Airborne and spaceborne remote sensing for assessment of forest structural attributes across tropical mosaic landscapes

High-resolution, accurate, and updated forest structure maps are urgently required for the implementation of REDD+, payment of ecosystem services, and other climate change mitigation strategies in tropical countries. The collection of forest inventory data is usually labor intensive and costly, and remote sites can be difficult to access. Remote sensing data, for example airborne laser scanning (ALS), hyperspectral imagery, and Landsat data, complement field-based forest inventories and provide high-resolution, accurate, and spatially explicit data for mapping forest structural attributes. However, issues such as the effect of topography, pulse density, and the single and combined use of various remote sensing data on forest structural attributes prediction warrant further research. The main objective of this thesis was to assess airborne and spaceborne remote sensing techniques for modeling forest structural attributes across a montane forest landscape in the Taita Hills, Kenya. The sub-objectives focused on a) the effect of the topographic normalization of Landsat images on fractional cover (Fcover) prediction, aboveground biomass (AGB), and forest structural heterogeneity modeling using ALS and other remote sensing data and b) the analysis of the maps of forest structural attributes. In Study I, the effect of topographic normalization on ALS-based Fcover modeling was evaluated using common vegetation indices and spectral-temporal metrics based on a Landsat time series (LTS). The results demonstrate that the fit of the Fcover models did not improve after topographic normalization in the case of ratio-based vegetation indices (Normalized Difference Vegetation Index, NDVI; reduced simple ratio, RSR) or tasseled cap (TC) greenness; however, the fit improved in the case of brightness and wetness, particularly in the period of the lowest sun elevation. However, if TC indices are preferred, then topographic normalization using a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is recommended. In Study II, field-based AGB estimates are modeled by ALS data and a multiple linear regression. The plot-level AGB was modeled with a coefficient of determination (R2) of 0.88 and a root mean square error (RMSE) of 52.9 Mg ha-1. Furthermore, the determinants for AGB spatial distribution are examined using geospatial data and statistical modeling. The AGB patterns are controlled mainly by mean annual precipitation (MAP), the distribution of croplands, and slope, which collectively explained 69.8% of the AGB variation. Study III investigated whether the fusion of ALS with LTS and hyperspectral data, or stratification of the plots to the forest and non-forest classes, improves AGB modeling. According to the results, the prediction model based on ALS data only provides accurate models even without stratification. However, using ALS and HS data together, and employing an additional forest classification for stratification, improves the model accuracy considerably in the studied landscape. Finally, in Study IV, the potential of single and combined ALS and LTS data in modeling forest structural heterogeneity (the Gini coefficient of tree size) was assessed, and the difference between three forest remnants and forest types is evaluated based on predicted maps. If the LTS metrics were included in the models, then ALS data with lower pulse density yield similar accuracy to more expensive, high pulse-density data. Furthermore, the GC map presents forest structural heterogeneity patterns at the landscape scale a

Nighttime Lights as a Proxy for Economic Performance of Regions

