Dinâmica de incêndios florestais e alterações biofísicas na Amazônia e Cerrado brasileiros a partir de séries temporais de sensoriamento remoto

Tese (doutorado)—Universidade de Brasília, Instituto de Ciências Humanas, Departamento de Geografia, Programa de Pós-Graduação em Geografia, 2019.Os biomas brasileiros se adaptaram a diferentes padrões de presença ou ausência do fogo. Dados derivados de sensoriamento remoto têm sido uma das principais bases para a detecção de incêndios florestais e os danos na estrutura da vegetação, especialmente com o desenvolvimento de sensores com alta resolução temporal e espectral, e o estabelecimento de longas séries contínuas. Nesse sentido, esta tese buscou aprofundamento em três pontos: (1) Qual a potencialidade de produtos de sensoriamento remoto para a descrição da dinâmica do fogo no Brasil? (2) Como detectar cicatrizes de queimadas a partir de séries temporais em ambientes amazônicos?; e por fim (3) Quais os danos na vegetação resultantes da alteração do regime histórico do fogo e como podem ser quantificados por sensoriamento remoto? Para ampliar o conhecimento sobre essas questões foram utilizados diversos produtos derivados dos sensores Moderate Resolution Imaging Spectroradiometer (MODIS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) e Operational Land Imager (OLI), além de diversos dados espaciais, em três escalas: uma para todo o território nacional, uma área específica do Cerrado e duas áreas específicas da Amazônia. A metodologia básica consistiu na análise de séries temporais MODIS para detecção e quantificação dos efeitos do fogo. Os resultados permitiram concluir que: (1) Os produtos globais MODIS de detecção de cicatrizes de queimadas apresentaram altas taxas de erros de omissão no Brasil, superiores a 78% em média no território nacional, sendo seu uso recomendado apenas para análises regionais ou globais. Os produtos de queimadas apresentaram as menores acurácias nos biomas dos Pampas, Amazônia e Mata Atlântica e as maiores acurácias nos biomas do Cerrado e da Caatinga. Apesar desta limitação, o produto MCD64 permitiu descrever o regime do fogo no país, as principais regiões de ocorrência e a influência da umidade e classe de vegetação neste padrão. Foram estabelecidas como limite para a ação do fogo, as zonas sem estiagem, como o Oeste da Amazônia e litoral leste do Brasil, assim como as áreas do semiárido nordestino. (2) Dentre os métodos analisados de diferença sazonal e normalização temporal, a normalização pela média da banda espectral do Infravermelho Próximo foi responsável pela maior acurácia na detecção de cicatrizes de queimadas na Amazônia, retificando a utilização de alguns índices especializados originalmente para vegetações temperadas, como o Normalized Burn Ratio (NBR). Outros métodos analisados, como a diferença sazonal e normalização por z-score, apresentaram melhor acurácia que imagens originais, mas inferior em comparação com a normalização pela média. (3) A alteração da recorrência do fogo teve influência direta no padrão biofísico e fenológico da vegetação nas áreas de estudo na Amazônia e no Cerrado. As variáveis de produtividade primária bruta e albedo apresentaram baixa representatividade espacial. As mudanças com maior inclinação da tendência, do Enhanced Vegetation Index (EVI) e temperatura superficial, foram tanto relacionadas com a recorrência do fogo, quanto com a classe de uso da vegetação, como nas terras indígenas. A inclinação da tendência, no EVI e temperatura superficial, foi maior na área do Cerrado, reforçando a necessidade urgente de conservação deste bioma. A pesquisa atestou a importância de dados de sensoriamento remoto para avaliação da dinâmica do fogo e dos seus efeitos na vegetação. A utilização de séries temporais do sensor MODIS permitiu tanto identificar as áreas queimadas com maior acurácia que outros produtos disponíveis, quanto quantificar as fragilidades da vegetação relacionadas ao padrão de fogo atual.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).Brazilian biomes have adapted to different patterns of presence or absence of fire. Data derived from remote sensing have been one of the main techniques for the detection of forest fires and damage to vegetation structure, especially with the development of high temporal and spectral resolution sensors and the establishment of long continuous series. Thus, we intend to focus on three points in this thesis: (1) What is the potential of remote sensing products for the description of fire dynamics in Brazil? (2) How to detect burn scars from remote sensing time series in Amazonian environments? And finally (3) What damages in the vegetation resulting from the alteration of the historical fire regime and how can they be quantified by remote sensing? In order to increase the knowledge about these issues, several products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) sensors were used, in addition to diverse spatial data, in three scales: one for the whole national territory, one specific area of the Cerrado and two specific areas of the Amazon. The basic methodology consisted of the analysis of MODIS time series for the detection and quantification of fire effects. The results allowed to conclude that: (1) MODIS global burned area products presented high omission errors rates in Brazil, higher than 78% on average in the national territory, and their use is recommended only for regional or global analyzes. The burned area products showed the lowest value in the biomes of the Pampas, Amazon Forest and Atlantic Forest, and the highest values in the biomes of the Cerrado and Caatinga. In spite of this limitation, the product MCD64 allowed to describe the fire regime in the country, the main regions of occurrence and the influence of moisture and vegetation class in this pattern. Were established as a limit for the action of the fire the areas without drought, such as the Western Amazon and the east coast of Brazil, as well as areas with low availability of rainfall and fuel, such as the semi-arid in the Northeast. (2) Among the analyzed methods of seasonal difference and temporal normalization, the normalization of the Near Infrared spectral band by the zero-mean, was responsible for the greater accuracy in the detection of burn scars in the Amazon region, rectifying the use of some indices originally specialized for temperate vegetation, such as the Normalized Burn Ratio (NBR). Other methods analyzed, such as the seasonal difference and z-score normalization, showed better accuracy than original images, but lower than normalization by the zero-mean. (3) The alteration of fire recurrence had a direct influence on the biophysical and phenological pattern of vegetation the study areas of Amazon and Cerrado. The variables of gross primary productivity and albedo showed low spatial representativeness. The changes with higher trend slope, of Enhanced Vegetation Index (EVI) and surface temperature, were related both to fire recurrence and to the vegetation use class, as in indigenous lands. The slope of the trend in EVI and surface temperature was higher in the Cerrado area, reinforcing the urgent need for conservation of this biome. The research attested the importance of remote sensing data for the evaluation of fire dynamics and its effects on vegetation. The use of MODIS time series allowed both identifying the burned areas with greater accuracy than other available products, and quantifying the fragilities of the vegetation related to the current fire pattern

