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e analysis. The graphical user interface of TecDEM provides several options:

s, st

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str

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gely inundersscalestical deproceselief, elmet alhenatentatioKurz e

n.

continuous or discontinuous terrain partition schemes. Drainage

Contents lists available at ScienceDirect

journal homepage: www.el

Computers & G

Computers & Geosciences 37 (2011) 250260data ow diagram in Fig. 1(a).gloaguen@geo.tu-freiberg.de (R. Gloaguen).network preparation consists of dividing a DEM into regionsdepending on shared characteristics (Arge et al., 2003; Kiss,2004; Lindsay, 2005). Here, we divide it into three subsectionsas outlined below. An overview of our approach can be found as a

0098-3004/$ - see front matter & 2010 Elsevier Ltd. All rights reserved.

doi:10.1016/j.cageo.2010.06.008

$Code available from server at http://www.rsg.tu-freiberg.de or at

http://www.iamg.org/CGEditor/index.htm. Corresponding author. Tel.: +49 3731 44 59 29.E-mail addresses: geoquaidian@gmail.com (F. Shahzad),Schoenbohmet al., 2004). This relationship canbe exploited to extractinformation regarding lithologyor tectonicmovementsusingbedrock

A DEM is a representation of topography as a nite set of points.Miliaresis (2001, 2008) provides an overview the various eitherto generate stream proles, determine ow directions, delineatewatersheds, select knickpoints, and calculate Hack indexes.

The gradient of bedrock channels is intimately linked to theunderlying geology and local tectonics (Kirby and Whipple, 2001;

and error procedure is used for drainage network delineatio

2.1. Drainage network preprocessingDifferent software tools exist for a wide range of tectonicgeomorphological analyses, TecDEM is the rst attempt to providea single software system that can executemost of the commonlyusedanalysis techniques. This work is the rst installment of a two-partseries on TecDEM, a MATLAB based software for understandingtectonics from digital elevation models (DEMs). TecDEM is also able

slope, elevation, downstream distance and Strahler order and thusthe analysis of geomorphic parameters. Here, we present algo-rithms for drainage network partitioning using the stream Strahler(1957) order and stream prole analysis using lled DEMs(Planchon and Darboux, 2002). A CSA threshold dened by a trial1. Introduction

Areas of the planet that are larreasons pose amajor limitation to ourgeomorphology at regional and localissues have resulted in recent theoregeomorphologyanddrainagenetworkexhibit critical relationshipsbetweenrrate (KirbyandWhipple, 2001; Schumdisruptsdrainagenetworks. Studying tgive cluesabout themagnitudeandoriactivity (Gloaguen et al., 2007, 2008;accessible for practicaltanding of tectonics and. Efforts to tackle thesevelopments in tectonicsing.Drainagenetworksevation, anddenudation., 2006). Tectonic activityureof this disruptioncannof theoriginal tectonict al., 2007).

channels as a proxy. We have developed a method for calculatingconcavity y and steepness (ks) indices for each streamwithin a basinand also for the spatial distribution of these streams. The Kaghanvalley in northern Pakistan was used as a case study in order to testthis method. Stream prole analyses and knickpoint identicationwere performed on a DEMof the Kaghan valley to evaluate the utilityof TecDEM and to explore the tectonic evolution of the region.

2. Methodology

The choice of DEM preprocessing and stream extraction algo-rithms can inuence stream parameters such as contributing area,TecDEM: A MATLAB based toolbox for tPart 1: Drainage network preprocessing

Faisal Shahzad , Richard Gloaguen

Remote Sensing Group, Institute of Geology, Freiberg University of Mining and Technolo

a r t i c l e i n f o

Article history:

Received 2 March 2010

Received in revised form

9 June 2010

Accepted 18 June 2010Available online 9 November 2010

Keywords:

Tectonics

Digital elevation models

Stream prole analysis

Hack index

MATLAB

a b s t r a c t

We present TecDEM, a so

tasks to digital elevationm

schemes and stream prol

determining ow direction

prole generation, knickp

knickpoints along selected

are computed using a sem

proles in theKaghanValle

with previous tectonic evo

applying complex tectonicream vectorization, watershed delineation, Strahler order labeling, stream

ts selection, Concavity, Steepness and Hack indices calculations. The

eams as well as stream prole analysis, and Hack index per stream prole

tomatic method. TecDEM was used to extract and investigate the stream

orthern Pakistan). Our interpretations of the TecDEMresults correlatewell

ion models for this region. TecDEM is designed to assist geoscientists in

omorphology tasks to global DEM data.

