MAPEAMENTO DE MUÇUNUNGAS NO SUL DA BAHIA E NORTE DO ESPÍRITO SANTO UTILIZANDO TÉCNICAS DE SENSORIAMENTO REMOTO

A Floresta Atlântica é constituída por um mosaico de formações florestais nativas e ecossistemas associados, dentre eles as muçunungas. Este tipo de vegetação apresenta formações desde campestres até florestais e ocorre sobre solos areno-quartzosos e hidromórficos, principalmente Espodossolos, na região dos Tabuleiros Costeiros do Sul da Bahia e Norte do Espírito Santo. Esse trabalho teve como objetivo avaliar o desempenho dos classificadores da Máxima Verossimilhança e Support Vector Machine, bem como a contribuição de diferentes composições de bandas multiespectrais, do Índice De Vegetação Da Diferença Normalizada (NDVI) e da análise de componentes principais das imagens do satélite Sensor TM/Landsat5 para a separação de feições das muçunungas. Foram adquiridas nove cenas do satélite/sensor TM/Landsat5. Foram coletadas 75 amostras de treinamento para cada classe de uso do solo e as amostras de validação foram obtidas a partir da base de dados de uso do solo fornecida pela empresa Fibria Celulose. Após a classificação e a avaliação de sua acurácia, as imagens foram utilizadas para confecção de mapas temáticos. Comparando o desempenho dos classificadores MaxVer e Support Vector Machine ambos tiveram resultados satisfatórios, entretanto, o MaxVer mostrou resultados superiores com as 1023 combinações realizadas no ArcGIS. As áreas classificadas como muçununga confundiram-se com outras classes tais como pastagem, eucalipto, mata e corpo d’água devido às características espectrais desta vegetação. O mapa temático produzido pela classificação supervisionada da melhor combinação, utilizando o algoritmo Maxver. A combinação de uma e duas bandas obtiveram resultados inferiores, enquanto que os melhores resultados foram com combinações de seis a oito bandas. O uso do NDVI promoveu melhoria no índice Kappa, mas o incremento é mais significativo na classificação obtida a partir da combinação deste com as bandas do visível. A utilização das componentes principais não representou aumento significativo na acurácia das classificações, exceto para aquelas que só apresentavam bandas do visível. O classificador superestimou a classe muçununga, o que pode ser explicado pela complexidade do comportamento espectral desta vegetação

Soils, Geoenvironments and Ecosystem Services of a Protected Area in Western Brazilian Amazonia

Abstract The Serra do Divisor National Park (SDNP) in the Westernmost Brazilian Amazonia possesses unique Mountain landscapes of sub-andean nature, with high geo-biodiversity and pristine environments, with a potential high contribution in ecosystems services. We studied and mapped the basic geo-environmental units of the main sector of the Park, evaluating soil carbon stocks as a key ecosystem service provided by the Protected Area. For the identification, characterization and mapping of the geoenvironmental units, we integrated pedological, geomorphological and vegetation data obtained by local soil survey and field campaigns, as well as secondary data. Eight geoenvironmental units were identified and mapped, distributed in three main compartments: the Serra do Divisor (SD) the upper Moa River and the medium Moa River. This region presents similar environments to the sub-Andean region, notably the Ceja Forest at the top surface of the SD. Soils at the SD have high organic carbon accumulation, with close association with the nutrient-poor, quartz-rich rocks, and shows organic matter illuviation indicating active podzolization. The SDNP encompasses important ecosystems and services linked with high geo-biodiversity, and high soil carbon stocks, representing a new frontier for scientific research in the only area of transitional sub-andean forested landscape in Brazil

Forest restoration monitoring through digital processing of high resolution images

