Academic literature on the topic 'Topographic wetness index'

Flood is the most frequent disaster occured in Indonesia. Flood events result in loss and damage to communities and the environment. Floods are triggered by several factors including hydrometeorological factors, topography, geology, soil and human activities. Topographic factor is one of the flood trigger control factors. Topographic calculation for flood inundation detection can be done by Topographic Wetness Index (TWI) method. The TWI method focuses on topographic conditions of the region, especially the upper slopes and lower slopes to assess the trend of water accumulation in a region. TWI calculations are based on the topography of an area represented by DEM (Digital Elevation Model) data in the form of DTM (Digital Terrain Model). The high value of TWI is associated with high flood vulnerability. Based on the calculation of TWI value, flood-prone areas in Kebumen District include Adimulyo Subdistrict, Puring Subdistrict, Ambal Subdistrict, Rowokele Subdistrict and Buayan Subdistrict.

Methods using remote sensing associated with artificial intelligence to forecast corn yield at the management zone level can help farmers understand the spatial variability of yield before harvesting. Here, spectral bands, topographic wetness index, and topographic position index were integrated to predict corn yield at the management zone using machine learning approaches (e.g., extremely randomized trees, gradient boosting machine, XGBoost algorithms, and stacked ensemble models). We tested four approaches: only spectral bands, spectral bands + topographic position index, spectral bands + topographic wetness index, and spectral bands + topographic position index + topographic wetness index. We also explored two approaches for model calibration: the whole-field approach and the site-specific model at the management zone level. The model’s performance was evaluated in terms of accuracy (mean absolute error) and tendency (estimated mean error). The results showed that it is possible to predict corn yield with reasonable accuracy using spectral crop information associated with the topographic wetness index and topographic position index during the flowering growth stage. Site-specific models increase the accuracy and reduce the tendency of corn yield forecasting on management zones with high, low, and intermediate yields.

Topographic parameters of high-resolution digital elevation models (DEMs) with meter to sub-meter spatial resolution, such as slope, curvature, openness, and wetness index, show the spatial properties and surface characterizations of terrains. The multi-parameter relief map, including two-parameter (2P) or three-parameter (3P) information, can visualize the topographic slope and terrain concavities and convexities in the hue, saturation, and value (HSV) color system. Various combinations of the topographic parameters can be used in the relief map, for instance, using wetness index for upstream representation. In particular, 3P relief maps are integrated from three critical topographic parameters including wetness or aspect, slope, and openness data. This study offers an effective way to explore the combination of topographic parameters in visualizing terrain features using multi-parameter relief maps in badlands and in showing the effects of smoothing and parameter selection. The multi-parameter relief images of high-resolution DEMs clearly show micro-topographic features, e.g., popcorn-like morphology and rill.

Research Highlights: A Topographic Wetness Index calculated using LiDAR-derived elevation models can help in identifying unpaved forest roads that need maintenance. Materials and Methods: Low-pulse LiDAR data were used to calculate a Topographic Wetness Index to predict unpaved forest roads’ quality. Results: The results of this analysis and comparison of road-quality features derived from LiDAR data at resolutions of 1, 10 and 25 m for assessing road quality in the boreal forests of Finnish Lakeland show that the wetness index can predict road quality correctly in up to 70% of cases and up to 86% when combined with other auxiliary GIS-based variables. Conclusions: Road-quality assessments, using airborne LiDAR data, can greatly help forest managers to decide which sections of the ageing road network will benefit the most from maintenance, while reducing the need of field visits.

Land suitability is the fitness of a given type of land for a defined use. The land may be considered in its present condition or after improvements. There are several methods used for land suitability analysis. In the paper, an attempt is made to derive land suitability classes by considering relief, landforms, slope, aspect, topographic wetness index (TWI), soils, soil texture, and erosion-prone areas. The relief map is prepared by digitizing contours from the Survey of India’s topographic maps in 1:50,000 scale. SRTM data also used to derive contours, slope, aspect, and topographic wetness index. The study area is chosen in Kannur district in Kerala State. It is situated in the northern part of Kerala. All these eight parameters were digitized using ArcGIS software. Weighted overlay analysis was done for identifying land suitability for agriculture, and derived into different classes based on values and labeled as most suitable (S1), moderately suitable (S2), marginally suitable (S3), not suitable (NS1), and not suitable (NS2). This analysis will be useful for identifying the main limiting factors for agricultural production and enables decision-makers to develop crop management able to increase land productivity. Keywords: Land suitability; topographic wetness index; Weighted overlay analysis

