Land-use changes impact the energy balance of the Earth system, and feedbacks in the Earth system can dampen or amplify this perturbation. We analyze here from satellite data the response of clouds and subsequently radiation to a change of land use for the example of deforestation in the Amazon Basin. In this region, the characteristics of different cloud types over two vegetation types (forest and crop-/grasslands) were calculated for a time period of five years by using satellite data from the instruments MODIS and CERES. The cloud types are defined according to height, optical thickness, and fraction of cloud cover. For calculating the radiative forcing caused by deforestation, the dependency of spatial and temporal averages for the reflected shortwave and outgoing longwave radiation of the top of the atmosphere on vegetation types were determined as well. The results show distinct differences in cloud cover and radiative forcing over crop-/grasslands and forests for the two vegetation regimes, implying a potentially significant positive cloud feedback to deforestation.

The IPCC's report in 2018 projects global warming will increase by 1.5oC in 2030, which makes contribution of each country to control their emissions becomes significant. This study seeks to investigate what entitlement human beings have over the absorptive capacity of the atmosphere as well as the harm it caused by elaborating the Entitlement Theory of Justice, thereto, finding out how the burden of climate change should be distributed according to the Polluter Pays Principle (PPP) and the Equal per Capita Shares Principle (ECSP). Furthermore, this study seeks to investigate Indonesia's part in increasing the burden of climate change and whether Indonesia should be held responsible for its part by comparing data of Indonesia's emissions to some developed countries' emissions. Humanity has a collective ownership over the absorptive capacity of the atmosphere, which implies that every individual has equal share of this absorptive capacity. A violation of this equal share should be compensated. The PPP suggests countries, who has the most cumulative amount of emissions from the past to present, to compensate and bear the climate change burden. While, the ECSP suggests countries, who emit more than their equal share per capita, to bear the climate change burden and reduce their emissions. Indonesia, despites massive amounts of CO2 released by its deforestation and annual haze, contributes insignificant to climate change due to both its cumulative and per capita emissions are considerably low compared to developed countries and even lower than acountry with large population size such as China.

As communities and managers become aware of the long-term impacts of mangrove loss, estimated at 1-2% per year, interest in sediment erosion and mangrove rehabilitation has increased substantially. In this thesis project I 1) examine erosion rates within coastal fringing Rhizophora mangle ecosystems following mangrove clearing and compare these rates to accretion rates in intact mangroves; and 2) investigate the abiotic factors influencing mangrove seedling survival and regeneration of naturally colonizing R. mangle, in historic mangrove habitat after anthropogenic clearing. Differences in erosion were compared between patches of open-coast intact and anthropogenically cleared R. mangle to quantify the sediment trapping function provided by mangroves and its loss following clearing over a 24 month period. Growth rates of mangrove seedlings in intact forest were compared to seedlings in cleared areas. Seedling growth indicators were measured on 100 seedlings at five sites (50 in the intact and 50 in the cleared areas). To examine the limiting factors on seedling growth rates, nutrient addition and wave protection treatments were applied to seedlings in three disturbed areas. Sites within intact mangroves had sediment accretion (M= +3.83 mm) while areas cleared of mangroves had sediment erosion (M= -7.30 mm). Seedling growth (height) over the 2 year study period significantly differed between intact mangrove (M = 15.6 cm) and cleared (M = 10.24 cm) areas. Seedling mortality from the cleared areas (31%) differed from the intact areas (13%). Average seedling growth (height) was: greater with both nutrient/wave (M = 18.4 cm) and nutrient (M = 17.65 cm) treatments compared to controls (M = 10.8 cm), which suggests that providing nutrients and/or wave protection result in growth outputs comparable to seedlings found in intact mangroves. This study may prove to be useful in identifying areas that are most vulnerable to erosion following mangrove removal and ideal location of restoration following mangrove removal. Areas cleared of mangroves can lead to intensified erosion in areas where fringing reefs are not continuous. When managers are determining areas to focus resources for restoration, focusing on areas with nutrient rich habitat may result in higher survival rates and growth outputs.

No description available.

