This study examined the severity of wind damage created by Hurricane Katrina in southeast Mississippi to determine how the disturbance was influenced by fragmentation based on different forest ownership groups (Non-corporate private forest, corporate private forest and public forest). MODIS-NDVI percent change products were coupled with ownership, rainfall, and Landsat based thematic maps depicting forest age and forest types using GIS techniques to examine potential contributing factors to possible damage for the study area. Multiple linear and binary logistic regression methods were used to explain the relationship between severity of damage and forest age, forest type, ownership, and rainfall. Results indicate that the NDVI percent change had a negative relationship with forest age diversity and a positive relationship with forest type diversity and rainfall. There was no clear and direct consistent relationship between NDVI percent change and forest ownership.

The discharge of sediment-laden rivers into the Mississippi Sound increases the turbidity of coastal waters. The concentration of suspended particulates is an important parameter in the analysis of coastal water quality factors. The spatiotemporal resolution associated with satellite sensors makes remote sensing an ideal tool to monitor suspended particulate concentrations. Accordingly, the presented research evaluated the validity of published algorithms that relate remote sensing reflectance (Rrs) with suspended particulate matter for the Mississippi Sound. Additionally, regression analysis was used to correlate in situ SPM concentrations with coincident observations of visible and near-infrared band reflectance collected by the MODIS Aqua sensor in order to develop a predictive model for SPM. The most robust algorithm yielded an RMSE of 15.53% (n = 86) in the determination of SPM concentrations. The application of this algorithm allows for the rapid assessment of water quality issues related to elevated SPM concentrations in the Mississippi Sound.

Wildfires burn millions of acres of land each year leading to the destruction of homes and wildland ecosystems while costing governments billions in funding. As climate change intensifies drought volatility across the Western United States, wildfires are likely to become increasingly severe. Wildfire risk assessment and hazard maps are currently employed by fire services, but can often be outdated. This paper introduces an image-based dataset using climate and wildfire data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). The dataset consists of 32 climate and topographical layers captured across 0.1 deg by 0.1 deg tiled regions in California and Nevada between 2015 and 2020, associated with whether the region later saw a wildfire incident. We trained a convolutional neural network (CNN) with the generated dataset to predict whether a region will see a wildfire incident given the climate data of that region. Convolutional neural networks are able to find spatial patterns in their multi-dimensional inputs, providing an additional layer of inference when compared to logistic regression (LR) or artificial neural network (ANN) models. To further understand feature importance, we performed an ablation study, concluding that vegetation products, fire history, water content, and evapotranspiration products resulted in increases in model performance, while land information products did not. While the novel convolutional neural network model did not show a large improvement over previous models, it retained the highest holistic measures such as area under the curve and average precision, indicating it is still a strong competitor to existing models. This introduction of the convolutional neural network approach expands the wealth of knowledge for the prediction of wildfire incidents and proves the usefulness of the novel, image-based dataset.

The Lower Mississippi Alluvial Valley (LMAV) was once the largest floodplain in the United States. Flooding regimes in the LMAV have strong impacts on the soil biogeochemical processes, nutrient cycling, forest species distribution, agricultural production, and wildlife habitat. This study characterized the LMAV flooding regimes using the 8-day-composite Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product from 2001 - 2018. The results showed significant spatial variations in the annual flooding duration in the LMAV, and the flooding area showed remarkable seasonal variations in the northern and central LMAV with the peak flooding area in winter and early spring. Digital Elevation Model (DEM) and slope were identified as the two major factors in determining the spatial pattern of flooding regimes. The LMAV flooding regimes dataset provides a scientific basis for the governments to design forest, agriculture, and wildlife management policies to enhance ecosystem services. Landowners also can use this information to make decisions for cropland retirement and tree plantation.

