Developing a global location optimization model for utility-scale solar power plants

The purpose of this Master's thesis was to create a new model for screening possible optimal locations for utility-scale solar power plants (i.e. solar parks, solar power stations and solar farms) in larger city areas. The model can be used as a part of a decision making when examining site potentiality in a particular city of interest. The model includes forecasts for the year 2040. The main questions of the thesis are as follows: 1) What are the main criteria for a good location for a utility-scale solar power plant and 2) how to build a geographic information system (GIS) model for solar power plant location optimization? Solar power plants provide an alternative to producing renewable energy due to the enormous distribution potential of solar energy. A disadvantage of utility-scale solar energy production is the fact that it requires larger areas of land than the more traditional power plants. Converting land to solar farms might threaten both rich biodiversity and food production, which is why these factors are included in the model. In this study, methods from the field of geographic information science were applied to quantitative location optimization. Spatial analytics and geostatistics, which are effective tools to narrow down optimal geographical areas, were applied for finding optimal locations for solar power plants, especially in larger city regions. The model was developed by an iterative approach. The resulting model was tested in Harare (Zimbabwe), Denver (United States) and Helsinki (Finland). The optimization model is based on three raster datasets that are integrated through overlay analysis. The first one contains spatial solar radiation estimates for each month separately and is derived from a digital elevation model and monthly cloud cover estimates. The resulting radiation estimates are the core factor in estimating energy production. The second and the third dataset are two separate global datasets, which were used to deal with land use pressure issues. The first of these is a hierarchically classified land systems model based on land cover and intensiveness of agriculture and livestock, while the second is a nature conservation prioritization dataset, which shows the most important areas for conserving threatened vertebrate species. The integration of these datasets aims to facilitate smart and responsible land use planning and sustainability while providing information to support profitable investments. The model is based on tools implemented in the ArcGIS 10 software. The Area solar radiation tool was used for calculating the global and direct radiation for each month separately on clear sky conditions. An estimate of the monthly cloud coverage was calculated from 30 years' empirical cloud data using a probability mapping technique. To produce the actual radiation estimates, the clear sky radiation estimates were improved using the cloud coverage estimates. Reclassifying the values from land use datasets enabled the exclusion of unsuitable areas from the output maps. Eventually, the integration and visualization of the datasets result in output maps for each month within a year. The maps are the end product of the model and they can be used to focus decision making on the most suitable areas for utility-scale solar power plants. The model showed that the proportion of possible suitable areas was 40 % in Harare (original study area 40 000 km2), 55 % in Denver (90 000 km2) and 30 % in Helsinki (10 000 km2). This model did not exclude areas with low solar radiation potential. In Harare, the yearly variation in maximum radiation was low (100 kWh/m2/month), whereas in Denver it was 2.5-fold and in Helsinki 1.5-fold. The solar radiation variations within a single city were notable in Denver and Harare, but not in Helsinki. It is important to calculate radiation estimates using a digital elevation model and cloud coverage estimates rather than estimating the level of radiation in the atmosphere. This spatial information can be used for directing further investigations on potential sites for solar power plants. These further investigations could include land ownership, public policies and investment attractiveness

Comparison of OpenFOAM turbulence models for numerical simulation of thermally-driven winds

Commercial computational fluid dynamics (CFD) codes have often been used for simulation of atmospheric boundary layer (ABL) flows. The present work explores the potential of the open-source CFD software OpenFOAM for simulating thermally-driven winds, by comparing several turbulence models. Indeed, in ABL and other large-scale flows, turbulence is critical to the mixing process of momentum and buoyancy, and simulations with commercial CFD codes have usually been done with Reynolds-Averaged Navier-Stokes (RANS) turbulence modelling. In this work, the formation of thermally-driven winds is studied in an idealised mountain-valley system, with realistic values of parameters such as the slope angle, the diurnal temperature cycle, etc. Performances of various OpenFOAM RANS turbulence models (k–e, re-normalisation group (RNG) k–e, k–¿ shear stress transport (SST)) are compared. A preliminary study of LES using Smagorinsky closure is also contemplated. Velocity contours, velocity and temperature profiles, the shapes of vortexes/convective cells, and the computational times are presented for all the studied turbulence models, to help identify the most suitable one for simulation of thermally-driven winds.This work is supported by the project PID2019-105162RB-I00 funded by MCIN/AEI/10.13039/501100011033 and by the project 2017 SGR 1278 from the AGAUR Generalitat de Catalunya.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.1 - Per a 2030, garantir l’accés universal a serveis d’energia assequibles, confiables i modernsObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.2 - Per a 2030, augmentar substancialment el percentatge d’energia renovable en el con­junt de fonts d’energiaPostprint (published version

