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ABSTRACT State parks are integral protection units created to protect ecosystems. However, anthropic activities may have been previously performed before their creation, forming transitional areas. Studies that evaluate the modifications of edaphic properties in these environments are scarce. The aim of this study was to evaluate the changes in soil properties and litter stock in areas of eucalyptus-forest ecotones. Litter stock (Stocklitter) and total soil organic carbon content and stock (TOCsoil), weighted mean diameter (MWD), origin of aggregates (biogenic or physicogenic) and respective content of total organic carbon (TOCBio and TOCPhy), total organic carbon (TOCAG), soil organic matter chemical fractions [fulvic acid (FAC), humic (HAC), and humin (HUMC)], and particulate, mineral-associated, free light and intra-aggregate light (POC, MAOC, FLFC, and ILFC) soil organic matter, fertility, and glomalin-related soil protein (GRSP) fractions were evaluated in aggregates (layer 0.00-0.10 m) in areas of eucalyptus-forest ecotone (Eco), preserved forest fragment (For), and eucalyptus plantation (Euc), in Nova Baden State Park, Lambari–MG. In the Euc and Eco areas, the highest Stocklitter content was found. Higher values of TOCsoil, TOCAG, GRSP, and MWD were observed in the Euc area. In the biogenic aggregates, the highest content of TOCBio, HAC, HUMC, POC, MAOC, FLFC, and ILFC was determined in detriment of the physicogenic ones. The dynamics of edaphic properties in the Eco area showed greater similarity with the For area than in the Euc area. In general, all vegetation covers contribute to the maintenance of soil quality.

ABSTRACT There is a need for greater knowledge about the medium- and long-term effects of prescribed fire management on soil in ecosystems prone to wildfires and more vulnerable to climate change. This study examined the short- and medium-term effects of prescribed fire on soil chemical properties and chemical fractions of soil organic matter (SOM) in two positions of the landscape in a high-elevation grassland environment. The ecosystem is located in the mountain peaks of southeastern Brazil associated with the Atlantic Forest biome. Prescribed fire was conducted in 2017 to reduce understory vegetation and thus prevent potential severe wildfires. Soil samples were collected at the layers of 0.00-0.10, 0.10-0.20, and 0.20-0.40 m, at eight composite sampling. The composite samples were collected on five different occasions: before the prescribed fire, and 10, 30, 90, and 240 days after the prescribed fire. Soil chemical properties, total organic carbon, labile C, and chemical fractionation of SOM were analyzed. All soil properties investigated were affected by the prescribed fire, with variations in landscape position, duration of effect, and soil layer. In the backslope area, the medium-term effect of fire was negative and induced soil degradation and induced soil degradation. In the footslope area, the system showed greater resilience to the effects of fire, as indicated by the recovery of the soil’s chemical properties. These results can help assess the suitability of controlled burning of vegetation for managing risks of fire in mountainous regions, such as high-elevation grasslands.

The “Forest Fires Prediction and Detection” edition highlights the importance of research on fires worldwide. In recent years, the increased frequency of fires caused by climate change has rendered the planet uninhabitable. Several works have been prepared and published in an effort to raise awareness among civil society and government bodies about the importance of developing new technologies for monitoring areas prone to mega-fires. This special issue includes nine important works from various countries. The goal is to better understand the impacts on the world’s most diverse regions, ecosystems, and forest phytophysiognomies. New geotechnologies and fire models were used, both of which are important and could be used in the future to improve short- and long-term planning in firefighting.

The objective of this study was to verify the link between climate change, changes in land use, and the increasing frequency of forest fires in the state of Acre. Recognizing the importance of an accurate assessment of fire risk, we also proposed a new fire risk index for the capital Rio Branco, using meteorological data. Validated reanalysis data from 1961 to 2020 extracted for Rio Branco and different land uses were used. Data on fire foci, deforestation, and agricultural crops were also obtained. The new model was based on the Fire Risk Atlantic Forest (FIAF) Index, developed for the Atlantic Forest biome, and was subjected to multiple regression analysis. To validate the new model, projections were calculated using different scenarios from the Intergovernmental Panel on Climate Change (IPCC). The new model, entitled Rio Branco Fire Risk (FIRERBR), revealed an increase in fire risk, especially associated with agriculture, in future scenarios (SSP2-4.5 and SSP5-8.5) from 2023 onward. Rainfall and relative air humidity also showed a reduction in projections, indicating a higher degree of fire danger for the region.

