Análise digital de terreno e evolução de longo-termo de relevo do centro-leste brasileiro

Geomorphological theories for long-term relief evolution postulate the existence of planation surfaces, created by the continuous work of erosion/deposition during periods of tectonic quiescence and recognized as extensive areas of very gentle relief disturbed only locally by residual elevations, or by the apparent leveling of summit heights in a given region. After decades since the publication of the main theories on landform evolution, the validity of these models is still an open discussion. In this paper, we present studies about the compartmentalization of landform elements, on a regional-scale basis, of central-eastern Brazil. The methods involved Digital Terrain Analysis in Geographic Information Systems, aiming the extraction and characterization of topographic variables and the compilation and mathematical analysis of geophysical and thermochronological data. Results were interpreted according to the geological context and the theories for long-term relief evolution. The integration of morphometric, thermochronological and geophysical data does not support the validity of using planation surfaces in regional stratigraphic correlations.As diversas teorias geomorfológicas para evolução do relevo em longo-termo (da ordem de dezenas de milhões de anos) contemplam a existência de superfícies de aplainamento, formadas pela ação contínua dos agentes erosivos/deposicionais em períodos de quiescência tectônica e reconhecíveis como extensas áreas de relevo muito suave perturbadas localmente por elevações residuais, ou pela aparente concordância altimétrica dos divisores de águas de uma região. Apesar de passadas várias décadas desde a publicação das principais teorias sobre evolução das formas de relevo, a validade desses modelos ainda é palco de discussão. Neste trabalho são apresentados estudos relativos à compartimentação do relevo, em escala regional, da região centro-leste brasileira. As análises foram focadas em análise digital de terreno, com processamento e integração de dados em Sistema de Informações Geográficas, visando a extração e caracterização de variáveis relativas à superfície topográfica e a compilação e tratamento matemático de dados termocronológicos e geofísicos. Os resultados obtidos foram interpretados tendo em vista o contexto geológico e as teorias de evolução do relevo em longo-termo. A integração entre dados morfométricos, termocronológicos e geofísicos não suporta a validade do uso de superfícies aplainadas em correlações estratigráficas de âmbito regional

3D FUNCTIONAL MODELING OF DBS EFFICACY AND DEVELOPMENT OF ANALYTICAL TOOLS TO EXPLORE FUNCTIONAL STN

Introduction: Exploring the brain for optimal locations for deep brain stimulation (DBS) therapy is a challenging task, which can be facilitated by analysis of DBS efficacy in a large number of patients with Parkinson’s disease (PD). The Unified Parkinson\u27s Disease Rating Scale (UPDRS) scores indicate the DBS efficacy of the corresponding stimulation location in a particular patient. The spatial distribution of these clinical scores can be used to construct a functional model which closely models the expected efficacy of stimulation in the region. Designs and Methods: In this study, different interpolation techniques were investigated that can appropriately model the DBS efficacy for Parkinson’s disease patients. These techniques are linear triangulation based interpolation, ‘roving window’ interpolation and ‘Monopolar inverse weighted distance’ (MIDW) interpolation. The MIDW interpolation technique is developed on the basis of electric field geometry of the monopolar DBS stimulation electrodes, based on the DBS model of monopolar cathodic stimulation of brain tissues. Each of these models was evaluated for their predictability, interpolation accuracy, as well as other benefits and limitations. The bootstrapping based optimization method was proposed to minimize the observational and patient variability in the collected database. A simulation study was performed to validate that the statistically optimized interpolated models were capable to produce reliable efficacy contour plots and reduced false effect due to outliers. Some additional visualization and analysis tools including a graphic user interface (GUI) were also developed for better understanding of the scenario. Results: The interpolation performance of the MIDW interpolation, the linear triangulation method and Roving window method was evaluated as interpolation error as 0.0903, 0.1219 and0.3006 respectively. Degree of prediction for the above methods was found to be 0.0822, 0.2986 and 0.0367 respectively. The simulation study demonstrate that the mean improvement in outlier handling and increased reliability after bootstrapping based optimization (performed on Linear triangulation interpolation method) is 6.192% and 12.8775% respectively. The different interpolation techniques used to model monopolar and bipolar stimulation data is found to be useful to study the corresponding efficacy distribution. A user friendly GUI (PDRP_GUI) and other utility tools are developed. Conclusion: Our investigation demonstrated that the MIDW and linear triangulation methods provided better degree of prediction, whereas the MIDW interpolation with appropriate configuration provided better interpolation accuracy. The simulation study suggests that the bootstrapping-based optimization can be used as an efficient tool to reduce outlier effects and increase interpolated reliability of the functional model of DBS efficacy. Additionally, the differential interpolation techniques used for monopolar and bipolar stimulation modeling facilitate study of overall DBS efficacy using the entire dataset