EFFECT OF VEGETATION STRUCTURE ON UNDERCANOPY SOLAR RADIATION USING LIDAR REMOTE SENSING

Estimation of under-canopy radiation is crucial for characterizing vegetation–energy interactions and for a better understanding of its implications for ecosystem studies and forestry applications. Under-canopy radiation regimes are difficult to model due to the complex interaction of light with vegetation structure. Also, measuring radiation under the canopy over large areas is challenging using traditional field-based procedures. In this context, LiDAR remote sensing shows great potential for radiation estimation because it directly measures the three-dimensional canopy structure. The primary aim of this dissertation is to improve the understanding of under-canopy light regime using discrete return LiDAR and estimate solar radiation in forests with different structural characteristics. Based on the availability of LiDAR data, research sites were chosen in the coniferous forests of Sierra National Forest (SNF), California, and a chronosequence of mixed deciduous forest plots located in the Smithsonian Environmental Research Center (SERC), Maryland. First, LiDAR-derived digital surface models with and without vegetation canopy were used to assess the first-order effect of vegetation on solar radiation in SNF. The results showed a significant difference (p value < 0.001) in insolation values between the two surface models, with the mean solar irradiation over the bare surface almost three times higher than vegetation canopy surface. Next, a ray-tracing method was used to estimate beam radiation using LiDAR point clouds, and estimates were compared with in situ pyranometer measurements across three forest plots in SERC and were found to be in good agreement (RMSE = 13.94 W/m2). Lastly, LiDAR-derived vertical light transmittance values were compared with measurements from field-based PAR sensors, across five forest plots in SERC and were found to be in good agreement (R2 = 0.84). These results suggest that LiDAR remote sensing can provide reliable fine-scale estimates of beam radiation and vertical transmittance values under the vegetation canopy without the need for extensive ground measurements. This information provides a better understanding of radiation variability under the canopy and can help potentially improve the estimates from a range of land surface models such as snowmelt and hydrological models, and possibly help downscale general circulation model (GCM) predictions

Using remote sensing and geographical information systems to classify local landforms using a pattern recognition approach for improved soil mapping