The topographic wetness index (TWI), frequently used in approximately characterizing the spatial distribution of soil moisture and surface saturation within a watershed, has been widely applied in topography-related geographical processes and hydrological models. However, it is still questionable whether the current algorithms of TWI can adequately model the spatial distribution of topographic characteristics. Based upon the widely-used multiple flow direction approach (MFD), a novel MFD algorithm (NMFD) is proposed for improving the TWI derivation using a Digital Elevation Model (DEM) in this study. Compared with MFD, NMFD improves the mathematical equations of the contributing area and more precisely calculates the effective contour length. Additionally, a varying exponent strategy is adopted to dynamically determine the downslope flow-partition exponent. Finally, a flow-direction tracking method is employed to address grid cells in flat terrain. The NMFD algorithm is first applied to a catchment located upstream of the Hanjiang River in China to demonstrate its accuracy and improvements. Then NMFD is quantitatively evaluated by using four types of artificial mathematical surfaces. The results indicate that the error generated by NMFD is generally lower than that computed by MFD, and NMFD is able to more accurately represent the hydrological similarity of watersheds.

Abstract The paper presents the results of research on the relationship between topography of undulated morainic plateau of postglacial landscape and distribution of organic carbon stocks in soil toposequences. The mean value of the soil organic carbon stocks (SOCS) for Retisols/Luvisols (RT/LV) was statistically lower than for the Phaeozems/Gleysols (PH/GL) but for RT/LV a higher variation of SOCS in comparison to PH/GL was observed. On the basis of Pearson correlation coefficient, the cartographic depth to water (DTW), the topographic wetness index (TWI) and the saga wetness index (SWI) were the most strongly correlated with the SOCS from among 13 analysed topographic attributes. In addition, the DTW was more correlated with SOCS than other topographic variables. Moreover, the DTW based on the channel networks with 2 ha flow initiation thresholds better correlate with SOCS than DTW obtained on the basis of channel networks with 1 ha and 4 ha flow initiation thresholds. Using Stepwise multiple regression analysis (SMLR), we concluded that the topographic attributes controlling the soil water content and slope shape had most impact on SOCS of the undulated morainic plateau of agricultural ecosystem. In this landform, where the RT/LV and PH/GL soil sequences dominate, the SOCS can be estimated by the DTW, TWI and GC (general curvature) with an estimation error of 0.21 kg m−2. In view of the increasing availability of LiDAR data and power of GIS tools, the use of topographic metrics to assess spatial variability of soil properties will play an increasingly important role in the estimation of soil properties.

Coping flood hazard risk needs to be done early on. One way of handling floods from the beginning is to predict flood-prone areas with topographic wetness index method. Serang regency is a fairly frequent area of flooding therefore it is necessary to conduct a study to predict flood-prone areas. The total area of flood-prone areas in Serang Regency is 62,608 Ha based on TWI saga modeling results. The area is dominated by high and low class with 25,050 Ha and 29,741 Ha respectively. While for the middle class of 7,817 ha.

Hydrological modeling, like runoff modelling for flood prevention, is based on digital elevation models (DEMs). The fact that the DEMs do not represent existing road culverts can lead to considerable hydrological misinterpretations. In order to overcome this limitation, a GIS method was developed to automatically adjust the elevation model, hydrologically enforcing the DEM, so that the results of hydrological modeling accounts for flow through culverts. The hydro-enforced DEM showed to better represent the drainage network than the former DEM when compared with the river map. The topographic wetness index is the most commonly applied topographic index and a good indicator of soil moisture distribution. It has been integrated into many hydrological models and pollution risk indices as well as into the prediction of wetland distribution. Using the hydro-DEM from the previous step and the soil map in conjunction with the TWI, an improved TWI was achieved, namely a soil-topographic wetness index (STI). The linkages between specific soil types and TWI or STI values were analyzed. They revealed a clear linkage between STI values and soil type based on the soil transmissivity (R2=0.77). However, the TWI values showed low correlations to the soil types (R2=0.02). As a specific application, both TWI and STI were tested for the detection of wetlands. Wetlands are important ecosystems which act as buffer zones by filtering pollutants and slowing floodwater. Being able to identify their distribution is important in landscape planning and ecology. A wetland threshold value was determined for each index and their results where compared with the wetland map from the property map (assumed as ground truth) and with the potential wetland area. Finally, a visual validation was performed with the use of an aerial photography. The results showed that the STI performed slightly better than the TWI for the detection of wetlands, detecting 3% more wetlands. The impact of the soil map on the topographic wetness index was therefore determined as positive.