Comparison of roving-window and search-window techniques for characterising landscape morphometry

Brazil`s State of Sao Paulo Research FoundationBrazil`s State of Sao Paulo Research Foundation[FAPESP 04/06260-5]Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)National Council of Scientific and Technological Development, CNPq[304649/2005-8

Congiungere la modellazione dei movimenti di massa alla realtà

I flussi di massa sono pericoli naturali di tipo gravitativo tipici delle zone montane che causano ogni anno perdite economiche e vittime. I modelli numerici sono strumenti per prevedere la propagazione di potenziali eventi di flussi di massa su una determinata topografia, ma questi richiedono diversi input. Gli input e i processi che sostanzialmente influenzano i risultati dei modelli sono rappresentati dalla dal volume, dalle condizioni di innesco e dalle interazioni topografia – flusso di massa. Pertanto, l'obiettivo principale della tesi è quello di migliorare la quantificazione del volume coinvolto in un evento di flusso di massa e di aumentare la rappresentazione dell’interazione tra il flusso e la topografia. Quindi, sono stati studiati due tipi di flussi di massa: debris flow e valanghe di neve. Per quanto riguarda i debris flow, la tesi vuole migliorare l'affidabilità dei modelli analizzando l'aumento del volume del flusso attraverso l'erosione del letto del canale e il collasso di strutture di mitigazione. Per le valanghe di neve, lo studio ha come obbiettivo quello di migliorare l'identificazione delle possibili aree di distacco. La tesi è strutturata come una raccolta di articoli dei quali tre sono stati pubblicati e uno è in fase di revisione. Il primo articolo ha migliorato la rappresentazione dei fenomeni erosivi nei modelli numerici grazie ai dati di un evento di debris flow avvenuto nel bacino del rio Gere (Veneto, IT). Una funzione basata sui valori di pendenza è stata definita per calcolare il coefficiente di erosione, successivamente utilizzato per riprodurre l’erosione osservata nel canale. I risultati sono utili per migliorare l'accuratezza di futuri scenari da debris flow per i quali l'erosione è un importante processo nella dinamica del flusso. Il secondo studio ha definito una procedura per simulare l'effetto del collasso delle briglie di consolidamento in un evento di debris flow. La metodologia è stata sviluppata nel rio Rotian (Trentino, IT), dove un evento di pioggia estrema ha innescato un debris flow che ha provocato il collasso di una serie di 15 briglie. La metodologia sviluppata può essere direttamente applicata per mappare il rischio residuo dei canali da debris flow in cui siano presenti opere o dove la mancanza di manutenzione delle misure di mitigazione può diminuire la loro stabilità. Il terzo progetto riguarda lo studio della rugosità del terreno. Sette algoritmi di calcolo della rugosità sono stati testati in due aree studio al fine di identificare quale algoritmo possa rappresentare nel modo più appropriato le tipologie del terreno che interagiscono con i fenomeni di massa. I risultati hanno mostrato che il miglior algoritmo è risultato il vector ruggedness e che l’utilizzo di una risoluzione maggiore non ha migliorato le performance. Il quarto progetto ha analizzato la capacità di protezione delle foreste colpite da tempeste di vento. Due nuovi algoritmi per valutare le caratteristiche degli alberi abbattuti sono stati sviluppati. I risultati hanno evidenziato che il momento di protezione minimo delle foreste contro le valanghe di neve è dopo 10 anni l'evento di tempesta. Inoltre, gli algoritmi possono essere applicati direttamente su scala regionale per la gestione e il monitoraggio delle aree forestali colpite da tempeste. I diversi studi hanno analizzato i processi di erosione, l'effetto del collasso di briglie e l'identificazione di potenziali aree di innesco. I risultati dei quattro progetti hanno risposto ai corrispondenti obbiettivi, migliorando la comprensione dei flussi di massa e quindi la previsione di eventi futuri. Inoltre, i progetti forniscono importanti risultati