Thesis (PhDAgric)--Stellenbosch University, 2022.ENGLISH ABSTRACT: Presently, a major focus of digital soil mapping (DSM) in South Africa is unlocking the soil-landscape relationships of legacy soil data by disaggregating the only source of contiguous soil information for South Africa, the National Land Type Survey (LTS) (ARC, 2003). Each land type is best defined as a homogenous mapping unit with a unique combination of terrain type, soil pattern and macroclimate properties (Paterson et al., 2015). One of the prevailing reasons for the LTS longevity and continual temporal-interoperability is that terrain description is expressly related to a suite of catenary soil property descriptions (Milne, 1936). These terrain types are further divided into terrain morphological units (TMUs) representing a sequence of patterns based on a 5-unit landscape model of 1-crest, 2-scarp, 3-midslope, 4-footslope and 5-valley bottom. Importantly, dominant soil distribution patterns are defined by terrain units relying on an elementary terrain topo-sequence pattern approach, with much of the work done on modelling soil variation related to variation in terrain (van Zijl, 2019). Whilst the LTS remains a source of national interest, there is immense opportunity to build on the existing soil inventory data rather than only focus on “breaking it down” (disaggregation). However, what is needed is a standard operating procedure that not only leverages the ability of digital elevation models (DEM) to explicate soil-landscape associations beyond the limited 5-unit landscape model but allows better refinement of soil descriptions with landscape features. Only once the nuances of optimal DEM parametrisation under controlled conditions are fully understood can the complete scope of DSM and digital geomorphological mapping (DGM) applications be explored. This dissertation attempts to synthesise knowledge on theory, methods, and applications of using remote sensing (RS) and geographical information systems (GIS) to classify local landforms using a pattern recognition approach for improved soil mapping in the context of multiscale problems of digital terrain analysis in KwaZulu-Natal. The dissertation is divided into three parts. Part one (Chapter 2) represents the DEM pre- processing and generalisation method and establishes the protocols for soil-landscape covariate application derived from various sensor platforms and spatial scales. Part two (Chapter 3) introduces the concept of improved terrain unit mapping through the geomorphon approach and describes DEM optimisation for standardised geomorphon representation for uniformly describing soil-landscape properties for inputs to DSM applications. Finally, part three (Chapters 4 & 5) looks at applications of DEM sources and geomorphons first from a holistic landscape context by linking digital terrain and soil-landscape analysis to geodiversity. Finally, the benefit of improved RS and GIS combined with quantitative modelling approaches on improving natural resource predictions are explored by modelling soil-ecotope and soil type mapping units and proposing improvements to an existing DSS designed for KwaZulu-Natal Natal. Specifically, this research is organised into four (4) research chapters with an overview of each chapter’s contribution outlined hereafter. Chapter 2 accounts for the recognition and requirements of DEM generalisation from high to medium resolution RS platforms and the influence these pre-processing approaches have on the extraction of a wide range of terrain attributes. Digital elevation data are elemental in deriving primary topographic attributes that are input variables to various regional soil-landscape models. DEMs' utility to extract different topographic indices as primary inputs to DSM allows the generalised soil-formative relationship between topography and soil characteristics to be measured quantitatively. Traditional landscape-scale approaches to extracting and analysing soils remain subjective and an expensive last resort for large-scale regional soil distribution and variability prediction. Selecting the right DEMs is a critical step in the development of any soil-landscape model. Therefore, the ability to represent soil-landscape relationships rapidly and objectively between soil properties and landscape position using emerging technologies and elevation data in a digital environment and at varying scales is fundamental for using soil-landscape mapping as a regional planning tool. There is, however, still varied consensus on the effect of DEM source and resolution on the application of these topographic attributes to landscape and geomorphic characterisation within South Africa. However, Atkinson et al. (2017) have shown that topographic variable extraction is highly dependent on the DEM source and generalisation approach. However, while higher resolution DEMs may represent the “true” landscape surface more accurately, they do not necessarily offer the best results for all extracted terrain variables for modelling soil-landscape outputs. Given the convenience of a wide range of open-source elevation data for South Africa, there is a need to quantify the impact that DEM generalisation approaches have on simplifying detailed DEMs and compare the accuracy and reliability of results between high resolution and coarse resolution data on the extraction of localised topographic variables as a primer for soil-landscape or digital soil models. Chapter 3 explores the harmonisation of geomorphons derived from various RS platforms to define the landscape character in central KwaZulu-Natal. Robust DGM approaches that can simplify and translate the inclusion of “human knowledge” to automatic terrain classification across a broader spectrum of terrain morphological units and a range of DEM spatial scales offer great potential for improved topographic and landscape analysis and must have their utility investigated. Continual advances in quantitative modelling of surface processes, combined with new spatio-temporal and geo-computational algorithms, have revolutionised the auto-classification and mapping of landform components through the automated analysis of high-quality DEMs. Therefore, a thorough assessment of the effects that different pixel resolution (grain size) and DEM sources have on replicating observed geomorphic spatial patterns and representing selected terrain parameters using advanced automated geomorphometric mapping approaches is necessary. Specifically, it would be valuable to interrogate the self-adapting ability of these automated mapping approaches under regional conditions to quantitatively analyse how the choice of terrain model and scale influences the extraction, generalisation, and representation of digitally derived terrain attributes such as slope gradient, elevation and terrain unit feature extent. Equally important is understanding how the variation in resulting terrain unit representation is limited by spatial resolution discontinuities that ultimately influence the extraction and representation of elementary soil properties. Chapter 4 is a shift from the technical aspects of digital terrain preprocessing and modelling and instead attempts to explore the contribution of gridded soil-landscape products to the abiotic landscape development agenda. It would be worthwhile to contextualise and decode these technical aspects of terrain and soil analyses to a holistic landscape development agenda. It is argued that current global environmental problems and questions demand exploration into new scientific perspectives and improved related paradigms and methodologies. Geodiversity (abiotic complexity) has not received the same level of attention as biodiversity (biotic complexity) despite its intrinsic and indivisible linkages to ecosystem and landscape richness characterisation. The ability to better describe the substrate in which biological and human activities occur is of top standing and must have its potential explored. To date, only one landmark study has successfully investigated the influence of environmental factors on geodiversity mapping in South Africa (Kori et al., 2019). Using an array of multimodal environmental covariates, including hydrographic, lithostratigraphic, pedological, climatic, topographic, solar morphometric and geomorphic variables, I aim to provide further confirmation to regional and international geodiversity research agendas. Chapter 5 culminates in applying quantitative DSM methods, with improved terrain representation, to classify productive soil units (ecotopes) as a proposed methodology to improve the current Bioresource Report Writer (BRW) soil-landscape recommendations. In KwaZulu-Natal, it has been accepted that detailed natural resource information based on scientifically accurate and relevant criteria is required to develop spatial layers that planners, developers, local government, and other stakeholders can use to guide future development. At present, the KwaZulu-Natal Department of Agriculture and Rural Development (KZNDARD) can provide high-level crop production approximations for various crops based on BioResource Units (BRU). However, the BRW has not seen a significant revision for over two decades. Still, the natural resource information it contains provides land managers, policymakers and farmers with invaluable access to regional and farm level qualitative estimations of agricultural productivity. There is a need to preserve this information while simultaneously providing modern measures of land management recommendation at multiple scales to the end-user. Against this backdrop, access to readily interpretable soil and crop information is increasingly being prioritised by provincial planning commissions as critical inputs to DSS for sustainable land management within KwaZulu-Natal.AFRIKAANSE OPSOMMING: Tans ontsluit 'n groot fokus van digitale grond kartering (DSM) in Suid-Afrika die grond landskap verhoudings van nalatenskap grond data deur die enigste bron van aaneenlopende