The objective of this study was to assess if new cloud datasets, namely horizontal fields of integrated cloud parameters and transects of cloud profiles becoming available from current and future satellites like MODIS and CloudSAT as well as EarthCARE will allow for the reconstruction of three-dimensional cloud fields. Because three-dimensional measured cloud fields do not exist, surrogate cloud fields were used to develop and test reconstruction techniques. In order to answer the question if surrogate cloud fields may represent real cloud fields and to evaluate potential constraints for cloud field reconstruction, statistics of surrogate cloud fields have been compared to statistics of various remote sensing retrievals. It has turned out that except for cloud droplet effective radius, which is too low, other cloud parameters are in line with parameters derived from measurements. The reconstruction approach is divided into two parts. The first one deals with the reconstruction of the cloud fields. Three techniques with varying complexity are presented constraining the reconstruction by measurements to various degrees. Whereas the first one applies only information of a satellite radiometer, the other two constrain the retrieval also by profile information measured within the domain. Comparing the reconstruction quality of the approaches, there is no superior algorithm performing better for all cloud fields. This might be ascribed to liquid water content profiles of the surrogate cloud fields close to their adiabatic reference. Consequently, the assumption of adiabatic liquid water content profiles of the first scheme yields adequate estimates and additional information from profiles does not improve the reconstruction. The second part of the reconstruction approach addresses the reconstruction quality by comparing parameters of radiative transfer describing photon path statistics as well as reflectances. Therefore three-dimensional radiative transfer simulations with a Monte Carlo code were carried out for the surrogate cloud fields as well as for the reconstructed cloud fields. It was assumed that deviations of the parameter simulated for the reconstructed cloud and the surrogate cloud field are smaller when reconstruction is more accurate. For parameter describing photon pathes it has been found that only deviations of geometrical pathlength statistics reflect the reconstruction quality to a certain degree. Deviations of other parameters like photon penetration depth do not allow for either assessing local differences in reconstruction quality by an individual reconstruction scheme or to infer the most appropriate reconstruction scheme. The differences in reflectances do also not enable to evaluate reconstruction quality. They prevent from gaining insight in local accuracy of reconstruction due to effects like horizontal photon transport weakening the relations between microphysical as well as optical properties and reflectances of the column. In order to address these effects, grids of various complexity, derived by applying photon path properties, were used to weight deviations of cloud properties when analyzing the relationships. Unfortunately, there is no increase of explained variance due to the application of the weighting grids. Additionally, the sensitivity of the results to the model set-up, namely the spatial resolution of the cloud fields as well as the simplification and neglection of ancillary parameters, were analyzed. Though one would assume a strengthening of relationships between deviations of cloud parameters and deviations of reflectances due to more reliable sampling and reduced inter-column transport of photons when column size increases, there is no indication for resolutions where an assessment of the reconstruction quality by means of reflectance deviations becomes feasible. It also has been shown that inappropriate treatment of aerosols in the radiative transfer simulation impose an error comparable in magnitude to differences in reflectances due to inaccurate cloud field reconstruction. This is especially the case when clouds are located in the boundary layer of the aerosol model. Consequently, appropriate aerosol models should be applied in the analysis. May be due to the low surface reflection and the high cloud optical depths, the representation of the surface reflection function seems to be of minor importance. Summarizing the results, differences in radiative transfer do not allow for the assessment of cloud field reconstruction quality. In order to accomplish the task of cloud field reconstruction, the reconstruction part could be constrained employing information from additional measurements. Observational geometries enabling to use tomographic methods and the application of additional wavelengths for validation might help, too. / Ziel der Arbeit war die Evaluierung inwieweit Datensätze von Wolkenparametern, horizontale Felder integraler Wolkenparameter und Schnitte vertikal aufgelöster Parameter, zur Rekonstruktion dreidimensionaler Wolkenfelder genutzt werden können. Entsprechende Datensätze sind durch MODIS und CloudSAT erstmals