In this study we applied the asymmetric Gaussian, double-logistic, and Savitzky-Golay filters to MODIS time-series NDVI data to compare the capability of smoothing algorithms in noise reduction for improving land cover classification in the Great Lakes Basin, and providing groundwork to support cyanobacteria and cyanotoxin monitoring efforts. We used inter-class separability and intra-class variability, at varying levels of pixel homogeneity, to evaluate the effectiveness of three smoothing algorithms. Based on these initial tests, the algorithm which returned the best results was used to analyze how image stratification by ecoregion can affect filter performance. MODIS 16-day 250m NDVI imagery of the Great Lakes Basin from 2001-2013 were used in conjunction with National Land Cover Database (NLCD) 2006 and 2011 data, and Cropland Data Layers (CDL) from 2008 to 2013 to conduct these evaluations. Inter-class separability was measured by Jeffries-Matusita (JM) distances between selected land cover classes (both general classes and specific crops), and intra-class variability was measured by calculating simple Euclidean distance for samples within a land cover class. Within the study area, it was found that the application of a smoothing algorithm can significantly reduce image noise, improving both inter-class separability and intra-class variability when compared to the raw data. Of the three filters examined, the asymmetric Gaussian filter consistently returned the highest values of interclass separability, while all three filters performed very similarly for within-class variability. The ecoregion analysis based on the asymmetric Gaussian dataset indicated that the scale of study area can heavily impact within-class separability. The criteria we established have potential for furthering our understanding of the strengths and weaknesses of different smoothing algorithms, thereby improving pre-processing decisions for land cover classification using time-series data. / Master of Science

Monitoring and understanding plant phenology is becoming an increasingly important way to identify and model global changes in vegetation life cycle events. Although numerous studies have used synoptically sensed data to study phenological patterns at the continental and global scale, relatively few have focused on characterizing the land surface phenology of specific ecosystems. Mountain environments provide excellent examples of how variations in topography, elevation, solar radiation, temperature, and spatial location affect vegetation phenology. High elevation biomes cover twenty percent of the Earth's land surface and provide essential resources to both the human and non-human population. These areas experience limited resource availability for plant growth, development, and reproduction, and are one of the first ecosystems to reflect the harmful impact of climate change. Despite this, the phenology of mountain ecosystems has historically been understudied due to the rough and variable terrain and inaccessibility of the area. Here, we use two MODIS/Terra satellite 16-day products, Vegetation Index and Nadir BRDF Adjusted Reflectance, to assess start of season (SOS) for the 2007 calendar year. Independent data for elevation, slope, aspect, solar radiation, and temperature as well as longitude and latitude were then related to the SOS output. Based on the results of these analyses, we found that SOS can be predicted with a significant R² (0.55-0.64) for each individual zone as well as the entire western mountain range. While both elevation and latitude have significant influences on the timing of SOS for all six study areas. When examined at the regional scale and accounting for aspect, SOS follows closely with Hopkins' findings in regard to both elevation and latitude. / Master of Science

O presente trabalho de pesquisa tem como principal objetivo produzir o Mapa de Uso e Cobertura da Terra na escala de 1: 2.500.000 para o estado de São Paulo, além de disponibilizar um conjunto de diversos mapas temáticos do Estado de São Paulo em formato digital e no contexto de um Sistema de Informação Geográfica. O referido mapa de Uso pretende caracterizar as diversas formas de uso e cobertura da terra observadas no referido território. Nesta abordagem metodológica em escala regional destaca-se o emprego de imagens de satélite de alta resolução temporal e técnicas avançadas de processamento digital e o Geoprocessamento, como instrumental de integração e análise dos conhecimentos das ciências Geografia, Agronomia e Cartografia, as quais possibilitaram um levantamento do espaço