grond inligting vir Suid-Afrika, die Nasionale Grondtipe-opname (ARC, 2003) te distreun. Elke land tipe word die beste gedefinieer as 'n homogene karterings eenheid met 'n unieke kombinasie van terrein tipe, grondpatroon en makro klimaat eienskappe (Paterson et al. , 2015) . Een van die heersende redes vir die LTS-langlewendheid en voortdurende temporale interoperabiliteit is dat terrein beskrywing uitdruklik verband hou met 'n reeks katalise grondeiendom beskrywings (Milne, 1936). Hierdie terrein tipes word verder verdeel in terrein morfologiese eenhede (TMUs) wat 'n reeks patrone verteenwoordig wat gebaseer is op 'n 5-eenheid landskap model van 1- kuif, 2-serp, 3-midslope, 4-voet en 5-vallei bodem. Belangrik, dominante grond verspreidings patrone word gedefinieer deur terrein eenhede wat staatmaak op 'n elementêre terrein topo-volgorde patroon benadering, met baie van die werk gedoen op modellering grond variasie wat verband hou met variasie in terrein (van Zijl, 2019). Terwyl die LTS bly 'n bron van nasionale belang; daar is enorme geleentheid om voort te bou op die bestaande grond voorraad data eerder as om net te fokus op "afbreek" (disaggregasie). Wat egter nodig is, is 'n standaard bedryfsprosedure wat nie net die vermoë van digitale hoogte modelle(DEM) gebruik om grond landskap verenigings buite die beperkte 5-eenheid landskap model te vererger nie, maar beter verfyning van grond beskrywings met landskap kenmerke moontlik te maak. Slegs sodra die nuanses van optimale DEM parametrisasie onder beheerde toestande ten volle verstaan word, kan die volledige omvang van DSM- en digitale geomorfologiese kartering (DGM) aansoeke ondersoek word. Hierdie verhandeling poog om-kennis oor teorie, metodes en toepassings van ute sintetiseer om afstand waarneming (RS) en geografiese inligtingstelsels (GIS) tesing om plaaslike land vorms te klassifiseer deur 'n patroonherkenning benadering vir verbeterde grond kartering in die konteks van multiskaal probleme van digitale terrein analise te klassifiseer. In KwaZulu-Natal. Die verhandeling word in drie dele verdeel. Deel een (Hoofstuk 2) verteenwoordig die DEM-voor verwerker- en veralgemenings metode en vestig die protokolle vir grondlandskap-kovariaat toediening afgelei van verskeie sensor platforms en ruimtelike skale. Deel twee (Hoofstuk 3) stel die konsep van verbeterde terrein eenheid kartering deur die geomorfon benadering bekend en beskryf DEM-optimalisering vir gestandaardiseerde geomorfon verteenwoordiging om grond landskap eienskappe eenvormig te beskryf vir insette tot DSM-toepassings. Ten slotte, deel drie (Hoofstukke 4 & 5) kyk na toepassings van DEM bronne en geomorfon eerste vanuit 'n holistiese landskap konteks deur die koppeling van digitale terrein en grond landskap analise aan geodiversiteit. Ten slotte word die voordeel van verbeterde RS en GIS gekombineer met kwantitatiewe modellerings benaderings op die verbetering van natuurlike hulpbron voorspellings ondersoek deur grond-ekopeïen- en grondtipe karterings eenhede te modelleer en verbeterings voor te stel aan 'n bestaande DSS wat vir KwaZulu-Natal ontwerp is. Spesifiek, tsy navorsing is organiseer in vier (4) navorsing hoofstukke met 'n oorsig van elke hoofstuk se bydrae wat hierna uiteengesit word. Hoofstuk 2 is verantwoordelik vir die erkenning en vereistes van DEM veralgemening van hoë tot medium resolusie RS platforms en die invloed wat hierdie preprocessing benaderings het op die onttrekking van 'n wye verskeidenheid van terrein eienskappe. Digitale hoogte data is elementêr in die afleiding van primêre topografiese eienskappe wat inset veranderlikes aan verskeie plaaslike grond landskap modelle is. DEMs se nut om verskillende topografiese indekse as primêre insette tot DSM te onttrek, laat die algemene grond vormende verhouding tussen topografie en grondeienskappe kwantitatief gemeet word. Tradisionele landskap skaal benaderings tot die onttrekking en ontleding van grond bly subjektief en 'n duur laaste uitweg vir grootskaalse streeks grond verspreiding en veranderlikheid voorspelling. Die keuse van die regte DEMs is 'n kritieke stap in die ontwikkeling van enige grond landskap model. Daarom is die vermoë om grond landskap verhoudings vinnig en objektief tussen grondeienskappe en landskap posisie te verteenwoordig deur opkomende tegnologieë en hoogte data in 'n digitale omgewing te gebruik en op verskillende skale fundamenteel vir die gebruik van grond landskap kartering as 'n streeksbeplanning instrument. Daar is egter steeds uiteenlopende konsensus oor die uitwerking van DEM-bron en resolusie oor die toepassing van hierdie topografiese eienskappe aan landskap- en geomorfiese karakterisering binne Suid-Afrika. Atkinson et al. (2017) het egter getoon dat topografiese veranderlike onttrekking baie afhanklik is van die DEM-bron en veralgemenings benadering. Alhoewel hoër resolusie-DEMs die "ware" landskap oppervlak meer akkuraat kan verteenwoordig, bied hulle nie noodwendig die beste resultate vir alle onttrokke terrein veranderlikes vir die modellering van grond landskap-uitsette nie. Gegewe die gerief van 'n wye verskeidenheid oopbron-hoogte data vir Suid-Afrika, is dit 'n behoefte om die impak wat DEM-veralgemenings benaderings het op die vereenvoudiging van gedetailleerde DEMs te kwantifiseer en die akkuraatheid en betroubaarheid van resultate tussen hoë resolusie en growwe resolusie data te vergelyk oor die onttrekking van gelokaliseerde topografiese veranderlikes as 'n primer vir grond landskap of digitale grond modelle. Hoofstuk 3 ondersoek die harmonisering van geomorfon wat van verskeie RS-platforms afkomstig is om die landskap karakter in Sentraal-KwaZulu-Natal te definieer. Robuuste DGM benaderings wat die insluiting van "menslike kennis" kan vereenvoudig en vertaal na outomatiese terrein klassifikasie oor 'n breër spektrum van terrein morfologiese eenhede en 'n verskeidenheid DEM ruimtelike skale bied groot potensiaal vir verbeterde topografiese en landskap analise en moet hul nut ondersoek. Voortdurende vooruitgang in kwantitatiewe modellering van oppervlak prosesse, gekombineer met nuwe spatio-temporale en geo-berekenings algoritmes, het die ou toklassifikasie en kartering van land vorm komponente omwentel deur die outomatiese analise van hoë gehalte DEMs. Daarom is 'n deeglike assessering van die effekte wat verskillende pixel resolusie (graan grootte) en DEM-bronne het op die replisering van waargenome geomorfiese ruimtelike patrone en verteenwoordig geselekteerde terrein parameters met behulp van gevorderde outomatiese geomorfon metriese karterings benaderings nodig. Spesifiek, dit sal waardevol wees om die self-aanpassing vermoë van hierdie outomatiese kartering benaderings onder streeks toestande te ondervra om kwantitatief te analiseer hoe die keuse van terrein model en skaal die onttrekking, veralgemening en voorstelling van digitaal afgeleide terrein kenmerke soos hellings gradiënt, hoogte- en terrein eenheid-funksie omvang beïnvloed. Ewe belangrik is om te verstaan hoe die variasie in gevolglike terrein eenheid verteenwoordiging beperk word deur ruimtelike resolusie-stakings wat uiteindelik die onttrekking en voorstelling van elementêre grondeienskappe beïnvloed Hoofstuk 4 is 'n verskuiwing van die tegniese aspekte van digitale terrein voor verwerking en modellering en poog eerder om die bydrae van geroosterde grond landskap produkte na die abiotiese landskap ontwikkelings agenda te verken. Ek sou die moeite werd wees om hierdie tegniese aspekte van terrein- en grond ontledings na 'n holistiese landskap ontwikkelings agenda te kontekstualiseer en te dekodeer. Daar word aangevoer dat huidige globale omgewingsprobleme en vrae eksplorasie in nuwe wetenskaplike perspektiewe en verbeterde verwante paradigmas en metodologieë vereis. Geodiversiteit (abiotiese kompleksiteit) het nie dieselfde vlak van aandag as biodiversiteit (biotiese kompleksiteit) ontvang nie, ten spyte van sy intrinsieke en ondeelbare verbande met ekosisteem- en landskap ryke karakterisering. Die vermoë om die substraat waarin biologiese en menslike aktiwiteite voorkom, beter te beskryf, is van bostaande en moet sy potensiaal ondersoek. Tot op hede het slegs een ander landmerk studie die invloed van omgewingsfaktore op geodiversiteits kartering in Suid-Afrika (Kori et al. , 2019). Met behulp van 'n verskeidenheid multimodale omgewings kovariaat, insluitend hidrografiese, lithostratigraphic, pedologiese, klimaat-, topografiese, son morfometriese en geomorfiese veranderlikes, beoog ek om verdere bevestiging te gee aan streeks- en internasionale geodiversiteits navorsing agendas. Hoofstuk 5 kulmineer in die toepassing van kwantitatiewe DSM-metodes, met verbeterde terrein verteenwoordiging, om produktiewe grondeenhede (ekotipes) te klassifiseer as 'n voorgestelde metodologie om die huidige BRW-grondlandskap aanbevelings te verbeter. In KwaZulu-Natal is aanvaar dat gedetailleerde natuurlike hulpbron inligting gebaseer op wetenskaplik akkurate en relevante kriteria nodig is om ruimtelike lae te ontwikkel wat beplanners, ontwikkelaars, plaaslike regering en ander belanghebbendes kan gebruik om toekomstige ontwikkeling te lei. Tans kan die KwaZulu-Natal Departement van Landbou en Landelike Ontwikkeling (KZNDARD) hoëvlak-gewasproduksie-benaderings vir verskeie gewasse op grond van BRUs verskaf. Die BRW het egter vir meer as twee dekades nie 'n beduidende hersiening gesien nie. Tog bied die natuurlike hulpbron inligting wat dit bevat, grond bestuurders, beleidmakers en boere van onskatbare waarde toegang tot streeks- en plaasvlak kwalitatiewe beramings van landbou produktiwiteit. Daar is 'n behoefte om hierdie inligting te bewaar, terwyl dit terselfdertyd moderne maatreëls van grondbestuur aanbeveling op verskeie skale aan die eindgebruiker verskaf. Teen hierdie agtergrond word toegang tot geredelik interpreteerbare grond- en gewas inligting toenemend deur provinsiale beplanningskommissie geprioritiseer as kritiese insette tot DSS vir volhoubare grondbestuur binne KwaZulu-Natal.Doctora

