derivation from secondary data sources, their internal homogeneity or the internal interrelationshipsand integration of data into useful databases are time- of their parts. Some authors argue that such homogeneity isconsuming, costly and difficult tasks to be performed in subjective and small-scale homogeneous units may not exist.support of a particular project and/or agency function For instance, this has led to the use of fuzzy logic approach(Nedovic-Budic 2000). In addition, the complexity of GIS (e.g. Zhu et al. 2001; Zhu and Mackay 2001; Shi et al. 2004).methodology, lack of suitably trained staff and the scarce Although detailed and spatially continuous terrain informa-organizational resources have been blamed for the under- tion may be attainable through these methods, the requiredutilisation of GIS methods (Harris and Weiner 1998; digital data derivation and computing operations tend to beVernez-Moudon and Hubner 2000). These difficulties and complex, thus necessitating specialist hard- and softwarelimitations inhibit both local and regional authorities in that are not always readily available.developing countries (like Brazil) from properly benefiting The characterisation of terrain units consists offrom geo-environmental terrain assessment outputs in ascribing and surveying relevant properties and character-planning and environmental management instruments. istics of terrain components that are expected to affect theFrom another viewpoint, some authors such as Sahay and ground conditions relevant to the particular application. ˆWalsham (1996); Barton et al. (2002); Camara and Fonseca Such characterisation can be achieved either directly or(2007) propose that developing countries should ensure indirectly, for instance, by means of (a) ground observa-that options for using low-cost technology are properly tions and measurements, including in situ tests (e.g. boring,considered as a way to gain knowledge about the tech- sampling, infiltration tests etc.); (b) laboratory tests (e.g.nology itself and also in the creation of products that fit grain size, strength, porosity, permeability etc.); (c) infer-their specific needs. ences derived from existing correlations between relevant123
  3. 3. Environ Earth Sciparameters and other data such as those obtained from characteristics in satellite images (or air-photos) correspondprevious mapping, remote sensing, geophysical and geo- with specific associations of geo-environmental componentschemical records. (such as bedrock, topography and landforms, soils and The final stage consists of evaluating and classifying the covering materials) with a common tectonic history and landterrain units in a manner relevant to the purposes of the surface evolution. Such associations are thought to implyparticular application (e.g. regional planning, transporta- specific ground responses to engineering and other land-usetion, hazard mapping). This is based on the analysis and actions.interpretation of properties and characteristics of terrain— The interpretation procedure is a top-down process thatidentified as relevant—and their potential effects in terms starts with the whole landscape which is then subdividedof ground behaviour, particularly in response to human into land parcels. It is assumed that there is a correlationactivities. between image texture and terrain characteristics that are In order to reduce the fieldwork effort required for the expressed at different scales and levels of compartmental-delimitation of terrain units, consideration was given to an isation, generally associated with regions or areal domainsincreased reliance on remote sensing tools, particularly of decreasing size. The main outcome of this is a singlesatellite imagery. The advantages include (a) the genera- cartographic product consisting of comprehensive unitstion of new data in areas where existing data are sparse, delimited by fixed spatial boundaries (that correspond withdiscontinuous or non-existent, and (b) the economical ground features). These are referred to as physiographiccoverage of large areas, availability of a variety of spatial compartments or basic compartmentalisation units (BCUs),resolutions, relatively frequent and periodic updating of which according to Vedovello and Mattos (1998), are theimages (Schmidt and Glaesser 1998; Lillesand and Kiefer smallest units for analysis of geo-environmental compo-2000; Latifovic et al. 2005; Akiwumi and Butler 2008). nents at the chosen cartographic scale. In other words, there The physiographic compartmentalisation technique is a relationship between the BCUs and the scales of(Vedovello 1993, 2000) utilises the spatial information observation and representation, which is governed by thecontained in images and the principles of convergence of spatial resolution of the satellite image or air-photos beingevidence (see Sabins 1987) in a systematic deductive used for the analysis and interpretation.process of image interpretation. The technique evolved The tracing of limits of textural zones concentrates onfrom engineering applications of the synthetic land classi- the analysis of the spatial arrangement of natural align-fication approach (e.g. Grant 1968, 1974, 1975; TRRL ments of image textural elements, particularly groups of1978), by incorporating and advancing the logic and pro- contiguous pixels related to the drainage network and reliefcedures of geological-geomorphological photo-interpreta- architecture. Tonal properties are used to help with thetion (see Guy 1966; Howard 1967; Soares and Fiori 1976), identification and interpretation of linear features. Imagewhich were then converted to monoscopic imagery as interpretation may also be supported by external sourcesproposed by Beaumont and Beaven (1977); Verstappen such as topographic, geological and soil maps.(1977); Soares et al. (1981) and others. The procedures for the delimitation of units include Magnitude and variations of light and shade play a key assessment of spatial characteristics of textural zones torole in the image interpretation, with texture and respective check for internal homogeneity and the degree of similaritypatterns being determined by an interaction between the between zones, particularly their form (spatial distribution)shapes of surface features and the angle of incidence of and directionality of texture elements (degree of isotropy).light. In this sense, texture expresses the frequency of tonal Usually, ground checks are carried out to confirm or adjust(grey-level value) change within an image and arises due to the photo-interpreted boundaries of physiographic unitsthe distribution and aggregation of minor components (BCUs). Figure 1 shows examples taken from the Campi-(texture elements) that preserve their own characteristics nas study area presented in this paper, in which two BCUs(e.g. shape, size, tone) at a determined spatial resolution. are compared in terms of spatial organisation of texturalThese unitary elements may be too small to be discerned elements associated with drainage and relief features.individually on the image, but define a consistent spatial After delimitation, the BCUs are then utilised as aarrangement that can be described in terms of visual texture module for storage, processing and analysis of geo-envi-features (Tamura et al. 1978). Image interpretation aims at ronmental data for further land assessments. The organisa-identifying and delineating textural zones on images tion of data and information in relation to the BCU polygonsaccording to the properties described in Table 1, wherein in a geo-referenced databank allows optimised proceduresfeatures such as coarseness, roughness, regularity, and of query and production of derived maps. The analysis anddirection are taken into account. evaluation is undertaken up to the (fixed) spatial boundaries The key assumption proposed by Vedovello (1993, 2000) of the BCUs so that different parameters or attributes can beis that zones with relatively homogeneous textural used in the subsequent stages of analysis (characterisation 123