vorhanden und werden zusätzlich mit dem Start von EarthCARE zur Verfügung stehen. Da dreidimensionale Wolkenfelder aus Messungen nicht existieren, wurden zur Entwicklung der Rekonstruktionsmethoden surrogate Wolkenfelder genutzt. Um die Qualität der surrogaten Wolkenfelder abzuschätzen und um mögliche Randbedingungen zur Rekonstruktion aufzuzeigen, wurden Statistiken der surrogaten Wolkenfelder mit denen unterschiedlicher Fernerkundungsprodukte verglichen. Dabei zeigte sich, dass, abgesehen von den gegenüber Messungen zu geringen Effektivradien der Wolkentropfen in den surrogaten Wolkenfeldern, die übrigen Wolkenparameter gut übereinstimmen. Der Rekonstruktionsansatz gliedert sich in zwei Teile. Der erste Teil beinhaltet die Rekonstruktion der Wolkenfelder. Dazu werden drei Techniken unterschiedlicher Komplexität genutzt, wobei die Komplexität durch den Grad der eingebundenen Messungen bestimmt wird. Während die einfachste Technik lediglich Informationen, wie sie aus Messungen mit einem Satellitenradiometer gewonnen werden können, nutzt, binden die anderen Techniken zusätzlich Profilinformationen aus dem beobachteten Gebiet ein. Analysen zeigten, dass keine der Methoden für alle untersuchten Wolkenfelder den anderen Methoden überlegen ist. Dies mag daran liegen, dass die Flüssigwasserprofile der surrogaten Wolkenfelder nur geringfügig von den in der ersten Rekonstruktionsmethode angenommenen adiabatischen Flüssigwasserprofilen abweichen, so dass die Nutzung der Profile kaum zusätzliche Information für die Rekonstruktion liefert. Im zweiten Teil des Rekonstruktionsansatzes wird die Qualität der rekonstruierten Wolkenfelder durch den Vergleich von Parametern des Strahlungstransfers, wie Photonenpfad-Statistiken und Strahlungsgrößen, evaluiert. Dazu wurden sowohl für die surrogaten Wolkenfelder als auch für die rekonstruierten Wolkenfelder dreidimensionale Strahlungstransfersimulationen mit einem Monte-Carlo-Modell durchgeführt. Angenommen wurde hierbei, dass eine bessere Rekonstruktionsqualität durch geringere Abweichungen der betrachteten Strahlungsparameter aus Simulationen mit rekonstruierten und surrogaten Wolkenfeldern gekennzeichnet ist. Bei den Parametern, die die Photonenwege beschreiben, unterstützen lediglich die Abweichungen der geometrischen Photonenweglängen diese These. Weder erlauben die Abweichungen der übrigen Parameter, zum Beispiel der Eindringtiefen, Rückschlüsse auf die lokale Rekonstruktionsqualität der einzelnen Methoden zu ziehen, noch ermöglichen sie die beste Rekonstruktionsmethode zu identifizieren. Auch die Unterschiede der simulierten Reflektanzen können nicht zur Bestimmung der Rekonstruktionsqualität herangezogen werden. Durch Effekte wie horizontale Photonentransporte werden die Zusammenhänge zwischen mikrophysikalischen und optischen Eigenschaften und Reflektanzen der jeweiligen Gittersäule aufgeweicht, und folglich sind keine Rückschlüsse auf die lokale Rekonstruktionsqualität möglich. Um auf entsprechende Effekte einzugehen, wurden für die Analyse Wichtungsfelder unterschiedlicher Komplexität aus Photonenwegeigenschaften generiert, um diese zur Wichtung der Abweichungen der Wolkeneigenschaften zu nutzen. Der Anteil der erklärten Varianz konnte jedoch durch die Nutzung der entsprechenden Wichtungsfelder nicht erhöht werden. Zusätzlich wurden Sensitivitätsstudien hinsichtlich einzelner Vorgaben der Untersuchung durchgeführt. Dazu wurden sowohl der Einfluss der räumlichen Auflösung der Wolkenfelder als auch die Vereinfachung oder Nichtbetrachtung einzelner Modellparameter analysiert. Eine Reduzierung der Auflösung einhergehend mit einem zuverlässigeren Sampling und reduzierten Photonentransport zwischen den Gittersäulen führte zu keinem direkteren Zusammenhang zwischen den Abweichungen der Reflektanzen und den Abweichungen der mikrophysikalischen Eigenschaften. Folglich existiert keine Auflösung, die die Anwendung des Verfahrens ermöglichen würde. Ebenso wurde gezeigt, dass die unzureichende Einbeziehung von Aerosolen bei den Strahlungstransfersimulationen einen Fehler verursachen kann, der in der Größe dem Unterschied der Reflektanzen unzureichender Wolkenfeldrekonstruktionen gleichkommt. Dies ist insbesondere der Fall, wenn die Wolken sich innerhalb der Grenzschicht des Aerosolmodells befinden. Entspechend sollte in solchen Situationen dem verwendeten Aerosolmodell besondere Beachtung geschenkt werden. Hingegen ist der Einfluss des Ansatzes, wie die Bodenreflektion beschrieben wird, eher gering. Dies mag an dem verwendeten Modell mit einer geringen Albedo in Kombination mit optisch dicken Wolken liegen. Zusammenfassend kann festgestellt werden, dass die Unterschiede im Strahlungstransfer nicht zur Abschätzung der Rekonstruktionsqualität der Wolkenfelder herangezogen werden können. Um dem Ziel einer dreidimensionalen Wolkenfeldrekonstruktion näher zu kommen, könnten beim Rekonstruktionsteil Informationen aus zusätzlichen Messungen als Vorgaben genutzt werden. Ebenso könnten Beobachtungsgeometrien, welche die Anwendung tomographischer Methoden erlauben, sowie zusätzliche Wellenlängen zur Validierung der Rekonstruktionsergebnisse verwendet werden.