A method was developed for extending a fine-scaled forest gap model to a watershed-scaled landscape, using the Eastern Cross Timbers ecoregion as a case study for the method. A topographic wetness index calculated from digital elevation data was used as a measure of hydrologic across the modeled landscape, and the gap model modified to have with a topographically-based hydrologic input parameter. The model was parameterized by terrain type units that were defined using combinations of USDA soil series and classes of the topographic wetness index. A number of issues regarding the sources, grid resolutions, and processing methods of the digital elevation data are addressed in this application of the topographic wetness index. Three different grid sizes, 5, 10, and 29 meter, from both LiDAR-derived and contour-derived elevation grids were used, and the grids were processed using both single-directional flow algorithm and bi-directional flow algorithm. The result of these different grids were compared and analyzed in context of their application in defining terrain types for the forest gap model. Refinements were made in the timescale of gap model’s weather model, converting it into a daily weather generator, in order to incorporate the effects of the new topographic/hydrologic input parameter. The precipitation model was converted to use a Markov model to initiate a sequence of wet and dry days for each month, and then daily precipitation amounts were determined using a gamma distribution. The output of the new precipitation model was analyzed and compared with a 100-year history of daily weather records at daily, monthly, and annual timescales. Model assumptions and requirements for biological parameters were thoroughly investigated and questioned. Often these biological parameters are based on little more than assumptions and intuition. An effort to base as many of the model’s biological parameters on measured data was made, including a new technique for estimating optimal volumetric growth rate by measuring tree rings. The gap model was set up to simulate various terrain types within the landscape.

Submitted by Rafael Marini Paschoaletti Perri dos Santos (rafaelmpps@hotmail.com) on 2017-10-30T19:28:34Z No. of bitstreams: 2 PPGAA_ Dissertação_Rafael Marini PP Santos_2017 (1).pdf: 3014297 bytes, checksum: f71dea6e56def749b21f955b1a8a1ad5 (MD5) Encaminhamento_Dissertação_Rafael Marini dos Santos_PPGAA.pdf: 792545 bytes, checksum: eec6f1001daf58a9614a859a1d455837 (MD5)
Approved for entry into archive by Alini Demarchi (alini@cca.ufscar.br) on 2017-11-30T16:55:11Z (GMT) No. of bitstreams: 2 PPGAA_ Dissertação_Rafael Marini PP Santos_2017 (1).pdf: 3014297 bytes, checksum: f71dea6e56def749b21f955b1a8a1ad5 (MD5) Encaminhamento_Dissertação_Rafael Marini dos Santos_PPGAA.pdf: 792545 bytes, checksum: eec6f1001daf58a9614a859a1d455837 (MD5)
Approved for entry into archive by Alini Demarchi (ri.bar@ufscar.br) on 2018-01-15T18:25:58Z (GMT) No. of bitstreams: 2 PPGAA_ Dissertação_Rafael Marini PP Santos_2017 (1).pdf: 3014297 bytes, checksum: f71dea6e56def749b21f955b1a8a1ad5 (MD5) Encaminhamento_Dissertação_Rafael Marini dos Santos_PPGAA.pdf: 792545 bytes, checksum: eec6f1001daf58a9614a859a1d455837 (MD5)
Made available in DSpace on 2018-02-01T13:31:38Z (GMT). No. of bitstreams: 2 PPGAA_ Dissertação_Rafael Marini PP Santos_2017 (1).pdf: 3014297 bytes, checksum: f71dea6e56def749b21f955b1a8a1ad5 (MD5) Encaminhamento_Dissertação_Rafael Marini dos Santos_PPGAA.pdf: 792545 bytes, checksum: eec6f1001daf58a9614a859a1d455837 (MD5) Previous issue date: 2017-06-27