metodologici e nuovi metodi sono stati sviluppati e testati al fine di migliorare la stima del volume dei flussi di massa. Tali metodi sono inoltre applicabili al di fuori delle aree di studio prese in esame, dando supporto a diversi stakeholder nella gestione dei rischi naturali.Mass flows are gravitational natural hazards typical of mountain areas causing economic losses and fatalities every year. Numerical models are a way to predict the propagation of potential mass flow events over a certain topography. To appropriately reproduce future events, models required different inputs. Inputs and processes consistently affecting the outcomes of mass flow models regard the released volume, the triggering conditions and the interaction with the topography and the features on the ground once the flow is in motion. Therefore, the main objective of the thesis is to improve the quantification of the input volume and to improve the implementation of processes of interaction with the basal topography. In this context, the focus has been placed on two types of mass flows: debris flows and snow avalanches. Regarding debris flows, the study aims to improve the reliability of models to capture the increase in flow volume through channel bed erosion and mitigation structure collapse. For snow avalanches, the study wants to improve the identification of possible avalanche release areas taking into account the role of different types of vegetation structures. The thesis was structured as a collection of articles of which three have been published and one is currently under review. The first paper investigated the improvement of debris flow erosion in computational models thanks to data of a severe event occurred in the Gere catchment (Veneto, IT). A function based on a smoothed terrain slope map was calibrated to derive the erosion coefficient, successively used to reproduce the observed erosion process occurred in the channel. Results can improve the reliability of future scenarios related to debris flows for which bed erosion plays an important role in volume increase. The second study defined a procedure to simulate the effect of check dam collapse in a debris flow event. The methodology was developed in the rio Rotian (Trentino, IT) where an extreme rainfall event triggered a debris flow that collapsed a series of 15 check dams. The adopted methodology can be straight applied to map the residual risk of mountain channels or where the lack of maintenance may decrease torrent countermeasure stability. The third project involves the study of terrain roughness. We tested seven algorithms computing terrain roughness in two study areas with the aim to identify which roughness algorithm can represent in the most appropriate way the features on the ground interacting with natural hazards. Outcomes showed that the best algorithm resulted the vector ruggedness and that the increase in data resolution did not improve the classification performance. Results can improve the reliability of mass flow propagation models over natural areas. The fourth project analysed the protection capacity of forests affected by windstorms. We developed and tested two algorithms to assess the characteristics of abated trees. Results assessed that the time of minimum level of forest protection against snow avalanches in 10 years after the storm event. The developed algorithms can be straight applied at regional scale to monitor and improve the management of windthrow areas. The projects investigated entrainment processes, effect of mitigation structure failures and the identification of potential triggering areas. Outcomes of the four projects filled the respective gaps of knowledge, improving the understanding of mass flows and then the prediction of future events. Furthermore, the projects have strong methodological outcomes and new methods to improve the volume estimation of mass flows have been developed and tested. Such methods are further applicable outside of the study areas, supporting different stakeholders in the management of natural hazards of mountain areas