M.Sc. / Light Detection and Ranging (LiDAR) provide decidedly accurate datasets with high data densities, in a very short time-span. However, the high volumes of data associated with LiDAR often require some form of data reduction to increase the data handling efficiency of these datasets, of which the latter could affect the feasibility of Digital Elevation Models (DEMs). Critically, when DEM processing times are reduced, the resultant DEM should still represent the terrain adequately. This study investigated three different data reduction techniques, (1) random point reduction, (2) grid resolution reduction, and (3) combined data reduction, in order to assess their effects on the accuracy, as well as the data handling efficiency of derived DEMs. A series of point densities of 1 %, 10 %, 25 %, 50 % and 75 % were interpolated along a range of horizontal grid resolutions (1-, 2-, 3-, 4-, 5-, 10- and 30- m). Results show that, irrespective of terrain complexity, data points can be randomly reduced up to 25 % of the data points in the original dataset, with minimal effects on the remaining dataset. However, when these datasets are interpolated, data points can only be reduced to 50 % of the original data points, before showing large deviations from the original DEM. A reduction of the grid resolution of DEMs showed that the grid resolution could be lowered to 4 metres before showing significant deviations. When combining point density reduction with grid resolution reduction, results indicate that DEMs can be derived from 75 % of the data points, at a grid resolution of 3 metres, without sacrificing more than 15 percent of the accuracy of the original DEM. Ultimately, data reduction should result in accurate DEMs that reduce the processing time. When considering the effect on the accuracy, as well as the processing times of the data reduction techniques, results indicate that resolution reduction is the most effective data reduction technique. When reducing the grid resolution to 4 metres, data handling efficiencies improved by 94 %, while only sacrificing 10 % of the data accuracy. Furthermore, this study investigated data reduction on a variety of terrain complexities and found that the reduction thresholds established by this study were applicable to both complex and non-complex terrain.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第18619号 / 情博第543号 / 新制||情||96(附属図書館) / 31519 / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 守屋 和幸, 教授 吉川 正俊, 准教授 小山 里奈 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Legal Amazon, the Brazilian region where much of the global tropical forest is located, has suffered from rapid deforestation for decades, undermining the provision of ecosystem services and the conservation of biodiversity on local and global scales. In order to prevent deforestation, the Brazilian government has established priority and protected areas to ensure the preservation of high biodiversity areas and ecosystem services. This study analyses whether the establishment of priority and protected areas have an impact in preventing deforestation, thus promoting biodiversity and ecosystem services. Furthermore, this study also analyses the extent to which deforestation affects priority areas for biodiversity conservation. Deforestation datasets from 2001 to 2014 of the Legal Amazon was processed and analyzed. The total area and density of deforestation were compared across three categories of land: (1) protected priority areas, (2) unprotected priority areas, and (3) non-priority areas. Spatial methods of geoprocessing and the statistical method one-way ANOVA were used to analyse the deforestation trends. As a result, the deforestation density was found to be lowest inside protected areas than in unprotected areas and non-priority areas. This implied that land-use restrictions in protected areas had more impact compared to unprotected areas and non-priority areas. Furthermore, deforestation has been more intensive in regions of lower biodiversity importance. Despite this positive evaluation, substantial tracts of forest had been converted