  4. 4. Environ Earth SciTable 1 Description of elements and properties used for recognition and delineation of distinctive textural zones on satellite imagery (Vedovello1993, 2000)Textural entities and properties DescriptionImage texture element The smallest continuous and uniform surface liable to be distinguishable in terms of shape and dimensions and likely to be repetitive throughout an image. Usual types of image texture elements taken for analysis include: segments of drainage or relief (e.g. crestlines, slope breaks) and grey tonesTexture density The quantity of textural elements occurring within an area on image. Texture density is defined as the inverse of the mean distance between texture elements. Although it reflects a quantitative property, textural density is frequently described in qualitative and relative terms such as high, moderate low etc. Size of texture elements combined with texture density determines features such as coarseness and roughnessTextural arrangement The form (ordered or not) by which textural elements occur and are spatially distributed on image. Texture elements of similar characteristics may be contiguous thus defining alignments or linear features on image. The spatial distribution may be repetitive and it is usually expressed by ‘patterns’ that tend to be recurrent (regularity). For example, forms defined by texture elements due to drainage expressed in rectangular, dendritic or radial patternsStructuring (degree of spatial The greater or lesser organisation underlying the spatial distribution of textural elements and defined by organisation) repetition of texture elements within a certain rule of placement. Such organisation is usually expressed in terms of regular or systematic spatial relations, such as length, angularity, asymmetry and especially prevailing orientations (tropy or directionality) Tropy reflects the anisotropic (existence of one, two or three preferred directions), or the isotropic (multi- directional or no predominant direction) character of textural features. Asymmetry refers to length and angularity of linear features (rows of contiguous texture elements) in relation to an axe or main feature identified on image. The degree of organisation can also be expressed by qualitative terms such as high, moderate, low or yet as well- or poorly definedStructuring order Complexity in the organisation of textural elements, mainly reflecting superposition of image structuring. For example, a regional directional trend of textural elements that can be extremely pervasive, distinctive and superimposed to other orientations also observed on imagery. Another example is given by drainage networks displaying different orders with reference to main stream lines and tributaries (first, second, third orders)Fig. 1 Examples of basiccompartmentalisation units(BCUs) taken from Test AreaT1 with similar codificationCRR: C crystalline basement,R granitic Gneiss, R largerolling hills with alignedcrestlines and rectilinear slopeprofile. Landsat TM5,composite image, Bands 3–4–5,greyscale. a Drainage lines;b relief lines; c frequencyhistograms for azimuthdirections of texture elementsassociated with drainage andrelief features. Fourth level ofcompartmentalisation of BCUsexpresses the predominantdrainage directions:CRR2 = ENE ? NW ? NE;CRR3 = NE ? NNE ? NWand relief line directions:CRR2 = NW ? NE;CRR3 = NNW ? NE in cfrequency histograms123
  5. 5. Environ Earth Sciand classification of units) while keeping their cartographic visual interpretation and vector format manual digitisingsignificance and cohesion as unitary entity, i.e. no changes with Erdas Imaging software.to the boundaries of existing polygons or generation of new The delimitation of units was based on image textureones are required (Tominaga et al. 2004). characteristics expressed by groups of contiguous pixels related to drainage and relief features. For this a minimum line segment length of 30 m (one pixel) was used. It shouldGeo-environmental terrain evaluation: a case study be noted that the dimensions of BCUs directly relate to the spatial resolution of the image and also to the visibility ofThe present study was carried out in two test areas, T1 and ground features, such as drainage and relief lineaments. InT2 (Fig. 2), located in the Metropolitan District of Cam- the present investigation, the smallest BCU in Area T1 waspinas (RMC), the State of Sao Paulo, Brazil, which 0.7 km2 (approx. 820 pixels) and the average area wasencompasses 19 municipalities and covers approximately 3.6 km2, whereas in Area T2 their areas were, respectively,1,800 km2. Area T1 (80 km2) comprises a rugged topo- 1.24 km2 (approx. 1,380 pixels) and 6.17 km2. Visualgraphy with small and large hills and ridges of significant image interpretation was supported by external ancillaryslope steepness, consisted mainly of Pre-Cambrian crys- data concerning bedrock lithology, structural geology,talline rocks (gneiss and granite). Area T2 (192 km2) con- topography and geomorphology.sists of Palaeozoic to Tertiary sedimentary and intrusive Depiction of natural linear features is dependent uponvolcanic rocks that form a flatter topography comprising grey-level values that are influenced by the gradient of landundulating and rolling hills together with Quaternary age surface and its position in relation to sunlight exposure.alluvial plain deposits. Drainage lines were frequently associated with dark pixel patches as follows: (a) enriched tonal contrast due toTerrain Compartmentalisation absorption of energy by surface water and strips of river- side vegetation in Band 3; (b) dark tonal contrast due toA Landsat 5 Thematic Mapper (TM) image (path 220, row high moisture content emphasised in Near-IR (Band 4) and076, captured on 12 September 1997, end of dry season) Mid-IR (Band 5); (c) patches of shading or relatively darkwas selected for this study. Factors influencing this choice tonal contrast as an expression of negative slope breaksincluded temporal, spectral, spatial, and synoptic charac- (decreasing slope steepness) in valleys and watercourses.teristics as well as good availability and lower cost than Relief lines were usually demarcated by subtle limitsother products. The date of image acquisition slightly between contrasting zones of lighting and shading on thepreceded recent major urban and industrial development in image that were defined by relatively bright ground slopingthe region. From the full scene two sub-sets of 250 9 313 towards the direction of sunlight. In areas of low vegetationand 375 9 500 pixels, corresponding to test areas T1 and density and soil exposure, lower moisture content tended toT2, respectively, were selected. The BCUs were delimited enhance these contrasts. In many cases, these featureson a geo-referenced composite sub-image—Band 3 (visible corresponded with ridge tops, crestlines and positive slopewavelength) ? Band 4 (Near-IR) ? Band 5 (Mid-IR)— breaks (increasing slope steepness), whose identificationfalse RGB colours at 30 m pixel resolution using on-screen was also facilitated by association with drainage heads.Fig. 2 Location map showingthe study region (MetropolitanDistrict of Campinas) in the ˜State of Sao Paulo, SoutheastBrazil, and the Test Areas T1and T2. Scale bar applies to themap of the Metropolitan Districtof Campinas 0 18 36 km 123