geográfico relacionando-o com as interferências e ações da sociedade na natureza. A área de estudo está localizada na região sudeste do Brasil e tem uma extensão de 248.209,426 km2 distribuídos em 645 municípios. Neste trabalho foram utilizadas as técnicas de segmentação e modelo linear de mistura espectral aplicados nas imagens do sensor MODIS, as quais facilitaram a delimitação das principais modalidades de uso e cobertura da terra. A classificação de uso e cobertura foi elaborada com base em mapeamentos clássicos de KELLER (1969), ANDERSON (1971) e et al.,(1979), JENSEN (1983) e TROPPMAIR (1983). Os produtos índices de vegetação (EVI e NDVI) contribuíram na aferição das classes temáticas de vegetação, os dados do Projeto CANASAT (INPE) nas classes de agricultura e as imagens do satélite CBERS e o do Google EARTH nas demais. Foram confeccionados diversos mapas temáticos em formato digital para a caracterização da área de estudo como, Geologia, Divisão geomorfológica, Bacias hidrográficas, Clima, Cobertura Vegetal Primitiva, alguns advindos do Projeto Atlas do estado de São Paulo: uma reflexão metodológica (MARTINELLI, 2009). Os mapas de relevo e declividade foram obtidos através dos dados do Shuttle Radar Topographic Mission (SRTM). Os resultados acerca das formas de uso e cobertura da terra destacam a supremacia agrícola pelo cultivo de cana-de-açúcar a qual vem pressionando e substituindo outros cultivos, o reflorestamento e as áreas de preservação e conservação ambiental. Esta ocupação desenfreada já vinha sendo apontada em pesquisas realizadas por RUDORFF et al., (2004) desde 2003 alavancada pela demanda na produção do etanol como biocombustível. Desta forma, esperamos que os resultados apresentados neste trabalho contribuam a futuros estudos quanto à ameaça aos fragmentos de cerrado e remanescentes de Mata Atlântica ainda presentes no estado de São Paulo, além das possibilidades de disponibilizar em formato WebGIS a cartografia temática elaborada para seu amplo uso e divulgação à comunidade nacional e internacional. / The main objective of this research work is to produce the Land Use and Cover Map of São Paulo State in scale 1: 2.500.000, and also to provide a diverse set of thematic maps of São Paulo State in digital format and in the context of a Geographic Information System. The Land Use and Cover Map have the purpose to characterize the diverse land use and cover forms observed in that territory. This mapping regional scale methodological approach is based on the use of high temporal resolution satellite images and advanced digital image processing and GIS technologies as an analysis and integration tool of Geography, Cartography and Agronomy science knowledge, creating a possibility of survey of geographical space linking it with the interference and actions of society in nature. The study area is located in southeastern Brazil and has an area of 248.209.426 km2 distributed in 645 municipalities. In this work the segmentation technique and linear mixture model were applied in the sensor MODIS images, to facilitate the delimitation of the main land use and land cover classes. The land use and land cover classification was developed based on KELLER (1969), ANDERSON (1971), et al. (1979), JENSEN (1983) and TROPPMAIR (1983) classical mappings. Vegetation indices (NDVI and EVI) products contributed in gauging the thematic classes of vegetation, the CANASAT project data (INPE) in the agricultural classes and CBERS satellite images and Google Earth as well in the others. Several thematic maps in digital format were made for the study area characterization, Geology, Geomorphology, Watersheds, Climate, Primitive Vegetation Cover, some comings from the Atlas of São Paulo State project: a methodological reflection (MARTINELLI, 2009). The topography and slope maps were obtained from Shuttle Radar Topographic Mission (SRTM) data. The land use and land cover mapping results highlights the agricultural supremacy of cane sugar crop, which has been pressing and substituting other crops, the reforestation and environmental conservation areas as well. This wild occupation had already been appointed since 2003 by RUDORFF et al. (2004) pushed by ethanol production demand as a bio-fuel. Therefore, we hope that the results presented in this work contributes to future studies regarding the threat to fragments of Cerrado and Atlantic Forest remnants that are still present in São Paulo State, besides the possibilities to put on line in a WebGIS format the elaborated thematic maps for its widespread use and dissemination by the national and international community.

