The seagrass extent has been declining globally. The human activities that are most likely to cause seagrass loss are those which affect the water quality and clarity. However, turbidity following coastal erosion is often left out from marine ecosystem vulnerability indices. This study quantified the coastal erosion for Tsimipaika Bay in northwestern Madagascar by using change detection analysis of satellite imageries. The annual coastal erosion data was then used to create an index for seagrass vulnerability to turbidity following coastal erosion. Considering that the height of seagrass species plays an important role in their survival following turbidity, the seagrass vulnerability index (SVI) was based on two factors; seagrass species height and their distance to the nearest possible erosion place. The results for the coastal erosion showed that the amount of erosion was particularly high in 1996, 2001 and 2009 for Tsimipaika Bay. The highest erosion occurred in 2001 with a land loss area of about 6.2 km2 . The SVI maps revealed that 40% of the seagrass communities had minimum mean SVI values in 2001 and 50% had the maximum mean SVI during the year 2009. This study showed that it is possible to use coastal erosion to measure seagrass vulnerability; however, the index requires configuration such as including the total amount of annual coastal erosion and incorporating bathymetric data. The entire project was built and automated in Jupyter Notebook using Python programming language, which creates a ground for future studies to develop and modify the project.

Natural disasters have become more severe and frequent than previous assessments with global warming. The increasing risk of natural disasters presents different groups of populations with diverse vulnerabilities, particularly those underrepresented social groups which need specific support before, during, and after extreme disasters. Hence, it is highly desired to examine vulnerability quantitatively and qualitatively across different social groups in risk to natural disasters. This dissertation study aims to investigate the measure of social vulnerability to two types of climate change-related natural disasters: sea-level-rise floodings and wildfires. In the study of sea-level-rise floodings, high-risk flooding areas are first identified for a coastal city. Then, we measure social vulnerability index (SVI) using a new SVI metric to identify vulnerable social groups which should be paid more attention for coastal flooding disaster mitigation. Compared to existing SVI methods, the new SVI leverages principal component analysis and analytic hierarchy process to achieve a better social vulnerability analysis. In the study of wildfires, we focus on the understanding of minority vulnerabilities and their disparities to wildfires over time and space. Minority vulnerabilities are analyzed with spatial clustering methods including Local Moran’s I and Getis-Ord Gi*. The vulnerability disparity is measured based on a reference point from which the quantity separates a minority group on a particular place. Both location quotient and location amplitude index are used to quantitively measure the vulnerability disparity among different minorities. Lastly, in addition to the “direct” impact of disasters on vulnerable population, this dissertation study also conducts vulnerability analysis to failed infrastructure (e.g., power systems) due to disasters, i.e., the “indirect” impact of disasters on different social groups. Recently, scheduled power outages known as Public Safety Power Shutoff (PSPS) are becoming increasingly common to mitigate threats of wildfires to power systems. However, current PSPS decision making processes do not consider the unequal distribution of various social groups, particularly those who are more vulnerable to the power outage. This study investigates the measure of social vulnerability in high-risk fire areas to PSPS, which will help decision makers to better determine the efficiency of a PSPS event for wildfire mitigation.