  6. 6. Environ Earth Sci The main characteristics considered for the delimitation Characterisation of unitsof BCUs included (a) density of texture elements related todrainage and relief lines, (b) spatial arrangement of Based on a minimum areal extent of 3 km2, accessibilitydrainage and relief lines in terms of form and degree of contiguity of units and the planned structural geologicalorganisation (direction, regularity and pattern), (c) length analysis, 13 BCUs in each test area were selected for fur-of lines and their angular relationships, (d) linearity of ther geo-environmental assessments in which both spatialmainstream channel and asymmetry of tributaries, (e) image characteristics and external data sources were con-density of interfluves, (f) hillside length, and (g) slope sidered. The areas were verified and complemented withforms. These characteristics were identified mainly on the ground checks.basis of image interpretation, but external ancillary data Inferences relating to environmental properties andwere also used to assist image interpretation for the iden- characteristics of geotechnical interest based on correla-tification of relief-related characteristics, such as slope tions of image properties from remotely sensed data wereforms and interfluve dimensions. particularly investigated. The principle postulated was that Figure 3 shows the basic compartmentalisation units image texture related to the properties/characteristics of the(BCUs) delineated for Test Areas T1 and T2, and the imaged target enables reasonable deductions about geo-respective drainage networks. As illustrated in Fig. 1, units technical-engineering attributes (Beaumont and Beavenare identified by three-letter codes and one numerical 1977; Beaumont 1985).character, corresponding, respectively, to (a) physiographic In view of the aims of the study to estimate suscepti-domain, (b) predominant bedrock lithology and geological bility of land to instability and the vulnerability ground-structure, (c) geomorphological setting including predom- water to pollution, as well as other factors such as scales ofinant landforms, and (d) specific characteristics such as soil observation and representation, data availability and deri-profile and erosional and aggradational features. Examples vation, the following attributes were primarily consideredof the codification of UBCs are provided in Table 2. A to be relevant and selected for the characterisation ofsummary of relationships between image texture charac- BCUs: (a) bedrock lithology, (b) tectonic discontinuitiesteristics, bedrock lithology and relief/landform system is (generically referred to as fracturing), (c) soil profilepresented in Table 3. (including thickness, texture and mineralogy), (d) slopeFig. 3 Drainage networks(a, b) and basic compart-mentalisation units (BCUs) inTest Areas T1 and T2 delineatedon a Landsat TM5 compositesub-image—bands 3, 4, 5,greyscale (c, d). Note greaterdensity, spatial organisation andangularity expressed bydrainage network of AreaT1 (crystalline rocks) incomparison with AreaT2 (predominantly sedimentaryrocks). UTM projection andcoordinates123
  7. 7. Environ Earth SciTable 2 Examples of codification of basic physiographic units (UBCs)UBC Code descriptionBAA1 Physiographic domain: B (sedimentary basin) Bedrock lithology: A (sandstone: medium to coarse grained, predominantly massif, quatzose) System of relief/landforms: A (wide undulating hills, convex to flat top, gentle to moderate slope) Specific characteristics: 1 (sandy-clayey soil grading to sandy-silty in depth, thickness 1 to 5 m, predominant uni-directional arrangement of drainage and relief lines)CLT1 Physiographic domain: C (crystalline basement) Bedrock lithology: L (laminated gneiss) System of relief/landforms: T (small rolling hills, sharp and narrow top, aligned crestlines, moderate slope) Specific characteristics: 1 (sandy to sandy-silty soils, thickness [4 m, concave hillside)Table 3 Relationships between second (bedrock lithology) and third (relief/landform systems) levels of physiographic compartmentalisationand image texture characteristics, particularly density and spatial organisation of texture elements associated with drainage and relief features Image texture characteristicsBedrock lithology (assigned code) Granites (S) and granitic-gneisses (R) Drainage and relief alignments that reflect structural geological lineaments at NW and N–S orientation. High-density (texture density related to) drainage forms ([3 km/km2) with directional anisotropy expressed by rectangular and oblique patterns Gneisses: banded (B, O), laminated (L), Moderate to high-density (2–3 km/km2) drainage forms: sub-dendritic, parallel, sub-parallel to schistose (N) angulated, tendency to bi- or tri-directional anisotropy (one direction mostly associated with metamorphic foliation) Sandstone: medium to coarse grained (A) Dendritic drainage forms, locally radial or angulated, low to moderate density (2 km/km2), and variable tropy (uni-bi, and tri-directional to isotropic) Mudstones (B), siltstones (G), Moderate to high (2–3 km/km2) density of drainage lineaments with sub-dendritic to angulated rythmites (B, G) and fine-grained forms, bi- or tri-directional anisotropic arrangements that grade into isotropic (sandy sandstones (C, F) constituency) Dolerites (intrusive volcanic rocks) (D) Lineaments associated with positive relief slope breaks of greater amplitude. Drainage forms tend to be isotropic and low to moderate (2 km/km2) density of drainage lines Aluvional deposits (no code) Smoother texture bounded by negative slope breaks in association with dense vegetation stripsRelief/landform system (assigned code) Wide undulating hills (A) Convex hillsides and flat tops characterised by relative scarcity of textural elements related to drainage. Subtle positive slope breaks. Gentle slopes Small undulating hills (P, M) Predominant concave hillsides and valleys identified by negative slope breaks, sharp and narrow ridges, aligned crestlines in some cases, gentle to moderate slope Large rolling hills (R) Variable and alternate concave and convex hillsides, mostly associated with positive slope breaks, sharp but wide ridges, aligned crestlines, steep slope Small rolling hills (T, C) Predominant concave hillsides and valleys identified by negative slope breaks, sharp and narrow ridges, aligned crestlines transverse to the main ridge top in some cases, moderate slopessteepness (as an expression of local topography), and (e) primary (inter-granular) permeability of the unsaturatedwater table depth. zone. Thus, this feature directly affects groundwater vul- nerability. In metamorphic and igneous rocks, which pre-Bedrock lithology dominate in Test Area T1, secondary permeability (due to discontinuities) would be more important in terms ofThe mineralogy, grain size and fabric of the bedrock and groundwater flow and it is also essential to consider therelated weathered materials, control properties such as weathered materials originating from such crystallineshear strength, pore water suction, infiltration capacity and rocks. In this sense, Fernandes (2003) suggests that twonatural attenuation of contaminants. According to Vrba and situations should be considered when estimating ground-Civita (1994), hydraulic accessibility to the saturated zone water vulnerability in crystalline rocks: (a) where weath-in sedimentary rocks and unconsolidated sediments, which ering cover is thick, the composition of the weatheredpredominate in Test Area T2, mainly depends on the materials will strongly influence vulnerability; and (b) 123