& 2010 Elsevier Ltd. All rights reserved.tonic geomorphology,nd stream prole analysis$

Bernhard-von-Cotta-Strasse 2, 09599 Freiberg, Germany

re shell implemented in MATLAB that applies tectonic geomorphologic

ls (DEMs). The rst part of this paper series describes drainage partitioning

sevier.com/locate/cageo

eosciences

tion

F. Shahzad, R. Gloaguen / Computers & Geosciences 37 (2011) 250260 2512.1.1. Flow directions and contributing area

For any DEM, ow directions represent the surcial movementof water to neighboring cells. A wealth of theoretical and algo-rithmic development in ow directions has been carried out in thelast three decades. These methods are usually based upon hydro-logical approaches i.e. using upslope areas. The most famous andbasic models for ow direction calculation are called deterministicow direction (D8) or single ow direction (SFD) (Arge et al., 2003;Fehr et al., 2009; Jana et al., 2007; Kiss, 2004;OCallaghan andMark,1984).

In this study we modied a MATLAB based robust code written

Fig. 1. (a) Simplied ow chart for drainage network preparaby Schwanghart and Kuhn (2009) to calculate D8 ow. Thisprogram only works for small data sets. We proposed a griddingapproach for calculating the ow direction for large data setsgreater than 500500 pixels. First, all subgrids are calculated bydividing the data size (no. of rows and columns) by 500. A uniquelinear index-based id is assigned to each subgrid and thenboundinglimits are computed. Each subset is processed to calculate the owdirection with a buffer value of 50 pixels such that the boundaryeffect of ow directions can be avoided. The calculated owdirections for each subgrid are updated in the flowang matrix.This matrix contains ow angle codes for each pixel (Jenson andDomingue, 1988; Schwanghart and Kuhn, 2009). Another matrixflowdir, of similar size to flowang, is used in order to store the(geographic) direction of ow. The flowang matrix is processedusing a moving window of 33 pixel to identify the linear indicesof each pixels. These linear indices are stored in the flowdirmatrix.Similarly, a concavitymatrix tzero represents the total number ofinow directions for each pixel of the DEM.

2.1.2. Drainage network delineation

Drainage network delineation consists of two steps: identify allstreams above a critical source area (CSA) (Tarboton et al., 1991)and then assign their respective Strahler orders. Algorithms 1 and 2represent the pseudocode for the preparation of drainage net-works. The rst algorithm takes only three input parameters:area,flowdir and CSA. This algorithm creates two data structures:str_net and netwk_order_ind. The rst structure stores thestream network with a unique id, its spatial location and Strahlerorder. The second structure is used to store the indices of all thestreams of specic orders, i.e. netwk_order_ind(od). CSA isused to remove all locations in the area matrix that are theconsequence of the hill slope effect (Tarboton et al., 1991). Thisstep produces a binary matrix parea with high bits representingall locations in area above CSA. Another matrix str_map repre-sents all the locations with area values equal to 1. In thenext step, this binary drainage network is vectorized and theirrespective Strahler orders (Garbrecht and Martz, 1997; Gleyzeret al., 2004) are assigned. Stream Strahler order are assigned as

and (b) calculation of concavity, steepness and Hack indices.illustrated in Fig. 2.

Algorithm1. Algorithmtoprepare drainagenetworkwithCSA as athreshold

Require: area, owdir, and CSAstr_net structure (id,rowid,colid,order),

netwk_order_ind structure(ind), noval 1, i1r size(owdir), area(area o CSA) 0area(areaZ CSA) 1, parea area, str_map noval * pareawhile i doto owdir(str_map noval)pzero zeros(r)

for i1 to lengthto doif to(i) a1 thenpzero(to(i)) pzero(to(i))+1

end ifend fornid nd(pzero 0)if notisempty(nid) then[str_net, netid, str_map] prepare_network(str_net,str_map, pzero, owdir, nid, i)netwk_order_ind(i).ind netid, i i + 1

elsei0

end ifend whilereturn str_net, netwk_order_ind, str_map

F. Shahzad, R. Gloaguen / Computers & Geosciences 37 (2011) 250260252Algorithm 2. Algorithm to describe the procedure prepare_network