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / This research aims to analyze the main counties belonging to the Territory Baturità Rural Massif, Cearà State of Brazil, compared to other cities in this State, according to the vulnerability degree of activities involving family farmers. The methodology consisted first in adopt the construction of a Vulnerability Index of Family Farm Agriculture (IMVAF) by using a set of ten (10) variables. The Index seeks to measure the degree of vulnerability of Family Farms in all over the cities of CearÃ, in order to compare with those estimated to the thirteen (13) counties of Baturità Massif. The study was based on two types of analysis: at first, all the counties of the Cearà State were analyzed in relation to the degree of vulnerability of Family Farming, through their respective IMVAF. Second it was made a survey in the counties belonging to region of the Baturità Massif in order to conduct the empirical analysis and with results coming from the secondary data. The construction of IMVAF, together with the use of cluster analysis, resulted in formation of three groups classified according to the degree of vulnerability of the family farms in each county. The results showed that only 22 of 184 (11.96%) counties in the Cearà 11.96% had a low level of vulnerability. The Family Farming in most counties of Cearà State are including in the cluster of medium to high vulnerability. Among the indicators that best differentiated the groups was the variables âentering into the marketâ; and âthe use of animal traction or mechanicalâ. The Baturità Massif Rural Territory presented an average IMVAF of .632. This value showed do not to be different from Rural Areas of Cearà State. Of the thirteen counties that belong to the Baturità Massif, only one (Pacoti) showed low IMVAF. In relation to empirical research, it should be noted that the situation in the farmers visited in the counties is very delicate, setting up, so short of envisioned by the results obtained by calculating the IMVAF. Although there was a time difference between the collecting of primary and secondary data, it can be infered that difficulties are persistent and that in some respects the change of results was negative. / A presente pesquisa tem como objetivo principal analisar os municÃpios que fazem parte do TerritÃrio Rural MaciÃo de BaturitÃ, em relaÃÃo aos demais municÃpios do estado do CearÃ, no que concerne ao grau de vulnerabilidade das atividades envolvendo agricultores familiares. A metodologia adotada consistiu na construÃÃo de um Ãndice Municipal de Vulnerabilidade da Agricultura Familiar (IMVAF) a partir do conjunto de 10 (dez) indicadores. O Ãndice visa a mensurar o grau de vulnerabilidade da Agricultura Familiar em cada municÃpio cearense, de maneira a conhecer a situaÃÃo em que esses municÃpios se encontram, nÃo tendo, portanto, nenhuma pretensÃo de ser considerado absoluto, pois ele funciona apenas como um sinalizador que busca expressar a vulnerabilidade da agricultura familiar no CearÃ. Dessa maneira, o estudo foi embasado em dois tipos de anÃlises: em um primeiro momento, os municÃpios do estado do Cearà foram analisados, no que concerne ao grau de vulnerabilidade da agricultura familiar, por meio dos seus respectivos IMVAF, e, em seguida, escolheu-se a regiÃo do MaciÃo de Baturità para realizar a pesquisa de campo e, assim, comparar os resultados obtidos mediante cÃlculo do Ãndice com aqueles observados nos municÃpios visitados. A construÃÃo do IMVAF, junto ao uso da AnÃlise de agrupamentos, resultou na formaÃÃo de trÃs grupos, classificados de acordo com o grau de vulnerabilidade da agricultura familiar diagnosticado em cada municÃpio. Apenas 22 municÃpios do Estado do CearÃ, 11,96% do total, apresentaram um baixo Ãndice de vulnerabilidade. Entre os indicadores que melhor diferenciaram os grupos, pode-se citar o uso de traÃÃo animal ou mecÃnica e a inserÃÃo no mercado. O TerritÃrio Rural do MaciÃo de Baturità apresentou um IMVAF mÃdio de 0,632, nÃo diferenciando, portanto, dos outros TerritÃrios Rurais do CearÃ. Dos treze municÃpios que compÃem o MaciÃo, apenas um, Pacoti, apresentou baixo IMVAF. Em relaÃÃo à pesquisa de campo, cumpre mencionar que, nos municÃpios visitados, a situaÃÃo dos agricultores, de uma forma geral, à bem delicada, configurando-se, portanto, aquÃm da vislumbrada por intermÃdio dos resultados obtidos pelo cÃlculo do IMVAF. Embora haja um lapso temporal entre os dados secundÃrios e os primÃrios, pode-se dizer que as dificuldades sÃo persistentes e que, em alguns aspectos, a mudanÃa foi negativa