Mapping of summer agricultural crops in the Alto Paraguai basin through EVI/MODIS time series.

The main land use and land cover (LULC) changes that a given area passes over the time can be evaluated by using spatial-temporal analysis of satellites images. Then, it is possible to identify the LULC changes, as well as the main causes of environmental impacts. The objective of this paper was to analyze the LULC changes of the main agricultural lands cultivated in the Alto Paraguai Basin (BAP). This paper focused on the summer crops (soybean and corn) and the analysis of agricultural expansion. The results, considering a16-year comparison, showed an increase of 40.60% in the expansion of agricultural areas. The evaluation of the accuracy showed the efficiency of the methodology of agricultural mapping, presenting a Kappa Index of 0.85 for the 2000/2001 and 0.86 for the 2015/2016 crop seasons.Especial - Geopantanal 2016

Drought impacts assessment in Brazil - a remote sensing approach

Climate extremes are becoming more frequent in Brazil; studies project an increase in drought occurrences in many regions of the country. In the south, drought events lead to crop yield losses affecting the value chain and, therefore, the local economy. In the northeast, extended periods of drought lead to potential land degradation, affecting the livelihood and hindering local development. In the southern Amazon, an area that experienced intense land use change (LUC) in the last, the impacts are even more complex, ranging from crop yield loss and forest resilience loss, affecting ecosystem health and putting a threat on the native population traditional way of living. In the studies here we analyzed the drought impacts in these regions during the 2000s, which vary in nature and outcomes. We addressed some of the key problems in each of the three regions: i) for the southern agriculture, we tackled the problem of predicting soybean yield based on within-season remote sensing (RS) data, ii) in the northeast we mapped areas presenting trends of land degradation in the wake of an extended drought and, iii) in southern Amazon, we characterized a complex degradation cycle encompassing LUC, fire occurrence, forest resilience loss, carbon balance, and the interconnectedness of these factors impacting the local climate. Advisor: Brian D. Wardlo