Studying and managing regional economic development in the current globalization era demands prompt, reliable, and comparable estimates for a region’s economic performance. Night-time lights (NTL) emitted from residential areas, entertainment places, industrial facilities, etc., and captured by satellites have become an increasingly recognized proxy for on-ground human activities. Compared to traditional indicators supplied by statistical offices, NTLs may have several advantages. First, NTL data are available all over the world, providing researchers and official bodies with the opportunity to obtain estimates even for regions with extremely poor reporting practices. Second, in contrast to non-standardized traditional reporting procedures, the unified NTL data remove the problem of inter-regional comparability. Finally, NTL data are currently globally available on a daily basis, which makes it possible to obtain these estimates promptly. In this book, we provide the reader with the contributions demonstrating the potential and efficiency of using NTL data as a proxy for the performance of regions

Assessing the Variations of Educational Attainment at National and Subnational Levels Using Hierarchical Linear Models

Education is a human right, and equal access to education is not only crucial for an individual’s well-being, but also essential for eradicating poverty, ensuring long-term prosperity for all, transforming the society, and achieving sustainable development. Measuring education development, especially the variations of educational attainment, in a timely and accurate manner can help educators, practitioners, scientists, and policymakers compare and evaluate various education indicators at both subnational and national levels. This research presents an approach that combines multi-source and multidimensional data including population distribution, human settlement, and education data to assess and explore educational attainment trajectories at both national and subnational levels across multiple years. In addition, this study contributes to the power discussions by validating the robustness of models using replication datasets with missing values

Consumption base Measures and Analysis of Urban Poverty the case of Miahcew Southern Tigray

This study explores the extent of poverty and vulnerability to poverty of households of urban residents of Maichew, southern Tigray Regional State. The town is ranked at the bottom in growth momentum among similar zonal towns of the region and the society exists in abject poverty. On the other hand, the area is nominated as a growth corridor of the region. Consumption approach is applied for the poverty analysis. The study thoroughly looks the welfare status at household level through different analytical techniques like Foster, Greer and Thorbecke (FGT), OLS, Probit, Tobit, 3FGLS and Gini coefficient. Using the Cost of Basic Needs approach, food and total poverty lines of the study area are Birr 187 and Birr 251 per month per adult respectively. Poverty profile of the town reveals that 31.70% head count, 8.9% poverty gap and 3.75% poverty gap square. Multinomial regression result indicates that deteriorating in social transition of household head’s is dominant.OLS regression results illustrate that female headed households, educational level of the household head and spouse have positive impact on welfare while family size, square age of household head, divorced and widowed headed households have negative effect to welfare. Except in few variables, most of OLS and probit results of welfare are consistent. Tobit model describes factors affecting poverty gap and poverty severity of the poor households. Accordingly, pensioner headship, family size and age square of household head aggravate the probability of falling in to poverty gap and poverty severity. But being petty trade household head, head education, ownership of property and service indices reduce the probability of falling to poverty severity. Using 3FGLS, the mean probability of vulnerable to poverty is 0.4 which ranges from 0.041 to 0.89. Welfare inequality of the entire population demonstrates that the bottom poor quintile shares only 6.37% of the total mean consumption expenditure while the top quintile takes 49.39%. Furthermore, using Lorenz curve analysis Gini coefficient accounts 0. 49 of total inequality. Factor decomposition of inequality typifies that property index and head social transition of household head take the greater share of 14.6% and 12.4% respectively

Climate change in a mingling-state: sea level rise confronts social susceptibility and justice in the southwestern coastal region of Bangladesh