Congiungere la modellazione dei movimenti di massa alla realtà

I flussi di massa sono pericoli naturali di tipo gravitativo tipici delle zone montane che causano ogni anno perdite economiche e vittime. I modelli numerici sono strumenti per prevedere la propagazione di potenziali eventi di flussi di massa su una determinata topografia, ma questi richiedono diversi input. Gli input e i processi che sostanzialmente influenzano i risultati dei modelli sono rappresentati dalla dal volume, dalle condizioni di innesco e dalle interazioni topografia – flusso di massa. Pertanto, l'obiettivo principale della tesi è quello di migliorare la quantificazione del volume coinvolto in un evento di flusso di massa e di aumentare la rappresentazione dell’interazione tra il flusso e la topografia. Quindi, sono stati studiati due tipi di flussi di massa: debris flow e valanghe di neve. Per quanto riguarda i debris flow, la tesi vuole migliorare l'affidabilità dei modelli analizzando l'aumento del volume del flusso attraverso l'erosione del letto del canale e il collasso di strutture di mitigazione. Per le valanghe di neve, lo studio ha come obbiettivo quello di migliorare l'identificazione delle possibili aree di distacco. La tesi è strutturata come una raccolta di articoli dei quali tre sono stati pubblicati e uno è in fase di revisione. Il primo articolo ha migliorato la rappresentazione dei fenomeni erosivi nei modelli numerici grazie ai dati di un evento di debris flow avvenuto nel bacino del rio Gere (Veneto, IT). Una funzione basata sui valori di pendenza è stata definita per calcolare il coefficiente di erosione, successivamente utilizzato per riprodurre l’erosione osservata nel canale. I risultati sono utili per migliorare l'accuratezza di futuri scenari da debris flow per i quali l'erosione è un importante processo nella dinamica del flusso. Il secondo studio ha definito una procedura per simulare l'effetto del collasso delle briglie di consolidamento in un evento di debris flow. La metodologia è stata sviluppata nel rio Rotian (Trentino, IT), dove un evento di pioggia estrema ha innescato un debris flow che ha provocato il collasso di una serie di 15 briglie. La metodologia sviluppata può essere direttamente applicata per mappare il rischio residuo dei canali da debris flow in cui siano presenti opere o dove la mancanza di manutenzione delle misure di mitigazione può diminuire la loro stabilità. Il terzo progetto riguarda lo studio della rugosità del terreno. Sette algoritmi di calcolo della rugosità sono stati testati in due aree studio al fine di identificare quale algoritmo possa rappresentare nel modo più appropriato le tipologie del terreno che interagiscono con i fenomeni di massa. I risultati hanno mostrato che il miglior algoritmo è risultato il vector ruggedness e che l’utilizzo di una risoluzione maggiore non ha migliorato le performance. Il quarto progetto ha analizzato la capacità di protezione delle foreste colpite da tempeste di vento. Due nuovi algoritmi per valutare le caratteristiche degli alberi abbattuti sono stati sviluppati. I risultati hanno evidenziato che il momento di protezione minimo delle foreste contro le valanghe di neve è dopo 10 anni l'evento di tempesta. Inoltre, gli algoritmi possono essere applicati direttamente su scala regionale per la gestione e il monitoraggio delle aree forestali colpite da tempeste. I diversi studi hanno analizzato i processi di erosione, l'effetto del collasso di briglie e l'identificazione di potenziali aree di innesco. I risultati dei quattro progetti hanno risposto ai corrispondenti obbiettivi, migliorando la comprensione dei flussi di massa e quindi la previsione di eventi futuri. Inoltre, i progetti forniscono importanti risultati metodologici e nuovi metodi sono stati sviluppati e testati al fine di migliorare la stima del volume dei flussi di massa. Tali metodi sono inoltre applicabili al di fuori delle aree di studio prese in esame, dando supporto a diversi stakeholder nella gestione dei rischi naturali.Mass flows are gravitational natural hazards typical of mountain areas causing economic losses and fatalities every year. Numerical models are a way to predict the propagation of potential mass flow events over a certain topography. To appropriately reproduce future events, models required different inputs. Inputs and processes consistently affecting the outcomes of mass flow models regard the released volume, the triggering conditions and the interaction with the topography and the features on the ground once the flow is in motion. Therefore, the main objective of the thesis is to improve the quantification of the input volume and to improve the implementation of processes of interaction with the basal topography. In this context, the focus has been placed on two types of mass flows: debris flows and snow avalanches. Regarding debris flows, the study aims to improve the reliability of models to capture the increase in flow volume through channel bed erosion and mitigation structure collapse. For snow avalanches, the study wants to improve the identification of possible avalanche release areas taking into account the role of different types of vegetation structures. The thesis was structured as a collection of articles of which three have been published and one is currently under review. The first paper investigated the improvement of debris flow erosion in computational models thanks to data of a severe event occurred in the Gere catchment (Veneto, IT). A function based on a smoothed terrain slope map was calibrated to derive the erosion coefficient, successively used to reproduce the observed erosion process occurred in the channel. Results can improve the reliability of future scenarios related to debris flows for which bed erosion plays an important role in volume increase. The second study defined a procedure to simulate the effect of check dam collapse in a debris flow event. The methodology was developed in the rio Rotian (Trentino, IT) where an extreme rainfall event triggered a debris flow that collapsed a series of 15 check dams. The adopted methodology can be straight applied to map the residual risk of mountain channels or where the lack of maintenance may decrease torrent countermeasure stability. The third project involves the study of terrain roughness. We tested seven algorithms computing terrain roughness in two study areas with the aim to identify which roughness algorithm can represent in the most appropriate way the features on the ground interacting with natural hazards. Outcomes showed that the best algorithm resulted the vector ruggedness and that the increase in data resolution did not improve the classification performance. Results can improve the reliability of mass flow propagation models over natural areas. The fourth project analysed the protection capacity of forests affected by windstorms. We developed and tested two algorithms to assess the characteristics of abated trees. Results assessed that the time of minimum level of forest protection against snow avalanches in 10 years after the storm event. The developed algorithms can be straight applied at regional scale to monitor and improve the management of windthrow areas. The projects investigated entrainment processes, effect of mitigation structure failures and the identification of potential triggering areas. Outcomes of the four projects filled the respective gaps of knowledge, improving the understanding of mass flows and then the prediction of future events. Furthermore, the projects have strong methodological outcomes and new methods to improve the volume estimation of mass flows have been developed and tested. Such methods are further applicable outside of the study areas, supporting different stakeholders in the management of natural hazards of mountain areas