[pt] Os dados de observação da Terra são freqüentemente afetados pelo fenômeno de mudança de domínio. Mudanças nas condições ambientais, variabilidade geográfica e diferentes propriedades de sensores geralmente tornam quase impossível empregar classificadores previamente treinados para novos dados sem experimentar uma queda significativa na precisão da classificação. As técnicas de adaptação de domínio baseadas em modelos de aprendizado profundo têm se mostrado úteis para aliviar o problema da mudança de domínio. Trabalhos recentes nesta área fundamentam-se no treinamento adversárial para alinhar os atributos extraídos de imagens de diferentes domínios em um espaço latente comum. Outra forma de tratar o problema é empregar técnicas de translação de imagens e adaptá-las de um domínio para outro de forma que as imagens transformadas contenham características semelhantes às imagens do outro domínio. Neste trabalho, propõem-se abordagens de adaptação de domínio para tarefas de detecção de mudanças, baseadas em primeiro lugar numa técnica de traslação de imagens, Cycle-Consistent Generative Adversarial Network (CycleGAN), e em segundo lugar, num modelo de alinhamento de atributos: a Domain Adversarial Neural Network (DANN). Particularmente, tais técnicas foram estendidas, introduzindo-se restrições adicionais na fase de treinamento dos componentes do modelo CycleGAN, bem como um procedimento de pseudo-rotulagem não supervisionado para mitigar o impacto negativo do desequilíbrio de classes no DANN. As abordagens propostas foram avaliadas numa aplicação de detecção de desmatamento, considerando diferentes regiões na floresta amazônica e no Cerrado brasileiro (savana). Nos experimentos, cada região corresponde a um domínio, e a precisão de um classificador treinado com imagens e referências de um dos domínio (fonte) é medida na classificação de outro domínio (destino). Os resultados demonstram que as abordagens propostas foram bem sucedidas em amenizar o problema de desvio de domínio no contexto da aplicação alvo. / [en] Earth observation data are frequently affected by the domain shift phenomenon. Changes in environmental conditions, geographical variability and different sensor properties typically make it almost impossible to employ previously trained classifiers for new data without a significant drop in classification accuracy. Domain adaptation (DA) techniques based on Deep Learning models have been proven useful to alleviate domain shift. Recent improvements in DA technology rely on adversarial training to align features extracted from images of the different domains in a common latent space. Another way to face the problem is to employ image translation techniques, and adapt images from one domain in such a way that the transformed images contain characteristics that are similar to the images from the other domain. In this work two different DA approaches for change detection tasks are proposed, which are based on a particular image translation technique, the Cycle-Consistent Generative Adversarial Network (CycleGAN), and on a representation matching strategy, the Domain Adversarial Neural Network (DANN). In particular, additional constraints in the training phase of the original CycleGAN model components are proposed, as well as an unsupervised pseudo-labeling procedure, to mitigate the negative impact of class imbalance in the DANN-based approach. The proposed approaches were evaluated on a deforestation detection application, considering different sites in the Amazon rain-forest and in the Brazilian Cerrado (savanna) biomes. In the experiments each site corresponds to a domain, and the accuracy of a classifier trained with images and references from one (source) domain is measured in the classification of another (target) domain. The experimental results show that the proposed approaches are successful in alleviating the domain shift problem.

[pt] Ascensão e queda da imagem de um Brasil ambientalmente responsável: uma análise à luz do arcabouço da diplomacia pública. A dissertação trata da aparente contradição na literatura de análise de política externa brasileira que ressalta a ativa participação brasileira em fóruns multilaterais de meio ambiente, mas também aponta sua falta de sistematicidade e contradições. A diplomacia pública é oferecida como saída para essa contradição ao interpretar os esforços brasileiros como iniciativas de comunicação visando lidar com pressões internacionais que retornam – após cerca de 30 anos - em uma aparente correlação com o abandono por parte do Estado da imagem construída de um país ambientalmente responsável. Para isso, o trabalho se vale de uma combinação de métodos qualitativos e quantitativos e de extensa revisão bibliográfica nos campos de política externa brasileira para meio ambiente e diplomacia pública. / [en] Ascensão e queda da imagem de um Brasil ambientalmente responsável: uma análise à luz do arcabouço da diplomacia pública. The dissertation deals with the apparent contradiction in the Brazilian foreign policy analysis literature that highlights the active Brazilian participation in multilateral environmental forums, but also points out its lack of systematicity and contradictions. Public diplomacy is offered as a way out of this contradiction when interpreting Brazilian efforts as communication initiatives aimed at dealing with international pressures that return - after 30 years - in an apparent correlation with the State s abandonment of the country s built image of itself as environmentally responsible. For this, the work uses a combination of qualitative and quantitative methods and an extensive bibliographic review in the fields of Brazilian foreign policy for the environment and public diplomacy.