Vid inträffandet av naturolyckor och katastrofer påverkas människor i olika omfattning, inte bara beroende på deras bostads läge utan även utifrån deras sociala förhållanden och förutsättningar. I denna studie genomförs en riskanalys samt utvecklas en metod för beräkning av ett områdes sociala sårbarhet genom ett index. Studiens geografiska avgränsning är en sträcka av Klarälven i Värmland och baseras på data framställt av Skogsstyrelsen, Myndigheten för samhällsskydd och beredskap (MSB), Lantmäteriet och Statistiska centralbyrån (SCB).   I studien beräknades ett socialt sårbarhetsindex genom att kombinera flera lager av SCB:s statistiska data i ett geodatalager med kvadratiska polygoner. Det sociala sårbarhetsindexet kombinerades sedan med resultatet från en flerfaroanalys (multi-hazard analysis) med flera översvämningsscenarion samt områden känsliga för jordskred och ras. Flerfaroanalysen utfördes genom en sammanställning av MSB:s kartering av potentiella översvämningsscenarion och Skogsstyrelsens kartering av områden som kan drabbas av ras eller jordskred. Det sociala sårbarhetsindexet och flerfaroanalysen karterades och överlagrades för att identifiera särskilt sårbara områden.   Med hjälp av det sociala sårbarhetsindexet identifieras en högre social sårbarhet i mer tätbebyggda områden. Indexet påvisar även en högre social sårbarhet i den södra halvan av studieområdet. I flerfaroanalysen ses naturolyckorna variera i omfattning över studieområdet. I den norra delen är risken för jordskred och ras större än i den södra delen som nästan enbart drabbas av översvämningar. Resultaten från riskanalysen visar en “medel-risk” längs en längre sträcka av Klarälven och ökad risk i tätbebyggda områden. För förbättring av det sociala sårbarhetsindexet behövs mer detaljerade data över mindre områden för att öka indexets tillförlitlighet och användningsområden. / When natural phenomena and disasters occur, people are affected to varying degrees, not only depending on the location of their homes, but also on the basis of their social background. In this study, a multi-hazard risk analysis and a method for estimating an area’s social vulnerability through an index were developed. The study was carried out along River Klarälven in Värmland and was based on data produced by the Swedish forest agency, The Swedish Civil Contingencies Agency (MSB), The Swedish Mapping, Cadastral and Land Registration Authority and Statistics Sweden (SCB).   The study presents a social vulnerability index by combining several layers of SCB's statistical data, in a geodata layer with square polygons. The social vulnerability index was combined with a multi-hazard analysis considering several flood scenarios and landslide susceptibility. The multi-hazard analysis was performed through a compilation of MSB's mapping of potential flood scenarios and the Swedish forest agency’s mapping of areas that may be affected by landslides. The social vulnerability index and the results from the multi-hazard analysis were mapped and combined in order to identify areas with substantial risk.    The social vulnerability index indicates a higher social vulnerability in more densely populated areas. The index also shows a slightly higher social vulnerability in the southern half of the study area. The results from the multi-hazard analysis, the spatial distribution of natural hazards varied. The northern part of the study area has a greater susceptibility to landslides than the southern part, which is almost exclusively are induced by floods and extreme flows. The result of the risk analysis shows a “medium risk” along the largest studied part of the River Klarälven and a slightly increased risk in densely populated areas. For future improvements in the development of the social vulnerability index, more data is needed with a higher spatial resolution to increase the index's reliability and areas of use.

A erosão costeira é um processo de grande poder destrutivo e que afeta pelo menos 70% da zona costeira no mundo. Entender as causas e os processos que levam à erosão, bem como as regiões mais ou menos sensíveis a ela, é essencial para o correto manejo costeiro. O presente trabalho visa identificar as áreas vulneráveis à erosão através da aplicação de um Índice de Vulnerabilidade Costeira em praias do norte do Espírito Santo (Pontal do Ipiranga, Conceição da Barra) e sul da Bahia (Mucuri, Nova Viçosa, Caravelas, Prado, Cumuruxatiba, Corumbau, Arraial d\'Ajuda, Porto Seguro). O cálculo do índice se deu pela análise de treze indicadores ambientais: número de frentes frias, regime de tempestade, força de ondas, ângulo de incidência das ondas, estimativa de deriva potencial, morfologia da praia, exposição às ondas, presença de rios e/ou desembocaduras, elevação do terreno, vegetação, taxa de