A multiscale assessment of snow leopard distribution, habitat-use and landscape connectivity in a new national park in China

The newly established Qilian Mountain National Park (QMNP), with and area of 50,200 km2, was one of the first ten pilot areas of the revised national park system in China. The snow leopard is an important flagship species of the QMNP, although only sporadic field surveys have been conducted since 2011 in the Qilian Mountain region. The lack of data and information has impeded the improvement of conservation and management planning and practice of the national parks. The target of this research was to use data collected from multiple surveys with spatial and temporal variance, with the employment of recent and powerful data analysis algorithms, to explore snow leopard ecology at micro and macro levels in QMNP and provide important contributions for the conservation and management planning of QMNP and surrounding areas. Firstly, snow leopard density was estimated in Yanchiwan National Nature Reserve (YNNR, an important component nature reserve of QMNP) using Spatially Explicit Capture-Recapture Models (SECR), across a 400 km2 area with 62 camera traps systematically set up. In total 14 snow leopard individuals were photo captured during the 4,760 camera trapping nights. The overall abundance of snow leopards was estimated to be 26.3 individuals (SE = 5.7, 95% CI 19.2-43.2) over the entire buffered survey area of 1,881.6 km2. The estimated average snow leopard density for the study was therefore 1.40 (SE=0.30, 95% CI 1.02-2.30) individuals per 100 km2. Covariates of wild and domestic prey (capture events of blue sheep and domestic livestock), and geography (terrain roughness index) were found had big impact on the model performance. In YNNR, 249 snow leopard presence locations were acquired from camera traps and genetically-verified fecal samples. Analysis was then conducted on snow leopard distribution, activity and linkage across the extent of YNNR, with an area of 13,600 km2. A key mountain system (Shulenanshan) in the east of YNNR was identified as the most important area in terms of habitat quality, activity and linkage of snow leopard populations. Based on these analyses, two further areas were identified with high importance for population connectivity, but which were also highly vulnerable from fence and road infrastructure. Analysis on snow leopard distribution, activity and linkage was then extended to the entire QMNP and areas around, based on a wider dataset of 393 snow leopard presence points. Results indicated 16 high-quality patches and 27 medium-quality patches in QMNP and surrounding areas. The largest high-quality patch located in the mid-east of QMNP, which was consistent with the results from connectivity surface and linkage network analysis about the most important key area. Second largest high-quality patch located at south out of the QMNP, which may play the role of bridge or step stones for the snow leopard population communication between the national park and the main part of Qinghai-Tibet Plateau. Result of least cost path analysis showed that most of the high-quality patch paths went through medium-quality patches, indicating the potential step stone function of the medium-quality patches for snow leopard individuals’ dispersal. Serving as the first case of snow leopard ecological study in national park level landscape in China, this thesis explored population density, distribution, activity and linkage of snow leopard population in QMNP from micro to macro level scale. The thesis demonstrated how the data with spatial and temporal difference can be used in flagship species with big range and scarce information. This study increased our understanding of snow leopard density in high quality habitat, improved the knowledge of the important impact factors of snow leopard distribution at nature reserve and national park level, and described the scenarios of snow leopard activity and linkage with multiple supposed biologically meaningful thresholds of movement and dispersal abilities. This study increased the knowledge of snow leopard ecology, and the results and suggestions provided in the thesis would be an important reference to the managers when making the conservation and management plan in QMNP and surrounding areas