This thesis examines the conservation narratives of Madagascar the ambiguity of forest cover and deforestation estimates, and the difficulty in deconstructing the narratives linked to the idea of a once fully forested island. In particular, shifts in the conservation debate are related to the discursive power of a large-scale international NGO, the WWF. A diachronic perspective is provided both through a discussion of earlier research and discourse analyses of selected texts, published by WWF Madagascar between 1991–2020. The theory and method are developed from Dryzek’s environmental discourse analysis with some modifications. The categories used in the conservation discourse analysis relate to baselines and intertextuality; underlying narratives such as problem representations and metaphors; the different values given to biodiversity; and possible hegemonic discourses within the conservation debate surrounding Madagascar. The discussion on WWF Madagascar also connects with the progression of environmental movements and conservationism, as reflected through shifting conservation priorities in both international contexts and local community conservation efforts. The conclusion demonstrates that shifts in WWF Madagascar’s conservation work reflect global perceptions and assumptions of what has protection value, and vice versa. It is concluded that the role of NGOs in creating and disseminating environmental narratives affects the conservation discourse on all levels and inmultiple contexts – such as media, academia, communities, and politics. In this discussion, the diachronic perspective on intertextuality presented here, especially regarding baselines and estimates of forest cover, illustrates how environmental history is key to conservation, and how at the same time NGOs can play a role as intermediaries in reshaping environmental narratives. / Denna avhandling undersöker Madagaskars bevarandeberättelser, oklarheten i uppskattningar av skogstäcke och avskogning samt svårigheten i att dekonstruera berättelser kopplade till idén om en tidigare helt skogbevuxen ö. Framför allt är förändringar i bevarandedebatten relaterade till det diskursiva inflytandet hos en storskalig internationell icke-statlig organisation, WWF (Världsnaturfonden). Ett diakront perspektiv ges både genom en diskussion av tidigare forskning och diskursanalyser av utvalda texter, publicerade av WWF Madagaskar mellan 1991–2020. Teorin och metoden är utvecklad med några modifieringar av Dryzeks miljödiskursanalys. De kategorier som används i diskursanalysen relaterar till skogsmätning och intertextualitet; underliggande berättelser såsom problemrepresentationer och metaforer; de olika värden som ges till biologisk mångfald; och eventuella hegemoniska diskurser inom bevarandedebatten kring Madagaskar. Diskussionen om WWF Madagaskar hänger också ihop med miljörörelsens och naturvårdens utveckling, sett genom växlande bevarandeprioriteringar i både internationella sammanhang och lokalsamhällets bevarandeinsatser. Slutsatsen visar att förändringar i WWF Madagaskars bevarandearbete återspeglar globala uppfattningar och antaganden om vad som har skyddsvärde och vice versa. Slutsatsen som dras är att de icke-statliga organisationernas roll i att skapa och sprida miljöberättelser påverkar bevarandediskursen på alla nivåer och i flera sammanhang – såsom media, akademi, samhällen och politik. Särskilt gällande uppskattningar av skogstäcke belyser denna diskussion det diakrona perspektivet på intertextualitet som presenteras här, hur miljöhistoria är nyckeln till bevarande, och samtidigt hur icke-statliga organisationer kanagera som förmedlare i omformningen av miljöberättelser.