  8. 8. Environ Earth Sciwhere weathering cover is thin or absent, the vulnerability underpinned inferences about major and small-scalewill be conditioned by the occurrence and characteristics of structures, including joints and schistosity.the discontinuities within the rock mass. As demonstrated by Fernandes and Rudolph (2001) and Bedrock lithology is also liable to influence land insta- Fernandes da Silva et al. (2005), lineament analysis can bebility processes depending on the mineralogical composi- integrated with empirical models of tectonic history basedtion, fabric and inherent structures. The orientations, on outcrop scale palaeostress regime determinations tocharacteristics and spacings of rock mass discontinuities identify areas of greater density and interconnectivity ofare particularly important in this regard (Hudec 1998). fractures as well as greater probability of open fractures. In In the present study, the bedrock types were grouped addition, it is possible to deduce angular relationshipsaccording to their fresh (unweathered) state as well as between rock structures (strike and dip) and between thesetaking account of any saprolitic and other altered materials and hill slope directions.where present. Crystalline rocks were grouped as follows: The following assumptions were made in order toGr—granites (mostly coarse-grained, massive or foliated); characterise fracturing in the rock or saprolitic soil mass:Gngr—granitic gneisses (mostly fine-grained, foliated); (a) Variations of density and connectivity of fracturesB—banded gneisses; X—schistose gneisses and shear zone could be mapped through lineament analysis by directmylonites; Bx—mixed gneisses (including both composi- correlation, respectively, with density and intersectiontional banding and schistosity); and D—dolerites. Sedi- of lineaments on images, because in the study areamentary rocks were grouped into Iam—sandstones most of the fractures were vertical or sub-vertical so(medium to coarse grained, mostly massive); Iaf—sand- they appeared as rectilinear traces at the surface.stones (fine grained, mostly stratified); IDR—mudstones (b) Late tectonic events (Cenozoic) control the aperturewith pebbles and laminated rhythmites; FRC—intercalated of fractures and according to Fernandes and Amaralsandstones, siltstones, claystones, and mudstones of the (2002), in most cases, a particular tectonic event givesweakly consolidated Tertiary age Rio Claro formation. rise to a generally pervading stress field which Clay content and its variation through the weathering controls the orientation and character of fractures inprofile have a particularly significant effect on groundwater a localised area. Those generated by extensionalvulnerability and erosional processes (Aller et al. 1987; tectonic stress are of particular interest as they usuallyHill and Rosenbaum 1998). In this regard, lithological display greater apertures. For instance, water flowgroups B, X and Bx give rise to predominantly clayey tends to be much faster in the wider aperture fracturesweathered materials that are likely to provide greater as gravity forces would prevail over capillarity forcesattenuation capacity and reduced hydraulic accessibility to and soil-matrix hydraulic conductivity in rainy epi-the saturated zone. On the other hand, groups Gr and Gngr sodes and nearly saturated conditions (Wang andwould produce sandy materials and greater hydraulic Narasimhan 1993).accessibility to the saturated zone. The presence of schis-tosity and foliation discontinuities within the rock and Lineaments extracted from images were cross-referencedsaprolitic materials would tend to cause slope failure and with field (structural-geological) measurements gathered inlandsliding hazards, depending on the orientation of those the present study and also available from Fernandes (1997).features with respect to the direction of slopes and also on Density of lineament (km/km2) and lineament intersectionsthe groundwater conditions. (number/km2) were computed automatically using a com- Data on bedrock lithology were derived from existing puter script written in MapBasicÒ in a MapInfo packagegeological maps which were cross-referenced with image and then cross-referenced with visual inspection andtextural characteristics including density of aligned textural manual counting to check the accuracy of the automatedelements related to drainage and relief in particular (see method.Table 3). Non-parametric statistical tests (see Fernandes da Silva et al. 2005; Fernandes da Silva and Cripps 2008) wereTectonic discontinuities performed in combination with visual analysis of trends of lineaments on rose diagrams (see Fernandes and RudolphGeological structures such as faults and joints in the rock 2001; Fernandes and Amaral 2002) to identify the tectonicmass, together with their relict structures in saprolitic structures associated with specific tectonic events in eachsoils, exert significant influences on shear strength and basic compartmentalisation unit (BCU). Greater probabil-hydraulic properties of geomaterials (Aydin 2002; Pine ity of occurrence (and frequency) of open fractures wasand Harrison 2003). In the present study, analysis of deduced from BCUs where extensional stress regimes werelineaments extracted from satellite images and knowledge considered to prevail due to the effect of tectonic event E3-about the regional tectonic evolution of the area (Table 4) NW (see Table 4).123