ABSTRACT In the Cerrado, the palm swamps ( veredas ) are characterized by being humid and stable environments that lead to the formation of Histosols ( Organossolos ). and soils with surface horizons of organic constitution, which are fragile and sensitive to anthropic action. This study aimed to evaluate the impact of anthropization (recurrent forest fires and livestock farming) on the chemical, physical and morphological properties of soils in two palm swamps in the Environmental Preservation Area (EPA) of Pandeiros River, Minas Gerais, namely: Água Doce, in preserved condition, and Taboa, in anthropized condition. Four soil profiles were morphologically described, two profiles in each palm swamp, with subsequent chemical and physical analyses, calculations of organic carbon stock and identification of the origin of organic matter. The results were analyzed using descriptive statistics and Pearson’s correlation coefficient. Soil morphological properties were influenced by vegetation cover, drainage and anthropization conditions. As for the physical and chemical properties, adequate values were observed in the preserved palm swamp, including lower bulk density values and higher cation contents. Anthropic actions in the anthropized palm swamp caused degradation of soils, revealed by subsidence, reduction in organic carbon content, increase in bulk density and decrease in fertility. Changes promoted in the soils of the palm swamps compromise ecosystem services, indicating that actions at either local or governmental level should be stimulated for the preservation and conservation of these environments.

Determining the period of weed coexistence with eucalyptus stands assists in the integrated management of weed competition, which reduces the application of herbicides, economic costs, and environmental damage. Therefore, the objectives of the present study were to evaluate the impact of a hybrid stand of Eucalyptus grandis × Eucalyptus urophylla trees on biomass production, the concentration and stock of macro and micronutrients, and the efficiency of nutrient utilization under different periods of coexistence with weeds. Our study is the first to report the impacts of weed management on the biomass and nutrients present in the leaves, branches, stembark, and stemwood at the time of mid-rotation (4.5 years old). The experiment was carried out in southern Brazil in the Pampa biome and followed a randomized block design, with three replications. The treatments consisted of increasing periods of coexistence with or control of weeds. The total biomass in the coexistence up to 378 days treatment was 53.7 Mg ha−1, and in the control treatment up to 168 days, it was 81.4 Mg ha−1, differing statistically. This reduction was in the order of 34%. The continuous presence of weeds led to a significant reduction in the production of wood and total biomass. The highest nutrient utilization efficiency (NUE) was observed for wood. The control of weeds for up to 168 days promoted greater productivity than controlling weeds for 378 days. This recommendation can be adopted by plantation managers for this region, reducing the amount of herbicide applied on the stand.

Tropical forests stand out among forest domains, due to their wide diversity of flora and fauna. However, these areas concentrate a large number of the forest fires that occur annually on the planet. In this context, the present study performs spatial modeling of the normalized multi-band drought index (NMDI) in the Central Atlantic Forest Corridor during past (2001-2020) and future (2021-2040) periods to identify the relationship between drought and forest fires. Fire foci data, soil moisture, and data from the MOD09A1 product were used to obtain the NMDI. Rainfall and mean air temperature data from the past and for different future scenarios (SSP126 and SSP585) were also used. The autoregressive integrated moving average model (ARIMA) was used for modeling the NMDI. The results found indicate a recurrence of fire in the CAFC during the period of 2001–2020. Future data indicate reductions in rainfall and an increase in temperature in the CAFC area. The NMDI data indicate that the central region of the corridor is the driest and, among the priority areas for conservation, the Ilha do Lameirão Municipal ecological station has the lowest index values. Future modeling indicates the drought intensifying in the coming years in the corridor area. The CAFC is an extremely important area for the maintenance of Atlantic Forest remnants; however, this area continues to suffer disturbances and without the adoption of public policies, these disturbances could compromise the conservation of natural resources.

The present study aimed to contribute to the diagnosis and advance the knowledge of the impacts of land use change and climate change on the tropical longleaf forest biome at the continental scale in South America (Biome 1 according to the WWF classification) for realizing scientific progress in the search for convincing strategies and actions by different actors for the preservation of forests in the continent. The status and climate of the area, which harbors the tropical longleaf forests of South America, were assessed. Moreover, volumetric soil moisture (VSM) was evaluated through maps and simulation using the autoregressive integrated moving average model (ARIMA). Furthermore, future climate scenarios were predicted based on El Niño–Southern Oscillation phenomena, meteorological systems, and scientific evidence, such as the shared socioeconomic pathways (SSPs) and sociopolitical dynamics evident in the region from the case analysis of the Brazilian states of Acre and Rio de Janeiro. An increase was noted in the temperature and range of precipitation variation in the biome. ARIMA analysis indicated changes of up to 0.24 m3 m−3 and an increased range of future VSM values. The December–January–February (DJF) quarter recorded the highest VSM median with the measurement scale of 0.05 to 0.44 m3 m−3, while the June–July–August (JJA) quarter recorded the lowest value. The regions of the biome with the lowest VSM values included southern Amazon (Ecuador, Peru, and the Brazilian states of Acre, Mato Grosso, Pará, and Maranhão), Brazilian Atlantic Forest, Southeast Region, and the Brazilian state of Bahia.