Made available in DSpace on 2017-05-12T14:47:02Z (GMT). No. of bitstreams: 1 _diego_della_justina.pdf: 3123259 bytes, checksum: 7482af0ac4e10eb7e14854f470ff3593 (MD5) Previous issue date: 2014-01-30 / Soybeans are an important agricultural crop, with expressive economical participation; thus, it is necessary the adoption of practices that enable crop forecasting, contributing for a better market position of this commodity. Remote sensing methodologies for monitoring production through are highly effective, due to their low cost, large-scale coverage and smaller time consumption. One of these techniques used is the NDVI Normalized Difference Vegetation Index, which has been employed on a large scale through use of the MODIS sensor. However, orbital sensors are subject to the influence of atmospheric factors and the culture dynamics, which may have different spectral behaviors among cultivars of the same species. In this context, non-orbital spectroscopy would be a viable solution for studying the existence of variations in the spectral behavior of any crop without further interference from exogenous factors. Thus, the aim of this work was to evaluate the temporal profiles of NDVI obtained with orbital MODIS sensor and non-orbital sensor GreenSeeker during the soybean development cycle. The study was conducted in two plots (T1 and T2) located on the Central Cooperative of Agricultural Research - COODETEC, in Cascavel State of Paraná. Samples of NDVI of thirteen pixels, three of them called pure pixels and ten non pure pixels, were taken at irregular intervals, but representing crop cycle. The data obtained by the non-orbital sensor were analyzed by exploratory analysis. Means of both orbital and non-orbital sensors were compared by test-t at 5% significance level. The means comparison test demonstrated the data obtained through the two sensors to be statistically different. However, both showed good dynamic range and sensibility to monitor and access spatial and temporal variations in the vegetation. / Uma vez que a soja é uma importante cultura agrícola, com expressiva participação econômica, se faz necessário a adoção de práticas que viabilizem a previsão de safra, contribuindo para melhor posicionamento da commodity no mercado. Metodologias de acompanhamento de produção por sensoriamento remoto orbital são alternativas eficazes devido ao baixo custo, grande escala de abrangência e rapidez. Uma das técnicas de acompanhamento agrícola empregada são os índices de vegetação, dentre eles o NDVI Índice de Vegetação por Diferença Normalizada, que vem sendo empregado em larga escala por meio do sensor MODIS. Porém, sensores orbitais estão sujeitos à influência dos fatores atmosféricos e da dinâmica das culturas, que podem apresentar diferentes comportamentos espectrais entre cultivares de uma mesma espécie. Nesse contexto, a espectroscopia terrestre, (não-orbital), pode ser uma solução viável para o estudo da existência de variações no comportamento espectral de qualquer cultura agrícola, sem maiores interferências de fatores exógenos. Sendo assim, o objetivo deste trabalho foi avaliar os perfis temporais de NDVI obtidos com o sensor orbital MODIS e o sensor não-orbital GreenSeeker durante o ciclo de desenvolvimento da soja. O estudo foi conduzido em dois talhões (T1 e T2) localizados nas dependências da Cooperativa Central de Pesquisa Agrícola COODETEC, no município de Cascavel PR. Amostras de NDVI de treze pixels, sendo três puros e dez não puros, foram tomadas em intervalos não regulares, porém, representativos ao desenvolvimento da cultura. Os dados obtidos por meio do sensor não-orbital foram submetidos a análise exploratória. As médias de ambos os sensores orbital e não-orbital foram comparadas pelo teste-t a 5% de significância. O teste de comparação de médias demonstrou que os dados obtidos entre os dois sensores são estatisticamente diferentes. No entanto, ambos demonstraram um bom alcance dinâmico e sensibilidade para monitorar e acessar variações espaciais e temporais da vegetação.