[pt] O desmatamento é uma das principais causas de redução da biodiversidade, mudança climática e outros fenômenos destrutivos. Assim, a detecção antecipada de desmatamento é de suma importância. Técnicas baseadas em imagens de satélite são uma das opções mais iteresantes para esta aplicação. No entanto, muitos trabalhos desenvolvidos incluem algumas operações manuais ou dependência de um limiar para identificar regiões que sofrem desmatamento ou não. Motivado por este cenário, a presente dissertação apresenta uma avaliação de métodos para detecção automática de desmatamento, especificamente de Early Fusion (EF) Convolutional Network, Siamese Convolutional Network (SN), Convolutional Support Vector Machine (CSVM) e Support Vector Machine (SVM), o último tomado como baseline. Todos os métodos foram avaliados em regiões dos biomas brasileiros Amazônia e Cerrado. Duas imagens Landsat 8 adquiridas em diferentes datas foram utilizadas nos experimentos, e também o impacto do tamanho do conjunto de treinamento foi analisado. Os resultados demonstraram que as abordagens baseadas no Deep Learning superaram claramente o baseline SVM em termos de pontuação F1-score e Overrall Accuracy, com uma superioridade de SN e EF sobre CSVM e SVM. Da mesma forma, uma redução do efeito sal e pimenta nos mapas de mudança gerados foi notada devido, principalmente ao aumento de amostras nos conjuntos de treinamento. Finalmente, realizou-se uma análise visando avaliar como os métodos podem reduzir o esforço humano na inspeção visual das áreas desmatadas. / [en] Deforestation is one of the main causes of biodiversity reduction, climate change, among other destructive phenomena. Thus, early detection of deforestation processes is of paramount importance. Techniques based on satellite images are one of the most attractive options for this application. However, many works developed include some manual operations or dependency on a threshold to identify regions that suffer deforestation or not. Motivated by this scenario, the present dissertation presents an evaluation of methods for automatic deforestation detection, specifically Early Fusion (EF) Convolutional Network, Siamese Convolutional Network (SN), Convolutional Support Vector Machine (CSVM) and Support Vector Machine (SVM), taken as the baseline. These methods were evaluated in regions of Brazilian Amazon and Cerrado Biomes. Two Landsat 8 images acquired at different dates were used in the experiments, and the impact of training set size was also analyzed. The results demonstrated that Deep Learning-based approaches clearly outperformed the SVM baseline in our approaches, both in terms of F1-score and Overall Accuracy, with the superiority of SN and EF over CSVM and SVM. In the same way, a reduction of the salt-and-pepper effect in the generated probabilistic change maps was noticed due, mainly, to the increase of samples in the training sets. Finally, an analysis was carried out to assess how the methods can reduce the time invested in the visual inspection of deforested areas.

This dissertation consists of three essays in theoretical and applied microeconomics: the first essay is in cooperative game theory, and the second and third essays relate to forest economics. The first chapter studies a class of cooperative games dubbed ``r-essential games''. Cooperative game theory has proposed different notions of powerful players. For example, big-boss games (Muto et al., 1988) and clan games (Potters et al., 1989) are particular cases of veto games (Bahel, 2016). The first chapter extends these veto games by assuming that there is a given subset of powerful (or essential) players, but only a few (as opposed to all) essential players are required for a coalition to have a positive value. The resulting games, which are called r-essential games, encompass convex games (Shapley, 1971) and veto games. We show that r-essential games have a nonempty core. We give a recursive description of the core. Moreover, it is shown that the core and the bargaining set are equivalent for every r-essential game. An application to networks is provided. The second chapter employs a two-principal, one-agent model to estimate the social cost of fiscal federalism in China's northeast native forests. China's key forested region is located in the northeast and consists of state forest enterprises which manage forest harvesting and reforestation. Deforestation is a major problem there and has resulted in several central government reforms. We develop a framework for assessing the social cost of state forest enterprise deforestation. We first develop a two-principal, one-agent model that fits the federalistic organization of state forests, in that state forest managers make (potentially hidden) decisions under influence of provincial and central government policies. This model is used to quantify the social cost of these hidden actions. We then use panel data from a survey conducted by Peking University to compute social welfare losses and to formally identify the main factors in these costs. A sensitivity analysis shows that, interestingly, command and control through lower harvesting limits and a more accurate monitoring system are more important to lowering social welfare losses than conventional incentives targeting the wages of forest managers. Through regression analysis we also find that the more remote areas with a higher percentage of mature natural forests are the ones that will always have the highest social welfare losses. The third chapter studies the problem of choosing a rotation under uncertain future ecosystem values and timber prices. This problem is nearly as old as the field of forest economics itself. A forest owner faces various uncertainties caused by climate change and market shocks, due to its long-term nature of production and the joint production of interrelated timber and amenity (non-harvesting) benefit streams. The vast