Modelação da concentração de poluentes agrícolas em aquíferos

A água subterrânea é um dos recursos naturais com maior importância, para além de ser necessária à vida dos organismos é utilizada no abastecimento das populações, atividades agrícolas e indústria. A presença de nitratos na água subterrânea é uma das formas de contaminação mais comuns, a sua presença ligada à agricultura intensiva e à aplicação excessiva de fertilizantes de base azotadas no solo. A acumulação de nitratos afeta os aquíferos pelo estado de eutrofização das águas e é prejudicial à saúde humana que pode causar problemas de saúde como como cancro no estomago em adultos e metahemoglobinemia nas crianças. A proteção dos aquíferos à poluição tem-se tornado numa preocupação daí a criação de normas legislativas como é o caso do Decreto-Lei n.º 235/97 de 3 de setembro com o objetivo de redução da poluição das águas causada ou induzida por nitratos de origem agrícola bem como impedir a propagação desta poluição. A utilização de métodos e técnicas adequadas para a avaliação de vulnerabilidade dos aquíferos e a poluição das águas subterrâneas tem sido outra medida adotada para a proteção de aquíferos. Para avaliar a vulnerabilidade aplicam-se modelos e produzem-se mapas, que permitem estimar qual o grau de suscetibilidade à contaminação, os mapas de vulnerabilidade depois de analisados permitem informar as estruturas de planeamento e ordenamento quer no sentido de uso sustentável de água subterrânea quer no sentido de implementação de atividades. Os mapas de vulnerabilidade podem ser calculados em ambiente SIG uma vez que permite a recolha de dados espaciais e ao mesmo tempo permite a realização de processamento de dados como a georreferenciação, integração, agregação e análise espacial. O presente estudo centra-se na avaliação da vulnerabilidade superficial e subterrânea à contaminação da água subterrânea por nitratos provenientes de atividades agrícolas na zona vulnerável a nitratos do Tejo, através de modelos subjetivos indexados e modelos baseados em processos. A zona vulnerável a nitratos do Tejo encontra-se numa região em que a prática agrícola é intensiva e onde se localiza o maior sistema aquífero de Portugal continental que contribui com os seus recursos hídricos para o abastecimento urbano, industrial e agrícola da região.One of the natural resources with more importance is groundwater, besides being essential to organisms is used for population supply, agriculture and industry. The presence of nitrate in groundwater is one of the most common contamination forms, their presence is usually related to intensive agriculture and excessive application of nitrogen based fertilizers in the soil. The accumulation of nitrates affects aquifers (water eutrophication) and is dangerous to human health, can cause health problems such as cancer in the stomach in adults and methemoglobin in children. The protection of groundwater pollution has become a concern in the last decades therefore the creation of legislative provisions such as Decree-Law No. 235/97 of 3 September with the objective of reducing water pollution caused or induced by nitrates from agricultural sources and prevents the spread of pollution. The use of methods and techniques for the assessment of vulnerability of aquifers and groundwater pollution has been another measure adopted for aquifer protection. To assess the vulnerability are produced maps that allow estimating the degree of susceptibility to contamination. After analysis, vulnerability mapping allow inform planning structures of the sustainable use of groundwater and also implementation activities. The vulnerability maps can be calculated in a GIS environment since it enables collecting spatial data and at the same time allows performing data processing such as georeferencing, integration, aggregation and spatial analysis. This study focuses on the assessment of surface and groundwater vulnerability to contamination of groundwater by nitrates from agricultural activities in the vulnerable zone the Tagus nitrates through indexed subjective models and models based on processes. The vulnerable zone Tagus nitrate is in a region where the agricultural practice is intensive and where is the largest aquifer system of continental Portugal contributing to its water resources for urban, industrial and agricultural supply in the region