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Nowadays, society has a challenge to deal with sustainable water use. High demand and water contamination, environmental degradation and the unpredictability of climate changes are some water insecurity causes. Riparian forests maintenance offers water ecosystems services, but in some cases the riparian ecosystem is in a degraded condition that require human intervention actions for forest restoration. In this way, geotechnologies help us to infer about physical landscape characteristics where watershed is a basic unity for environmental planning. This study aimed to identify important hydrologically areas of Consulta stream watershed and Retiro stream watershed and propose priorities areas for forest restoration and sustainable agricultural destination. The two watersheds are the main sources of public water supply in the city of Bebedouro (Brazil). It is hypothesized that the limits established by Brazilian forest law (BFL) riparian buffers zones may not fully guarantee the two watersheds riparian areas protection. It was assumed that the forest community plays an important role in the attenuation of chemical elements and sediments, and that is essential that there is a disruption of potentially polluting activities near riparian areas. It was used in the study images from orbital sensors spatial resolution 30 m and 90 m and topographical map 1:50.000 for obtaining and processing elevations data and land use in geographic information system (GIS), and environmental legislation. The results allowed to characterize the watersheds that are surrounding and presented similarities in their physical parameters (basin form, drainage density, channel length, and others) and the Topographic Wetness Index (TWI) class distribution, slope class, landscape elements and land use. Three scenarios of priority areas for forest restoration were generated. It was observed that the priority areas are distributed close to the drainage channel of watersheds and are partially related to required areas by BFL. It can be concluded that in the three scenarios established the BFL may not be sufficient for the full protection of riparian sites and the adopted methodology proved to be efficient for guiding water resources management actions at larges scales.
Resolver conflitos relacionados ao uso da água é um desafio para a sociedade atual. Dentre os fatores que preocupam a segurança hídrica destacam-se a crescente demanda de consumo, a contaminação dos mananciais, a degradação de áreas naturais e a imprevisibilidade das mudanças climáticas que resultam em períodos irregulares de secas e estiagens. As matas ripárias oferecem funções importantes para os serviços ecossistêmicos de provisão hídrica, mas em algumas regiões encontram-se degradadas e com baixa resiliência, necessitando de ações de restauração florestal. As geotecnologias permitem inferir as características físicas da paisagem e a microbacia hidrográfica (MBH) é uma unidade básica para o planejamento ambiental. Este trabalho teve por objetivo identificar áreas hidrologicamente importantes nas MBHs do Córrego da Consulta e do Córrego do Retiro, de abastecimento público do município de Bebedouro (SP), e propor áreas prioritárias para a restauração florestal e manejo diferenciado. A hipótese é que as áreas de preservação permanente (APPs) de 30 m não são suficientes para abranger por completo as áreas ripárias destas MBHs. Considerou-se a eficiência da comunidade florestal em atenuar agentes químicos, sedimentos e a necessidade de interrupção de atividades potencialmente poluidoras próximas às áreas ripárias. Foram utilizadas imagens orbitais com resoluções espaciais de 30 m e 90 m, carta topográfica em escala 1:50.000 para obtenção e processamento de dados de elevação e uso e ocupação dos solos em sistema de informações geográficas (SIG), e legislação ambiental pertinente. Os resultados permitiram caracterizar as duas MBHs que são circunvizinhas e apresentaram semelhanças nos seus parâmetros físicos (fator de forma de bacia, densidade de drenagem, comprimento de canais, entre outros), na distribuição das classes do índice topográfico de umidade (ITU), de classes de declividade, de elementos de paisagem e de uso e ocupação dos solos. Foram gerados três cenários de áreas prioritárias para a restauração florestal. Observou-se que as áreas prioritárias para a restauração florestal e manejo diferenciado estão distribuídas próximas ao canal de drenagem das MBHs e estão relacionadas às APPs. Conclui-se que, nos três cenários estabelecidos, as APPs não são suficientes para a integral proteção de locais de caráter ripário e a metodologia adotada se mostrou eficiente para apontar ações de gestão de recursos hídricos em escalas maiores.