  9. 9. Environ Earth SciTable 4 Cenozoic tectonic evolution of the region of Campinas according to Fernandes and Amaral (2002)Age Principal palaeostress directions Shear fracture Extensional fracture Tectonic (plan view) orientations orientations eventQuaternary σ1 N20–30W and N50–60E N10–30E E5-NNE σ3 σ1 N30–50W and N30–50E NS E4-NS σ3 σ1 WNW and NNW–NS N30–60 W E3-NW σ3Neogene σ3 N45–65W and N45–65E EW E2-EW σ1Cretaceous to paleogene σ1 EW-ENE and NNE-NS NE E1-NE σ3 Estimates of the potential magnitude of fracturing were drainage conditions. In this regard slope steepness is aderived from qualitative scores given according to the meaningful and measurable indicator. Similarly, waterfollowing attributes (Table 5): (a) lineament density (per table depth is also controlled by the local topography.km2); (b) lineament intersections (per km2); and (c) pre- Hence, the assessment of potential for land instability anddominant tectonic event in each BCU. Such scores were enhanced groundwater vulnerability were based upon soilassigned in relation to statistical mean values determined profile, slope steepness and water table depth, either solelyfor each attribute except for the relevant predominant or in combination.tectonic event. In this case, maximum score (A) was For instance, infiltration capacity is a function of slopeassigned to tectonic event E3-NW and minimum score (B) steepness and inter-granular (primary) permeability of theto any other event including E4-NS (also extensional). uppermost layer of the unsaturated zone (Rubin andClasses of fracturing were derived from the relative pro- Steinhardt 1963, quoted by Fernandes 2003). As observedportion of these qualitative scores as follows: Class 1: three by Thornton et al. (2001), contaminants are mostly atten-scores ‘‘B’’; Class 2: one score ‘‘A’’; Class 3: two or three uated by processes of biodegradation and adsorption thatscores ‘‘A’’. These classes were designed to express depend on the mineralogical composition, texture andincreasing magnitude of fracturing and therefore greater thickness of the unsaturated zone materials.potential influence on ground behaviour. For the present investigation, data on thickness and texture of soil profiles were assembled to express theSoil profile, slope steepness and water table depth mineralogy, grain size, structure, strength and density/ degree of compaction of generic soil types. Soil horizonsThe development of a particular thickness and type of were characterised using a geotechnical approach as sap-tropical soil profile depends not only upon the parental rolite, residual, superficial and gravity-transported hori-materials present but also upon local topography and zons. Primary data were derived from existing soil mapsTable 5 Qualitative scores attributed to the parameters (density of lineaments, density of lineament intersections, predominant tectonic event)taken for derivation of classes of fracturingParameter Density of lineaments (km/km2) Density of lineament intersections (km/km2) Predominant tectonic event a a b bParameter value [3.90 3.90 [2.99 2.99 E3-NW E4-NS UndefinedScore A B A B A B Ba Range of average values of density of fracturing for BCUs in Test Areas T1 and T2: from 1.26 and 7.97 km/km2b Range of average values of density of lineament intersections for BCUs in Test Areas T1 and T2: from 0.06 to 10.97 intersections per km2 123
  10. 10. Environ Earth Scisupplemented with field observations for representative soil classification of units as this was consistent with relativelyprofiles in each BCU. Soil profile data were stored as a coarse scale of the cartographic maps (1:50,000), and theBCU attribute table using the MapInfo package. amount of data available. Thirteen representative soil weathering profiles, fromsandy to clayey, were identified and three classes of soil Evaluation and classification of unitsthickness were defined as follows: (a) 2 m, (b) 2–5 m;and (c) [5 m. These classes were designed to account for Three steps were required for the evaluation and classifi-the different impacts of soil thickness on hydraulic acces- cation of units: (a) definition of classes to express thesibility to the saturated zone as well as to the potential estimated magnitude of the parameter being analysed; (b)impacts of construction work. definition of classification rules depending on the purposes Average slope steepnesses were derived both manually of the study; and (c) evaluation and final cartography,and semi-automatically for each BCU. The manual pro- including the application of classification rules and analysiscedure involved measurements from existing printed of units for presentation on maps or other forms of output.topographic 1:50,000 scale maps. The freeware GIS and First, four classes each of groundwater vulnerability and ˆimage processing package SPRING (Camara et al. 1996; of susceptibility to land instability were designated as veryINPE 2009) was used for the semi-automated methods. The high, high, moderate and low. Attribute or ‘‘synthesis’’procedure included (a) digitising of sub-sets of 20-m con- tables were constructed (in GIS MapInfo package) specif-tour lines from the existing paper record 1:50,000 topo- ically for these purposes. These contained data on thegraphic maps (as no digital maps were available); (b) selected attributes for each BCU, which were allocated inderivation of heights from 50 9 50-m square numerical fields or columns as follows (see Table 6a, b): (a) BCU:grids obtained by interpolation from 20-m contour lines. unit code; (b) G_LITO: grouped bedrock lithology; (c)Generation of numerical grids was performed using a built- CLAS_FRAT: classes of fracturing; (d) TYPE_SOIL:in weighted mean interpolator based on quadrants and predominant soil type considering the whole weatheredrestriction of repeated elevation values. Overlaying oper- profile; (e) THICK_SOIL: average thickness of the wholeations and use of a computer routine written in LEGALÒ profile; (f) NA: average water table depth; and (g)(Spatial Language for Geo-processing Algebra) to perform CLAS_DECLIV: class of slope steepness (declivity).neighbourhood operations over the numerical grids pro- Qualitative and semi-quantitative rules of classificationvided average slope steepness values for each polygon. The were devised from a mixture of empirical knowledge andfollowing slope steepness classes were used: Low—less statistical approaches and then applied to each BCU. Thethan 5°; Medium—between 5° and 10°; High—between classification tool was a spreadsheet-based model that used10° and 15°; Very high—greater than 15°. nominal, interval and numerical average values as assigned Tonal contrast in Near-IR (Band 4) and Mid-IR (Band 5) in the synthesis attribute tables, in a two-step procedure towas used to indicate the presence of water in the sub-sur- produce the required estimates. In the first step, eachface, particularly in the unsaturated zone. However, such selected attribute was analysed and grouped into threeproxy information was insufficient for use in engineering categories shown in Tables 7 and 8, as follows: high (A),land assessments. Therefore, data on water table depth from moderate (M), and low (B) depending upon their potentialexisting borehole and well records were also used and cross- influence on groundwater vulnerability and land instabilityreferenced with image interpretation. Data on hydrostatic processes. In the second step, all attributes were considereddepth from borehole and well records were plotted on the as having the same relative influence and final classifica-digitised topographic maps to allow derivation by interpo- tion for each BCU was the sum of the scores (either A, Mlation and extrapolation where water table depth contours or B) respective to each attribute considered. The possiblewere assumed to be approximately parallel to the topo- combinations of these are illustrated in Table 9.graphic contours. However, such derivation approach led to As discussed later in the paper, limitations for derivinginaccuracies such as major variations of hydrostatic level in information on soil thickness and water table depth as wellsimilar topographic situations, and in order to reduce them, as to make such information compatible to BCUs preventedimage interpretation and statistical parameters (median and the incorporation of all selected attributes into the classifi-standard deviation) were combined to determine the trends cation scheme. Therefore, the evaluation/classification ofin hydrostatic depth in top, hillside and valley situations. By units was based upon bedrock lithology, tectonic disconti-this means contour lines for 5, 10, and 20 m depth were nuities (fracturing), soil type and slope steepness (declivity).traced with approximately 80% of confidence, where the The classification of units was performed either manu-confidence level was determined by validation against the ally or semi-automatically through GIS-based operations.original data. For convenience, the 10-m contour line was The latter involved logical spatial operations to set attri-then adopted as a criterion in further evaluation and butes into categories high (A), moderate (M) and low (B)123