A agricultura é um dos setores que mais se destaca na economia do Brasil, sendo necessário muitas vezes o emprego do sensoriamento remoto, para identificação da expansão das áreas agrícolas e estimativas da sua produção. Esse trabalho tem por objetivo mapear as áreas agrícolas do noroeste de Minas Gerais por meio de máquina de vetor de suporte e comparar os resultados obtidos com o censo estatístico do Instituto Brasileiro de Geografia e Estatística. Para identificação das áreas agrícolas foi utilizado o algoritmo Service Vector Machine e imagens dos satélites e sensores Landsat 8 / OLI e Terra / MODIS. As amostras de treinamento do algoritmo foram obtidas por meio de imagem de alta resolução espacial, disponível no programa Google Earth Pro, nas classes rios, floresta, agricultura, pastagem e silvicultura. O mapeamento utilizando imagem do sensor OLI apresentou melhor Acurácia Global (0,81) e Kappa (0,66). A classificação com imagem OLI e MODIS apresentaram maior precisão na classe agricultura quando comparada as demais classes, apresentando confusão com pastagem, em decorrência da alta fitomassa da pastagem na época de aquisição das imagens (verão). O cálculo das áreas agrícolas demonstra superestimativa do Service Vector Machine (SVM) na classificação das imagens OLI e MODIS, com forte relação dos dados MODIS com o censo do IBGE (R²=0,83). Apenas municípios com áreas agrícolas superiores a 50.000 ha apresentaram menor erro na estimativa das áreas agrícolas. A aplicação do algoritmo mostra-se potencial para mapeamento da agricultura por meio de imagens dos sensores MODIS e OLI, porém deve-se avaliar a época de aquisição das imagens orbitais e variações nos parâmetros do algoritmo para melhorar a acurácia da classificação.

Climate change due to global warming has significant impacts on the Atlantic forest biome. Many forest fires are caused by extreme drought events, which present an uncertain future for their vegetation, and their associated risks are sensitive mainly at the local scale. In this context, the present study evaluated and correlated the normalized multi-band drought index (NMDI) with biophysical variables in the monthly period from 2001 to 2019 in 12 land cover classes. The Auto Regressive Integrated Moving Average (ARIMA) model was applied to the NMDI series and its ability to simulate data from the observed time series (2001–2019) and the future (2020–2030). The results showed a decrease in the NMDI values for the period considered dry in the State of Rio de Janeiro (SRJ), mainly for the classes of pasture and savannah, which presented greater sources of heat. The non-parametric analysis was performed using the Mann-Kendall test for all biophysical variables. The variables soil moisture and NMDI showed negative trends (Z = −1.68 and Z = −0.76), whereas gross primary productivity (GPP) showed a positive trend (Z = 1.89). The generated and validated ARIMA modeling simulated NMDI well and the Willmott coefficient (d) was approximately 1.0 for the study period. The 10-year projection (2020–2030) from NMDI for SRJ pointed to a change in class from wet to dry in the mixed forest area (D) and cultivated land (L). The ARIMA model can represent the drought index in the seasonality of the series for the different classes of vegetation. These results showed that the applicability of NMDI in predicting fire risk conditions would be adequate in other areas of tropical forests, standing out mainly for being a drought index that can be used in future modeling.

The general objective of this research was to propose a new fire risk index, specifically the Fire Risk Atlantic Forest (FIAF) index in Itatiaia National Park (PNI). The data were collected from two levels (2 and 10 m) of a micrometeorological tower, with a time series on an hourly scale, daily from 2018 to 2021. Two multiple regression models were generated for the two collection levels (FIAF 2 and 10 m) and, based on the statistical criteria and the choice of the best model, a future simulation was generated using the scenario SSP 4.5 for 2022 to 2050. The correlation matrix between the data from the FIAF and fire foci models was also analyzed. The FIAF model was compared with the traditional models already used in Brazil, such as the Angström indices, Monte Alegre Formula (FMA), and the improved Monte Alegre Formula (FMA+) models. The results showed that the FIAF model at 10 m overestimated the results observed mainly during the dry season. The FIAF 2 m model presented the highest correlation with a fire foci value greater than 0.74. In the future simulation, the years that presented the highest extreme risks were: 2025, 2035, 2041, and 2049. Thus, it is possible to state that the FIAF model at the 2 m level was the best model for predicting the degree of fire risk in the PNI.