Monitoring and evaluating forest restoration projects is a challenge especially in large-scale, but the remote monitoring of indicators with the use of synoptic, multispectral and multitemporal data allows us to gauge the restoration success with more accurately and in small time. The objective of this study was to elaborate and compare methods of remote monitoring of forest restoration using Light Detection and Ranging (LIDAR) data and multispectral imaging from Unmanned Aerial Vehicle (UAV) camera, in addition to comparing the efficiency of supervised classification algorithms Maximum Likelihood (ML) and Random Forest (RF). The study was carried out in a restoration area with about 74 ha and five years of implementation, owned by Fibria Celulose S.A., in the southern region of Bahia State, Brazil. We used images from Canon S110 NIR (green, red, Near Infrared) on UAV and LIDAR data composition (intensity image, Digital Surface Model, Digital Terrain Model, normalized Digital Surface Model). The monitored restoration indicator was the land cover separated in three classes: canopy cover, bare soil and grass cover. The images were classified using the ML and RF algorithms. To evaluate the accuracy of the classifications, the Overall Accuracy (OA) and the Kappa index were used, and the last was compared by Z test. The area occupied by different land cover classes was calculated using ArcGIS and R. The results of OA, Kappa and visual evaluation of the images were excellent in all combinations of the imaging methods and algorithms analyzed. When Kappa values for the two algorithms were compared, RF presented better performance than ML with significant difference, but when sensors (UAV camera and LIDAR) were compared, there were no significant differences. There was little difference between the area occupied by each land cover classes generated by UAV and LIDAR images. The highest cover was generated for canopy cover followed by grass cover and bare soil in all classified images, indicating the need of adaptive management interventions to correct the area trajectory towards the restoration success. The methods employed in this study are efficient to monitor restoration areas, especially on a large scale, allowing us to save time, fieldwork and invested resources

OPTIMIZING THE MONITORING OF NATURAL PHENOMENA THROUGH THE COUPLING OF ORBITAL MULTI-SENSORS

High frequency of images and high spatial resolution are necessary characteristics in studies with high temporal and spatial dynamics, which are difficult to find in a single orbital sensor. Therefore, the possibility of using multiple satellites to overcome this obstacle in monitoring is of fundamental importance. The aim of the study was to evaluate the multi-sensor coupling for the monitoring of phenomena that require a greater frequency of spatial detail and high-temporal observations by intercalibrating the reflectance images of the LISS III sensor, which is on board the satellite ResourceSat-II, and the MSI sensor onboard the Sentinel-2A, utilizing the Landsat-8 OLI sensor as standard. To perform the methodology, prior the intercalibration, it was necessary to convert the digital numbers of the bands into reflectance at the top of the atmosphere, so that intercalibration of data with simple linear regression could be subsequently performed. The results demonstrate that, with the intercalibrations of the reflectance images of the LISS III and MSI sensors, it is possible to couple the information of these sensors with those coming from OLI, enabling the increase of the frequency and availability of information in studies that require more observations, as in agricultural monitoring, natural disasters, and deforestation among others

Modeling Actual Evapotranspiration with MSI-Sentinel Images and Machine Learning Algorithms

The modernization of computational resources and application of artificial intelligence algorithms have led to advancements in studies regarding the evapotranspiration of crops by remote sensing. Therefore, this research proposed the application of machine learning algorithms to estimate the ETrF (Evapotranspiration Fraction) of sugar can crop using the METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration) model with data from the Sentinel-2 satellites constellation. In order to achieve this goal, images from the MSI sensor (MultiSpectral Instrument) from the Sentinel-2 and the OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) sensors from the Landsat-8 were acquired nearly at the same time between the years 2018 and 2020 for sugar cane crops. Images from OLI and TIR sensors were intended to calculate ETrF through METRIC (target variable), while for the MSI sensor images, the explanatory variables were extracted in two approaches, using 10 m (approach 1) and 20 m (approach 2) spatial resolution. The results showed that the algorithms were able to identify patterns in the MSI sensor data to predict the ETrF of the METRIC model. For approach 1, the best predictions were XgbLinear (R2 = 0.80; RMSE = 0.15) and XgbTree (R2 = 0.80; RMSE = 0.15). For approach 2, the algorithm that demonstrated superiority was the XgbLinear (R2 = 0.91; RMSE = 0.10), respectively. Thus, it became evident that machine learning algorithms, when applied to the MSI sensor, were able to estimate the ETrF in a simpler way than the one that involves energy balance with the thermal band used in the METRIC model

OS SOLOS DAS CAMPINARANAS NA AMAZÔNIA BRASILEIRA: ECOSSISTEMAS ARENÍCOLAS OLIGOTRÓFICOS

http://dx.doi.org/10.5902/1980509820581“Campinaranas” are sandy ecosystems of great extension in the Brazilian Amazon, and are determinant for the great systems of rivers with black waters. Due to the lack of studies on this ecosystem, the objective of the present work was to study the distribution of “Campinaranas” and their relationship with the predominant soils and geology in the western portion of the Brazilian Amazon. We used geographic data of vegetation, geology and soils, and analytical data of the soil profiles collected by the RADAMBRASIL project, updated and systematized by IBGE, and data from reference profiles collected in the National Park of Viruá, are predominantly sandy, developed on parent materials rich in quartz. The overlaying of geological data with areas dominated by “Campinaranas”, reveals the prevalence of recent sedimentary formations (Quaternary), constituted mainly of sandy materials. Based on the studied dataset, we suggest a minimum limit of 55 dag kg-1 of sand in the soils for the occurrence of “Campinaranas”.  Soils with higher clay content are present only in Forest-Campinaranas transitions, adjacent to the sandy deposits. It is verified the absolute prevalence of Spodosols and Psamments in “Campinaranas”. Even in different geological formations and under distinct pedogenetic processes, these soils possess similar morphological, chemical and physical properties. In spite of the pedological diversity found in the transitional areas, the soils keep similarities with the soils of “Campinaranas”. http://dx.doi.org/10.5902/1980509820581As Campinaranas são ecossistemas arenícolas de grande extensão na Amazônia brasileira, determinantes para os grandes sistemas de rios de águas pretas. Em vista da carência de estudos nestes ecossistemas, este trabalho teve como objetivos gerais estudar a distribuição das Campinaranas e suas relações com os solos predominantes e sua geologia na porção ocidental da Amazônia brasileira. Foram utilizados dados analíticos dos perfis de solos coletados pelo Projeto RADAMBRASIL, atualizados e sistematizados pelo IBGE, somados a perfis de referência coletados no Parque Nacional do Viruá, Roraima. De modo geral, os solos das Campinaranas são predominantemente arenosos, desenvolvidos sobre materiais de origem de natureza arenoquartzosa. Do cruzamento dos dados geológicos com áreas dominadas por Campinaranas, tem-se um predomínio das formações sedimentares recentes (Quaternário), constituídas principalmente de materiais arenosos. A partir da análise dos dados, sugere-se um limite mínimo de 55 dag kg-1 de areia nos solos para a ocorrência das Campinaranas. Os solos mais argilosos são reportados apenas para as áreas ecotonais Florestas - Campinaranas, marginais aos corpos arenosos. Verifica-se predomínio absoluto dos Espodossolos e Neossolos Quartzarênicos nas Campinaranas. Mesmo em diferentes formações geológicas e com processos pedogenéticos distintos, estes solos possuem características morfológicas, químicas e físicas muito semelhantes. Apesar da diversidade pedológica das áreas ecotonais, os solos encontrados guardam semelhanças com os solos das Campinaranas

Management Recommendation Generation for Areas Under Forest Restoration Process through Images Obtained by UAV and LiDAR

Evaluating and monitoring forest areas during a restoration process is indispensable to estimate the success or failure of management intervention and to correct the restoration trajectory through adaptive management. However, the field measurement of several indicators in large areas can be expensive and laborious, and establishing reference values for indicators is difficult. The use of supervised classification techniques of high resolution images, combined with an expert system to generate management recommendations, can be considered promising tools for monitoring and evaluating restoration areas. The objective of the present study was to elaborate an expert system of management recommendation generation for areas under restoration, which were monitored by two different remote sensors: UAV (Unmanned Aerial Vehicle) and LiDAR (Light Detection and Ranging). The study was carried out in areas under restoration with about 54 ha and five years of implementation, owned by Fibria Celulose S.A. (recently acquired by Suzano S.A.), in the southern region of Bahia State, Brazil. We used images from Canon S110 NIR (green, red, near infrared) on UAV and LiDAR data compositions (intensity image, digital surface model, digital terrain model, normalized digital surface model). The monitored restoration indicator entailed land cover separated into three classes: Canopy cover, bare soil and grass cover. The images were classified using the Random Forest (RF) and Maximum Likelihood (ML) algorithms and the area occupied by each land cover classes was calculated. An expert system was developed in ArcGIS to define management recommendations according to the land cover classes, and then we compared the recommendations generated by both algorithms and images. There was a slight difference between the recommendations generated by the different combinations of images and classifiers. The most frequent management recommendation was “weed control + plant seedlings” (34%) for all evaluated methods. The image monitoring methods suggested by this study proved to be efficient, mainly by reducing the time and cost necessary for field monitoring and increasing the accuracy of the generated management recommendations

Processos hidrológicos na bacia hidrográfica do Córrego Zerede em Timóteo-MG

The increasing water demand and changes in the land use in the watershed of the Zerede Ceek stimulated hydrological analyses to improve the understanding of the dynamics of the local hydrological cycle, focusing on the relationship with forests and the consequences for the water quality. To this purpose, the hydrological monitoring was carried out by measurements of rainfall, flow rate and estimated evapotranspiration, using a digital wireless rain gauge, a modified atmometer, a Parshall flume set and ITS-2000. For the water quality analysis, samples were collected at five different points of the water course and analyzed for color, turbidity, pH, total suspended solids (TSS), electrical conductivity (EC), chemical oxygen demand, biochemical oxygen demand and heat-tolerant coliforms. The results showed that evapotranspiration contributed more to the amount of water leaving the basin than outflow, except from November to January (2006/2007). The final fluid balance of 247.7 mm was negative, showing that rainfall was lower than expected for the period and reinforcing the importance of using techniques that allow greater water retention in the basin. The parameters EC and TSS differed statistically between the means of the points analyzed by the F test at 5% probability, unlike the other parameters. The microbiological tests were negative, with coliform-free water. It was concluded that the analyzed water parameters meet the standards of Class 1 defined by Resolution No 357 of CONAMA (2005), indicating good water quality in the Zerede Creek basin.A crescente demanda de água e as modificações no uso do solo que vêm ocorrendo na bacia hidrográfica do Córrego Zerede ensejaram a realização de análises hidrológicas a fim de um melhor entendimento da dinâmica do ciclo hidrológico local, focando na relação com as florestas e suas consequências para a qualidade da água. Para isso, foi realizado o monitoramento hidrológico através de medições de precipitação, vazão e estimativa de evapotranspiração, utilizando-se um pluviômetro digital sem fio, um atmômetro modificado e pelo conjunto calha Parshall e ITS-2000. Para as análises da qualidade da água, foram coletadas amostras em 5 pontos distintos do curso d’água e analisadas quanto à cor, turbidez, pH, sólidos suspensos totais (SST), condutividade elétrica (CE), demanda química de oxigênio, demanda bioquímica de oxigênio e coliformes termotolerantes. Os resultados mostraram que a evapotranspiração apresentou maior contribuição para saída de água da bacia que o deflúvio, com exceção dos meses de novembro a janeiro (2006/2007). No balanço final, verificou-se o saldo hídrico negativo de 247,7 mm, refletindo precipitações abaixo do esperado para o período e reforçando a importância de utilizar técnicas que permitam uma maior retenção de água na bacia hidrográfica. Os parâmetros CE e SST apresentaram diferenças estatísticas entre as médias dos pontos analisados pelo teste F a 5% de probabilidade, sendo que os demais parâmetros revelaram a inexistência de diferença estatística entre as médias. As análises microbiológicas apresentaram resultados negativos, com a água livre de coliformes termotolerantes. Conclui-se que a água se encontra nos padrões da Classe 1, da Resolução no 357 do Conama (2005) nos parâmetros analisados, indicando uma boa qualidade na Bacia Hidrográfica do Córrego Zerede.