  11. 11. Environ Earth SciTable 6 Summary dataUBC GROUP_ LITO CLAS_FRAT TYPE_SOIL THICK_SOIL N_A CLAS_DECLIV(a) Test Area T1 CSA1 Gr 2 Sandy [6.5 m 10, [10 Low CLC1 X 3 No information No information [10 to 10 Medium CRA1 Gr 3 Sandy [6.5 m [10 to 10 Medium CNC2 X, Bx 3 Sandy to sandy-silty [4.0 m 10, [10 Medium CRR3 Bx/GnGr 3 Sandy grading to clayey in depth [3.5 m [10 to 10 Very high CNC1 B, X 3 Clayey to sandy in depth [1.0 m [10 to 10 Medium BAC1 IAM, Gr/X 1 Sandy No information 10, [10 Medium CRR2 GnGr/B 3 No information No information [10 to 10 Very high CRR5 GnGr/B, Bx 3 Sandy-clayey grading to clayey- 5–10 m [10, 10 High sandy or sandy-silty in depth; occurrence of detached blocks COC3 Bx, B 3 Sandy 3.5 m [10, 10 Medium/high CSR3 Gr, Bx 3 Occurrence of detached blocks 1–5 m 10, [10 High CLR3 X, Bx/GnGr 3 No information No information 10, [10 High CLT1 B, X, Bx/GnGr 3 Sandy to sandy-silty 4.0 m 10, [10 Medium(b) Test Area T2 BAA1 IAM, IAF 1 Sandy-clayey grading sandy-silty 1–5 m [10, 10 Low/medium in depth BBP2 IDR, IAF, D 3 Sandy-silty grading to sandy- 1–5 m 10, [10 Medium clayey in depth; medium to low compacity BAA2 IAF, IAM 1 Clayey-sandy 1–5 m [10 to 10 Medium BAP1 IAM, D 2 Sandy to sandy-silty grading to [2 m [10, 10 Low/medium silty-sandy in depth BBM3 IDR, FRC, D 1 Sandy-clayey; blocky; moderately [2 m 10, [10 Low compact BCA1 IAF 1 Clayey-sandy grading to sandy- [1.8 m 10 to [10 Medium silty in depth; blocky BGA1 (1) FRC 1 Sandy-clayey grading to sandy- [2 m [10, 10 Low silty and clayey-sandy in depth BBP7 IDR, IAF, D 3 Sandy-clayey to sandy-silty [2 m 10 to [10 Low/medium BCP2 FRC, D 2 Sandy to sandy-silty; massif 5–10 m [10 Low BFA1 FRC, IAF 1 Sandy-clayey; friable; granular [2 m [10, 10 Low BGA1 (2) FRC, IAF 1 Sandy-clayey grading to sandy- [2 m [10, 10 Low silty and clayey-sandy in depth BDA2 D, IAF 2 Clayey-sandy No information 10, [10 Low BDA1 D, IAF 1 Clayey-sandy a clayey No information 10, [10 LowBCU basic compartmentalisation unit code, G_LITO grouped bedrock lithology, CLAS_FRAT class of fracturing, TYPE_SOIL predominant soiltype, THICK_SOIL average soil thickness, NA average water table depth, CLAS_DECLIV class of slope steepnesswith mathematical (summation) to produce the final Relatively greater slope steepness and fracturing as wellestimates. as predominant sandy soils in Test Area T1 were associated The outcomes presented here were achieved manually with a greater number of BCUs classified as to high andusing GIS to display and manipulate results. Tables 10 and very high susceptibility to land instability processes (12 out11 show the estimated susceptibility to land instability of 13) in comparison with Test Area T2 (just 1 out of 13).processes and groundwater vulnerability in the two test On the other hand, by reducing rates of infiltration, greaterareas with each attribute considered individually and slope steepness may lower the impact of fracturing onsummed for all the attributes. Figures 4 and 5 show overall groundwater vulnerability, particularly in crystalline andclassifications in spatial map format. less weathered rocks, which predominate in Area T1. 123
  12. 12. Environ Earth SciTable 7 Attributes used for evaluation/classification of units (BCUs) according to their potential influence (high, moderate, low) on ground-water vulnerability to pollution hazardsAttributes High (A) Moderate (M) Low (B)Bedrock IAM, Gr/Xa (coarse-grained Gr (granites) B (banded gneisses) lithology sandstones ? mix of granites GnGr/B, X, Bxa (mix of granitic and banded X (laminated to schistose and schists) gneisses ? laminated to schistose gneisses ? banded gneisses) IAM (coarse-grained mylonitic gneisses) Bx (banded mylonitic gneisses) sandstones) B, X, Bx/Gngra (banded gneisses ? schistose gneisses ? mix IDR (mudstones with pebbles of banded mylonitic gneisses and granitic-gneisses) and rythmites) FRC (Rio Claro Formation—mix of sandy mudstones, D (dolerites) siltstones, muddy sandstones and rythmites) IAF (fine-grained sandstones)Fracturing 3 2 1Soil type Sandy Sandy-clayey Clayey Sandy-silty Sandy- silty to sandy-clayey Clayey-sandy Sandy-clayey grading to sandy- Sandy grading to clayey silty Sandy-clayey grading to clayey Sandy to sandy-silty Clayey-sandy grading to sandy-clayey Clayey-sandy grading to Clayey grading to sandy sandy-siltySlope Low Low to medium High steepness Medium Very high Medium to higha Groups separated by forward slash comprise an undistinguished mixture of bedrock lithologies. The ‘‘comma’’ sign indicates the occurrence ofmore than one group of bedrock lithology listed in decreasing order according to their occurrence in terms of areal distributionTable 8 Attributes used for evaluation/classification of units (BCUs) according to their potential influence (high, moderate, low) on suscep-tibility to land instability processesAttributes High (A) Moderate (M) Low (B)Bedrock lithology Iam, Gr/Xa (coarse-grained sandstones ? mix of granites and IAF (fine-grained IDR (mudstones with schists) sandstones) pebbles and rythmites) IAm (coarse-grained sandstones) B (banded gneisses) D (dolerites) FRC (Rio Claro Formation—mix of sandy mudstones, Bx (banded mylonitic siltstones, muddy sandstones and rythmites) gneisses) X (laminated to schistose gneisses) Gr (Granites) GnGr/B, X, Bxa (mix of granitic and banded gneisses ? laminated to schistose gneisses ? banded mylonitic gneisses) B, X, Bx/Gngra (banded gneisses ? schistose gneisses ? mix of banded mylonitic gneisses and granitic-gneisses)Fracturing 3 2 1Soil type Sandy Sandy-clayey Clayey Silty-sandy Sandy grading to clayey Clayey-sandy Sandy-clayey grading to silty-sandy Clayey-sandy grading to Clayey-sandy grading to Sandy to silty-sandy sandy-silty sandy-clayey Sandy-silty to sandy-clayey Clayey grading to sandy Sandy-clayey grading to clayeySlope steepness High Medium Low Very high Low to medium Medium to higha Groups separated by forward slash comprise an undistinguished mixture of bedrock lithologies. The ‘‘comma’’ sign indicates the occurrence ofmore than one group of bedrock lithology listed on decreasing order according to their occurrence in terms of areal distribution123