literature in stochastic rotation problems simply assumes a known probability distribution for whatever parameter is uncertain, but this type of assumption may lead to misspecification of a rotation decision model if a forest owner has no such information. We study a more relevant question of how to choose rotation ages when there is pure (or Knightian) uncertainty, in that the forest owner does not know distributional features of parameters and further can be averse to this type of information deficit. This chapter is the first to investigate pure uncertainty in amenity benefit streams and is also the first to analytically solve a stochastic rotation problem under pure uncertainty in either amenity streams or market prices. We use robust methods developed in macroeconomics that are particularly suited to forest capital investment problem, but with important differences owing to the nature of forest goods production. The results show that newer models suggesting rotation ages could be longer under volatile parameter distributions do not hold generally when pure uncertainty and forest owner uncertainty aversion is considered. Rather, the earlier literature showing faster or greater harvesting with increases in risk under risk neutrality may actually be a more general result than current literature supposes. In particular, we find that a landowner tends to harvest more when his degree of uncertainty aversion is higher and the model is misspecified by assumption, or when the volatility of an uncertain process is higher. These situations tend to magnify model misspecification costs, especially because the forest manager always assumes the worst case will happen when there is uncertainty. This implies the decision maker is pessimistic in the sense that he or she is always trying to maximize the utility under the worst possible state of nature (the lowest amenity benefit or the lowest timber price). Whether landowners are in fact uncertainty averse and assume the worst case in their decisions remains to be empirically investigated, but our work suggests it is an important question that must be answered. / Doctor of Philosophy / This dissertation consists of three essays in theoretical and applied microeconomics: the first essay is in cooperative game theory, and the second and third essays relate to forest economics. The first chapter studies a class of cooperative games dubbed ``r-essential games''. Cooperative game theory has proposed different notions of powerful players. For example, veto games (Bahel, 2016) have powerful players that are named veto players. Any coalition needs to include all these powerful players to achieve a positive coalition value. The first chapter extends these veto games by assuming that there is a given subset of powerful (or essential) players, but only a few (as opposed to all) essential players are required for a coalition to have a positive value. The resulting games, which are called r-essential games, encompass two classic games, convex games (Shapley, 1971) and veto games. We show that each r-essential game has at least one solution that is an allocation guaranteeing that no coalition can do better on its own. We provide a process allowing to compute this allocation in each r-essential game. An application to networks is provided. The second chapter estimates the damage of deforestation in China's northeast forests. This region consists of state forest enterprises which manage harvesting and reforestation and have represented the most important source of wood supplies since the 1950s. Deforestation is a major problem there. We develop a framework for assessing the damage to the society because of deforestation. We develop a theoretical model to describe the forest management structure, in which state forest managers make (potentially hidden) decisions under influence of provincial and central government policies. This model is used to quantify the damage. We then use data from a survey conducted by Peking University to compute the damage and confirm the main factors in these damages in practice. We find that lower harvesting limits and a more accurate monitoring system are the keys to lowering the damage. These are more important than conventional instruments used by the governments such as the wages for managers that achieve certain targets. We also find that the remote areas with a higher percentage of mature natural forests are the ones that will always have the largest damage. These areas are the hardest to monitor, but our results show they must be a critical focus moving forward. The third chapter studies when should a forest owner harvest under uncertain future ecosystem values and timber prices. A forest owner faces various uncertainties caused by climate change and market shocks, due to its long-term nature of production and the joint production of interrelated timber and non-harvesting benefit streams (such as the recreation value, the biodiversity value and the clean air supported by forests). Previous studies assume a known probability distribution for whatever parameter is uncertain, but this type of assumption may lead to a wrong decision model if a forest owner has no such information. We study a more relevant question of how to choose when to harvest with pure uncertainty, in that the forest owner does not know distributional features of parameters and further can be averse to this type of information deficit. This chapter is the first to investigate pure uncertainty and is also the first to analytically solve a harvest decision making problem under pure uncertainty in either non-harvesting benefit streams or market prices. We use macroeconomics methods that are particularly suited to forest capital investment problem. We find that a landowner tends to harvest more when there is pure uncertainty. Because the forest manager is pessimistic and always thinks the worst case will happen when there is uncertainty.