This research aimed to analyze the possibility to estimate and automatically map large areas of soybean cultivation through the use of MODIS (Moderate-Resolution Imaging Spectroradiometer) images. Two major techniques were used: GEOgraphic-Object-Based Image Analysis (GEOBIA) and Data Mining (DM). In order to obtain the images, the segmentation algorithm implemented by Definiens Developer was used. A decision tree (DT) was created from a training set previously prepared. Time-series of images from the MODIS sensor aboard the Terra satellite were acquired in order to represent the wide variation of the vegetation pattern along the soybean crop cycle. The time-series data were used only for the CEI index. Furthermore, to compare the results obtained from GEOBIA, the slicing technique was used at the CEI level. After the training, the DT was applied to the vegetation indices generating the thematic map of the spatial distribution of soybean. In accordance with the error matrix and kappa parameter analysis, tests for statistical significance were created. Results indicate that the classification achieved by Kappa coefficients is 0.76. In short, the obtained results proved that combining vegetation indices and time-series data using GEOBIA return promising results for mapping soybean plantation on a regional scale.

The prediction of a forest production requires knowledge of the dendrometric and edaphoclimatic variables. This study aimed to adjust and evaluate the accuracy of the 3-PG model in estimating the variables height, diameter at breast height (DBH), volume and mean annual increment (MAI) in commercial plantations of Eucalyptus spp. in northern of Minas Gerais state, using meteorological data from automatic surface stations and remote sensing. To validate the model, data of height, DBH, volume and MAI by 3-PG were estimated and compared with forest inventory data, totaling 335 measurements in 10 plots in the period 2005 to 2011. Linear statistical correlation methods (Pearson - r), the coefficient of determination (R²), the standard error of estimate (Syx), the standard error of the estimate in percentage (Syx%) and the efficient model (EF) were applied. It was observed that the model tends to overestimate the dendrometric variables when using the parameterization proposal for northern region of Minas Gerais state. After adjusting the parameters for the age of canopy closure (fullCanAge), the relationship between stem and DBH (nS) and parameterization of allometric equations for the total height and volume of wood incorporated in the 3-PG, obtained satisfactory results with values of R² = 0.94 and EF = 0.87 for DBH, height and volume and R² = 0.85 and EF = 0.58 for the MAI, as presented distribution of estimated data close to the average values of the observed data. The 3-PG was shown to be effective in estimating the DBH, height, volume and MAI become a potential tool for evaluating suitable areas for the expansion of new crops.

The objective of this study was to evaluate the space-time dynamics of the soil use and occupation of the Rio Roncador river basin between 1985 and 2010. The scenes were classified by two methods (partially unsupervised - K-Means and supervised - Maximum likelihood), the Thematic Mapper sensor products on the LANDSAT 5 orbital platform were used for both images of a 25-year time series (1985 to 2000). In order to measure the accuracy of the field the computer application Google Earth was used, in which nine classes (urban area, agricultural area, pasture, exposed soil, native forest, secondary vegetation, mangrove, altitude field and water) were collected. A multiple linear regression was performed, correlating the Normalized Difference Vegetation Index - mean NDVI (dependent variable) with the independent climatic variables (global solar radiation - MJm-2day-1, average air temperature - °C, relative humidity -%, evapotranspiration - mm d-1, and rain - mm). According to the general classification by Kappa parameter of the images for 2005 and 2010, they were identified as very good (68% and 74%). These results confirm that the Roncador River Basin is undergoing transformation in its landscape, with an average reduction of -49% in native vegetation areas due to the increase in urban areas (25%) and agriculture (31%). The statistical analysis showed that rainfall and air temperature were the only variables that presented significant sigma (0.04) and (0.02). The obtained coefficient of determination indicated that 47% of the variations of the "vegetation index" are explained by the environmental variables.

The aim of this study was to evaluate the variability of the Atlantic Forest in the municipality of Cunha-SP, Brazil, based EVI index (Enhanced Vegetation Index) and climatic variables (air temperature and rainfall). Images of MOD13Q1 product from MODIS sensor, which represent the index EVI were used. The descriptive statistics and multiple were applied to climate variables and EVI for the cycle 2007/2008 (strong La Niña event). The lowest average values of the rain were found for 2008 (171.60 mm), while the highest average rainfall was found for 2007 (187.02 mm). The vegetation behaved in a manner contrary, where the lowest average EVI index was found for 2007 (0.38), already 2008 had the highest rate (0.46), respectively. The coefficient of determination between the rainfall and the EVI in 2007 (R² = 0.43) higher than in 2008 (R² = 0.12), followed by correlation indexes in 2007 (r = 0.65) and 2008 (r = 0.34). However, both indexes were low, except correlation index in 2007. In the multiple regression analysis for the year 2007 obtained 87% correlation, while in 2008 only 27%. There is no correlation between vegetation and air temperature.