3D Spatial Data Infrastructures for web-based Visualization

In this thesis, concepts for developing Spatial Data Infrastructures with an emphasis on visualizing 3D landscape and city models in distributed environments are discussed. Spatial Data Infrastructures are important for public authorities in order to perform tasks on a daily basis, and serve as research topic in geo-informatics. Joint initiatives at national and international level exist for harmonizing procedures and technologies. Interoperability is an important aspect in this context - as enabling technology for sharing, distributing, and connecting geospatial data and services. The Open Geospatial Consortium is the main driver for developing international standards in this sector and includes government agencies, universities and private companies in a consensus process. 3D city models are becoming increasingly popular not only in desktop Virtual Reality applications but also for being used in professional purposes by public authorities. Spatial Data Infrastructures focus so far on the storage and exchange of 3D building and elevation data. For efficient streaming and visualization of spatial 3D data in distributed network environments such as the internet, concepts from the area of real time 3D Computer Graphics must be applied and combined with Geographic Information Systems (GIS). For example, scene graph data structures are commonly used for creating complex and dynamic 3D environments for computer games and Virtual Reality applications, but have not been introduced in GIS so far. In this thesis, several aspects of how to create interoperable and service-based environments for 3D spatial data are addressed. These aspects are covered by publications in journals and conference proceedings. The introductory chapter provides a logic succession from geometrical operations for processing raw data, to data integration patterns, to system designs of single components, to service interface descriptions and workflows, and finally to an architecture of a complete distributed service network. Digital Elevation Models are very important in 3D geo-visualization systems. Data structures, methods and processes are described for making them available in service based infrastructures. A specific mesh reduction method is used for generating lower levels of detail from very large point data sets. An integration technique is presented that allows the combination with 2D GIS data such as roads and land use areas. This approach allows using another optimization technique that greatly improves the usability for immersive 3D applications such as pedestrian navigation: flattening road and water surfaces. It is a geometric operation, which uses data structures and algorithms found in numerical simulation software implementing Finite Element Methods. 3D Routing is presented as a typical application scenario for detailed 3D city models. Specific problems such as bridges, overpasses and multilevel networks are addressed and possible solutions described. The integration of routing capabilities in service infrastructures can be accomplished with standards of the Open Geospatial Consortium. An additional service is described for creating 3D networks and for generating 3D routes on the fly. Visualization of indoor routes requires different representation techniques. As server interface for providing access to all 3D data, the Web 3D Service has been used and further developed. Integrating and handling scene graph data is described in order to create rich virtual environments. Coordinate transformations of scene graphs are described in detail, which is an important aspect for ensuring interoperability between systems using different spatial reference systems. The Web 3D Service plays a central part in nearly all experiments that have been carried out. It does not only provide the means for interactive web-visualizations, but also for performing further analyses, accessing detailed feature information, and for automatic content discovery. OpenStreetMap and other worldwide available datasets are used for developing a complete architecture demonstrating the scalability of 3D Spatial Data Infrastructures. Its suitability for creating 3D city models is analyzed, according to requirements set by international standards. A full virtual globe system has been developed based on OpenStreetMap including data processing, database storage, web streaming and a visualization client. Results are discussed and compared to similar approaches within geo-informatics research, clarifying in which application scenarios and under which requirements the approaches in this thesis can be applied