ocupação, obras de engenharia costeira e evidências de erosão. Os resultados mostraram que os indicadores \"morfologia da praia\" e \"exposição às ondas\" parecem ser os principais contribuintes para a erosão costeira nos municípios em que foram observados grandes prejuízos na infraestrutura urbana e perigo iminente à população local. Já nos demais municípios que também apresentaram focos de erosão, a combinação entre os indicadores \"estimativa de deriva potencial\" e \"regimes de tempestade\" parece ser a principal influência ao processo erosivo. Com exceção de Pontal do Ipiranga (que obteve um resultado de baixa vulnerabilidade), todas as praias apresentaram um IVC correspondente à vulnerabilidade moderada à erosão. O estudo se mostra eficiente para a determinação do nível de vulnerabilidade relativo entre as praias estudadas. / Coastal erosion is a process with great destructive power and affects more than 70% of worldwide coastlines. In order to achieve an effective coastal management, it is important to find and understand not only the causes and process that leads to erosion, but also areas that are more or less vulnerable to it. This study aims to identify erosion vulnerable areas through application of a Coastal Vulnerability Index in Brazilian beaches in north Espírito Santo (Pontal do Ipiranga, Conceição da Barra) and south Bahia (Mucuri, Nova Viçosa, Caravelas, Prado, Cumuruxatiba, Corumbau, Arraial d\'Ajuda, Porto Seguro). The index was calculated using 13 indicators: number of cold fronts, storm impact scale, wave power, angle of wave approach, longshore drift estimation, beach morphology, wave exposure, presence of inlets or river mouths, terrain elevation, vegetation, occupation rate, coastal engineering structures and erosion evidences. In places where great urban infrastructure destruction and imminent danger to local community were observed, both \"beach morphology\" and \"wave exposure\" seem to be the main contributors to coastal erosion. In other locations where erosion evidences were also observed, the combination between the indicators \"longshore drift estimation\" and \"storm impact scale\" seems to be the main influence to erosive process. IVC results showed that all the beaches are in a moderate vulnerability context, except in Pontal do Ipiranga, where the result was for low vulnerability. The study has proven to be effective in defining the relative vulnerability of the studied beaches.

L’érosion éolienne est un problème environnemental parmi les plus sévères dans les régions arides, semi-arides et les régions sèches sub-humides de la planète. L’érosion des sols accélérée par le vent provoque des dommages à la fois localement et régionalement. Sur le plan local, elle cause la baisse des nutriments par la mobilisation des particules les plus fines et de la matière organique. Cette mobilisation est une des causes de perte de fertilité des sols avec comme conséquence, une chute de la productivité agricole et une réduction de la profondeur de la partie arable. Sur le plan régional, les tempêtes de poussières soulevées par le vent ont un impact non négligeable sur la santé des populations, et la déposition des particules affecte les équipements hydrauliques tels que les canaux à ciel ouvert ainsi que les infrastructures notamment de transport. Dans les régions où les sols sont fréquemment soumis à l’érosion éolienne, les besoins pour des études qui visent à caractériser spatialement les sols selon leur degré de vulnérabilité sont grands. On n’a qu’à penser aux autorités administratives qui doivent décider des mesures à prendre pour préserver et conserver les potentialités agropédologiques des sols, souvent avec des ressources financières modestes mises à leur disposition. Or, dans certaines de ces régions, comme notre territoire d’étude, la région de Thiès au Sénégal, ces études font défaut. En effet, les quelques études effectuées dans cette région ou dans des contextes géographiques similaires ont un caractère plutôt local et les approches suivies (modèles de pertes des sols) nécessitent un nombre substantiel de données pour saisir la variabilité spatiale de la dynamique des facteurs qui interviennent dans le processus de l’érosion éolienne. La disponibilité de ces données est particulièrement problématique dans les pays en voie de développement, à cause de la pauvreté en infrastructures et des problèmes de ressources pour le monitoring continu des variables environnementales. L’approche mise de l’avant dans cette recherche vise à combler cette lacune en recourant principalement à l’imagerie satellitale, et plus particulièrement celle provenant des satellites Landsat-5 et Landsat-7. Les images Landsat couvrent la