  13. 13. Environ Earth Sci In Test Area T2, high and moderate groundwater vul- is less than that in the coarse- and medium-grainednerability (6 out of 13 BCUs) was associated with sand- sandstones.stone-dominated bedrock lithology, sandy soils and lowslope steepness. In addition, BCUs with greater frequencyand connectivity of fractures were classified as having high Discussionand moderate groundwater vulnerability despite consistingof clayey bedrock lithologies such as mudstones and As described in previous sections, a physiographic approachrhythmites in which inter-granular primary permeability provided basic compartmentalisation units (BCUs) which were experimentally used for terrain assessments. The opportunity is taken here to discuss the advantages andTable 9 Possible combinations of scores ‘‘A’’ (high), ‘‘M’’ (moder- limitations of the approach taken, particularly how theseate), and ‘‘B’’ (low) respective to the four attributes (bedrock lithol-ogy, fracturing, soil type and slope steepness) used for evaluation/ have affected the outcomes, and what can be done toclassification of units (BCUs) and evaluation classes resulting from enhance the results or to overcome difficulties.these combinations The analysis of fracturing proved that there is goodCombinations of scores Evaluation association between physiographic compartments and classes homogeneous tectonic domains for which the density and directional trends were relatively uniform, as proposed byAAAA Very high Fernandes and Amaral (2002). In most BCUs it was pos-AAAM, AAAB, AAMM High sible to determine particularly significant tectonic events,AAMB, AABB, AMMM, AMMB, MMMM Medium for example those of an extensional nature (see E3 and E4AMBB, ABBB, MMMB, MMBB, MBBB, BBBB Low in Table 4). In addition, non-parametric statistical tests andTable 10 Partial susceptibility Test Area UBC Attributes liable to influence susceptibility Susceptibility classassociated with each individualattributes and overall Lithology Fracturing Soil type Declivitysusceptibility to land instabilityprocesses resulting from the T1 CSA1 A M A B Highsummation of all influential CLC1 A A Ma M Highfactors (attributes) CSA2 A A A M High CNC2 A A A M High CRR3 A M M A High CNC1 M A M M Moderate BAC1 A B A M High CRR2 A A Ma B High CRR5 A A M A High COC3 M A A A High a CSR3 A A A A Very high CLR3 A A Aa A Very high CLT1 A A A M Alta High T2 BDA 1 B B B B Low BDA 2 B M B B Low BAA 1 A B A B Moderate BBP 2 B A A M High BAA 2 A B B M Moderate BAP 1 A M A B Moderate BBM 3 B B M B Low BCA 1 M B M M Moderate BGA 1 A B M B Moderate BBP 7 B A A B ModerateA, high; M, medium; and B, low BCP 2 A M A B Moderatea Soil type deduced according BFA 1 A B M B Moderateto predominant bedrock BGA 1 A B A B Moderatelithology with BCU 123
  14. 14. Environ Earth SciTable 11 Partial vulnerability Test Area UBC Attributes liable to influence vulnerability Vulnerability classassociated with each individualattribute and overall Lithology Fracturing Soil type Declivitygroundwater vulnerability topollution hazards resulting from T1 CSA1 M M A A Highthe summation of all influential CLC1 B A Ba M Lowfactors CSA2 M A A M High CNC2 B A A M Moderate CRR3 M M M M Moderate CNC1 B A M M Moderate BAC1 A B A M Moderate CRR2 M A Ma B Moderate CRR5 M A M B Moderate COC3 B A A M Moderate CSR3 M A Ma B Moderate CLR3 M A Ma B Moderate CLT1 M A A M High T2 BDA 1 B B B A Low BDA 2 B M B A Low BAA 1 A B A M Moderate BBP 2 B A M M Moderate BAA 2 A B B M Low BAP 1 A M A M High BBM 3 A B M A Moderate BCA 1 M B A M Moderate BGA 1 M B A A Moderate BBP 7 M A A M HighA, high; M, medium; and B, low BCP 2 M M A A Higha Soil type deduced according BFA 1 M B M A Moderateto predominant bedrock BGA 1 M B A A Moderatelithology with BCUvisual inspection of rose diagrams provided similar reas- allow derivation of 3D relationships. The main aspects tosuringly consistent inferences. This association between be considered include (a) angular and cut-crossing rela-tectonic domains and physiographic compartments would tionships between different types and sets of structuresprobably express the influence of the Cenozoic tectonics (planes of fractures and other discontinuities); and (b)over the arrangement and structuring of drainage and relief spatial relationships between structures and natural slopestextural elements on images. Although some variability did (thus taking steepness into account). Consideration of theseexist, the results demonstrated considerable regularity and relationships should enhance the evaluation of BCUs andpersistence of spatial relations held by tectonic structures convey key information to local scale analysis.across the test areas. These aspects were fully corroborated A general issue of relevance is that monoscopic satelliteby good matching between predominant orientations of images are bi-dimensional representations of land surfaceinferred structures and palaeostress regimes as indicated by whilst the intended geo-environmental assessments relatea regional empirical tectonic model and field observations. to both surface and sub-surface aspects. Thus spatial Density and interconnectivity of fractures were the key information rather than spectral information needs to beattributes in the characterisation and evaluation of BCUs in analysed. On the other hand, data on determined attributesterms of engineering geological and hydrogeological had to be derived from external sources using imagery as aapplications. This empirical tectonic modelling enabled subsidiary tool. Accordingly, textural zones with relativelyboth major structures and also small-scale fractures to be high internal homogeneity and fixed spatial boundariesconsidered in the analysis where the latter were incorpo- which were observed on images may require practicalrated in the interpretation and evaluation procedures. adaptations to be translated into conceptual classes such asAdditionally, it is suggested that further interpretations comprehensive physiographic units. In this experimentalsupported by the use of empirical tectonic models would study such adjustments were incorporated in the later123
  15. 15. Environ Earth SciFig. 4 Maps of susceptibility to land instability processes. Test Areas T1 and T2. UTM projection and coordinatesstages of characterisation and evaluation/classification of profile (thickness), which precluded proper incorporationunits but as explained below, this was not universal. of these attributes in the evaluation/classification of units. For the sake of the present implementation, some terrain Data on water table depth were derived through anattributes such as bedrock lithology and related weathered experimental approach that combined hydrostatic depthmaterials, degree of fracturing and slope steepness were obtained from borehole and well records with interpolationselected and taken as proxies for properties and processes and extrapolation of values following topographic contourincluding shear strength, permeability, natural attenuation lines. This was manually implemented as semi-automatedcapacity, infiltration rates and hydraulic accessibility to procedures based only on spatial data analysis would notsaturated zone. It was assumed that the selected terrain allow direct correlation between interpolated values ofattributes would exert some control over the properties and water table depth and surface contour lines. However, it wasprocesses. Data on such attributes were derived qualita- found that the manual derivation of data led to