Sweden have faced decreasing groundwater storage with critical low groundwater levels for several years. Gotland is one example with issues of providing freshwater due to the low groundwater levels. These circumstances can be related to impacts caused by early agriculture development, an increased demand of freshwater and climate change. There is a need in this region to increase the groundwater storage to ensure enough freshwater. The aim of the study is to increase freshwater storage. Digital geographical information system (GIS) was chosen as a tool in this study in order to cover large geographical areas.  The study was divided into two parts, with focus to determine hydrological and hydrogeological conditions and to identify suitable areas where groundwater storage could be increased. The first part studied: specific capacity, groundwater storage, groundwater balance and topographic wetness index. The second part locked at four methods to increase freshwater storage: Lakes, controlled drainage, wetland and subsurface dam. The result tells us that lakes have the potential to provide freshwater for the municipal distribution network. The controlled drainage method has the ability reduce the outflow of surface water and to increase the groundwater infiltration. Earlier drained wetland areas was identified which could serve as freshwater storage. Suitable areas for subsurface dams were identified. They could work as a large groundwater storage as a decentralized system with the ability to provide groundwater for wells that are spread out. However the identified areas for each methods needs further investigations in more detail to determine the accuracy of the results.

Temporary streams have received undeservedly little scientific attention and as a result their role in hydrological, biogeochemical and ecological processes is not yet fully understood. The ultimate goal of the research was to gain a better understanding of the temporary stream network and the processes that control it and determine how the active and connected stream length change with catchment wetness conditions to find simple methods to map seasonal and event-based changes in temporary flowing stream networks. Streams, springs and wetlands of four relatively small headwater catchments (11.7 – 25.3 km2) and one wetland in the steep and remote Zwäckentobel catchment in Alptal, canton Schwyz (Switzerland), were mapped and stream segments were classified by flow type during different weather conditions using direct observations. The mapping was performed by an elite orienteer with mapping experience. The variation in streamflow was analysed and related to the catchment wetness and topography using the TWI-values and the upslope accumulated area of the stream segments. As the catchments wetted up in response to fall rainfall events after a dry summer the flowing stream density increased up to five times and the connected stream density increased up to six times with a 150-fold increase in discharge. Also the number of flowing stream heads increased up to ten times. The best description of the pattern of stream expansion is a combination of the variable source area and the element threshold concepts, where surface topography, particularly TWI (Topographic Wetness Index) and upslope accumulated area (A), and local storage areas controls where streamflow is initiated and how flow in different stream segments connects. Streams in the Alptal show a seasonally bottom up or disjointed connection pattern. Mapping the temporary streams in steep and remote watersheds as a function of hydrological conditions is not an easy task. It is however necessary in order to fully understand where water is flowing or not. A combination of field observations with monitoring equipment can facilitate this extensive work by providing a more detailed temporal resolution.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Social demands on soil information have grown dramatically, meanwhile the soil surveys are seldom carried out in the country. Digital soil mapping techniques can be applied to infer the spatial distribution of soil from existing soil maps or from reference areas, extrapolating this information to areas not mapped. The purpose of this study was to apply in a Geographic Information System the Multiple Logistic Regressions (MLR) using Principal Components (PC) as explanatory variables to predict soil classes spatial distribution. The study area was the region of municipality São Pedro do Sul / RS. For the development of predictive models a set of nine terrain attributes were used. Model training was executed on an existing soil map and with a survey carried out in a reference area, both in a 1:50.000 scale. The first three retained PC explained 65.57% of the data variability. The predictive models which used PC had lower values of kappa index. The most accurate predicted map reached a kappa value of 63.20% and was generated by using the nine attributes of land as predictive covariates. The mapping accuracy is sensitive to similarities between the mapped classes, and mapping in a more homogeneous categorical level reduces the accuracy of the predicted maps. Soil classes relatively not representative in the training maps are not properly spatialized. The use of MLR allows spatializing of soil classes to areas not mapped, although the use of PC needs to be tested with a larger number of covariates.
As demandas da sociedade pela informação solo têm crescido, porém levantamentos pedológicos praticamente não ocorrem mais no país. Técnicas de Mapeamento Digital do Solo podem ser empregadas para inferir a distribuição espacial de classes de solos a partir de mapas existentes e áreas de referência, extrapolando esta informação para áreas não mapeadas. O objetivo deste estudo foi empregar em um Sistema de Informações Geográficas as Regressões Logísticas Múltiplas (RLM) utilizando-se de Componentes Principais (CP) como variáveis explicativas para a predição espacial de classes de solos. A área de estudo foi na região do município de São Pedro do Sul / RS. Para o desenvolvimento dos modelos preditivos foram utilizados um conjunto de nove atributos do terreno. O treinamento dos modelos foi executado em um mapa de solos existente, e em um levantamento realizado em áreas de referência, ambos na escala 1:50.000. As três primeiras CP retidas explicaram 65,57% da variabilidade dos dados. Os modelos preditivos que empregaram CP obtiveram menores valores do índice kappa. O mapa predito mais acurado empregou os nove atributos do terreno e alcançou um valor de kappa de 63,20%. A acurácia do mapeamento é sensível a semelhança entre as classes mapeadas, e o mapeamento em níveis categóricos mais homogêneos reduz a precisão dos mapas preditos. Classes de solos relativamente pouco representativas não são corretamente espacializadas. O emprego de RLM permite espacializar classes de solos para áreas não mapeadas, embora o emprego de CP necessite ser testado com um maior número de covariáveis.