Shyamnagar Upazila, within the Southwestern part of Bangladesh encompassing the entire Sundarbans, is located in the deltas of the Ganges, Brahmaputra and Megna rivers in the Bay of Bengal and is an area extremely vulnerable to climate change, with serious consequences at the socioeconomic level. This doctoral research involved collecting data on physical, hydrological, geographical aspects, land cover change, rainfall changing patterns, water and soil trace elements, and tidal gauges. These data were complemented with the analysis of social and economic vulnerability dimensions through qualitative methods (interviews, focus groups and observation). Qualitative data collection techniques, including focus group discussions (FGDs), case studies, PRA (Participatory rural appraisal) questionnaires, workshops, in-depth interviews, key informant interviews and participant observation, was undertaken in the Shyamnagar Upazila from 2017 to 2019 (through Skype + messenger + over telephone 2020 to 2022). A survey with a close ended questionnaire was applied at the first stage in nine unions (series-based analysis), at the second stage in 12 unions (risk, hazards, vulnerability and adaptation analysis) and at a third stage in 3 unions (safe drinking water and health analysis) with a total of (320 +387 +1579) household samples (n = 2286). Sea level rise has negative impacts on agriculture, riverbank erosion, and salinity, loss of natural ecosystems, gender vulnerability, poverty, food security, fisheries, safe water resources, migration, and public health factors that affect the development of SWCRB populations and cause climate injustices. This thesis analyzed the implications of coastal risks and hazards to the vulnerability of the local populations, while also addressing their perceptions of justice and adaptation strategies.A subida acelerada do nível médio do mar (SLR) é o impacto mais importante das alterações climáticas nas zonas costeiras do Bangladesh. Esta investigação de doutoramento centrou-se na região costeira do sudoeste do Bangladesh (SWCRB), que enfrenta um perigo iminente com a subida do nível do mar, com consequências diretas nas desigualdades sociais e na justiça climática. Com enfoque nos temas-chave dos ODS, esta compilação de artigos contribui para a implementação da Agenda 2030 das Nações Unidas, nomeadamente para os ODS1 – “Erradicar a pobreza”, ODS2 –“Erradicar a fome”, ODS3 – “Saúde de qualidade, ODS5 – “Igualdade de género”, ODS6 – “Água potável e saneamento”, ODS10 – “Redução das desigualdades”, ODS13 – “Ação climática” e ODS16 – “Paz, justiça e instituições eficazes”. Para analisar a vulnerabilidade induzida pela subida do nível do mar, esta investigação considerou a atual e futura modelização da subida do nível do mar. A metodologia utilizada é interdisciplinar e foi baseada numa abordagem de métodos mistos. Esta investigação inclui quatro artigos publicados em revistas revistas revistas por pares, integrados no corpo da tese como capítulos de resultados (capítulos 4 a 7), tendo o autor submetido ainda durante o período do doutoramento dois outros artigos e dois capítulos de livros que foram aceites e que, por conseguinte, estão incluídos como material suplementar a esta tese (anexos). O primeiro artigo (capítulo 4) centrou-se na modelação da subida do nível médio do mar (NMM). As projeções locais do nível do mar indicam que o este pode aumentar em meio metro ou até mais de um metro até ao final do século XXI. A região da Baía de Bengala revela taxas superiores às médias globais, devido à fusão dos glaciares dos Himalaias. Contudo, devido à natureza não linear da subida do NMM, é de esperar que as projeções sejam ultrapassadas, o que representa uma ameaça para a vida de milhões de pessoas no Bangladesh. Além disso, as zonas costeiras do sudoeste do Bangladesh são altamente vulneráveis à intrusão de água salgada, sobretudo devido aos ciclones e à subida do NMM, especialmente a região de Shyamnagar Upazila, e espera-se que isto se agrave durante o próximo século devido às alterações climáticas. Por conseguinte, este estudo analisa a geoquímica da água salgada e compostos relacionados, a resposta à intrusão salina nos sistemas fluviais e as possíveis áreas afetadas pelos eventos climáticos extremos nas condições actuais e em 2100. Esta análise mostrou que os níveis de salinidade do solo e da água são já altamente inadequados para os