unreliabletively and semi-quantitatively by a combination of means estimates of water table depth, thus resulting in consider-that included image interpretation, input from existing data able variations at similar topographic conditions. Theseand field observations. Shortcomings and inaccuracies may variations may have arisen because the primary boreholestem from this process of derivation. data were affected by (a) groundwater exploitation in dif- For instance, in a number of cases, BCUs comprised ferent media and at varied piezometric depths in a sameconsiderable portions of two or more bedrock lithologies in well (e.g. weathered materials at shallow sub-surface andwhich case priority was given to the lithology liable to fractures in fresh rock at depth); (b) heterogeneousresult in greater likelihood of hazard. However, adoption of hydraulic conductivity of the aquifer and of the unsaturatedsuch criterion may be biased and lead to a greater number zone. These shortcomings suggest that derivation of data onof BCUs being classified as having higher vulnerability or water table depth from external sources may require moresusceptibility. specific data, particularly on shallow sub-surface layers. Major difficulties found during the characterisation of Such data could possibly be derived from open pit wellunits included the estimation of water table depth and soil measurements, which appears to be more compatible with 123
  16. 16. Environ Earth SciFig. 5 Maps of groundwater vulnerability to pollution. Test Areas T1 and T2. UTM projection and coordinatesthe characterisation of the unsaturated zone in the shallow depth’’) appeared to produce more accurate results, whichsub-surface and with the physiographic approach itself were then used in the classification process. Inaccuracies(based on land surface features on images). Data from open observed in the semi-automatic procedure possibly stem-pit well measurements could be then cross-referenced with med from the averaging process with respect to polygons.remotely sensed data and topographic maps before extrap- The calculated mean value was meant to be representativeolation of values following topographic contour lines. of slope steepness for the whole BCU. However, slope Another issue to be considered is data on soil profile steepness was observed to range considerably in somethickness. In the study these were based on field observa- BCUs, which would affect the interpolated numerical grids.tions and they were considered to be insufficient for the For instance, in 80% of the area of a BCU slope steepnessintended analysis. In general, difficulties with the charac- ranged between 8° and 10° whilst in 15% of area rangedterisation of soil profiles in terms of thickness and texture from 15° to 18°, and in 5% of area it ranged between 24°stem from limited knowledge about the processes that and 27°. The expected representative value would be thecontrol landscape evolution and soil formation and the 8°–10° range. Nonetheless, since the semi-automatic cal-ways by which these processes influence image texture. culation took a much greater number of interpolated valuesImproved understanding of these issues would allow than the manual procedure, the resulting mean value maysuperior correlations and extrapolation of values to be be unnecessarily influenced by outlying values. Furtherachieved. Therefore, future work should investigate the investigations into semi-automatic derivation of slopedistribution and the characteristics of soil profiles and steepness data would need to look into ways of restrictingpotential correlations of these with image texture due to the range of variation that would be acceptable and con-relief features, with particular reference to morphometric sidered for calculation of a BCU mean value. For instance,aspects such as density and amplitude of interfluves (or the calculation procedure could incorporate a priori proba-ridges) and length of natural slopes. bilities by weighting the resulting value according to the The manual procedure for derivation of data on slope proportion of the area of a BCU on which slope steepnesssteepness (see ‘‘Soil profile, slope steepness and water table intervals were derived.123
  17. 17. Environ Earth Sci In the stage of evaluation/classification of units, all relationships and enable interpretations the angular rela-attributes were given equal weight, although the relative tionships between rock structures (strike and dip) and hillinfluence of each attribute is not known. The main uncer- slopes to be made. This would greatly enhance the poten-tainties would be the influence of degree of fracturing tial of the method for engineering applications at a local(Class 3) on permeability, and the effects of low-slope scale. There is also potential for the development ofsteepness and sandy superficial soil on aquifer recharge. automated procedures. For example, for the delimitation ofFor instance, in Test Area T1 (see Fig. 4), the high number terrain units based on image classification of spatial prop-of units (12 out of 13) classified as high to very high erties such as detection of groups of contiguous pixels andpotential for land instability appears to be strongly influ- recognition of line patterns based on length, direction andenced by steeper slope gradients. Further investigations are angular relations between groups of contiguous pixels.to consider different weights for each attribute with checks Future and specific investigations should include revi-on the influence of these on the final classification results. sion of procedures of data derivation from external sources other than imagery, such as water table depth. Further implementation of the physiographic compartmentalisationConclusions approach for engineering and geo-environmental terrain assessments are required to evaluate its application in otherIn the present study, remote sensing techniques were used geological and geomorphological settings and differentto delimit terrain units and to derive geo-environmental scales of observation, analysis and graphic representation.data. Data from external sources, including water well logsand records, existing thematic maps and field studies were Acknowledgments The authors would like to thank Dr. Mara A. Iritani and Dr. Lidia K. Tominaga for their contribution to data der-also used. The delimited units were further interpreted in ivation and interpretation, the UK Foreign Commonwealth Officeterms of potential to land instability and vulnerability to (FCO) and the Brazilian National Council for Scientific and Tech-groundwater contamination at a semi-regional scale of nological Development (CNPq) for their financial support, and the1:50,000. anonymous reviewers for their helpful advice. The successful use of low-cost techniques based onsatellite image interpretation, non-commercial software Referencespackage (SPRING) and manual data processing proceduresjustified this approach and a wide range of difficulties and Abella EAC, Van Westen CJ (2008) Qualitative landslide suscepti-limitations liable to be experienced by local and regional bility assessment by multicriteria analysis: a case study from Sanagencies in developing countries were addressed. Particular ´ Antonio del Sur, Guantanamo, Cuba. 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