within regions of high biodiversity importance. Therefore, the regulation of priority and protected areas must be evaluated and improved in the future. / Den brasilianska regionen Legal Amazon, där mycket av den globala andelen av tropisk skog ligger, har drabbats av snabb avskogning i årtionden, vilket underminerar tillhandahållandet av ekosystemtjänster och bevarandet av den biologiska mångfalden både på lokal och global skala. För att förhindra avskogning har den brasilianska regeringen etablerat prioriterade och skyddade områden för att säkerställa bevarandet av områden med hög biologisk mångfald och ekosystemtjänster. Denna studie analyserar huruvida etableringen av prioriterade och skyddade områden påverkar förebyggandet av denna avskogning. Dessutom analyserar denna undersökning också hur omfattningen av avskogningen påverkar prioriterade områden för bevarande av biologisk mångfald. Avskogningsdata från 2001 till 2014 i Legal Amazon bearbetades och analyserades. Total areal och densitet av avskogningen jämfördes mellan tre kategorier av mark: (1) skyddade prioriterade områden, (2) oskyddade prioriterade områden och (3) icke prioriterade områden. Rumsliga metoder för bearbetning och den statistiska metoden envägs-ANOVA användes för att analysera avskogningstrenderna. Resultaten visar att avskogningstätheten var lägst inom skyddade områden jämfört med oskyddade områden och icke-prioriterade områden. Det innebär att markanvändningsbegränsningar i skyddade områden har haft större inverkan jämfört med oskyddade områden och icke prioriterade områden. Vidare har avskogningen varit mer intensiv i områden med lägre värden för biologisk mångfald. Trots denna positiva utvärdering hade ett betydande skogsområde omvandlats inom områden med höga värden för biologisk mångfald. Därför måste regleringen av prioriterade och skyddade områden utvärderas och förbättras i framtiden.

Geospatial analysis involves application of statistical methods, algorithms and information retrieval techniques to geospatial data. It incorporates time into spatial databases and facilitates investigation of land cover (LC) dynamics through data, model, and analytics. LC dynamics induced by human and natural processes play a major role in global as well as regional scale patterns, which in turn influence weather and climate. Hence, understanding LC dynamics at the local / regional as well as at global levels is essential to evolve appropriate management strategies to mitigate the impacts of LC changes. This can be captured through the multi-resolution remote sensing (RS) data. However, with the advancements in sensor technologies, suitable algorithms and techniques are required for optimal integration of information from multi-resolution sensors which are cost effective while overcoming the possible data and methodological constraints. In this work, several per-pixel traditional and advanced classification techniques have been evaluated with the multi-resolution data along with the role of ancillary geographical data on the performance of classifiers. Techniques for linear and non-linear un-mixing, endmember variability and determination of spatial distribution of class components within a pixel have been applied and validated on multi-resolution data. Endmember estimation method is proposed and its performance is compared with manual, semi-automatic and fully automatic methods of endmember extraction. A novel technique - Hybrid Bayesian Classifier is developed for per pixel classification where the class prior probabilities are determined by un-mixing a low spatial-high spectral resolution multi-spectral data while posterior probabilities are determined from the training data obtained from ground, that are assigned to every pixel in a high spatial-low spectral resolution multi-spectral data in Bayesian classification. These techniques have been validated with multi-resolution data for various landscapes with varying altitudes. As a case study, spatial metrics and cellular automata based models applied for rapidly urbanising landscape with moderate altitude has been carried out.