Require: str_net, str_map, pzero, owdir, nid, inoutid [], netid []

for i1 to length(nid) dostr_map(nid(i)) in, outid [outid; nid(i)], idowdir(nid(i))

if ida1 thenid2pzeroid

elseid2 pzero(nid(i))

end ifwhile and(id2 1, ida1) dostr_map(id) in, outid [outid; id], id owdir(id)

if ida1 thenid2 pzero(id), str_map(id) in, tid id

end ifend whileif and(length(outid) 4 1, tida1) thenoutid [outid; tid]

elseoutid [outid; owdir(tid)]

end if

Fig. 2. Simplied illustration for assigning streamStrahler orders (see text for details): (a)(c) Strahler order 3 streams are highlighted and (d) Complete drainage network with rsrid length(str_net)+1, str_net(srid).id istr_net(srid).rowid r, str_net(srid).colid cstr_net(srid).order in, netid [netid srid], outid []

end forreturn str_net, netid, str_map

For this purpose, rst the pzero matrix is prepared to representthenumberof inows for all thepixelswherestr_map is equal to 1.The procedure prepare_network as shown in Algorithm 2 is called,when all pixels have been assigned a Strahler order and no location isequal to 1. This algorithm requires six input parameters (str_net,str_map, pzero, flowdir, nid and in), where nid represents thestarting location of all the streams of Strahler order in. Streamsegments of Strahler order in are identied using the flowdirmatrixand terminates at locationswherepzero is greater than1. This loop isrepeated until all the stream segments of order in are successfullyidentied. The prepare_network function returns three parameters:str_net, netid and str_map. The netid is an array containing theindices of all the streams of Strahler order in and is assigned innetwk_order_ind structure. This algorithm returns three para-meters (str_net, netwk_order_ind, str_map), where str_mapcontains a spatial distribution of stream Strahler orders.

Strahler order 1 streamsare highlighted, (b) Strahler order 2 streams arehighlighted,

espective Strahler order.

2.1.3. Watershed extraction

The watershed/drainage partition framework is implemented inthe TecDEM (Curkendall et al., 2003; Fehr et al., 2009; Jensonand Domingue, 1988; Miliaresis, 2001, 2008; Ruiz et al., 2007;Turcotte et al., 2001). The drainage basin/watershed objectsare labelled according to the Strahler order labeling scheme.This is a 2 step procedure from the algorithmic point of view: (1)tracing a unique ow code for each pixel and (2) assigning a uniqueidentication to all the pixels above a certain required threshold. Agraphical illustration of this methodology is shown in Fig. 3.

Algorithm 3. Algorithm to extract drainage basins of specicStrahler order

Require: netwk_order_ind, str_net, str_map, tdbsngrd str_map,for k 1:1:length(netwk_order_ind) dostrid netwk_order_ind(k).ind;for j 1:1:length(strid) dor str_net(strid(j)).rowid, c str_net(strid(j)).colidbsngrd(r, c) k + i*strid(j);

end forend forto nd(tzero 0)

for a 1:1:length(to) doind owdir(to(a)), output to(a)while and(ind a 1, bsngrd(ind) 0) dooutput [output; ind]if ind a owdir(owdir(ind)) thenind owdir(ind)

end ifend whileif owdir(output(end)) a 1 thenbsngrd(output) bsngrd(owdir(output(end)));

elsebsngrd(output) bsngrd(output(end));

end ifend forcatchment_matrix(bsngrd, td)

These procedures have been shown in Algorithms 3 and 4. The rstalgorithm takes only three input parameters (str_net, netwk_or-der_ind,str_map). This algorithmcreates a variablebsngrdwhich isinitialized with str_map. Contrary to previous methods, we use anindexing code to identify unique basins. The idea is to use a complexnumber (composed of a real and an imaginary part) for drainage

(a) Dr d 2,

F. Shahzad, R. Gloaguen / Computers & Geosciences 37 (2011) 250260 253Fig. 3. Simplied illustration for drainage basins extraction (see text for details):

(c) Drainage Basins of Strahler order 1, 2 and 3 and (d) Full drainage basin of desired Straainage Basins of Strahler order 1, (b) Drainage Basins of Strahler order 1 anhler order (4 in this case).