Using middle-infrared reflectance for burned area detection

Tese de doutoramento, Ciências Geofísicas e da Geoinformação (Meteorologia), Universidade de Lisboa, Faculdade de Ciências, 2011A strategy is presented that allows deriving a new index for burned area discrimination over the Amazon and Cerrado regions of Brazil. The index is based on information from the near-infrared (NIR) and middle-infrared (MIR) channels of the Moderate Resolution Imaging Spectroradiometer (MODIS). A thorough review is undertaken of existing methods for retrieving MIR reflectance and an assessment is performed, using simulated and real data, about the added value obtained when using the radiative transfer equation (RTE) instead of the simplified algorithm (KR94) developed by Kaufman and Remer (1994), the most used in the context of burned area studies. It is shown that use of KR94 in tropical environments to retrieve vegetation reflectance may lead to errors that are at least of the same order of magnitude of the reflectance to be retrieved and considerably higher for large values of land surface temperature (LST) and solar zenith angle (SZA). Use of the RTE approach leads to better estimates in virtually all cases, with the exception of high values of LST and SZA, where results from KR94 are also not usable. A transformation is finally defined on the MIR/NIR reflectance space aiming to enhance the spectral information such that vegetated and burned surfaces may be effectively discriminated. The transformation is based on the difference between MIR and NIR in conjunction with the distance from a convergence point in the MIR/NIR space, representative of a totally burnt surface. The transformation allows defining a system of coordinates, one coordinate having a small scatter for pixels associated to vegetation, burned surfaces and soils containing organic matter and the other coordinate covering a wide range of values, from green and dry/stressed vegetation to burned surfaces. The new set of coordinates opens interesting perspectives to applications like drought monitoring and burned area discrimination using remote-sensed information.O coberto vegetal da superfície da Terra tem vindo a sofrer mudanças, por vezes drásticas, que conduzem a alterações tanto na rugosidade da superfície terrestre como no seu albedo, afectando directamente as trocas de calor sensível e latente e de dióxido de carbono entre a superfície terrestre e a atmosfera (Sellers et al., 1996). Neste contexto, as queimadas assumem um papel de extremo relevo (Nobre et al., 1991; O’Brien, 1996; Xue, 1996) na medida em que constituem uma das mais importantes fontes de alteração do coberto vegetal, resultando na destruição de florestas e de recursos naturais, libertando carbono da superfície continental para a atmosfera (Sellers et al., 1995) e perturbando as interacções biosfera-atmosfera (Levine et al., 1995; Scholes, 1995) através de mudanças na rugosidade do solo, na área foliar e noutros parâmetros biofísicos associados ao coberto vegetal. Ora, neste particular, a Amazónia Brasileira constitui um exemplo notável de mudanças no uso da terra e do coberto vegetal nas últimas décadas, como resultado da desflorestação induzida pelo homem bem como por causas naturais (Gedney e Valdes, 2000; Houghton, 2000; Houghton et al., 2000; Lucas et al., 2000), estimando-se que as regiões tropicais sejam responsáveis por cerca de 32% da emissão global de carbono para a atmosfera (Andreae, 1991). Neste contexto, a disponibilidade de informações pormenorizadas e actualizadas sobre as distribuições espacial e temporal de queimadas e de áreas ardidas em regiões tropicais afigura-se crucial, não só para uma melhor gestão dos recursos naturais, mas também para estudos da química da atmosfera e de mudanças climáticas (Zhan et al., 2002). A detecção remota constitui, neste âmbito, uma ferramenta indispensável na medida em que permite uma monitorização em tempo quase real, a qual se revela especialmente útil em áreas extensas e/ou de difícil acesso afectadas pelo fogo (Pereira et al., 1997). Diversos instrumentos, tais como o Land Remote Sensing Satellite/Thematic Mapper (LANDSAT/TM) e o National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) têm vindo a ser extensivamente utilizados na gestão dos fogos florestais, em particular aos níveis da detecção de focos de incêndio e da monitorização de áreas queimadas. Mais recentemente, o instrumento VEGETATION a bordo do Satellite Pour l'Observation de la Terre (SPOT) tem vindo a ser utilizado com sucesso na monitorização de fogos. Finalmente, são de referir os sensores da série Along Track Scanning Radiometer (ATSR) para os quais têm vindo a ser desenvolvidos algoritmos de identificação de focos de incêndio, e ainda o sensor Moderate Resolution Imaging Spectroradiometer (MODIS) que tem vindo a demonstrar capacidades óptimas no que respeita à observação global de fogos, plumas e áreas queimadas. Neste contexto, os métodos actuais de detecção de áreas ardidas através da detecção remota têm vindo a dar prioridade à utilização das regiões do vermelho (0.64 μm) e infravermelho-próximo (0.84 μm) do espectro eletromagnético. No entanto, tanto a região do vermelho quanto a do infravermelho-próximo apresentam a desvantagem de serem sensíveis à presença de aerossóis na atmosfera (Fraser e Kaufman, 1985; Holben et. al., 1986). Desta forma, em regiões tropicais como a Amazónia, onde existem grandes camadas de fumo devido à queima de biomassa, a utlização destas duas regiões do espectro eletromagnético torna-se insatisfatória para a detecção de áreas ardidas. Por outro lado, a região do infravermelho médio (3.7 – 3.9 μm) tem a vantagem de não ser sensível à presença da maior parte dos aerossóis, exceptuando a poeira (Kaufman e Remer, 1994) mostrando-se, ao mesmo tempo, sensível a mudanças na vegetação devido à absorção de água líquida. Com efeito, estudos acerca dos efeitos do vapor de água na atenuação do espectro eletromagnético demonstraram que a região do infravermelho médio é uma das únicas regiões com relativamente pouca atenuação (Kerber e Schut, 1986). Acresce que a região do infravermelho médio apresenta uma baixa variação da irradiância solar (Lean, 1991), tendo-se ainda que a influência das incertezas da emissividade na estimativa da temperatura da superfície é pequena quando comparada com outras regiões térmicas tais como as de 10.5 e 11.5 μm (Salysbury e D’Aria, 1994). A utilização da radiância medida através de satélites na região do infravermelho médio é, no entanto, dificultada pelo facto de esta ser afectada tanto pelo fluxo térmico quanto pelo fluxo solar, contendo, desta forma, duas componentes, uma emitida e outra reflectida, tendo-se que a componente reflectiva contém os fluxos térmico e solar reflectidos pela atmosfera e pela superfície enquanto que as emissões térmicas são oriundas da atmosfera e da superfície. Ora, a componente solar reflectida é de especial interesse para a detecção de áreas ardidas pelo que se torna necessário isolá-la do sinal total medido pelo sensor. Devido à ambiguidade deste sinal, a distinção dos efeitos da reflectância e da temperatura torna-se uma tarefa muito complexa, verificando-se que os métodos em que se não assume nenhuma simplificação, levando-se, portanto, em consideração todos os constituintes do sinal do infravermelho médio se tornam complexos e difíceis de serem aplicados na prática, na medida em que requerem dados auxiliares (e.g. perfis atmosféricos) e ferramentas computacionais (e.g. modelos de tranferência radiativa). Kaufman e Remer (1994) desenvolveram um método simples para estimar a reflectância do infravermelho médio o qual assenta em diversas hipóteses simplificadoras. Apesar do objectivo primário que levou ao desenvolvimento do método ser a identificação de áreas cobertas por vegetação densa e escura em regiões temperadas, este método tem sido lagarmente utilizado nos estudos acerca da discriminação de áreas queimadas, algumas das vezes em regiões tropicais (Roy et al., 1999; Barbosa et al., 1999; Pereira, 1999). Na literatura não existe, no entanto, nenhum estudo acerca da exactidão e precisão deste método quando aplicado com o objectivo de detectar áreas ardidas, em especial em regiões tropicais. Neste sentido, no presente trabalho procedeu-se a um estudo de viabilidade do método proposto por Kaufman e Remer (1994) em simultâneo com a análise da equação de tranferência radiativa na região do infravermelho médio, tendo sido realizados testes de sensibilidade dos algoritmos em relação aos erros nos perfis atmosféricos, ruído do sensor e erros nas estimativas da temperatura da superfície. Para tal recorreu-se ao modelo de transferência radiativa Moderate Spectral Resolution Atmospheric Transmittance and Radiance Code (MODTRAN), dando-se especial atenção ao caso do sensor MODIS. Os resultados demonstraram que a utilização do método proposto por Kaufman e Remer (1994) em regiões tropicais para a estimativa da reflectância no infravermelho médio, leva a erros que são pelo menos da mesma ordem de magnitude do parâmetro estimado e, em alguns casos, muito maior, quando ocorre a combinação de altas temperaturas da superfície terrestre com baixos ângulos zenitais solares. A utilização da equação de transferência radiativa mostrouse uma boa alternativa, desde que estejam disponíveis dados acerca da temperatura da superfíce terrestre assim como dos perfis atmosféricos. Entretanto, nas regiões onde ocorrem altos valores de temperatura da superfície terrestre e baixos ângulos zenitais solares, quaisquer dos dois métodos se mostra pouco utilizável, já que nesta região a estimativa da reflectância constitui um problema mal-posto. Em paralelo, utilizaram-se informações sobre aerossóis de queimada para efectuar simulações do MODTRAN que permitiram avaliar a reposta do canal do infravermelho-médio à este tipo de perturbação do sinal, muito comum na Amazónia Brasileira. A fim de tornar o estudo o mais realístico possível, procedeu-se à coleta de material resultante de queimadas na região Amazónica, mais especificamente em Alta Floresta, Mato Grosso, Brasil. Estes resultado foram então integrados nos estudos em questão, possibilitando a caracterização espectral das áreas ardidas. Com base nos resultados obtido definiu-se uma tranformação no espaço do infravermelho próximo e médio com o objetivo de maximizar a informação espectral de forma a que as superfícies vegetadas pudessem ser efectivamente discriminadas e as áreas ardidas identificadas. A tranformação baseia-se na diferença entre a reflectância nos infravermelhos próximo e médio, em conjunto com a distância a um ponto de convergência no espaço espectral dos infravermelhos próximo e médio, ponto esse representativo de uma área completamente ardida. A tranformação permitiu a definição de um novo sistema de coordenadas, o qual provou ser bastante útil no que diz respeito á identificação de áreas ardidas. Este novo espaço de coordenadas constitui uma inovação na área dos estudos de queimadas, já que permite ao mesmo tempo definir dois tipos de índices, o primeiro dos quais identifica superfícies que contém ou não biomassa e o segundo identifica, de entre as superfícies que contêm biomassa, a quantidade de água presente, podendo variar de vegetação verde (abundância de água) até áreas ardidas (ausência de água). Além de distiguir áreas ardidas, os índices desenvolvidos podem ainda ser aplicados em outros casos como, por exemplo, estudos de estresse hídrico e secas.DSA/INPE; Portuguese Foundation of Science and Technology (Fundação para a Ciência e Tecnologia / FCT)(SFRH/BD/21650/2005

Analysis of spectral separability for detecting burned areas using Landsat-8 OLI/TIRS images under different biomes in Brazil and Portugal

Data supporting the findings of this study are available in the public domain. Landsat-8 data (https://earthexplorer.usgs.gov/, accessed on 20 April 2020). BDQueimadas vector data (https://queimadas.dgi.inpe.br/queimadas/aq30m/, accessed on 20 April 2020). ICNF burned areas vector data (https://www.icnf.pt/florestas/gfr/gfrgestaoinformacao/dfciinformacaocartgrafica, accessed on 20 April 2020).Fire is one of the natural agents with the greatest impact on the terrestrial ecosystem and plays an important ecological role in a large part of the terrestrial surface. Remote sensing is an important technique applied in mapping and monitoring changes in forest landscapes affected by fires. This study presents a spectral separability analysis for the detection of burned areas using Landsat-8 OLI/TIRS images in the context of fires that occurred in different biomes of Brazil (dry ecosystem) and Portugal (temperate forest). The research is based on a fusion of spectral indices and automatic classification algorithms scientifically proven to be effective with as little human interaction as possible. The separability index (M) and the Reed–Xiaoli automatic anomaly detection classifier (RXD) allowed the evaluation of the spectral separability and the thematic accuracy of the burned areas for the different spectral indices tested (Burn Area Index (BAI), Normalized Burn Ratio (NBR), Mid-Infrared Burn Index (MIRBI), Normalized Burn Ratio 2 (NBR2), Normalized Burned Index (NBI), and Normalized Burn Ratio Thermal (NBRT)). The analysis parameters were based on spatial dispersion with validation data, commission error (CE), omission error (OE), and the Sørensen–Dice coefficient (DC). The results indicated that the indices based exclusively on the SWIR1 and SWIR2 bands showed a high degree of separability and were more suitable for detecting burned areas, although it was observed that the characteristics of the soil affected the performance of the indices. The classification method based on bitemporal anomalous changes using the RXD anomaly proved to be effective in increasing the burned area in terms of temporal alteration and performing unsupervised detection without relying on the ground truth. On the other hand, the main limitations of RXD were observed in non-abrupt changes, which is very common in fires with low spectral signal, especially in the context of using Landsat-8 images with a 16-day revisit period. The results obtained in this work were able to provide critical information for fire mapping algorithms and for an accurate post-fire spatial estimation in dry ecosystems and temperate forests. The study presents a new comparative approach to classify burned areas in dry ecosystems and temperate forests with the least possible human interference, thus helping investigations when there is little available data on fires in addition to favoring a reduction in fieldwork and gross errors in the classification of burned areas.The article processing charge (APC) was funded by the University of Jaén through the Center for Advanced Studies on Earth Sciences, Energy and Environment CEACTEMA and the University of Minho.Research was supported by the project “Applied Remote Sensing in the Study of Hot Spots in Forests in Brazil and the Iberian Peninsula” from the Department of Cartographic Engineering and Surveying (DECart) of the Federal University of Pernambuco (UFPE/Brazil), by POIUJA-2023/2024 and CEACTEMA from University of Jaén (Spain), and RNM-282 research group from the Junta de Andalucía (Spain). This work was also supported by national funding awarded by FCT—Foundation for Science and Technology, I.P., projects UIDB/04683/2020 and UIDP/04683/2020

Standardized time-series and interannual phenological deviation : new techniques for burned-area detection using long-term MODIS-NBR datase

Typically, digital image processing for burned-areas detection combines the use of a spectral index and the seasonal differencing method. However, the seasonal differencing has many errors when applied to a long-term time series. This article aims to develop and test two methods as an alternative to the traditional seasonal difference. The study area is the Chapada dos Veadeiros National Park (Central Brazil) that comprises different vegetation of the Cerrado biome. We used the MODIS/Terra Surface Reflectance 8-Day composite data, considering a 12-year period. The normalized burn ratio was calculated from the band 2 (250-meter resolution) and the band 7 (500-meter resolution reasampled to 250-meter). In this context, the normalization methods aim to eliminate all possible sources of spectral variation and highlight the burned-area features. The proposed normalization methods were the standardized time-series and the interannual phenological deviation. The standardized time-series calculate for each pixel the z-scores of its temporal curve, obtaining a mean of 0 and a standard deviation of 1. The second method establishes a reference curve for each pixel from the average interannual phenology that is subtracted for every year of its respective time series. Optimal threshold value between burned and unburned area for each method was determined from accuracy assessment curves, which compare different threshold values and its accuracy indices with a reference classification using Landsat TM. The different methods have similar accuracy for the burning event, where the standardized method has slightly better results. However, the seasonal difference method has a very false positive error, especially in the period between the rainy and dry seasons. The interannual phenological deviation method minimizes false positive errors, but some remain. In contrast, the standardized time series shows excellent results not containing this type of error. This precision is due to the design method that does not perform a subtraction with a baseline (prior year or average phenological curve). Thus, this method allows a high stability and can be implemented for the automatic detection of burned areas using long-term time series

Remote Sensing of Savannas and Woodlands

Savannas and woodlands are one of the most challenging targets for remote sensing. This book provides a current snapshot of the geographical focus and application of the latest sensors and sensor combinations in savannas and woodlands. It includes feature articles on terrestrial laser scanning and on the application of remote sensing to characterization of vegetation dynamics in the Mato Grosso, Cerrado and Caatinga of Brazil. It also contains studies focussed on savannas in Europe, North America, Africa and Australia. It should be important reading for environmental practitioners and scientists globally who are concerned with the sustainability of the global savanna and woodland biome

MAPPING OF SUMMER AGRICULTURAL CROPS IN THE ALTO PARAGUAI BASIN THROUGH EVI/MODIS TIME SERIES

The main land use and land cover (LULC) changes that a given area passes over the time can be evaluated by using spatial-temporal analysis of satellites images. Then, it is possible to identify the LULC changes, as well as the main causes of environmental impacts. The objective of this paper was to analyze the LULC changes of the main agricultural lands cultivated in the Alto Paraguai Basin (BAP). This paper focused on the summer crops (soybean and corn) and the analysis of agricultural expansion. The results, considering a16-year comparison, showed an increase of 40.60% in the expansion of agricultural areas. The evaluation of the accuracy showed the efficiency of the methodology of agricultural mapping, presenting a Kappa Index of 0.85 for the 2000/2001 and 0.86 for the 2015/2016 crop season

Disaggregating Tree And Grass Phenology In Tropical Savannas

Savannas are mixed tree-grass systems and as one of the world’s largest biomes represent an important component of the Earth system affecting water and energy balances, carbon sequestration and biodiversity as well as supporting large human populations. Savanna vegetation structure and its distribution, however, may change because of major anthropogenic disturbances from climate change, wildfire, agriculture, and livestock production. The overstory and understory may have different water use strategies, different nutrient requirements and have different responses to fire and climate variation. The accurate measurement of the spatial distribution and structure of the overstory and understory are essential for understanding the savanna ecosystem. This project developed a workflow for separating the dynamics of the overstory and understory fractional cover in savannas at the continental scale (Australia, South America, and Africa). Previous studies have successfully separated the phenology of Australian savanna vegetation into persistent and seasonal greenness using time series decomposition, and into fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil (BS) using linear unmixing. This study combined these methods to separate the understory and overstory signal in both the green and senescent phenological stages using remotely sensed imagery from the MODIS (MODerate resolution Imaging Spectroradiometer) sensor. The methods and parameters were adjusted based on the vegetation variation. The workflow was first tested at the Australian site. Here the PV estimates for overstory and understory showed best performance, however NPV estimates exhibited spatial variation in validation relationships. At the South American site (Cerrado), an additional method based on frequency unmixing was developed to separate green vegetation components with similar phenology. When the decomposition and frequency methods were compared, the frequency method was better for extracting the green tree phenology, but the original decomposition method was better for retrieval of understory grass phenology. Both methods, however, were less accurate than in the Cerrado than in Australia due to intermingling and intergrading of grass and small woody components. Since African savanna trees are predominantly deciduous, the frequency method was combined with the linear unmixing of fractional cover to attempt to separate the relatively similar phenology of deciduous trees and seasonal grasses. The results for Africa revealed limitations associated with both methods. There was spatial and seasonal variation in the spectral indices used to unmix fractional cover resulting in poor validation for NPV in particular. The frequency analysis revealed significant phase variation indicative of different phenology, but these could not be clearly ascribed to separate grass and tree components. Overall findings indicate that site-specific variation and vegetation structure and composition, along with MODIS pixel resolution, and the simple vegetation index approach used was not robust across the different savanna biomes. The approach showed generally better performance for estimating PV fraction, and separating green phenology, but there were major inconsistencies, errors and biases in estimation of NPV and BS outside of the Australian savanna environment

Identifying and assessing vegetation behaviour in riparian zones at large scale in the Brazilian Savannah

Riparian zones (RZs) have a clear distinct behaviour than the rest of the landscape. Particularly in water-limited regions, such as the Brazilian Savannah (Cerrado biome), where dry season may extend 5 months, the difference between riparian and upland zones is highly pronounced due to vegetation water access to groundwater, and this can have implications on the climatic and hydrological cycles. In order to quantify this difference at large-scale, it was herein proposed to (1) map RZs using topographical information, (2) investigate how land cover is distributed among topographic gradients and (3) investigate vegetation behaviour through remote sensing vegetation measurements and evapotranspiration (ET) estimation. A 140,000 km² upland region inside the Cerrado biome, called the Urucuia aquifer system, was chosen as study site. The region has seen a huge agricultural expansion during the last decades, with mechanized and irrigated crops increasingly using water from its underground reserves, which associated with climate change can have a big impact on the ecosystem, and understanding the role of RZs can be essential to quantify this impact. The height above nearest drainage (HAND) index was used to map RZs, by visually assessing bellow which values the index provided a reasonable RZ buffer comparing with Google Earth imagery. We also used HAND to quantify across its values the historical land cover distribution obtained by the MapBiomas database, and analyse vegetation behaviour in RZs and upland zones (UZs) using remote sensing vegetation measurements of normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) and ET estimation from the surface energy balance algorithm for land (SEBAL). A necessary step for HAND computation is a defined stream network, for which the main challenge is identifying channel heads. Herein it was developed an algorithm that produced a varying draining area threshold (vDAT) map for channel initiation, using the topographic position index (TPI) as an auxiliary variable. This algorithm was tested using MERIT-DEM. With the stream network, HAND values bellow 5 m provided the best RZ buffer. As for land cover distribution, we captured that forests naturally occur more densely in the extreme values of HAND (very shallow and very deep) and that farmland historical occupation in the Urucuia region occur more in the upper portions of the terrain, possibly due to soil conditions stablished during landscape formation and evolution. As for vegetation activity, the land cover class seems to have more influence on vegetation behaviour than topographic position, for all indicators computed. Yet, NDMI values in Riparian Forests are greater than in Upland Forests, particularly towards drier conditions, in terms of both seasonality (drier months) and inter-annual variability (drier years). Despite this indication of more water available in RZs than UZs, the ET estimation could not capture these differences, possibly due to difficulties in estimating this variable in natural vegetation with high degree of water stress