padrões de fertilidade do solo e a qualidade da água na região. Além disso, analisaram-se os principais impactos das alterações climáticas na saúde pública, começando pelo global e passando pelo local, estudando as comunidades costeiras na área de influência das Sundarbans. Discutimos quais são os principais desafios enfrentados pelos diferentes atores a nível local, incluindo o agravamento de certos riscos para a saúde da comunidade com os impactos das alterações climáticas. Os países em desenvolvimento estão a enfrentar grandes desafios em termos de mitigação e adaptação, no entanto são os que têm contribuído menos para as causas das alterações climáticas. Verificou-se que a maioria dos inquiridos vive abaixo do limiar da pobreza, com níveis de desigualdade relativamente baixos baseados num coeficiente de Gini de 28,5 (capítulo 5). Algumas das questões mais graves que afetam a subsistência das populações locais são os ciclones e as inundações, bem como o aumento da salinidade do solo e da água doce. Os mais pobres estão muito mais expostos aos eventos extremos, têm reduzidos recursos económicos para prevenir e recuperar dos seus impactos, e as suas fontes diretas de rendimento, na sua maioria baseadas em recursos naturais, são também duramente afetadas. Os resultados mostraram que o impacto das alterações climáticas difere entre homens e mulheres nas comunidades examinadas (capítulo 6). Entre os principais fatores que influenciam a vulnerabilidade da comunidade estão os níveis de escolaridade, as normas culturais locais. Ainda assim, estas mulheres têm potencial para participar em planos de conservação ambiental, para liderar movimentos sociais e ambientais, e para promover estratégias de gestão sustentável dos recursos naturais, uma vez que são consideradas como as guardiãs do conhecimento local. Finalmente, esta investigação propõe que, a fim de reduzir a vulnerabilidade feminina, as mulheres devem ser capacitadas e integradas em medidas de mitigação e planos de adaptação, tanto como partes interessadas como como agentes de mudança. Ao analisar o impacto socioeconómico das alterações climáticas, esta investigação contribui para o debate sobre a justiça climática, que é uma problemática social, política e económica (capítulo 7). Os países industrializados que mais contribuíram para o problema através da emissão excessiva de gases com efeito de estufa (GEE) são os menos propensos a sofrer as consequências. Tanto a abordagem baseada nos direitos humanos como a abordagem baseada nas capacidades são aqui discutidas, mas concluímos que esta última é a mais adequada para compreender a realidade no Bangladesh. Esta área está a sofrer enormes mudanças devido aos efeitos devastadores das alterações climáticas e da subida do NMM. Com base em extensivos estudos locais, a tese conclui que as populações locais gostariam de estar mais envolvidas na conceção, planeamento e implementação de estratégias para reforçar a resiliência das suas comunidades. A população local destaca como as suas principais necessidades ter acesso a água doce a preços acessíveis, a segurança alimentar e as infraestruturas sustentáveis, tais como estradas, casas, escolas e unidades de saúde. Nestas áreas, muitas vezes as formas de assistência centram-se na ajuda de emergência após grandes catástrofes; contudo, isto não é suficiente. A intensidade da subida do nível do mar torna cada vez mais difícil a reconstrução após a ocorrência de cada catástrofe. Foram ainda efetuadas análises para avaliar o estado da água, da vegetação e do solo na região. O estudo analisa os dados pluviométricos recolhidos pelo BWDB entre 1968 e 2018, mostrando as mudanças no padrão de precipitação ao longo dos anos e a diminuição da produção agrícola no SWCRB e reforçando o diagnóstico de declínio das terras agrícolas durante o período 1989-2019. Como forma de diversificar as suas fontes de rendimento, alguns agricultores converteram as suas terras para a criação de camarão, o que aumenta ainda mais a salinidade do solo. Além disso, a Barragem Farakka afecta negativamente a população da SWCRB ao reduzir o fluxo do rio Ganges para o Bangladesh. As medidas adaptativas utilizadas pelos agricultores incluem a construção de aterros, a recolha das águas da chuva, a drenagem adequada para