GIS-based landscape design research

Landscape design research is important for cultivating spatial intelligence in landscape architecture. This study explores GIS (geographic information systems) as a tool for landscape design research - investigating landscape designs to understand them as architectonic compositions (architectonic plan analysis). The concept ‘composition’ refers to a conceivable arrangement, an architectural expression of a mental construct that is legible and open to interpretation. Landscape architectonic compositions and their representations embody a great wealth of design knowledge as objects of our material culture and reflect the possible treatment of the ground, space, image and program as a characteristic coherence. By exploring landscape architectonic compositions with GIS, design researchers can acquire design knowledge that can be used in the creation and refinement of a design.&nbsp; The research aims to identify and illustrate the potential role of GIS as a tool in landscape design research, so as to provide insight into the possibilities and limitations of using GIS in this capacity. The critical, information-oriented case of Stourhead landscape garden (Wiltshire, UK), an example of a designed landscape that covers the scope and remit of landscape architecture design, forms the heart of the study. The exploration of Stourhead by means of GIS can be understood as a plausibility probe. Here the case study is considered a form of ‘quasi-experiment’, testing the hypothesis and generating a learning process that constitutes a prerequisite for advanced understanding, while using an adjusted version of the framework for landscape design analysis by Steenbergen and Reh (2003). This is a theoretically informed analytical method based on the formal interpretation of the landscape architectonic composition addressing four landscape architectonic categories: the basic, the spatial, the symbolic and the programmatic form. This study includes new aspects to be analysed, such as the visible form and the shape of the walk, and serves as the basis for the landscape architectonic analysis in which GIS is used as the primary analytical tool.&nbsp; GIS-based design research has the possibility to cultivate spatial intelligence in landscape architecture through three fields of operation: GIS-based modelling: description of existing and future landscape architectonic compositions in digital form; GIS-based analysis: exploration, analysis and synthesis of landscape architectonic compositions in order to reveal latent architectonic relationships and principles, while utilizing the processing capacities and possibilities of computers for ex-ante and ex-post simulation and evaluation; GIS-based visual representation: representation of (virtual) landscape architectonic compositions in space and time, in order to retrieve and communicate information and knowledge of the landscape design.&nbsp; Though there are limitations, this study exemplifies that GIS is a powerful instrument to acquire knowledge from landscape architectonic compositions. The study points out that the application of GIS in landscape design research can be seen as an extension of the fundamental cycle of observation, visual representation, analysis and interpretation in the process of knowledge acquisition, with alternative visualisations and digital landscape models as important means for this process. Using the calculating power of computers, combined with inventive modelling, analysis and visualisation concepts in an interactive process, opened up possibilities to reveal new information and knowledge about the basic, spatial, symbolic and programmatic form of Stourhead. GIS extended the design researchers’ perception via measurement, simulation and experimentation, and at the same time offered alternative ways of understanding the landscape architectonic composition. This gave rise to the possibility of exploring new elements in the framework of landscape design research, such as the visible form and kinaesthetic aspects, analysing the composition from eyelevel perspective. Moreover, the case study showcases that GIS has the potential to measure phenomena that are often subject to intuitive and experimental design, combining general scientific knowledge of, for instance, visual perception and way-finding, with the examination of site-specific design applications. GIS also enabled one to understand the landscape architectonic composition of Stourhead as a product of time, via the analysis of its development through reconstruction and evaluation of several crucial time-slice snapshots. The study illustrates that GIS can be regarded an external cognitive tool that facilitates and mediates in design knowledge acquisition. GIS facilitates in the sense that it can address the ‘same types of design-knowledge’ regarding the basic, spatial, symbolic and programmatic form, but in a more precise, systematic, transparent, and quantified manner. GIS mediates in the sense that it influences what and how aspects of the composition can be understood and therefore enables design researchers to generate ‘new types of design-knowledge’ by advanced spatial analysis and the possibility of linking or integrating other information layers, fields of science and data sources. The research contributes to the development and distribution of knowledge of GIS-applications in landscape architecture in two ways: (1) by ‘following’ the discipline and developing aspects of it, and (2) by setting in motion fundamental developments in the field, providing alternative readings of landscape architecture designs

Development of a base model for flood forecasting studies in the Humber River Basin (NL) and selection of an appropriate model forcing dataset