Les forêts tropicales abritent la plus grande diversité d'espèces au monde, un fait qui reste en partie inexpliqué et dont l'origine est sujette à débat. Même à l'échelle de l'hectare, les forêts tropicales abritent des genres riches en espèces, avec des espèces d’arbres étroitement apparentées qui coexistent en sympatrie. En raison de contraintes phylogénétiques, on s'attend à ce que les espèces étroitement apparentées possèdent des niches et des stratégies fonctionnelles similaires, ce qui questionne les mécanismes de leur coexistence locale. Les espèces étroitement apparentées peuvent former un complexe d'espèces, composé d’espèces morphologiquement similaires ou qui partagent une importante proportion de leur variabilité génétique en raison d'une ascendance commune récente ou d'hybridation, et qui peut résulter d'une radiation écologique adaptative des espèces selon des gradients environnementaux. Malgré le rôle clé des complexes d'espèces dans l'écologie, la diversification et l'évolution des forêts néotropicales, les forces éco-évolutives qui créent et maintiennent la diversité au sein des complexes d'espèces néotropicales restent peu connues. Nous avons exploré la variabilité génétique intraspécifique comme un continuum au sein de populations structurées d'espèces étroitement apparentées, et mesuré son rôle sur la performance individuelle des arbres à travers la croissance dans le temps, tout en tenant compte des effets d'un environnement finement caractérisé au niveau abiotique et biotique. En combinant des inventaires forestiers, des données topographiques, des traits fonctionnels foliaires et des données de capture de gènes dans la station de recherche de Paracou, en Guyane Française, nous avons utilisé la génomique des populations, les analyses d'associations environnementales et génomiques, et la modélisation Bayésienne sur les complexes d'espèces Symphonia et Eschweilera clade Parvifolia. Nous avons montré que les complexes d'espèces d'arbres couvrent l’ensemble des gradients locaux de topographie et de compétition présents dans le site d'étude alors que la plupart des espèces qui les composent présentent une différenciation de niche marquée le long de ces mêmes gradients. Plus précisément, dans les complexes d'espèces étudiés, la diminution de la disponibilité en eau, par exemple depuis les bas-fonds jusqu’aux plateaux, a entraîné une modification des traits fonctionnels foliaires, depuis des stratégies d'acquisition à des stratégies conservatrices, tant entre les espèces qu'au sein de celles-ci. Les espèces de Symphonia sont génétiquement adaptées à la distribution de l'eau et des nutriments, elles coexistent donc localement en exploitant un large gradient d'habitats locaux. Inversement, les espèces d'Eschweilera sont différentiellement adaptées à la chimie du sol et évitent les habitats les plus humides et hydromorphes. Enfin, les génotypes individuels des espèces de Symphonia sont différentiellement adaptés pour se régénérer et croître en réponse à la fine dynamique spatio-temporelle des trouées forestières, avec des stratégies adaptatives de croissance divergentes le long des niches de succession. Par conséquent, la topographie et la dynamique des trouées forestières entraînent des adaptations spatio-temporelles à fine échelle des individus au sein et entre les espèces des complexes d'espèces Symphonia et Eschweilera. Je suggère que les adaptations à la topographie et à la dynamique des trouées forestières favorisent la coexistence des individus au sein et entre les espèces des complexes d'espèces, et peut-être plus généralement entre les espèces d'arbres de forêts matures. Dans l'ensemble, je soutiens le rôle primordial des individus au sein des espèces dans la diversité des forêts tropicales, et suggère que nous devrions élaborer une théorie de l'écologie des communautés en commençant par les individus, car les interactions avec les environnements se produisent après tout au niveau de l’individu
Tropical forests shelter the highest species diversity worldwide, a fact that remains partly unexplained and the origin of which is subject to debate. Even at the hectare-scale, tropical forests shelter species-rich genera with closely-related tree species coexisting in sympatry. Due to phylogenetic constraints, closely related species are expected to have similar niches and functional strategies, which raises questions on the mechanisms of their local coexistence. Closely related species may form a species complex, defined as morphologically similar species that share large amounts of genetic variation due to recent common ancestry and hybridization, and that can result from ecological adaptive radiation of species segregating along environmental gradients. Despite the key role of species complexes in Neotropical forest ecology, diversification, and evolution, little is known of the eco-evolutionary forces creating and maintaining diversity within Neotropical species complexes. We explored the intraspecific genomic variability as a continuum within structured populations of closely related species, and measured its role on individual tree performance through growth over time, while accounting for effects of a finely-characterized environment at the abiotic and biotic level. Combining tree inventories, LiDAR-derived topographic data, leaf functional traits, and gene capture data in the research station of Paracou, French Guiana, we used population genomics, environmental association analyses, genome-wide association studies and Bayesian modelling on the tree species complexes Symphonia and Eschweilera clade Parvifolia. We showed that the species complexes of Neotropical trees cover all local gradients of topography and competition and are therefore widespread in the study site whereas most of the species within them exhibit pervasive niche differentiation along these same gradients. Specifically, in the species complexes Symphonia and Eschweilera clade Parvifolia, the decrease in water availability due to higher topographic position, e.g., from bottomlands to plateaus, has led to a change in leaf functional traits from acquisitive strategies to conservative strategies, both among and within species. Symphonia species are genetically adapted to the distribution of water and nutrients, hence they coexist locally through exploiting a broad gradient of local habitats. Conversely, Eschweilera species are differentially adapted to soil chemistry and avoid the wettest, hydromorphic habitats. Last but not least, individual tree genotypes of Symphonia species are differentially adapted to regenerate and thrive in response to the fine spatio-temporal dynamics of forest gaps with divergent adaptive growth strategies along successional niches. Consequently, topography and the dynamics of forest gaps drive fine-scale spatio-temporal adaptations of individuals within and among distinct but genetically connected species within the species complexes Symphonia and Eschweilera clade Parvifolia. Fine-scale topography drives genetic divergence and niche differentiation with genetic adaptations among species, while forest gap dynamics maintains genetic diversity with divergent adaptive strategies within species. I suggest that adaptations of tree species and individuals to topography and dynamics of forest gaps promote coexistence within and among species within species complexes, and perhaps among mature forest tree species outside species complexes. Overall, I defend the primordial role of individuals within species in tropical forest diversity, suggesting that we should develop a theory of community ecology starting with individuals, because interactions with environments happen after all at the individual level