presque totalité de la zone optique du spectre exploitable par télédétection (visible, proche infrarouge, infrarouge moyen et thermique) à des résolutions relativement fines (quelques dizaines de mètres). Elles permettant ainsi d’étudier la distribution spatiale des niveaux de vulnérabilité des sols avec un niveau de détails beaucoup plus fin que celui obtenu avec des images souvent utilisées dans des études environnementales telles que AVHRR de la série de satellites NOAA (résolution kilométrique). De plus, l’archive complet des images Landsat-5 et Landsat-7 couvrant une période de plus de 20 ans est aujourd’hui facilement accessible. Parmi les paramètres utilisés dans les modèles d’érosion éolienne, nous avons identifiés ceux qui sont estimables par l’imagerie satellitale soit directement (exemple, fraction du couvert végétal) soit indirectement (exemple, caractérisation des sols par leur niveau d’érodabilité). En exploitant aussi le peu de données disponibles dans la région (données climatiques, carte morphopédologique) nous avons élaboré une base de données décrivant l’état des lieux dans la période de 1988 à 2002 et ce, selon les deux saisons caractéristiques de la région : la saison des pluies et la saison sèche. Ces données par date d’acquisition des images Landsat utilisées ont été considérées comme des intrants (critères) dans un modèle empirique que nous avons élaboré en modulant l’impact de chacun des critères (poids et scores). À l’aide de ce modèle, nous avons créé des cartes montrant les degrés de vulnérabilité dans la région à l’étude, et ce par date d’acquisition des images Landsat. Suite à une série de tests pour valider la cohérence interne du modèle, nous avons analysé nos cartes afin de conclure sur la dynamique du processus pendant la période d’étude. Nos principales conclusions sont les suivantes : 1) le modèle élaboré montre une bonne cohérence interne et est sensible aux variations spatiotemporelles des facteurs pris en considération 2); tel qu’attendu, parmi les facteurs utilisés pour expliquer la vulnérabilité des sols, la végétation vivante et l’érodabilité sont les plus importants ; 3) ces deux facteurs présentent une variation importante intra et inter-saisonnière de sorte qu’il est difficile de dégager des tendances à long terme bien que certaines parties du territoire (Nord et Est) aient des indices de vulnérabilité forts, peu importe la saison ; 4) l’analyse diachronique des cartes des indices de vulnérabilité confirme le caractère saisonnier des niveaux de vulnérabilité dans la mesure où les superficies occupées par les faibles niveaux de vulnérabilité augmentent en saison des pluies, donc lorsque l’humidité surfacique et la végétation active notamment sont importantes, et décroissent en saison sèche ; 5) la susceptibilité, c’est-à-dire l’impact du vent sur la vulnérabilité est d’autant plus forte que la vitesse du vent est élevée et que la vulnérabilité est forte. Sur les zones où la vulnérabilité est faible, les vitesses de vent élevées ont moins d’impact. Dans notre étude, nous avons aussi inclus une analyse comparative entre les facteurs extraits des images Landsat et celles des images hyperspectrales du satellite expérimental HYPERION. Bien que la résolution spatiale de ces images soit similaire à celle de Landsat, les résultats obtenus à partir des images HYPERION révèlent un niveau de détail supérieur grâce à la résolution spectrale de ce capteur permettant de mieux choisir les bandes spectrales qui réagissent le plus avec le facteur étudié. Cette étude comparative démontre que dans un futur rapproché, l’amélioration de l’accessibilité à ce type d’images permettra de raffiner davantage le calcul de l’indice de vulnérabilité par notre modèle. En attendant cette possibilité, on peut de contenter de l’imagerie Landsat qui offre un support d’informations permettant tout de même d’évaluer le niveau de fragilisation des sols par l’action du vent et par la dynamique des caractéristiques des facteurs telles que la couverture végétale aussi bien vivante que sénescente. / Wind erosion is an environmental issue among the most critical one in arid, semi-arid and dry sub-humid regions of the planet. Soil erosion accelerated by the wind action causes damages both locally and regionally. Locally, wind erosion decreases the soil nutrients by the mobilization of finer particles and organic matter. This mobilization is one of the causes of lost of soil fertility with lead to the drop in agricultural productivity and to the reduction of the topsoil depth. Regionally, dust storms raised by the wind have a significant impact on population health and infrastructure because of particles deposition. In areas where soils are