La compréhension des facteurs qui déterminent la nature et la dynamique du couvert végétal en Afrique centrale représente un enjeu important face aux changements climatiques et à la pression sociale en cours. Forêt et savane sont souvent considérées comme deux états alternatifs stables et très contrastés, déterminés par de complexes interactions entre le couple sol-climat et les perturbations. Les liens actuels entre structure du couvert arboré et déterminants (déficit hydrique annuel, fréquence des feux, densité de population, intensité d'utilisation des terres et type de sol) ont été caractérisés à l'aide d'images satellites et d'un modèle statistique. Il a ainsi été montré qu'il non pas un mais existe plusieurs états stables de savane. Pour les états de faible couvert arboré (≤ 35%), ce sont principalement le type de sol et le climat qui déterminent leur présence et le passage de l'un à l'autre de ces états. Les savanes plus arborées (> 35%) ainsi que les forêts semblent être les états les plus sensibles aux perturbations anthropiques. Cependant, ce modèle statistique ne décrit que les liens contemporains entre structure de la végétation et déterminants. En revanche, l'étude des bio-indicateurs environnementaux conservés dans des archives naturelles, et qui représente l'approche paléo-écologique, permet de reconstruire sur le temps long la végétation, les perturbations et certaines données climatiques, et ainsi obtenir une vision dynamique de leurs relations. Trois lacs, situés actuellement en forêt, en mosaïque de forêt et de savane, et en savane ont été étudiés. En comparant sédiments récents et images satellites, ainsi qu'en calibrant un modèle entre bio-indicateurs dans les sols et relevés de végétation, il a été possible de mieux comprendre ce qu'enregistrent les bio-indicateurs disponibles pour notre étude (phytolithes et charbons principalement) et donc d'estimer la structure de la végétation et l'activité de feux. Les résultats de ces études soulignent l'importance de bien cerner les processus taphonomiques pour reconstruire précisément les paléo-environnements. Les résultats préliminaires d'une paléo-séquence lacustre couvrant les 3000 dernières années sont présentés en discussion. Bien que l'environnement autour du lac soit resté une savane, cette dernière a subi des changements de structure important dus à la fois aux changements climatiques et aux modifications des régimes de feu. De plus, ces changements de structure ne semblent pas graduels, mais s'effectuent de façon abrupte, comme ils le sont actuellement le long du gradient climatique. Ces travaux prédisent donc une réponse critique des biomes tropicaux aux changements globaux en cours. / Understanding the factors that determine vegetation nature and dynamics in Central Africa is an important issue given climatic changes and increasing human pressure. Forest and savanna are often considered as two alternative stable and highly contrasted states, driven by complex interactions between climate, soil and disturbances. The current relationships between tree cover and its determinants (annual water deficit, fire frequency, population density, intensity of land use and soil type) were characterized using remote sensing data and a statistical model. It has been shown that there is not one, but several savanna stable states. For savanna states of low tree cover (≤ 35%), it is mainly the soil type and the annual water deficit which determine their presence and the transition from one to another. The most wooded savannas (> 35%) and the forests seem to be the most sensitive to anthropogenic disturbances. However, this statistical model can only describe the contemporary relationships between vegetation structure and its determinants. Conversely, studying environmental bio-proxies preserved in natural archives, which constitutes the paleo-ecological approach, enables reconstructing long-term vegetation, disturbances and some climatic features, in order to obtain a dynamic view of their relationships. Paleo-sequences from three lakes, currently located in a forest, in a savanna-forest mosaic, and in a savanna, were investigated. On the one hand bio-proxies from recent lake sediments were compared to satellite images, and on the another hand a statistical model between bio-proxies from modern soils and vegetation surveys was calibrated. The results of these studies enabled to better understand the information carried by phytoliths and charcoals, and therefore to better estimate vegetation structure and fire history. Moreover, they emphasize the importance of precisely identifying taphonomic processes in order to accurately reconstruct paleo-environments. The preliminary results of a lacustrine paleo-sequence covering the last 3000 years are presented in discussion. Although the environment around the lake has remained a savanna, vegetation structure has undergone significant changes due to both climate change and modifications in fire regimes. Moreover, it seems that these structural changes were not gradual but happened abruptly, as it happens currently along the climatic gradient. This work therefore predicts a critical response of tropical biomes to global changes.