2000; Wobus et al., 2006). In this regard different spatiallydistributed streams are identied for stream prole analysis. Thesestreams of different spatial distribution have elevation, length,contributing area and spatial locations, i.e. latitude and longitudeinformation. This data is obtained by processing the DEM, flowdir,area, and flowlength grids and is processed using procedureshown in Fig. 1(b). The following sections provide a theoreticaloverview of these measures and how they are calculated.

2.2.1. Concavity and steepness index

The bedrock incision model states that due to the equal streamgradients for erosion and uplift detachment-limited, channels donot have a continuous cover of alluvial sediments even at negligibleow levels (Shahzad et al., 2009; Snyder et al., 2000; Wobus et al.,2006). Stream morphology can be represented by three differentstages: initial steady state, transient and nal steady-state prole.This transition reects lithological contrasts or fault boundariesthat set the streams to a new equilibrium condition as shown inFig. 4. The shear stress incision law states that under steady-stateconditions the upstream contributing area (A) and slope (S) of astream at any stage can be represented using

S ksAy 1where y and ks are concavity and steepness indices, respectively.These values depend on basin morphology, underlying rockstrengths and hydraulic geometry. They can be measured directlyby regression analysis between A and S (Montgomery et al., 1996;Snyder et al., 2000; Wobus et al., 2006). Fig. 4 shows that the loglog plot between area (A) and slope (S) separates the three differentstages of a stream. These stages are usually separated by trends in

F. Shahzad, R. Gloaguen / Computers & Geosciences 37 (2011) 250260254for kk 1:1:length(strid) doif str_net(strid(kk)).order ord thenr1 str_net(strid(kk)).rowid(end)c1 str_net(strid(kk)).colid(end)bsngrd(imag(bsngrd) strid(kk)) bsngrd(r1,c1)

end ifend for

end foruids unique(imag(bsngrd(real(bsngrd)td)))basinmatrix zeros(size(bsngrd))for ij 1:1:length(uids) dobasinmatrix(imag(bsngrd) uids(ij)) ij

end forreturn basinmatrix

The catchment_matrix algorithm takes four input arguments:bsngrd, td, str_net, netwk_order_ind and str_map. At this stagebsngrd is a complexmatrixwhose real part consists of the respectiveStrahler order and whose imaginary part denotes the respectiveindices of stream segments. In this algorithm td is the threshold limitat which a drainage network is required. A set of nested loops is usedto traverse all pixels until a pixel of desired Strahler order (td) isencountered. At each iteration, the location of stream segments oforderord in thebsngrdmatrix is updated to the indexing code of thelast element of that segment. In thenext step, uniquepixel ids of eachbasin are identied. A newmatrix basinmatrix equal to the size ofbsngrd is created and all elements are set to zero. A variable uidsconsists of unique elements of all imaginary parts of bsngrd, wherethe real part of bsngrd is equal to td. This ensures the extraction ofunique ids of basins. Now the imaginary part of bsngrd matrixconsists of unique basin ids and hence a loop is operated on allelements of uids to store them in basinmatrix. A tracing algorithmusing eight connected neighbors was also implemented to trace theboundary of the basins. Beyond the extraction process, additionalparameters like hypsometric integral and basin elongation ratios canalso be calculated for each basins.

2.2. Stream prole analysis

Stream prole analysis is a quantitative geomorphic approachto describe streammorphology. This involves calculating the Hacknetworkrepresentation.The realpartof thisnumbercorresponds to theStrahler order and an imaginary part stores the node id for a givenlocation. It can be easily conducted using a pair of nested loops. Theouter loop traverses netwk_order_ind to nd indices of streamsegments of respective Strahler orders. The inner loop operates on thenodes of stream segments and the nodeid is assigned to the imaginarypart. This process assigns an indexing code for all the pixels above theCSA value. Thus in the next step, this algorithm assigns code toremaining pixels using the tzeromatrix which contains informationabout all inwardowingdrainagecodes for eachpixel.Gridpointswithno inow(i.e.tzero 0)are the local elevationmaximaandrepresentthe starting points (seeds) into the algorithm that delineate drainagebasins. Each seeding pixel is then traced down until the end of the hillslope.This limit is identiedonthepixelsofbsngrd 0.All streamsonthe hill slope are also marked with the Strahler order 1 as they are allthe part of the order 1 basin. Once all the respective sub-basins areidentied they aremerged to formauniquebasin that are basedon theuser-dened drainage basin.

Algorithm 4. Algorithm to describe the catchment_matrixprocedure

Require: bsngrd, td, netwk_order_ind, str_netfor ord 1:1:td-1 dostrid netwk_order_ind(ord).ind(1973) SL index and concavity and steepness indices (Snyder et al.,the loglog plot. Steam units with lithological contrasts and faultboundaries are delineated using the concavity and steepnessindices. The normalized steepness index (ksn) is calculated using

Fig. 4. Transient stream prole is showing a relationship between low uplift andhigh uplift along migration of knickpoint. Inset shows a logarithmic plot between

stream slope and upstream contributing area. It shows that concavity index yremains same for both initial and nal proles, while steepness index (ks) is higherfor nal prole. Modied from Shahzad et al. (2009) and Snyder et al. (2000).

a x reference concavity value yref usually taken around 0.45(Snyder et al., 2000; Wobus et al., 2003, 2006). The yref is used tointerpret steepness values as they are strongly correlated (Eq. (1)).The normalized steepness index (ksn) can be used to calculaterelative uplift rates using

U knsnK 2

where K is the erosion coefcient, n depends upon basin morphol-ogy and U is relative uplift rates. This equation gives us relativeuplift rate for area within a steady-state landscape by choosingappropriate values of n and K which can be found from previousstudies (Anderson et al., 1994; Seidl and Dietrich, 1992; Tucker andSlingerland, 1996;Wobus et al., 2006). The calculation procedure is

shown in Fig. 1(b). First, the desired stream is smoothed using amoving window lter along the prole in order to remove highfrequency noise evident in global DEMs. Trends can then beselected for the desired stream and the choice of which variesfrom stream to stream. Regression analysis is applied to each trendto derive concavity and steepness indices. A normalized steepnessindex is then calculated for each trend using the referenceconcavity. Over a region of constant K the relative uplift ratesare obtained using Eq. (2). This procedure is repeated for all streamsin the study area.

2.2.2. Hack index

TheHack index can be calculated using Eq. (3) as shown in Fig. 5.Hack (1973) proposed this method by studying the change instream length and channel slope using semi-log plots. He proposeda mathematical relationship as

SL k LnDHiDLi

3

where H is elevation and L is stream length. The vertical linear axisrepresents elevation whereas the horizontal logarithmic axisindicates stream length. The slope of this graph is a straight lineand is called Hack index or the stream gradient index (SL).Calculation of the SL index is simple and can be applied to anylongitudinal stream prole using a user-dened contour interval.First, the desired stream is partitioned into several segments/reaches using the specied contour interval. The distance andelevation difference between two consecutive reaches and thedistance between the center of these reaches are used to calculate

Fig. 5. Graphical illustration of Hack Index at specied contour intervals in a streamprole. Modied from Hack (1973).

d et

F. Shahzad, R. Gloaguen / Computers & Geosciences 37 (2011) 250260 255Fig. 6. (a) Tectonic setting of India Eurasia collision zone (Kamp et al., 2008; Shahza

2010) and (c) Kaghan valley and surrounding area with major tectonic features (Kampal., 2010), (b) Geographical location of study area (Kamp et al., 2008; Shahzad et al.,et al., 2008; Kazmi and Jan, 1997; Monalisa et al., 2007; Shahzad et al., 2007).

this measure. Change in SL values along a stream corresponds tochanges in lithologies and the presence of faults.