frequently submitted to wind aggressions, studies are urgently required in order to spatially characterize the soils according to their degree of vulnerability. Such characterization is important for many reasons, especially for administrative authorities who must decide what action to undertake in order to preserve and conserve the agricultural potentialities of soils, often with limited financial resources available. However, in some regions, as in our study area, the region of Thiès in Senegal, such studies are lacking. In fact, in regions where soil erosion is active, the studies undertaken are much localized because of their approaches (soil erosion models) which require a substantial amount of data for short intervals of time to "capture" the spatial variability of the dynamics of the factors involved in the process of wind erosion. The availability of these data at a regional level is particularly problematic in developing countries because infrastructures and resources to support continuous monitoring of environmental variables are not always available. The approach in this research aims to fill this gap, mainly through satellite imagery and more particularly those provided by Landsat-5 and Landsat-7. Landsat images cover almost the entire optical spectrum (visible, near/mid/thermal infrared) at resolutions which allow to characterize spatially the soils, according to their vulnerability at a finer level (decametric resolution) than what is possible with satellite imagery often used in environmental studies (AVHRR images from the NOAA satellite series) with a kilometric resolution. In addition, the full archive of Landsat-5 and -7 covering more than 20 years is now easily accessible. This is an undeniable asset in order to study the dynamics of the process affecting soils vulnerability to wind erosion. Taking into account the parameters used in wind erosion models (climate, soil, vegetation), we have identified those we can estimate from satellite imagery either directly (e.g. fractional vegetation cover) or indirectly (e.g. characterization of soils by their degree of degradation). Using Landsat images acquired during to the two seasons of the region (rainy and dry season) as well as climatic data and the existing low scale soil map of the region, we developed a database describing the environmental conditions from 1988 to 2002. These data were then considered as inputs (criteria) in an empirical model we made, by modulating the impact of each criterion (weight and score). By this model, we created maps showing the degree of vulnerability (vulnerability index) of the region by date according to Landsat image acquisition date. Several tests are done to validate the internal consistency of the model. To evaluate the dynamic of the erosion process for the period we studied, we have compared our maps. Our principal conclusions are as follows: 1) the proposed model has a good internal consistency and is sensitive to spatial and temporal variation of the factors taken into consideration; 2) as expected, among the factors used to explain soil vulnerability, erodibility and fractional green vegetation cover are the most important; 3) these two factors present a high intra and inter-season variation so that it is difficult to bring out long term trends even if some parts of the territory (North and East) have high vulnerability indices regardless of season; 4) the diachronic analysis of vulnerability index maps shows seasonal trend because areas with low vulnerability indices are increasing in rainy season, when the surface moisture is higher and vegetation is particularly active, and significantly decrease in dry season; 5) as expected, susceptibility, or the impact of wind on vulnerability, is stronger when the wind speed is high and vulnerability is high. In areas where vulnerability is low, an increase in wind speed has less impact. In our study we have also included a comparative analysis of some factors derived from Landsat images and from the hyperspectral sensor of the experimental satellite HYPERION. Even if spatial resolution of the images provided by both sensors is similar, the accuracy of factors extracted from the hyperspectral images is definitely higher. This is due to the spectral resolution of the sensor which permits the selection of appropriate bands with the highest level of interaction with the factor of interest. This comparative study shows that in the near future, the accessibility to this type of images will improve the calculation of the index of vulnerability by our model. For now, Landsat imagery provides very interesting information to monitor the process of soil erosion by wind.

No description available.