reduzir o alagamento, o controlo da expansão das explorações de camarão e a introdução de culturas de de alto rendimento mas que são mais tolerantes à salinidade, bem como o emprego de novas técnicas de irrigação. Além disso, as técnicas agrícolas Sorjan e o cultivo flutuante, a pecuária e a agricultura apoiadas pela comunidade, são vistas pelos agricultores das zonas costeiras como uma forma de mitigar os impactos climáticos. A análise de vulnerabilidade revela que a população local já implementou com sucesso oito estratégias de adaptação baseadas na comunidade para reduzir a vulnerabilidade causada pela subida do mar e pelas inundações. Tem sido testemunhado que as práticas de adaptação implementadas com a participação direta das comunidades tem contribuído para a redução das vulnerabilidades e o reforço da resiliência das populações locais. Após as catástrofes, a reabilitação dos aterros costeiros com o envolvimento da comunidade local é uma resposta favorecida nos processos de adaptação estrutural, bem como a reflorestação costeira e os abrigos polivalentes construídos pelo governo para os furacões. Concluiu-se também que o governo deveria ter em consideração as propostas da comunidade local para ajudar no processo de adaptação. Já há um vasto número de vítimas das alterações climáticas na SWCRB. Ao mesmo tempo, estas regiões tornaram-se um campo de ensaio para estratégias de adaptação que são particularmente adequadas para as comunidades de pequena escala. Considerando as contribuições empíricas de todos os artigos incluídos nesta tese, pode argumentar-se que as estratégias de adaptação e resiliência, até à data, não têm considerado plenamente indicadores sociais tais como pobreza, desigualdade de género, empoderamento ou desigualdades de rendimentos. A subida do nível do mar, agravada pelas alterações climáticas, tem impactos negativos na agricultura, na erosão das margens dos rios e no aumento da salinidade, levando à perda de ecossistemas naturais, a uma menor segurança alimentar das populações e a maiores fluxos de migração, contribuindo ainda para agravar problemas de saúde pública que afetam o desenvolvimento das populações da SWCRB e geram crescentes injustiças

Remote sensing based assessment of land cover and soil moisture in the Kilombero floodplain in Tanzania

Wetlands provide important ecological, biological, and social-economic services that are critical for human existence. The increasing demand for food, arable land shortage and changing climate conditions in East Africa have created a paradigm shift from upland cultivation to wetland use due to their year-round soil water availability. However, there is need to control and manage the activities within the wetlands to ensure sustainable use while negating any negative effects caused by these activities. This is implemented through the decisions made by the land managers within the wetlands. Providing the users of the wetlands with scientific knowledge acts as a support tool for policy-making geared towards the sustainable use of the wetlands. The overall research contains two main components: First, the need for timely land cover maps at a reasonable scale, and secondly, the assessment of soil moisture as a major contributor to agricultural production. The objectives of the study were to generate land cover maps from multi-sensor optical datasets and to assess the performance of single-polarized Sentinel-1 Gray Level Co-occurrence Matrix (GLCM) texture and Principal Component Analysis (PCA) features by applying multiple classification algorithms in a floodplain in the Kilombero catchment. Furthermore, soil moisture spatial-temporal patterns over three hydrological zones was assessed, estimation of soil moisture from radar data and generation of soil moisture products from global products was investigated. The correlation of the merged products to Normalized Difference Vegetation Index (NDVI) measures was also investigated. RapidEye, Sentinel-2 and Landsat images were used in determining the areal extents of four major land cover classes namely vegetated, bare, water and built up. The acquisition period of the images ranges from August 2013 to June 2015 for the RapidEye images, December 2015 to August 2016 for the Sentinel-2 images and 2013 to 