3. Testing and evaluation in an active tectonic region

The Kaghan valley is an active geomorphic feature which lies innorthern Pakistan. Valley drainage is dominated by the KunharRiver, also known as Kaghan River. Geographically, most of thestudy area lies in Pakistani Kashmir and was severely damagedduring the October 8, 2005 earthquake. The elevation of this regionvaries mainly between 600 and 5000 m. Tectonically, the valley islocated in the Hazara Kashmir Syntaxis (HKS) which is an activepart of the NWHimalayas. Previous studies suggest that this regionis under considerable crustal shortening and uplift (Hussain andKhan, 1996; Kamp et al., 2008; Kazmi and Jan, 1997). The HKS wasformed as a hair-pin structure consisting of the NNW-SSE trendingMain Boundary Thrust (MBT) and its splays. The outer boundary ofthe HKS is represented by the Punjal Khairabad Fault which has aNE-SW orientation near Kaghan (Kamp et al., 2008; Kazmi and Jan,1997; Shahzad et al., 2007). An overview of the geology, geomor-phology and climatology of the region can be found in Kamp et al.(2008) and Kazmi and Jan (1997).

We prepared the drainage network of the Kaghan valley andsurrounding area using 90 m Shuttle Radar Topography MissionData (SRTM-DEM) (Farr et al., 2007). A list of freely available DEMsand their sources is given in Appendix B. The drainage network of

the study area with the streams of Strahler orders greater than4 and the drainage basin of the Kunhar river is shown in Fig. 6(c).A total of 22 streams were selected in the Kunhar river drainagebasin. A simplied user manual is given in Appendix A. Thesestreams are extracted from the source to their conuence pointwith the main channel. The major lithological units in the studyarea are Tertiary sedimentary rocks (Kamp et al., 2008; Kazmi andJan, 1997). The area was selected because it is undergoing variablesurface deformation conditions. Stream prole analysis wasapplied to selected streams as shown in Fig. 8. This type of analysisinvestigates the concavity, stream gradient and steepness of theregion underlying any stream and can be investigated in detailusing their spatial distribution in map view (Shahzad et al., 2007).We use a reference concavity of yref 0:45 as suggested bySchoenbohm et al. (2004) and Snyder et al. (2000). Proles consistof one to several channel segments with distinct concavity andsteepness indices. The selection of stream segments depends uponstream morphology.

Fig. 7 shows the stream prole analysis of stream no. 3. Thelogarealogslope plot shows three prominent trends. We selectedtwo concave trends to calculate their concavity and normalizedsteepness (Schoenbohm et al., 2004). The convex trend is notanalyzed here but can be interpreted separately (Kirby andWhipple, 2001). Both concave trends are marked with differentcolors and are also visible in the longitudinal prole. The startingportion of this streambefore the rst trend represents the hill slopeeffect. According to Schoenbohm et al. (2004), this type of stream

n id

niqu

F. Shahzad, R. Gloaguen / Computers & Geosciences 37 (2011) 250260256Fig. 7. Concavity and Steepness analysis of streamno. 3. Two concave trends have beeprole (upper). Green line represents area prole of stream. Selected streams with ulegend, the reader is referred to the web version of this article.)entied on logarealogslope data (bottom). These trends also appear on longitudinal

e ids are shown in Fig. 8. (For interpretation of the references to color in this gure

represents an area where the intermediate channel segment hasbeen removed by headward erosion. The lower segment is usuallyset in response to an earlier local base level related to the paleo-river. The portion of this prole where slope does not change,normally dictates areas of debris ow or landslide. The rst trendhas a very high concavity value (2.16) and a low steepness (103.12)which indicates the presence of relict landscape. The lowersegment gives lower concavity (0.67) and high steepness(936.14) values for the downstream section of the river. Thesudden change in geomorphic indices, especially increased steep-ness indices are attributed to regions of rapid uplift.

We observe that streams outside theHKS have convex behavior,represented by a high concavity index (see Fig. 8 (a)). Inside theHazara Kashmir Syntaxis which is delineated by the PunjalKhariabad Fault (PKF), streams show a low concavity index, whichis attributed to increasingly incisional conditions. Another reasonfor the presence of highly concave channels outside of the HazaraKashmir Syntaxis may be because this area is compressed betweenthe PKF and the Main Mantle Thrust (MMT). This also supports theidea that the spatial distribution of concavity index can be used todelineate variable steepness zones even though there is nostatistical signicance of concavity index between channels inthe low and high steepness zones. As the steepness of a region isattributed to the uplift prevailing conditions, the plan viewdistribution of normalized steepness indices for all the tributariesin a catchment is a useful tool to identify regions of rapid uplift. Inthe present study there is no clear steepness distribution trend asshown in Fig. 8(b) except for the central portion with a highsteepness index along the PKF. This area is sandwiched betweenaccommodating shear zones (PKF and MBT) and can be oneexplanation for these high values.