The Humber River basin (7860 km²) in Newfoundland is the second largest watershed on the island portion of the province. Efforts are underway to establish a base model for a flow forecasting system within the basin for flood damage mitigation and hydroelectric power optimization. This study examines three model forcing datasets (temperature and precipitation) and attempts to identify the best option based on the simulated streamflow amounts. In past stochastic studies, difficulty has been encountered due to a lack of observed data and the complexity of the hydrologic system, especially during the snowmelt period. Strong topographic influences within the basin limit the representativeness of observations. Given the strong topographic influences on orographic precipitation and temperature, the WATFLOOD gridded hydrologic model was selected, which permits the use of topographically adjusted gridded meteorological inputs as well as station data. Adjusted station data from APC2 (Second Generation Adjusted Precipitation for Canada), NARR (North American Regional Reanalysis) and CaPA (Canadian Precipitation Analysis) were used in the study. Based on 30-year run sequences, a base model able to translate weather and antecedent moisture to streamflow has been developed. Generation of initial conditions for forecasting purposes cannot rely on APC2 data due to its production lag. Instead, the NARR and CaPA products were evaluated against gridded station observations. Results indicated that APC2 produces the best results in terms of streamflow followed by NARR and CaPA. For model initialization purposes, the NARR precipitation dataset is recommended over CaPA for the Humber River

GIS-based landscape design research:

Landscape design research is important for cultivating spatial intelligence in landscape architecture. This study explores GIS (geographic information systems) as a tool for landscape design research - investigating landscape designs to understand them as architectonic compositions (architectonic plan analysis). The concept ‘composition’ refers to a conceivable arrangement, an architectural expression of a mental construct that is legible and open to interpretation. Landscape architectonic compositions and their representations embody a great wealth of design knowledge as objects of our material culture and reflect the possible treatment of the ground, space, image and program as a characteristic coherence. By exploring landscape architectonic compositions with GIS, design researchers can acquire design knowledge that can be used in the creation and refinement of a design.&nbsp; The research aims to identify and illustrate the potential role of GIS as a tool in landscape design research, so as to provide insight into the possibilities and limitations of using GIS in this capacity. The critical, information-oriented case of Stourhead landscape garden (Wiltshire, UK), an example of a designed landscape that covers the scope and remit of landscape architecture design, forms the heart of the study. The exploration of Stourhead by means of GIS can be understood as a plausibility probe. Here the case study is considered a form of ‘quasi-experiment’, testing the hypothesis and generating a learning process that constitutes a prerequisite for advanced understanding, while using an adjusted version of the framework for landscape design analysis by Steenbergen and Reh (2003). This is a theoretically informed analytical method based on the formal interpretation of the landscape architectonic composition addressing four landscape architectonic categories: the basic, the spatial, the symbolic and the programmatic form. This study includes new aspects to be analysed, such as the visible form and the shape of the walk, and serves as the basis for the landscape architectonic analysis in which GIS is used as the primary analytical tool.&nbsp; GIS-based design research has the possibility to cultivate spatial intelligence in landscape architecture through three fields of operation: GIS-based modelling: description of existing and future landscape architectonic compositions in digital form; GIS-based analysis: exploration, analysis and synthesis of landscape architectonic compositions in order to reveal latent architectonic relationships and principles, while utilizing the processing capacities and possibilities of computers for ex-ante and ex-post simulation and evaluation; GIS-based visual representation: representation of (virtual) landscape architectonic compositions in space and time, in order to retrieve and communicate information and knowledge of the landscape design.&nbsp; Though there are limitations, this study exemplifies that GIS is a powerful instrument to acquire knowledge from landscape architectonic compositions. The study points out that the application of GIS in landscape design research can be seen as an extension of the fundamental cycle of observation, visual representation, analysis and interpretation in the process of knowledge acquisition, with alternative visualisations and digital landscape models as important means for this process. Using the calculating power of computers, combined with inventive modelling, analysis and visualisation concepts in an interactive process, opened up possibilities to reveal new information and knowledge about the basic, spatial, symbolic and programmatic form of Stourhead. GIS extended the design researchers’ perception via measurement, simulation and experimentation, and at the same time offered alternative ways of understanding the landscape architectonic composition. This gave rise to the possibility of exploring new elements in the framework of landscape design research, such as the visible form and kinaesthetic aspects, analysing the composition from eyelevel perspective. Moreover, the case study showcases that GIS has the potential to measure phenomena that are often subject to intuitive and experimental design, combining general scientific knowledge of, for instance, visual perception and way-finding, with the examination of site-specific design applications. GIS also enabled one to understand the landscape architectonic composition of Stourhead as a product of time, via the analysis of its development through reconstruction and evaluation of several crucial time-slice snapshots. The study illustrates that GIS can be regarded an external cognitive tool that facilitates and mediates in design knowledge acquisition. GIS facilitates in the sense that it can address the ‘same types of design-knowledge’ regarding the basic, spatial, symbolic and programmatic form, but in a more precise, systematic, transparent, and quantified manner. GIS mediates in the sense that it influences what and how aspects of the composition can be understood and therefore enables design researchers to generate ‘new types of design-knowledge’ by advanced spatial analysis and the possibility of linking or integrating other information layers, fields of science and data sources. The research contributes to the development and distribution of knowledge of GIS-applications in landscape architecture in two ways: (1) by ‘following’ the discipline and developing aspects of it, and (2) by setting in motion fundamental developments in the field, providing alternative readings of landscape architecture designs

Soil Erosion in a Highly Dynamic, Terraced Environment - the Effect of the Three Gorges Dam in China