2016 Landsat-8 images were included in the land cover time series dynamic study. However, the major challenge arising was cloud coverage and hence Sentinel-1 images were tested in the application of Synthetic Aperture Radar (SAR) in wetland mapping. Variograms were used in spatial-temporal assessment of soil moisture data collected from three hydrological zones, riparian, middle and fringe. A roughness parameter was derived from a semi-empirical model. Soil moisture was retrieved from TerraSAR-X and RadarSAT-2 with the retrieved roughness parameter as an input in a linear regression equation. Triple collocation was applied in error assessment of the global soil moisture products prior to development of a merged product. Cross-correlation was applied in relating NDVI to soil moisture. Optical data (RapidEye, Landsat-8, and Sentinel-2) generated land cover maps used in assessing the land cover dynamics over time. The land cover ratios were related to depth to groundwater. As the depth to groundwater reduced in June the bare land coverage was 45-57% while that of vegetation was 34-47%. In December when the depth to groundwater was highest, bare land coverage was 62-69% while that of the vegetated area was 27-25%. This indicates that depth of groundwater and vegetation coverage responds to seasonality. During the dry season, 68-81% of the total vegetation class is within the riparian zone. In the classification of the SAR images, the overall accuracies for the single polarized VV images ranged from 54-76%, 60-81% and 61-80% for Random Forest (RF), Neural Network (NN) and Support Vector Machine (SVM) respectively. GLCM features had overall accuracies of 64-86%, 65-88% and 65-86% for RF, NN, and SVM respectively. PCA derived images had similar overall accuracies of 68-92% for NN, RF, and SVM respectively. The PCA images had the highest overall accuracy for the entire time series indicating that reduction in the number of texture features to layers containing the maximum variance improves the accuracy. The standard deviation of soil moisture was noted to increase with increasing soil moisture. Soil texture plays a key role in soil moisture retention. The riparian fields had a high water content explained by the high clay and organic matter content. A roughness parameter was derived and utilized in the retrieval of soil moisture from SAR resulting to R2 of 0.88- 0.92 between observed and simulated soil moisture values from co-polarized RadarSAT-2 HH and TerraSAR-X HH and VV. Merged soil moisture product from FEWSNET Land Data Assimilation System_NOAH (FLDAS_NOAH), ECMWF Re-Analysis Interim (ERA-Interim) and Soil Moisture and Ocean Salinity (SMOS) and FLDAS_Variable Infiltration Capacity (VIC), ERA-Interim and SMOS had similar patterns attributed to FLDAS_NOAH and FLDAS_VIC forced by the same precipitation product (RFE). Cross-correlation of Moderate-resolution Imaging Spectrometer (MODIS) NDVI and the merged soil moisture products revealed a 2-month lag of NDVI. Hence, the relationship is useful in determining the Start of Season from soil moisture products. In conclusion, the successful land cover mapping of the study area demonstrated the use of satellite imagery for wetland characterization. The vast coverage and frequent acquisitions of optical and microwave remotely sensed data additionally make the approaches transferable to other locations and allow for mapping at larger scales. Soil moisture assessment from point data revealed varied soil moisture patterns whereas global remotely sensed and modeled products rather provide complementary information about growing conditions, and hence a situational assessment tool of potential of physical availability dimension of food security. This study forms a baseline upon which additional monitoring and assessment of the Kilombero wetland ecosystem can be performed with the current results marked as a reference. Moreover, the study serves as a demonstration case of remote sensing based approaches for land cover and soil moisture mapping, whose results are useful to stakeholders to aid in the implementation of adapted production techniques for yield optimization while minimizing the unsustainable use of the natural resources.Feuchtgebiete erbringen wichtige ökologische, biologische