In the study area, the Hack Index was applied on a contourinterval of 300 m. The resultant values range between 1 and1552 m and are grouped into ve classes as shown in Fig. 8(c).As with the steepness index, Hack values are also spatiallydistributed. This change in sudden variation is attributed tovariable lithological units (Hussain and Khan, 1996; Kamp et al.,2008; Kazmi and Jan, 1997). The second observation is that theHack index shows sharp changes close to faults and/or along knickpoints. Inside the Hazaral Kashmir Syntaxis the Hack index hasrelatively lowvalues. Thismay also be attributed to the fact that thedownstream section of the Kunhar River is fully equilibrated. Thesevalues also suggest that along with tectonics, lithology is playing amajor role in forming the landscape. In the northern portion highervalues also suggest that the increased topography is disturbing thestreams and producing higher slopes. The results from theseanalyses suggest that tectonic deformation is unevenly distributed.We identify two zones of variable deformation in the study area.Inside the Hazara Kashmir Syntaxis we observe a zone of rapiduplift whilst the deformation outside of the Hazara KashmirSyntaxis can be attributed to sandwiching between the MainMantle Thrust and Punjal Khairabad Fault.

4. Concluding remarks

TecDEM is a valuable new software tool for the processing ofDEMdata. Drainage basin partitioning fromDEMs is a fundamentalprocessing option of TecDEM. The presented algorithms assignStrahler orders to each stream and extract sub-basins. Streamprole analysis of selected streams reveals the spatial distributionof concavity, steepness and Hack indices. The quantitative

to u

F. Shahzad, R. Gloaguen / Computers & Geosciences 37 (2011) 250260 257Fig. 8. Map view of spatial distribution of geomorphic indices. Numbers correspond

Index map.nique ids for selected streams: (a) Concavity map, (b) steepness map and (c) Hack

analysis, spatial statistics and basin analysis. When the user runs

A.1. File menu

Drainage Network sub-menu requires a CSA value (usually 1 kmkm2) to remove the hillside effect. It saves the drainage network asa structure consisting of stream segments along with their respec-tive Strahler order in n_ADN.matle. Thewatershed extraction sub-menu is used to extract drainage basins of specic Strahler order.This type of drainage extraction is usually useful for drainagesystem visualization as well as basin analysis (Shahzad andGloaguen, in press).

A.3. Display

The display menu is used not only to display the DEM, drainagenetworks, and watersheds but is also used to select the individualstreams for stream prole analysis. When the data is displayed itshows the stream extraction interface. This module consists ofthreemenus: Plot, Edit and Extract. The Plot sub-menu allows us tochange thebase plot betweenDEMand extracteddrainagenetworkat variable Strahler orders. The extract sub-menu is used to identifythe desired stream. The save stream commandwill save the streaminto stream data structure and is saved in a n_stream.mat le. Eachstream is assigned a unique id as shown in a list box on the righthand side.When all desired streams have been extracted and savedthe edit menu can be used to format the data if desired. This menuallows auser to delete a desired streamor subtract one stream fromanother. The Subtract sub-menu is used to subtract streams with