A erosão costeira é um processo de grande poder destrutivo e que afeta pelo menos 70% da zona costeira no mundo. Entender as causas e os processos que levam à erosão, bem como as regiões mais ou menos sensíveis a ela, é essencial para o correto manejo costeiro. O presente trabalho visa identificar as áreas vulneráveis à erosão através da aplicação de um Índice de Vulnerabilidade Costeira em praias do norte do Espírito Santo (Pontal do Ipiranga, Conceição da Barra) e sul da Bahia (Mucuri, Nova Viçosa, Caravelas, Prado, Cumuruxatiba, Corumbau, Arraial d\'Ajuda, Porto Seguro). O cálculo do índice se deu pela análise de treze indicadores ambientais: número de frentes frias, regime de tempestade, força de ondas, ângulo de incidência das ondas, estimativa de deriva potencial, morfologia da praia, exposição às ondas, presença de rios e/ou desembocaduras, elevação do terreno, vegetação, taxa de ocupação, obras de engenharia costeira e evidências de erosão. Os resultados mostraram que os indicadores \"morfologia da praia\" e \"exposição às ondas\" parecem ser os principais contribuintes para a erosão costeira nos municípios em que foram observados grandes prejuízos na infraestrutura urbana e perigo iminente à população local. Já nos demais municípios que também apresentaram focos de erosão, a combinação entre os indicadores \"estimativa de deriva potencial\" e \"regimes de tempestade\" parece ser a principal influência ao processo erosivo. Com exceção de Pontal do Ipiranga (que obteve um resultado de baixa vulnerabilidade), todas as praias apresentaram um IVC correspondente à vulnerabilidade moderada à erosão. O estudo se mostra eficiente para a determinação do nível de vulnerabilidade relativo entre as praias estudadas. / Coastal erosion is a process with great destructive power and affects more than 70% of worldwide coastlines. In order to achieve an effective coastal management, it is important to find and understand not only the causes and process that leads to erosion, but also areas that are more or less vulnerable to it. This study aims to identify erosion vulnerable areas through application of a Coastal Vulnerability Index in Brazilian beaches in north Espírito Santo (Pontal do Ipiranga, Conceição da Barra) and south Bahia (Mucuri, Nova Viçosa, Caravelas, Prado, Cumuruxatiba, Corumbau, Arraial d\'Ajuda, Porto Seguro). The index was calculated using 13 indicators: number of cold fronts, storm impact scale, wave power, angle of wave approach, longshore drift estimation, beach morphology, wave exposure, presence of inlets or river mouths, terrain elevation, vegetation, occupation rate, coastal engineering structures and erosion evidences. In places where great urban infrastructure destruction and imminent danger to local community were observed, both \"beach morphology\" and \"wave exposure\" seem to be the main contributors to coastal erosion. In other locations where erosion evidences were also observed, the combination between the indicators \"longshore drift estimation\" and \"storm impact scale\" seems to be the main influence to erosive process. IVC results showed that all the beaches are in a moderate vulnerability context, except in Pontal do Ipiranga, where the result was for low vulnerability. The study has proven to be effective in defining the relative vulnerability of the studied beaches.

Social factors moderate the impacts of natural hazards, which means that households are affected differently when exposed to the same hazard. This differential impact of hazards can be explained by the concept of social vulnerability, which is commonly assessed to inform disaster preparedness and response action. Most of these assessments, however, focus their analyses on large administrative units and, consequently, neglect the heterogeneity of households within these units. This thesis leverages data from Malawi’s social registry (the UBR) to construct a Household Social Vulnerability Index for Nsanje – one of the most disaster-prone districts in Malawi. In Nsanje, geocoded socio-economic data was collected using a census-sweep approach with the goal of registering 100% of the district’s residents. From this dataset, indicators are deductively selected and analyzed using Principal Component Analysis to produce a social vulnerability score for each household. These index scores are mapped at a spatial resolution of 0,01°. By repurposing a social registry to inform a new set of actors, including humanitarian and disaster risk management practitioners, the thesis highlights the considerable scope for collaboration within the realm of data and information by actors and policy fields that traditionally largely have operated in isolation from one another.