Thermal remote sensing is a powerful tool for measuring the spatial variability of evapotranspiration due to the cooling effect of vaporization. The residual method is a popular technique which calculates evapotranspiration by subtracting sensible heat from available energy. Estimating sensible heat requires aerodynamic surface temperature which is difficult to retrieve accurately. Methods such as SEBAL/METRIC correct for this problem by calibrating the relationship between sensible heat and retrieved surface temperature. Disadvantage of these calibrations are 1) user must manually identify extremely dry and wet pixels in image 2) each calibration is only applicable over limited spatial extent. Producing larger maps is operationally limited due to time required to manually calibrate multiple spatial extents over multiple days. This dissertation develops techniques which automatically detect dry and wet pixels. LANDSAT imagery is used because it resolves dry pixels. Calibrations using 1) only dry pixels and 2) including wet pixels are developed. Snapshots of retrieved evaporative fraction and actual evapotranspiration are compared to eddy covariance measurements for five study areas in Florida: 1) Big Cypress 2) Disney Wilderness 3) Everglades 4) near Gainesville, FL. 5) Kennedy Space Center. The sensitivity of evaporative fraction to temperature, available energy, roughness length and wind speed is tested. A technique for temporally interpolating evapotranspiration by fusing LANDSAT and MODIS is developed and tested. The automated algorithm is successful at detecting wet and dry pixels (if they exist). Including wet pixels in calibration and assuming constant atmospheric conductance significantly improved results for all but Big Cypress and Gainesville. Evaporative fraction is not very sensitive to instantaneous available energy but it is sensitive to temperature when wet pixels are included because temperature is required for estimating wet pixel evapotranspiration. Data fusion techniques only slightly outperformed linear interpolation. Eddy covariance comparison and temporal interpolation produced acceptable bias error for most cases suggesting automated calibration and interpolation could be used to predict monthly or annual ET. Maps demonstrating spatial patterns of evapotranspiration at field scale were successfully produced, but only for limited spatial extents. A framework has been established for producing larger maps by creating a mosaic of smaller individual maps. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

Research Report submitted in partial fulfilment for the degree of Master of Science (Geographical Information Systems and Remote Sensing) School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg. August 2016. / The thematic classification of land use and land cover (LULC) from remotely sensed imagery data is one of the most common research branches of applied remote sensing sciences. The performances of the pixel-based image analysis (PBIA) and object-based image analysis (OBIA) Support Vector Machine (SVM) learning algorithms were subjected to comparative assessment using WorldView-2 and SPOT-6 multispectral images of the Mokhotlong District in Lesotho covering approximately an area of 100 km2. For this purpose, four LULC classification models were developed using the combination of SVM –based image analysis approach (i.e. OBIA and/or PBIA) on high resolution images (WorldView-2 and/or SPOT-6) and the results were subjected to comparisons with one another. Of the four LULC models, the OBIA and WorldView-2 model (overall accuracy 93.2%) was found to be more appropriate and reliable for remote sensing application purposes in this environment. The OBIA-WorldView-2 LULC model was subjected to spatial overlay analysis with DEM derived topographic variables in order to evaluate the relationship between the spatial distribution of LULC types and topography, particularly for topographically-controlled patterns. It was discovered that although that there are traces of the relationship between the LULC types distributions and topography, it was significantly convoluted due to both natural and anthropogenic forces such that the topographic-induced patterns for most of the LULC types had been substantial disrupted. / LG2017

The German Government’s Integrated Energy and Climate Programme (IEKP) and the National Biomass Action Plan set ambitious targets for the further development of bioenergy until 2020. The share of energy from biomass is supposed to reach 8 % and 9.7 % of the total power consumption and of the total heat usage, respectively. The share of biofuels on the total consumption of fuels for transportation should rise up to 12 % (energetic) by 2020. This project aims to assess the possibilities of achieving the IEKP targets for bioenergy in a regional and global context. On a regional as well as global level, the potentials of different biomasses were determined in different development scenarios until 2020. Furthermore, the extent to which remote sensing could contribute in improving the spatial specification of biomass resources and whether it could be used as a monitoring system for the early detection of land use changes was investigated. On the regional level, the spatial implications of energetic biomass use was analysed with regard to environmental impacts and land use conflicts. Depending on their significance of spatial impacts, instruments of spatial planning were assessed in order to steer the supply of bioenergy. [... from Executive Summary]