Worldwide, soil erosion is one of the most pressing environmental problems of present times. Particularly, soil erosion triggered by overland flow and runoff seriously affects the productivity and stability of ecosystems. The loss of fertile topsoil and soil's water storage capacity, and the discharge of sediments and associated contamination of waterbodies due to diffuse matter transport of particle-bounded agrochemicals from cropland highly elicit call a for action to combat soil erosion for a future securing of food supply and high drinking water quality. Globally, China belongs to one of those countries most affected by soil erosion. Technical problems as well as high economic off-site damages and costs resulting from reservoir siltation and thus, reduced project's lifespan due to soil erosion are typical for numerous large-scale dam projects in China. In addition to the natural disposition to soil erosion, especially, anthropogenic impacts associated to the dam construction distinctly affect the soil erosion risk potential in the adjacent ecosystems. This can be exemplarily seen at the currently worldwide largest dam project, the Three Gorges Dam at the Yangtze River in Central China. This megaproject has been controversially discussed since its planning, and most recently since its construction and full operation in 2007. It contains the largest installed hydropower capacity worldwide, and is supposed to distinctly improve the river navigation and to secure the water supply to the northern country in the long-term. The realization of the dam project has already required massive resettlements of rural and urban population of more than one million people long before its start of operation. Additionally, large-scale land use changes, e.g., land reclamation for the road and settlement construction, for small scale subsistence farming and for cash crop production as well as shifts in land uses, on the steep sloping uphill-site above the impounded area are expected to considerably foster the soil erosion in the short- to long-term. Due to their partially direct connection to the stream network agriculturally used land with high soil erosion potential affects the water quality. Precise knowledge on the quality and quantity of soil loss, and its spatial and temporal variability can help to control the soil erosion by developing an adapted land use management and identifying conducive soil conservation measures, such as contour-aligned bench terraces. Under optimum conditions, bench terraces balance the geomorphic settings and anthropogenic use and can present a fair and sound basis for economic growth in mountainous areas. The focus of the present thesis lies on the risk potential of soil erosion by water in the newly created reservoir of the Three Gorges Dam. Therefore, the central research questions aimed at the natural soil erosion risk potential and the effect of the dam-induced land use dynamics on the dimension and spatial and temporal distribution of soil losses. Due to the data scarcity and limited access to the terrain, a further focus of the research conducted lied on the data-based regionalization of soil erosion factors to use as input in soil erosion modeling. The research was conducted in the subtropical Xiangxi catchment (3,200 km²) that was considered to adequately represent the Three Gorges Area in terms of physical settings and human interventions attributing to the dam project. The Xiangxi River joins the Yangtze River as a first class tributary approximately 40 km upstream the Three Gorges Dam. Due to the dam construction, the widely terraced landscape of the Xiangxi catchments is also affected by rapid, high land use dynamics with consequences on the slope stability. Particularly, the backwater area in the southern catchment area with the impounded lower reach of the Xiangxi River is characterized by steep to extremely steep sloping terrain and predominantly shallow soils with moderate to very high soil erodibility. Additionally, the very high rainfall erosivity increases the high physical vulnerability of the entire Xiangxi catchment. Between 1987 and 2007, a governmental-driven decrease of arable land and an increase of woodland and shrubland affected the northern headwater zone of the catchment. In the immediate reservoir area, the land use change from 1987 to 2007 was mainly controlled by a distinct conversion of arable land to orange orchards. Within the framework of this thesis, methods for data survey and data processing were tested and adapted in order to evaluate the risk potential of soil erosion. In addition, comprehensive field investigations focusing on soil erosion processes and on pedological properties and further erosion-relevant factors were conducted. Relevant parameters derived from remote sensing data and land use classifications as well as the documented land use change from 1987 to 2007 were used for the parameterization of the empirical soil erosion model RUSLE. This model was applied to estimate and evaluate the spatial distribution and dynamic of the soil erosion risk potential, and to spatially localize high-risk areas. The new conceptual model TerraCE was developed and tested for the identification and spatial analysis of different terrace conditions and their causes. By means of data mining approaches, a prediction of the spatial distribution of the identified terrace conditions was computed. By integrating environmental and anthropogenic indicators on the impact of the terrain and the human influence, the causes and the strength of disturbances on the terrace conditions, and thus terrace degradation were analyzed. During the observation period from 1987 to 2007, the Xiangxi catchment is generally characterized by a decrease of average annual soil losses and their maxima due to implemented environmental programs. However, a very high soil erosion risk potential in the entire catchment must be assumed. Frequency and intensity of soil erosion mainly concentrate in the backwater area at the lower reaches of the Xiangxi River. Here, land use changes, resettlements, and infrastructure construction have the highest impact. An inadequate construction of terraces that is not adapted to the local terrain conditions and an insufficient maintenance of the farming terraces can further strongly affect the soil erosion dynamic. Moreover, rapid ecosystem changes and an associated intensification and reclamation of terraces can lead to their degradation. The tempo of the land use dynamics hardly considers available capital and labor for the cost and time-consuming restoration and maintenance of terraces, mainly cultivated with oranges. The high increase of the reclaimed area for the orange production within very short term caused a surplus production and thus, a price decline on the local and regional markets. Due to the not very profitable sale of oranges, a lack of farmers' motivation and little or no capital are made responsible for the gradual worsening of the terrace conditions. As many of the resettled peasants, that were formerly used to farm the flat valley bottoms, are often not familiar with the new and difficult terrain settings and farming techniques, there is also a lack of knowledge on adequate terrace cultivation. Subsequently, inappropriate management of those terraces leads to an increase in the soil erosion The findings of the present thesis suggest designating the terraces as important, sensitive ecosystem service as they present - if properly maintained - a very effective soil erosion control and enable for a sustainable land use in the mountainous Xiangxi catchment and throughout the entire Three Gores Area. Considering the data scarcity in terms of spatial and temporal resolution, the results further show that soil erosion factors can be successfully regionalized and used for a valid soil erosion modeling. Against the background of ongoing research within the 'Yangtze Project' as well as further projected large dam projects at the Yangtze River and worldwide, the research conducted offers an important starting point for further research on the soil erosion risk potential and associated environmental threats, such as water pollution