<p>Рањивост од&nbsp; природних хазарда представља атрактивну тему<br />данашњице, која произилази из значаја који има за проблематику<br />природних непогода. Рањивост представља обавезну компоненту<br />сваке природне непогоде, тачније схвата се као &bdquo;контролна<br />полуга&ldquo; за смањење ризика од природних непогода. Социјална<br />рањивост од природних хазарда треба да укаже и опише ко или<br />шта је угрожено деловањем природног хазарда и у којој мери, као<br />и на обим и озбиљност последица које из потенцијалне колизије<br />могу произаћи. Из тог разлога, јавила се&nbsp; потреба да се социјална<br />рањивост измери, премери или процени у тежњи да се теоријске<br />поставке боље разумеју и добију практичну примену. Тај<br />комплексан приступ треба да пружи информације о нивоима<br />рањивости, као и отпорности одређених елемената у простору,&nbsp; а<br />потом и да омогући идентификацију покретачких фактора који<br />утичу на формирање и развој појаве социјалне рањивости. С<br />обзиром да је процена социјалне рањивости базирана на<br />званичним статистичким подацима, који дају уопштену, стерилну<br />слику стварности, за&nbsp; њено употпуњавање и хуманизацију<br />неопходно је истраживање перцепције, знања, ставова и искуства<br />становништва са природним хазардима и природним непогодама.<br />Најбољи приступ за испуњење тог циља је анкетно истраживање<br />које треба да омогући увид у поменуте карактеристике код<br />појединца, а потом обрадом добијених података и њиховим<br />уопштавањем стиче се потпуна слика о друштву и његовом<br />односу према природним хазардима и спремност за природне<br />непогоде.</p> / <p>Ranjivost od&nbsp; prirodnih hazarda predstavlja atraktivnu temu<br />današnjice, koja proizilazi iz značaja koji ima za problematiku<br />prirodnih nepogoda. Ranjivost predstavlja obaveznu komponentu<br />svake prirodne nepogode, tačnije shvata se kao &bdquo;kontrolna<br />poluga&ldquo; za smanjenje rizika od prirodnih nepogoda. Socijalna<br />ranjivost od prirodnih hazarda treba da ukaže i opiše ko ili<br />šta je ugroženo delovanjem prirodnog hazarda i u kojoj meri, kao<br />i na obim i ozbiljnost posledica koje iz potencijalne kolizije<br />mogu proizaći. Iz tog razloga, javila se&nbsp; potreba da se socijalna<br />ranjivost izmeri, premeri ili proceni u težnji da se teorijske<br />postavke bolje razumeju i dobiju praktičnu primenu. Taj<br />kompleksan pristup treba da pruži informacije o nivoima<br />ranjivosti, kao i otpornosti određenih elemenata u prostoru,&nbsp; a<br />potom i da omogući identifikaciju pokretačkih faktora koji<br />utiču na formiranje i razvoj pojave socijalne ranjivosti. S<br />obzirom da je procena socijalne ranjivosti bazirana na<br />zvaničnim statističkim podacima, koji daju uopštenu, sterilnu<br />sliku stvarnosti, za&nbsp; njeno upotpunjavanje i humanizaciju<br />neophodno je istraživanje percepcije, znanja, stavova i iskustva<br />stanovništva sa prirodnim hazardima i prirodnim nepogodama.<br />Najbolji pristup za ispunjenje tog cilja je anketno istraživanje<br />koje treba da omogući uvid u pomenute karakteristike kod<br />pojedinca, a potom obradom dobijenih podataka i njihovim<br />uopštavanjem stiče se potpuna slika o društvu i njegovom<br />odnosu prema prirodnim hazardima i spremnost za prirodne<br />nepogode.</p> / <p>Today,&nbsp; vulnerability&nbsp; to natural hazards is one of the most attractive topic, which stems from its importance for the research field of natural disasters. Vulnerability is a mandatory component of any natural disasters, more precisely understood as the &quot;control lever&quot; to reduce the natural disasters risk. Social vulnerability should point to and describe who or what is at risk from natural hazards and the extent and severity of the consequences of potential collisions. For this reason, there is a need to&nbsp; measure or estimate social vulnerability, which will enable theoretical assumptions to be better understood and receive practical application. This complex approach should provide information on the levels of vulnerability, as well as the resistance of certain elements in space,&nbsp; and then to allow the identification of the driving factors that influence the formation and development of the social vulnerability phenomena. Social vulnerability assessment is based on official statistics, which provide a general, sterile picture of reality, but its humanization is necessary through exploring of perceptions, knowledge, awareness and experiences of the society to natural hazards and natural disasters. The best approach for achieving that goal is the survey that should provide insight into the mentioned characteristics of the individual, and then processing the data and their generalization gets the full picture of the society and its relation to natural hazards and natural disasters preparedness.</p>