F. Shahzad, R. Gloaguen / Computers & Geosciences 37 (2011) 250260258The Filemenu is used for data handling. It provides functions forthe import and export of data in a variety of formats. Data handlingis carried out in native MATLAB les (n.mat). The import DEMsubmenu is used to import the lled DEM in GEOTIFF format. Thelocation of theDEMle is set as theworking and result directory forthe current project. Two les (n_INFO.mat and n_DEM.mat) areautomatically created and placed in the current working directory.The denotes the project name specied by the DEMle name. TheOpen Project sub-menu is used to open those projects, which havebeen fully or partially processed in TecDEM. Settings frompreviouscomputations are automatically loaded when a user loads anexisting project. The export sub-menu is used to export the gridsthe TecDEM.m le all code in the sub-folders will be automaticallycongured to work efciently. TecDEM consists of a graphical userinterface (GUI) as shown in Fig. 9. This GUI is organized into onetext box and sixmenus: File, Prepare, Display, Analyze, Results andHelp. The text box is used to record the log of processes and will beconstantly updated. This box will provide information about thestart and end of any process and can be saved for future references.The following sub-sections provide an overview about softwareusage for drainage network partitioning and stream prole analy-sis. Details concerning the use of the software can also be found inthe accompanying user guide.representation of drainage systems, sub-basins, knick points, etc. isexported in shape les and ENVI headers. Users canwrite their ownMATLAB functions in order to expand the software capabilities. Thesoftware is available from the IAMGwebsite and uses Global DEMs.This provides new opportunities for education and research intectonic geomorphology. We have tested TecDEM in an investiga-tion of the tectonic geomorphology of theKanhar valley in Pakistan.The results conform well with existing morphotectonic/geomor-phologic knowledge of the area. Stream prole analysis identiedtwo distinct zones of variable surface deformation marked by thePunjal Khairabad Fault. Deformation of the area outside the HKShas resulted from sandwiching between the Punjal Khairabad Faultand the Main Mantle Thrust in a zone of convergence.

Acknowledgements

Financial support to Faisal Shahzad from the State Governmentof Saxony (Germany), German Academic Exchange Association(DAAD) and graduate student research grant for year 2008 from theInternational Association for Mathematical Geosciences (IAMG) isgratefully acknowledged. We thank George Miliaresis and ananonymous reviewer who helped us to improve the quality andpresentation of this paper series. Anja Bretzler and Adam Szulc areacknowledged for help in proof reading and Louis Andreani for hissupport in GIS matters.

Appendix A. TecDEM user guide

This software has been written in MATLAB (release 2008b and2009b) using the Mapping toolbox and has been tested onWindows XP, Linux and MacOS. In order to run the softwareproperly MATLAB must be running with current path set to theprovided folder TecDEM 1.0. Source code has been organized intothree folders: Extraction, Methods and Drainage. The Extractionfolder contains the code to extract drainage networks from theDEMwhile the other two folders contain the code for streamprolein n.HDR and vectors in n.SHP le formats.A.2. Process

The Process menu consists of commands for drainage prepara-tion. The Flow Direction (D8) sub-menu performs the D8 ow-routing algorithm on the DEM using a gridding approach. Thisfunction will route the ow at each pixel location to the eightpossible adjacent cells. The Link File sub-menu will create a owlink between each pixel using their ow directions. This will createa n_FLOW.mat le which contains the linear indices for the inowdirection of each pixel. The Contributing Area sub-menu willcalculate the contributing area at each pixel and stores itin n_AREA.mat. It uses a linking approach and calculates thecumulative sum for each pixels ow to a neighboring pixel. The

Fig. 9. Screenshot of the TecDEM startup window.similar drainage outlet in order to remove redundant data due to

This calculation is discussed in the methodology section and will

F. Shahzad, R. Gloaguen / Computers & Geosciences 37 (2011) 250260 259calculate the Hack Index for all the streams automatically. All theresults will be updated in the n_stream.mat le.

Appendix B. Data sources

TecDEM is expected to support geologists in applying complextectonic geomorphology tasks and morphotectonic analysis fromglobal DEMs (SRTM DEM-1, ASTER GDEM-2, GLOBE DEM-3) thatare freely available from theWEB at various scales and resolutions.These data sets provide new possibilities for applying digitalgeologic mapping and tectonic interpretation. Here is a short listof websites providing free data sources.

1. http://srtm.csi.cgiar.org/ (90 m DEM grid).2. http://www.gdem.aster.ersdac.or.jp/search.jsp (30 m DEM grid).3. http://www.ngdc.noaa.gov/mgg/topo/globe.html (1 km DEM grid).

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A.4. Analyze

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F. Shahzad, R. Gloaguen / Computers & Geosciences 37 (2011) 250260260

TecDEM: A MATLAB based toolbox for tectonic geomorphology, Part 1: Drainage network preprocessing and stream profile...IntroductionMethodologyDrainage network preprocessingFlow directions and contributing areaDrainage network delineationWatershed extraction

Stream profile analysisConcavity and steepness indexHack index

Testing and evaluation in an active tectonic regionConcluding remarksAcknowledgementsTecDEM user guideFile menuProcessDisplayAnalyze

Data sourcesReferences