Diese Dissertation ist innerhalb eines Teilprojekts des Schwerpunktprogramms SPP1233 ”Megacities Megachallenge - Informal Dynamics of Global Change“ entstanden. Thema der vorliegenden Arbeit ist die Untersuchung der heterogenen Reflexion der Sonnenstrahlung an urbanen Bodenoberflächen, sowie deren Einfluss auf die Bestimmung der optischen Dicke von Aerosolpartikeln aus Satellitendaten. Zu diesem Zweck wurden flugzeuggetragene Messungen der spektral aufgelösten, reflektierten solaren Strahlung durchgeführt. In dieser Arbeit werden Messungen mit dem SMART-Albedometer (Spectral Modular Airborne Radiation measurement sysTem) präsentiert, die im Rahmen zweier Messkampagnen in Leipzig im September 2007 und in Zhongshan, China im Dezember 2009 erfasst wurden. Die spektrale Bodenreflektivität und Bodenalbedo wurden aus den spektralen Messungen der aufwärtsgerichteten Stahldichte (Radianz) und Strahlungsflussdichte (Irradianz) bestimmt. Dazu wurden eindimensionale Strahlungsübertragungsrechnungen durchgeführt. Der Einfluss der Flughöhe auf die Bodenreflektivität und Bodenalbedo wird anhand eines Messbeispiels, sowie einer Modellstudie mit ein- und dreidimensionalen Strahlungsübertragungsrechnungen diskutiert. Für beide Untersuchungsgebiete, Leipzig und Zhongshan, wird die Heterogenität der Reflexion solarer Strahlung an urbanen Oberflächen gezeigt. Der Einfluss der im operationellen Aerosolalgorithmus des satellitengetragenen Instrumentes MODIS (MODerate resolution Imaging Spectroradiometer) getroffenen Annahmen zur Bodenreflektivität auf die optische Dicke von Aerosolpartikeln, wurde mittels der gemessenen spektralen Bodenreflektivität und einer auf Strahlungsübertragungsrechnungen basierenden Modellstudie quantifiziert. Ein linearer Zusammenhang zwischen Bodenreflektivität und optischer Dicke von Aerosolpartikeln wird für beide Fallbeispiele gezeigt. Mittels der Messungen in Zhongshan kann bestätigt werden, dass die Bodenreflektivität für urbane Oberflächen im Aerosolalgorithmus unterschätzt wird. Im Rahmen der Modellstudie wird die Sensitivität des Aerosolalgorithmus auf die programminternen Annahmen zur Bodenreflektivität quantifiziert.

Submitted by Cláudia Bueno (claudiamoura18@gmail.com) on 2015-12-04T17:06:29Z No. of bitstreams: 2 Tese - Fernando Moreira de Araújo - 2015.pdf: 6967405 bytes, checksum: 6a3a47f12667e66913e2ad2c041d7e21 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2015-12-07T11:21:38Z (GMT) No. of bitstreams: 2 Tese - Fernando Moreira de Araújo - 2015.pdf: 6967405 bytes, checksum: 6a3a47f12667e66913e2ad2c041d7e21 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2015-12-07T11:21:38Z (GMT). No. of bitstreams: 2 Tese - Fernando Moreira de Araújo - 2015.pdf: 6967405 bytes, checksum: 6a3a47f12667e66913e2ad2c041d7e21 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2015-03-03 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Fire is an important ecological and environmental disturbance phenomenon in the Cerrado biome, which is influenced by climatic, ecological, cultural and economic factors. Burning biomass promotes change in the structure and composition of the soil, accelerates the erosion and sedimentation processes, promotes seed germination, renewal of grasses and releases large amounts of trace gases and aerosols into the atmosphere. This research seeks to understand the location patterns and the recurrence of burned areas to the Cerrado biome according to their different geographical regions from the land cover and land use class, and climatic variables. In particular, we evaluated quantitatively the performance of the MODIS MCD45A1 product for the Cerrado biome, in accordance with the different land use and land cover classes depending on the landscape, using as reference 130 randomly selected burned area polygons, and four randomly selected medium resolution orbital images, both from the month of September. In addition, we analyzed the burned areas spatial and temporal patterns in Brazil, considering both the territorial limits of the six biomes (i.e. Amazônia, Caatinga, Cerado, Mata Atlântica, Pampa and Pantanal) and their main land cover and land use classes (PROBIO MMA). At last, for burned areas greater than 2 km², we evaluated their patterns (spatial and temporal) and frequency of recurrence (burned areas that intersect more than 50%), as well as their interanual and seasonal climatic variations from vegetation index (EVI), precipitation (TRMM) and evapotranspiration (MOD16) images. These images were analyzed in association with the four groups of recurrence (burned areas with recurrence every four years) to determine the different burning regimes and the pre and post burning vegetation