[pt] A conservação de florestas propicia, através de seus serviços ecológicos, uma série de benefícios ao ambiente. As melhorias no ambiente incluem a manutenção da biodiversidade, a conservação dos recursos hídricos e a redução de carbono na atmosfera. Apesar dos benefícios mencionados, as áreas de floresta são submetidas à incêndios florestais, desmatamentos e outras degradações que desconsideram sua importância para o equilíbrio geoecológico e produtivo. Com objetivo de conservar o ambiente e promover o desenvolvimento sustentável, países estão implementando modernos sistemas de administração territorial, que visam realizar a regularização do território, em seus diversos aspectos (fundiário, ambiental, fiscal, entre outros). Como exemplo, cita-se o programa Cadastro Ambiental Rural (CAR) e o Programa de Regularização Ambiental (PRA), sistema de administração de terras que tem o objetivo de implementar as restrições ao uso do solo, nos imóveis rurais brasileiros. Assim, o estudo busca analisar em que medida o PRA, do CAR, está contribuindo para a redução dos desmatamentos, focos de queimada, alertas de degradação e embargos ambientais federais, nos imóveis rurais brasileiros. Para desenvolver o estudo, foi utilizado como recorte espacial o estado do Acre, no Brasil. Para tal, são realizadas análises espaciais e estatísticas visando avaliar a tendência e cenário futuro das variáveis supracitadas. Os resultados obtidos indicam que a adesão ao PRA contribui para a redução dos desmatamentos, focos de queimada e alertas de degradação ambiental. Nos embargos ambientais, foi identificada tendência similar em imóveis com e sem adesão ao PRA e análise preditiva maior, em imóveis que aderiram ao PRA. Também são realizadas entrevistas semiestruturadas abordando os impactos do PRA e do CAR nas condições ambientais e socioeconômicas dos imóveis rurais brasileiros e desafios e oportunidades para a regularização ambiental no Brasil. Por último, o estudo propõe um sistema de monitoramento que analisa as contribuições do PRA do CAR na redução dos desmatamentos, focos de queimada, alertas de degradação ambiental e embargos ambientais, nos imóveis rurais do Acre. O sistema proposto promove a interoperabilidade dos dados espaciais do CAR, com as bases de dados do Instituto Nacional de Pesquisas Espaciais (INPE) e do Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA). / [en] The conservation of forests provides a range of benefits to the environment through its ecological services. Environmental improvements include the maintenance of biodiversity, the conservation of water resources, and the reduction of carbon in the atmosphere. Despite the mentioned benefits, forest areas are subjected to wildfires, deforestation, and other degradations that disregard their importance for the geoecological and productive balance. With the aim of conserving the environment and promoting sustainable development, countries are implementing modern land administration systems, which aim to regularize the territory in its various aspects (tenure, environmental, fiscal, among others). As an example, the Rural Environmental Cadaster (CAR) program and the Environmental Regularization Program (PRA), a land administration system which aims to implement the restrictions on land use in Brazilian rural properties, are cited. Thus, the study seeks to analyze the extent to which the PRA, from the CAR, is contributing to the reduction of deforestation, fire outbreaks, alerts of degradation, and federal environmental embargoes on Brazilian rural properties. To develop the research, the state of Acre, in Brazil, was used as a case study. For this purpose, spatial and statistical analyses are carried out to evaluate the trend and future scenario of the aforementioned variables. The results obtained indicate that adherence to the PRA contributes to the reduction of deforestation, fire outbreaks, and alerts of environmental degradation. In environmental embargoes, a similar trend was observed in properties with and without adherence to the PRA, and a greater predictive analysis in properties that adhered to the PRA. Semi-structured interviews are also conducted to address the impacts of the PRA and CAR on the environmental and socioeconomic conditions of Brazilian rural properties and the challenges and opportunities for environmental regularization in Brazil. Lastly, the study proposes a monitoring system that analyzes the contributions of the PRA and CAR in reducing deforestation, fire outbreaks, environmental degradation alerts, and environmental embargoes on rural properties in Acre. The proposed system promotes the interoperability of the CAR s spatial data with the databases of the Instituto Nacional de Pesquisas Espaciais (INPE) and the Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA).