A tool for assessing error in digital elevation models from a user’s perspective

A Digital Elevation Model (DEM) is a representation of geographic reality. The elevations recorded within DEMs have been shown to contain errors pertaining to sampling, measurement and interpolation (Fisher, 1998). Even a small amount of elevation error can greatly affect derivative products (Holmes et al., 2000). This can potentially have a significant impact on the application of DEMs in Geographical Information Systems (GIS) where first and second order derivatives are considered

Digital Elevation Model Error in Terrain Analysis

Digital elevation models (DEMs) have been an important topic in geography and surveying sciences for decades due to their geomorphological importance as the reference surface for gravita-tion-driven material flow, as well as the wide range of uses and applications. When DEM is used in terrain analysis, for example in automatic drainage basin delineation, errors of the model collect in the analysis results. Investigation of this phenomenon is known as error propagation analysis, which has a direct influence on the decision-making process based on interpretations and applications of terrain analysis. Additionally, it may have an indirect influence on data acquisition and the DEM generation. The focus of the thesis was on the fine toposcale DEMs, which are typically represented in a 5-50m grid and used in the application scale 1:10 000-1:50 000. The thesis presents a three-step framework for investigating error propagation in DEM-based terrain analysis. The framework includes methods for visualising the morphological gross errors of DEMs, exploring the statistical and spatial characteristics of the DEM error, making analytical and simulation-based error propagation analysis and interpreting the error propagation analysis results. The DEM error model was built using geostatistical methods. The results show that appropriate and exhaustive reporting of various aspects of fine toposcale DEM error is a complex task. This is due to the high number of outliers in the error distribution and morphological gross errors, which are detectable with presented visualisation methods. In ad-dition, the use of global characterisation of DEM error is a gross generalisation of reality due to the small extent of the areas in which the decision of stationarity is not violated. This was shown using exhaustive high-quality reference DEM based on airborne laser scanning and local semivariogram analysis. The error propagation analysis revealed that, as expected, an increase in the DEM vertical error will increase the error in surface derivatives. However, contrary to expectations, the spatial au-tocorrelation of the model appears to have varying effects on the error propagation analysis depend-ing on the application. The use of a spatially uncorrelated DEM error model has been considered as a 'worst-case scenario', but this opinion is now challenged because none of the DEM derivatives investigated in the study had maximum variation with spatially uncorrelated random error. Sig-nificant performance improvement was achieved in simulation-based error propagation analysis by applying process convolution in generating realisations of the DEM error model. In addition, typology of uncertainty in drainage basin delineations is presented.Lukuisten käyttötarkoitusten ja sovellusmahdollisuuksien ansioista digitaaliset korkeusmallit, eli maan pinnanmuotoja esittävät numeeriset mallit, ovat olleet tutkimuksen kohteena maantieteen ja maanmittaustieteiden aloilla vuosikymmeniä. Kun korkeusmallia käytetään maastoanalyysissä, esimerkiksi automaattisessa valuma-aluerajauksessa tai tulvavaarakartoituksessa, mallissa olevat virheet kasautuvat analyysin tulokseen. Virheenkasautumisanalyysillä on suora vaikutus maastoanalyysipohjaiseen päätöksentekoon ja lisäksi sen avulla voidaan vaikuttaa epäsuorasti korkeusmallin luontiin tähtäävään tiedonkeruuseen sekä mallin tuottavien laskentamenetelmien käyttöön. Väitöskirja esittää kolmevaiheisen prosessin korkeusmallipohjaisten maastoanalyysien virheenkasautumisen tutkimiseksi. Työssä käytetyissä korkeusmalleissa maanpinnan korkeudet esitettiin 10-30m hilassa tyypillisen sovellusmittakaavan ollessa 1:10 000-1:50 000. Prosessiin kuuluu menetelmiä korkeusmallien karkeiden virheiden visuaaliseen havaitsemiseen, virheen tilastolliseen karakterisointiin ja virhemallin luontiin, analyyttiseen ja simulaatio-pohjaiseen virheenkasautumisanalyysiin sekä virheenkasautumisanalyysin tulosten tulkintaan. Virhemallin luonnissa käytettiin spatiaalisen tilastotieteen menetelmiä. Tulokset osoittivat, että tutkittujen korkeusmallien virheiden kuvaaminen ja mallintaminen kattavasti oli haastavaa. Tämä johtui mallien virhejakauman poikkeavien havaintojen suuresta määrästä sekä morfologisista karkeista virheistä, joiden visuaaliseksi havaitsemiseksi esitetään jakojäännöskarttojen käyttöä. Lisäksi korkeusmallien virheiden globaali karakterisointi osoittautui karkeaksi yleistykseksi todellisuudesta johtuen virheen paikkariippuvuudesta. Tämä osoitettiin empiirisesti käyttäen vertausaineistona koko tutkimusalueen kattavaa topografiseen laserkeilaukseen perustuvaa korkeusmallia. Virheenkasautumisanalyysit osoittivat, että korkeusmallin virheen kasvaessa myös maastoanalyysien virheet kasvoivat ja joissain tapauksissa virheiden kasvu oli huomattavasti ennalta arvioitua suurempaa. Virheen spatiaalisen autokorrelaation vaikutus analyysituloksiin oli sovellusriippuvaa. Spatiaalisesti autokorreloimatonta virhemallia on yleisesti pidetty pahimman tapauksen huomioonottavana mallina, mutta millään työssä käsitellyistä maastoanalyyseistä suurin epävarmuus ei liittynyt autokorreloimattomaan virhemalliin. Simulaatiopohjaisen virheenkasautumisanalyysin toteutuksessa sovellettu prosessikonvoluutiomenetelmä mahdollistaa korkeustiedon epävarmuuden huomioonottavien vuorovaikutteisten paikkatietopalvelujen luomisen. Esimerkkeinä mainittakoon jääpatojen aiheuttama tulvavaarakartoitus ja vaarallisten aineiden kuljetuksiin liittyvät onnettomuudet, joissa nestemäisten kemikaalien leviämisestä ympäristöön on saatava nopeasti luotettava kuva mikrotason valuma-alueanalyysillä

Effect of topography on the risk of malaria in the Usambara Mountains, Tanzania

There has been a progressive rise in malaria in parts of the African highlands over the last 50 years. In this area of unstable malaria, devastating epidemics are experienced at irregular intervals. Altitude plays a very important role in determining malaria transmission and infection. However, other landscape features may also influence this relationship. This research investigates whether the risk of malaria is related to the shape of the surrounding land, at various altitudes. We hypothesized that households situated close to flat areas where water is expected to accumulate, and are thus potential mosquitoes breeding sites, are at greater risk from malaria than those further away. Cross-sectional clinical surveys were carried out in seven villages along an altitudinal transect rising from 300 m to 1650 m in the western Usambara Mountains, Tanzania. Each village was mapped and incorporated within a geographical information system (GIS). Univariate analysis showed that the risk of an enlarged spleen was positively correlated with decreasing altitude. Other influential topographic variables identified were: water accumulation, flatness and swampiness. Logistic regression analysis produced two models and their equations were used in the GIS to map the risk of malaria infection within each village area. Model 1 included only altitude and correctly predicted the malaria status of 73% of households, whereas Model 2 incorporated altitude and the amount of swampiness within 400 m radius of each household to predict with 76% accuracy whether households were positive or not. We have identified that between 750 m and 1200 m, characteristics of the landscape play an important role in governing malaria risk. At these elevations malaria is highly unstable, and favourable meteorological conditions can cause malaria epidemics. This novel approach of exploring how topography affects the risk of malaria could be used to identify epidemic-prone areas m other African highland regions and help to improve the targeting of control activities in high-risk areas

Semi-automated geomorphological mapping applied to landslide hazard analysis

Computer-assisted three-dimensional (3D) mapping using stereo and multi-image (“softcopy”) photogrammetry is shown to enhance the visual interpretation of geomorphology in steep terrain with the direct benefit of greater locational accuracy than traditional manual mapping. This would benefit multi-parameter correlations between terrain attributes and landslide distribution in both direct and indirect forms of landslide hazard assessment. Case studies involve synthetic models of a landslide, and field studies of a rock slope and steep undeveloped hillsides with both recently formed and partly degraded, old landslide scars. Diagnostic 3D morphology was generated semi-automatically both using a terrain-following cursor under stereo-viewing and from high resolution digital elevation models created using area-based image correlation, further processed with curvature algorithms. Laboratory-based studies quantify limitations of area-based image correlation for measurement of 3D points on planar surfaces with varying camera orientations. The accuracy of point measurement is shown to be non-linear with limiting conditions created by both narrow and wide camera angles and moderate obliquity of the target plane. Analysis of the results with the planar surface highlighted problems with the controlling parameters of the area-based image correlation process when used for generating DEMs from images obtained with a low-cost digital camera. Although the specific cause of the phase-wrapped image artefacts identified was not found, the procedure would form a suitable method for testing image correlation software, as these artefacts may not be obvious in DEMs of non-planar surfaces.Modelling of synthetic landslides shows that Fast Fourier Transforms are an efficient method for removing noise, as produced by errors in measurement of individual DEM points, enabling diagnostic morphological terrain elements to be extracted. Component landforms within landslides are complex entities and conversion of the automatically-defined morphology into geomorphology was only achieved with manual interpretation; however, this interpretation was facilitated by softcopy-driven stereo viewing of the morphological entities across the hillsides.In the final case study of a large landslide within a man-made slope, landslide displacements were measured using a photogrammetric model consisting of 79 images captured with a helicopter-borne, hand-held, small format digital camera. Displacement vectors and a thematic geomorphological map were superimposed over an animated, 3D photo-textured model to aid non-stereo visualisation and communication of results

Landslide damming hazard susceptibility maps: a new GIS-based procedure for risk management

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Techniques for augmenting the visualisation of dynamic raster surfaces

Despite their aesthetic appeal and condensed nature, dynamic raster surface representations such as a temporal series of a landform and an attribute series of a socio-economic attribute of an area, are often criticised for the lack of an effective information delivery and interactivity.In this work, we readdress some of the earlier raised reasons for these limitations -information-laden quality of surface datasets, lack of spatial and temporal continuity in the original data, and a limited scope for a real-time interactivity. We demonstrate with examples that the use of four techniques namely the re-expression of the surfaces as a framework of morphometric features, spatial generalisation, morphing, graphic lag and brushing can augment the visualisation of dynamic raster surfaces in temporal and attribute series

Application of Geographical Information Systems to Lahar Hazard Assessment on an Active Volcanic System

Lahars (highly dynamic mixtures of volcanic debris and water) have been responsible for some of the most serious volcanic disasters and have killed tens of thousands of people in recent decades. Despite considerable lahar model development in the sciences, many research tools have proved wholly unsuitable for practical application on an active volcanic system where it is difficult to obtain field measurements. In addition, geographic information systems are tools that offer a great potential to explore, model and map hazards, but are currently under-utilised for lahar hazard assessment. This research pioneered a three-tiered approach to lahar hazard assessment on Montserrat, West Indies. Initially, requirements of potential users of lahar information (scientists and decision-makers) were established through interview and evaluated against attainable modelling outputs (given flow type and data availability). Subsequently, a digital elevation model, fit for modelling lahars, was used by a path of steepest descent algorithm and a semi-empirical debris-flow model in the prediction of lahar routes and inundation areas. Limitations of these established geographical information system (GIS) based models, for predicting the behaviour of (relatively under-studied) dilute lahars, were used to inform key parameters for a novel model, also tightly coupled to a GIS, that simulated flow routes based on change in velocity. Importantly, uncertainty in model predictions was assessed through a stochastic simulation of elevation error. Finally, the practical utility of modelling outputs (visualisations) was assessed through mutual feedback with local scientists. The new model adequately replicated past flow routes and gave preliminary predictions for velocities and travel times, thus providing a short-term lahar hazard assessment. Inundation areas were also mapped using the debris-flow model to assist long-term planning. Ultimately, a GIS can support ‘on the ground’ planning decisions, but efficacy is limited by an active volcanic system which can restrict feedback to and from end-users. *[The appendices for this thesis were submitted as separate files which could not be uploaded to the repository. Please contact the author for more information.]