und sozial-ökonomische Dienstleistungen, welche entscheidend für das menschliche Dasein sind. Der steigende Bedarf an Nahrung, der Mangel an landwirtschaftlichen Nutzflächen und die Veränderung der klimatischen Bedingungen in Ostafrika haben zu einem Paradigmenwechsel vom Anbau im Hochland hin zur Nutzung von Feuchtgebieten geführt. Allerdings sind Kontrolle und Management der Aktivitäten in Feuchtgebieten notwendig, um die nachhaltige Nutzung zu sichern und negative Effekte dieser Aktivitäten zu vermeiden. Die Implementierung erfolgt durch die Landverwalter in den Feuchtgebieten. Den Nutzern von Feuchtgebieten wissenschaftliche Erkenntnisse bereitzustellen dient als Hilfsmittel zur politischen Entscheidungsfindung für die nachhaltige Feuchtgebietsnutzung. Die Forschung im Rahmen der Dissertation beinhaltet zwei Hauptkomponenten: erstens den Bedarf an aktuellen Landbedeckungskarten auf einer angemessenen Skalenebene und zweitens die Erfassung der Bodenfeuchte als wichtiger Einflussfaktor auf die landwirtschaftliche Produktion. Das Ziel der Untersuchung war, Landbedeckungskarten auf Grundlage von multisensorischen optischen Daten zu erstellen und die Eignung der Textur der einfach polarisierten Sentinel-1 Grauwertmatrix (GLCM) sowie der einer Hauptkomponentenanalyse (PCA) bei Anwendung unterschiedlicher Klassifikationsalgorithmen zu beurteilen. Des Weiteren wurden raum-zeitliche Bodenfeuchtemuster über drei hydrologische Zonen hinweg modelliert, die Bodenfeuchte aus Radardaten abgeleitet sowie die Erstellung von Bodenfeuchteprodukten auf Basis von globalen Produkten untersucht. Die Korrelation der Bodenfeuchteprodukte mit dem Normalisierten Differenzierten Vegetationsindex (NDVI) wurde ebenfalls analysiert. RapidEye, Sentinel-2 und Landsat Bilder wurden genutzt um die räumliche Ausdehnung der vier Hauptklassen (Vegetation, freiliegender Boden, Wasser und Bebauung) der Landbedeckung zu ermitteln. Für die Zeitreihenanalyse der der Landbedeckungsdynamik wurden RapidEye-Daten von August 2013 bis Juni 2015, Sentinel-2-Bilder von Dezember 2015 bis August 2016 und Landsat-8-Bilder von 2013 bis 2016 verwendet. Die größte Herausforderung war jedoch die Wolkenbedeckung, weshalb die Anwendung von Synthetic Aperture Radar (SAR) für die Feuchtgebietskartierung getestet wurde. Die gemessene Bodenfeuchte wurde mittels Variogrammen für die drei hydrologischen Zonen (Uferzone, Mitte und Randgebiete) raum-zeitlich interpoliert. Ein Rauhigkeitsparameter wurde aus einem semi-empirischen Modell hergeleitet. Die Bodenfeuchte wurde aus TerraSAR-X und RadarSAT-2- Bildern unter Verwendung des Rauhigkeitsparameters als Eingangsgröße in einer linearen Regression abgeleitet. Vor der Zusammenführung der Produkte wurde das globale Bodenfeuchteprodukt mithilfe von dreifacher Kollokation auf Fehler überprüft. Die Kreuzkorrelation zwischen NDVI und Bodenfeuchte wurde berechnet. Optische Daten (RapidEye, Landsat-8 und Sentinel-2) wurden genutzt, um die zeitliche Dynamik der Landbedeckung zu bestimmen. Die Landbedeckungsverhältnisse wurde mit der Höhe des Grundwasserspiegels korreliert. Ein hoher Grundwasserstand im Juni resultierte in 45-57% unbedecktem Boden, während der Anteil der Vegetation 34-47% betrug. Im Dezember, als der Grundwasserspiegel seinen Tiefststand hatte, erhöhte sich der Anteil des freiliegenden Bodens auf 62-69% und der Anteil der Vegetation verringerte sich auf 27-25%. Das zeigt, dass Grundwasserspiegel und Vegetation saisonalen Schwankungen unterworfen sind. Während der Trockenzeit liegen 68-81% der gesamten als Vegetation klassifizierten Fläche innerhalb der Uferzone. In der Klassifikation der SAR-Bilder liegt die Gesamtgenauigkeit der einfach polarisierten VV-Bilder im Rahmen von 54-76%, 60-81% und 61-80%, entsprechend für Random Forest (RF), Neuronale Netze (NN) und Support Vector Machine (SVM). Die GLCM ergab eine Gesamtgenauigkeit von 64-86%, 65-88% und 65-86% für RF, NN und SVM. Die über eine PCA abgeleiteten Bilder erreichten eine ähnliche Genauigkeit von 68-92% für NN, RF und SVM. Die PCA-Bilder weisen die höchste Gesamtgenauigkeit der gesamten Zeitreihe auf, was darauf hinweist, dass eine Reduktion von Textureigenschaften auf Layer der maximalen Varianz enthalten, die Genauigkeit erhöht. Die Standardabweichung der