碩士
國立中興大學
森林學系所
104
Species distribution models (SDMs) are widely used in ecological conservation and decision-making of biological resource management because of SDM’s prospective and great contribution. In most SDMs study, researchers probably usually consider causal factors. However, data for such factors are expensive or even difficult to collect. Instead, it is proper to use Terrain-related variables which can be easily obtained by remote sensing as proxies of ecological factors. Topographic wetness index (TWI) is one kind of measurements that can represent and control the local situation of topography on hydrological processes; solar radiation index (SRI) is a proxy factor that indicate local amount of solar radiation, which affects the ground surface temperature and moisture, and lead to different micro-climate. They both are important to plant growth. Thus, this study take TWI and SRI as new predictors into the model which developed with discriminant analysis (DA), decision tree (DT), maximum entropy (MaxEnt), and support vector machine (SVM), in order to predict the potential habitats of three species, which are Schima superba var. superba (Chinese guger tree, CGT), Rhododendron formosanum (RF) and Elaeocarpus japonica (JE) in the Huisun Experimental Forest Station (HEFS) in central Taiwan. Besides, it also applied two interpolated methods into DEM to regenerate TWI (called krig-TWI), SRI (called krig-SRI) and tried to evaluate the effects of TWI, krig-TWI, SRI and krig-SRI on the performance of SDMs. The results show that SRI did not promote accuracy of model, while krig-SRI did. TWI-M potentially raised the accuracy of model, while TWI-S did not advance the accuracy in most model. In DT and DA model, such significantly improved as krig-SRI be, krig-TWI-S did not come up with it, and either did krig-TWI-M. Among the performance of four models, MaxEnt is the best for three species; DT is second for RF and CGT; SVM is worst for JE and CGT, but it is as second as DT for RF. More importantly, TWI value can represent the ecological traits of three target species statistically, and agrees with our observations from field surveys. TWI-M is more robust than TWI-S due to TWI-M is quiet not affected by different interpolation. Consequently, this study confirms that TWI and krig-SRI can somehow improve the performance of SDMs, where they are different in any single type of model result. In models with high specificity (like SVM) or with high omission error (like DA) pefromed well, while models with strict rule (like MaxEnt and DT) did not arise apparently. SDM must be considered to run on an iterative basis with topographic data in initial rounds, and thereby saving both cost and labor. This process is inevitable in impoving the predictive performance of SDM in mountain area.