Orientadores: Alvaro Penteado Crósta, Archimedes Perez Filho / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Geociências / Made available in DSpace on 2018-08-20T12:01:29Z (GMT). No. of bitstreams: 1 GelerRoffe_Tatiana_D.pdf: 15272397 bytes, checksum: bf09c202cab7336cc64657ab797e6966 (MD5) Previous issue date: 2012 / Resumo: Modelos matemáticos de predição de erosão e produção de sedimentos tem um grande potencial para uso em estudos da degradação e manejo dos recursos naturais, pois permitem estimar os impactos causados pela atividade agrícola. Este trabalho trata da aplicação do modelo hidrológico SWAT (Soil Water Assessment Tool), com a finalidade de previsão dos riscos de erosão devido às mudanças no uso da terra, na bacia do rio Chambas na província Ciego de Ávila, em Cuba. Este modelo tem sido utilizado de forma eficaz em estudos da dinâmica ambiental na representação da variabilidade espacial e temporal de processos hidrosedimentológicos em bacias hidrográficas. O método desenvolvido para modelagem descreve a dinâmica da perda de solo devido à enxurrada produzida pela água e às mudanças no uso da terra. Este permite a avaliação dos riscos de erosão do solo, utilizando um modelo implementado em um Sistema de Informação Geográfica (SIG) em modo raster. O mapeamento de cobertura e uso da terra foi realizado com base na utilização de técnicas de sensoriamento remoto e processamento digital das imagens. O estudo baseou-se no desenvolvimento de diferentes cenários de previsão de comportamento das taxas de erosão do solo, segundo mudanças da cobertura e uso da terra. Tendo em conta este procedimento, o mapeamento da erosão atual e/ou a sua predição no tempo e no espaço, desempenha um papel importante na determinação da variabilidade espacial dos fenômenos, tornando-se uma ferramenta essencial para o planejamento na conservação dos solos. Os resultados obtidos permitem avaliar a aplicabilidade do modelo na modelagem do escoamento superficial e produção de sedimentos em bacias hidrograficas em escala média com predominio de uso agrícola. Esta foi avaliada através dos resultados da simulação em uma escala de tempo mensal e anual sem calibração durante um período de 20 anos de simulação para três cenários de estudo. Foram utilizadas diferentes condições de uso e ocupação do território. A análise dos resultados das simulações no âmbito destes cenários permitiu identificar as mudanças e contrastes que ocorreram e potenciais dos processos hidrosedimentológicos na bacia, o cálculo dos volúmes do fluxo de escoamento e as taxas na produção de sedimentos anual e mensal e a sazonalidade destes processos. Neste sentido se desenvolveu uma metodologia para o cálculo e a avaliação da erosão dos solos por meio da utilização das ferramentas de geoprocessamento. Posteriormente, pretende-se aplicar esta metodologia para outras regiões do país, constituindo-se numa poderosa ferramenta para o prognóstico dos riscos à erosão nas regiões agrícolas de manejo inadequado e também, como instrumento para a tomada de decisões relativas aos impactos da erosão, acelerada pela atividade humana / Abstract: Mathematical models for predicting erosion and sediment production has great potential for use in studies of the degradation and planning of natural resources, that allow estimating impacts caused by agricultural activity. This work deals with the application of the hydrological model SWAT (Soil Water Assessment Tool), in order to forecast the risks of soil erosion due to land use changes, in the Chambas river basin, Ciego de Avila province, Cuba. This model has been successfully used in studies of environmental dynamics in the representation of spatial and temporal variability of hydro-sedimentological processes in watersheds. The method developed for modeling, describes the dynamic in the loss of soil due to runoff produced by water and changes in land use. This allows us to assess the risks in soil erosion, using a model implemented in a Geographic Information System (GIS) raster mode. In determining the mapping of land cover/land use will be use remote sensing techniques and digital image processing. The study is based on the development of different scenarios to predict behavior in the rates of soil erosion when the Land cover /land use change. Taking into account this procedure, the mapping of the existing erosion and/or its prediction in time and space, plays an important role in determining the spatial variability of the phenomena, becoming an essential tool for soils conservation planning. The results obtained allow evaluating the applicability of the model in modeling runoff and sediment yield in medium scale watersheds with predominance of agricultural use. This was evaluated through simulation results on a monthly and annual time scale without calibration over a period of 20 years of simulation to three study scenarios. We used different stages of use and occupation of the territory. The analysis of simulation results under these scenarios, allowed identifying changes and contrasts, occurring and potential in hydro-sedimentological processes in the watershed, the calculation of flow rates of runoff and sediment yield annual and monthly and the seasonality of these processes. In this sense, was developing a methodology that enables using geoprocessing tools for the calculation and assessment of soil erosion and its subsequent generalization to other regions. This provides a powerful tool for forecasting the risk of erosion in agricultural regions, which facilitates decision making about the negative effects of accelerated erosion by human activity / Doutorado / Análise Ambiental e Dinâmica Territorial / Doutor em Geografia