Bodenfeuchte stieg mit zunehmender Bodenfeuchte. Die Bodentextur spielt dabei eine Schlüsselrolle für das Wasserhaltevermögen des Bodens. Die Uferzone wies einen hohen Wassergehalt auf, was durch den hohen Anteil von Ton und Humus zu erklären ist. Die beobachteten und simulierten Bodenfeuchtewerte von co-polarisierten RadarSAT-2 HH, TerraSAR-X HH und VV Daten korrelieren mit einem R2 von 0.88 - 0.92. Die zusammengesetzten globalen Bodenfeuchteprodukte von FLDAS_NOAH, ERA-Interim sowie SMOS und FLDAS_VIC, ERA-Interim und SMOS zeigen ähnliche Muster wie FLDAS_NOAH und FLDAS_VIC, was über die Verwendung desselben Niederschlagsproduktes (RFE) zu erklären ist. Die Kreuzkorrelation von MODIS NDVI und den zusammengeführten Bodenfeuchteprodukten ergab eine zeitliche Verzögerung des NDVI von zwei Monaten. Dieser Zusammenhang kann daher bei der Bestimmung des Saisonbeginns aus Bodenfeuchtigkeitsprodukten nützlich sein. Zusammengefasst hat die Studie gezeigt, wie Satellitenbilder zur Charakterisierung von Wetlands genutzt werden können. Die große Abdeckung und häufige Aufnahme der optischen und Mikrowellen-Fernerkundungsdaten ermöglichen darüber hinaus die Übertragung der Ansätze auf weitere Gebiete und Kartierung auf größeren Skalen. Die Punktmessungen zeigen kleinräumige Muster der Bodenfeuchte, während globale Fernerkundungsprodukte und Modelle Informationen über die Wachstumsbedingungen liefern und somit ein Bewertungsinstrument der Ernährungssicherheit darstellen können. Weiterhin bildet die Studie eine Basis, auf der ein weitergehendes Monitoring und eine Bewertung des Feuchtgebietsökosystems durchgeführt werden kann. Sie ist ein Beispiel für fernerkundungsbasierte Ansätze zur Landbedeckungs- und Bodenfeuchtekartierung; ihre Ergebnisse sind nützlich, um Akteuren bei der Implementierung von Produktionstechniken zu unterstützen, welche die Erträge maximieren und gleichzeitig die nicht nachhaltige Nutzung der natürlichen Ressourcen minimieren

Essays on the history of economic development and inequality in the US South

This dissertation consists of three essays investigating the historical roots of economic development and inequality in the US South. The first essay examines the impact of slavery on long-run development. Using county-level data from the US South, I show that slavery has impeded long-run development through the human capital channel. The mechanism involves labor market institutions and their impact on demand for human capital. I find that the history of slavery hindered integration of black workers into the labor market. Moreover, border-county analyses show that selective application of laws and regulations was a primary tool for impeding labor market integration. Through estimating the relative return to education for each county, I further argue that blacks in a region with a greater legacy of slavery had fewer incentives to invest in human capital. The second essay studies the long run effects of cotton agriculture focusing on a novel aspect of structural change. I show that cotton specialization in the late 19th century had long-run negative impact on local development, and the negative relationship became only evident in the second half of the 20th century. I argue that the change was caused by the mechanization of cotton production. After cotton mechanization, cotton labor with low human capital was relocated to local manufacturing. In response to the inflow of cotton labor, there was a decline in labor productivity in manufacturing which persisted through directed technical change. Using census data, I show that initial cotton specialization reduces demand for skills in manufacturing even to this day. The third essay addresses the legacy of cotton agriculture on economic inequality. Using the Gini index of household income, I show that initial cotton specialization increased long-run economic inequality at the county level. Moreover, evidence from the census data indicates that cotton specialization increased wage inequality exclusively in the local service sector, without any effects on the other non-agricultural sectors. As an explanation, I argue that wage inequality in the service sector increased due to expansion of employment in low-wage occupations followed by a decrease in their wage level