responses. The MCD45A1 polygons (September) had good relationship with the reference mapping (Landsat base) (r² = 0.92) and also with the hotspots (MOD14 and MYD14 - monthly data) (r² = 0.89). The omission error found is high, but this is associated with landscape structure patterns, as found for the four reference images. The Product MCD45A1 even with spatial and temporal limitations promotes temporal mapping consistency and provides understanding the behavior and impacts of the burned on the Cerrado landscape. Among the Brazilian biomes, Cerrado is the one with the highest record of fires between 2002 and 2010 (73%), followed by Amazon (14%), while 81% of the records of the burned areas occur on the remnant vegetation cover class. The records of the burning recurrences in the Cerrado focus on the remnant class, 59% whereas the frequency of recurrence presented a higher proportion up to 3 times for the period 2000-2013. For the four groups of recurrences analyzed after the first fire record, 2002, the vegetative vigor records declines, especially after 2010, on average 4% for the remnant classes and 3.5% for the anthropogenic. The minimum distance between the fragments presents that 42% of recurrences analyzed are between 1-2 kilometers, providing greatest spatial concentration. / O fogo é um importante fenômeno ecológico e de perturbação ambiental no bioma Cerrado, o qual sofre influência de fatores climáticos, ecológicos, culturais e econômicos. A queima da biomassa promove a alteração da estrutura e composição do solo, acelera os processos erosivos e de sedimentação, promove a germinação de sementes, renovação das gramíneas e libera grandes quantidades de gases traços e aerossóis para a atmosfera. A presente pesquisa busca entender os padrões de localização e de recorrência das áreas queimadas para o bioma Cerrado, segundo suas diferentes regiões geográficas a partir das classes de uso da terra e cobertura vegetal remanescente e variáveis climáticas. Em específico busca-se avaliar quantitativamente a performance do produto MODIS MCD45A1 para o bioma Cerrado, de acordo com as distintas classes de uso e cobertura da terra em função da paisagem com base em 130 polígonos de áreas queimadas e 4 imagens orbitais de resolução espacial média, ambas amostras localizadas no mês de setembro. Outro interesse é de analisar os padrões espaciais e temporais da distribuição das áreas queimadas no território brasileiro considerando os limites territoriais dos biomas brasileiros e seus principais tipos de cobertura vegetal natural e antrópica (base PROBIO MMA), para tanto foi considerado os limites territoriais dos 6 biomas brasileiros (i.e. Amazônia, Caatinga, Cerrado, Mata Atlântica, Pampa e Pantanal). Por fim, avaliar os padrões (espaciais e temporais) e as frequências de recorrências das queimadas no Cerrado, com base em áreas queimadas >= 2km² e interseções >= 50% para as recorrências, bem como entender como a sazonalidade e variação interanual climática a partir dos dados de índice da vegetação (EVI), precipitação (TRMM) e evapotranspiração (MOD16) determinam os diferentes regimes de queima das várias classes de uso da terra e cobertura vegetal remanescente, para tanto foram analisados quatro grupos de recorrências com recortes temporais distintos. Os polígonos do produto MCD45A1 (setembro) apresentaram boa relação com o mapeamento de referência (base Landsat) (r² = 0.92) e também com os focos de calor (MOD14 e MYD14 - dados mensais) (r² = 0.89). O erro de omissão encontrado é alto, mas este está associado aos padrões de estrutura da paisagem, como o encontrado para as quatro imagens de referência. O Produto MCD45A1 mesmo apresentando limitações espaciais e temporais promove mapeamento com série temporal consistente, fornecendo entendimento do comportamento e os impactos do fogo sobre a paisagem do Cerrado. Entre os biomas brasileiros, o Cerrado é o que apresenta o maior registro de queimadas entre 2002 a 2010 (73%), seguido do Amazônico (14%), enquanto 81% dos registros das áreas queimadas ocorrem sobre as classes de cobertura vegetal remanescente. O registro das recorrências de queimadas no Cerrado se concentra sobre as classes remanescentes, 59%, já a frequência da recorrência apresenta maior proporção até 3 vezes para o período de 2000 a 2013. Para os quatro grupos de recorrências analisados, após o primeiro registro de fogo, 2002, o vigor vegetativo registra queda, principalmente após o ano de 2010, sendo em média 4% para as classes remanescentes e 3,5% para as antrópicas. A distância mínima entre os fragmentos mostra que 42% de recorrências analisadas estão entre 1 a 2 quilômetros, conferindo maior concentração espacial.