Thesis (M.Sc. (Geography)) --University of Limpopo, 2018
Soil erosion, which is a critical component of land degradation, is one of the serious global environmental problems often threatening food security, water resources, and biodiversity. A comprehensive assessment and analysis of remote sensing applications in the spatial soil erosion mapping and monitoring over time and space is therefore, important for providing effective management and rehabilitation approaches at local, national and regional scales. The overall aim of the study was to assess the use of multispectral remote sensing sensors in mapping and monitoring the spatio-temporal variations in levels of soil erosion in the former homelands of Sekhukhune district, South Africa. Firstly, the effectiveness of the new and freely available moderate-resolution multispectral remote sensing data (Landsat 8 Operation Land Imager: OLI and Sentinel-2 Multi-Spectral Instrument: MSI) derived spectral bands, vegetation indices, and a combination of spectral bands and vegetation indices in mapping the spatio-temporal variation of soil erosion in the former homelands of Sekhukhune District, South Africa is compared. The study further determines the most optimal individual sensor variables that can accurately map soil erosion. The results showed that the integration of spectral bands and spectral vegetation indices yielded high soil erosion overall classification accuracies for both sensors. Sentinel-2 data produced an OA of 83, 81% whereas Landsat 8 has an OA of 82.86%. The study further established that Sentinel-2 MSI bands located in the NIR (0.785-0.900 μm), red edge (0.698-0.785μm) and SWIR (1.565-2.280 μm) regions were the most optimal for discriminating degraded soils from other land cover types. For Landsat 8 OLI, only the SWIR (1.560-2.300 μm), NIR (0.845-0.885 μm) region were selected as the best regions. Of the eighteen spectral vegetation indices computed, Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) and Global Environmental Monitoring Index (GEMI) were selected as the most suitable for detecting and mapping soil erosion. Secondly, the study assessed soil erosion in the former homelands of Sekhukhune, South Africa by applying a time-series analysis (2002 and 2017), to track changes of areas affected by varying degrees of erosion. Specifically, the study assessed and mapped changes of eroded areas (wet and dry season), using multi-date Landsat products 8 OLI and 7 Enhanced Thematic Mapper (ETM+)). Additionally, the study used extracted eroded areas and overlay analysis was performed together with geology, slope and the Topographic Wetness Index (TWI) of the area under study to assess whether and to what extent the observed erosional trends can be explained. ii Time series analysis indicated that the dry season of 2002, experienced 16.61 % (224733 ha) of erosion whereas in 2017 19.71% was observed. A similar trend was also observed in the wet season. This work also indicates that the dominant geology type Lebowa granite: and Rustenburg layered its lithology strata experienced more erosional disturbances than other geological types. Slopes between 2-5% (Nearly level) experienced more erosion and vice-versa. On the hand, the relationship between TWI and eroded areas showed that much erosion occurred between 3 and 6 TWI values in all the seasons for the two different years, however, the dry season of 2002 had a slightly higher relationship and vice-versa. We, therefore, recommend use and integration of freely and readily available new and free generation broadband sensors, such as Landsat data and environmental variables if soil erosion has to be well documented for purposes of effective soil rehabilitation and conservation. Keywords: Food security Global changes, Land degradation, Land-based ecosystems, Land management practices, Satellite data, Soil conservation, Sustainable Development; Topographic Wetness Index; Time series analysis.

In recent years, geographical information systems (GISs) and Remote Sensing (RS) have proven to be common tools adopted for different studies in different scientific disciplines. GIS defined as a set of tools for the input, storage, retrieval, manipulation, management, modeling, analysis and output of spatial data. RS, on the other hand, can play a role in the production of a data and in the generation of thematic maps related to spatial studies. This study focuses on use of GIS and RS data for landslide susceptibility mapping. Five factors including Normalized Difference Vegetation Index (NDVI) and Topographic Wetness Index (TWI), slope; lineament density and distance to roads were used for the grid based approach for landslide susceptibility mappings. Results of this study suggest that geographic information systems can effectively be used to obtain susceptibility maps by compiling and overlaying several data layers relevant to landslide hazards.

In recent years, geographical information systems (GISs) and remote sensing (RS) have proven to be common tools adopted for different studies in different scientific disciplines. GIS is defined as a set of tools for the input, storage, retrieval, manipulation, management, modeling, analysis, and output of spatial data. RS, on the other hand, can play a role in the production of a data and in the generation of thematic maps related to spatial studies. This study focuses on use of GIS and RS data for landslide susceptibility mapping. Five factors including normalized difference vegetation index (NDVI) and topographic wetness index (TWI), slope, lineament density, and distance to roads were used for the grid-based approach for landslide susceptibility mappings. Results of this study suggest that geographic information systems can effectively be used to obtain susceptibility maps by compiling and overlaying several data layers relevant to landslide hazards.

The aim of this study is to produce landslide susceptibility maps of Şavşat district of Artvin Province using machine learning (ML) models and to compare the predictive performances of the models used. Tree-based ensemble learning models, including random forest (RF), gradient boosting machines (GBM), and extreme gradient boosting (XGBoost), were used in the study. A landslide inventory map consisting of 85 landslide polygons was used in the study. The inventory map comprises 32,777 landslide pixels at 30 m resolution. Randomly selected 70% of the landslide pixels were used for training the models and the remaining 30% were used for the validation of the models. In susceptibility analysis, altitude, aspect, curvature, distance to drainage network, distance to faults, distance to roads, land cover, lithology, slope, slope length, and topographic wetness index parameters were used. The validation of the models was conducted using success and prediction rate curves. The validation results showed that the success rates for the GBM, RF, and XGBoost models were 91.6%, 98.4%, and 98.6%, respectively, whereas the prediction rate were 91.4%, 97.9%, and 98.1%, respectively. Therefore, it was concluded that landslide susceptibility map produced with XGBoost model can help decision makers in reducing landslide-associated damages in the study area.