The objective of this study was to perform a temporal and spatial analysis of the changes in the past global solar radiation based on climate models and remote sensing data in the State of Rio de Janeiro, Brazil for the baseline period (1961-1990). Data from two climate models - the Canadian Centre for Climate Modelling and Analysis and Geophysical Fluid Dynamic Laboratory, were used for the A1B intermediate scenario, data from Conventional Weather Stations and orbital sensor Moderate Resolution Imaging Spectroradiometer (MODIS) MODIS Land Cover Type (MCD12Q1). The results of the Spatial Dependence Degree indicate that the best model to represent the global solar radiation is CCCMA-Exponential dry 70.01 and rainy 0.21 respectively. It was possible to verify that in places where the areas are occupied by forests there was reduction of global solar radiation for both dry and rainy periods of approximately 13 MJ m-2d-1. These results indicate that these forest areas can function as islands of freshness, while maintaining the thermal comfort balanced. It was concluded that the dry period had the highest values of solar radiation compared to the rainy (57%), which can be justified by the occurrence of fires in Rio de Janeiro.

The objective of this study was to conduct a temporal analysis of biophysical attributes of the river basin of Rio Roncador, located in the municipality of Magé, Rio de Janeiro. SRTM data were used for the determination of the river basin morphometry and two images of the orbital platform Landsat5 TM sensor (01/28/1986 and 02/15/2010) applied the SEBAL algorithm to characterize the landscape dynamics. The results indicate that The river basin has a drainage area equivalent to 186.21 km2, perimeter 101.78 km, circularity index equal to 0.22, form factor 0.26 and compares index 2.09. These results indicate that the river basin is not prone to flooding, mainly due to its elongated form. It was possible to verify that in the interval of 24 years, degradation occurred in the region beyond the change in the coverage of the soil of the river basin. The results indicated a tendency of reduction in the areas of permanent preservation -13.4% of the river basin. It is concluded that anthropogenic actions were able to alter the surface cover of the soil and that, by the way, may have influenced the water dynamics of the river basin.

The objective of this study was to analyze a spatiotemporal study of the vegetation dynamics of the hydrographic basin of the Ribeirão Cachimbal in Rio de Janeiro (Brazil), based on Moderate-Resolution Imaging Spectroradiometer imagery acquired by the TERRA satellite. A total of 23 images were used for each year of El Niño (2005 and 2015), 250-m-resolution images from collection 006 of the 16-day Enhanced Vegetation Index (MOD13Q1) product were used. Daily rainfall and temperature data were obtained from a conventional meteorological station at Resende (Rio de Janeiro State), which were made available by the National Institute for Meteorology of Brazil. Simple linear regression analysis was performed to evaluate the dependence of the temporal series of vegetation as a function of the daily series of rainfall and temperature in terms of the significance of their correlation coefficients. Multivariate analysis of the main components was also undertaken. The results of the simple linear regression between the vegetation index and meteorological variables (temperature and rainfall) were significant in the respective years (p-value < 5%), except for rainfall in 2015, which presented a value of 0.06 (p-value < 25%). Observing the trend, both years (2005 and 2015 showed an increase in vegetation in the study area (Z = 0.37 and 0.24, respectively). By quantifying the values of the respective vegetation classes, it was possible to verify that a reduction of 40% had occurred in areas with dense vegetation coverage by 2015. The vegetation dynamics of the Ribeirão Cachimbal basin are influenced by rainfall and temperature variables and they have greatest correlation in spring and summer.

ABSTRACT Incoming longwave radiation was estimated using air temperature data from the output of the regional HadRM3 model in the Intergovernmental Panel on Climate Change’s (IPCC) A2 scenario for projections up to 2070, 2080 and 2090 and using Swinbank’s equation. Spatial distribution was done by Ordinary Kriging through three theoretical mathematical models for the IPCC A2 scenario for the whole Legal Amazon. It was found that the highest averages and outliers occurred in 2090 compared to other years evaluated. The average incoming longwave radiation for 2070, 2080 and 2090 was 394.8, 403.9 and 413.0 Wm-2year-1 , respectively. The coefficients of variation (CV) were higher for 2080 (2.6%) and 2090 (2.8%), similar to the results found by standard deviation. 2070 obtained CV (2.2%) for estimated values of incoming longwave radiation with greater accuracy. Again, 2070 was the only year that could be interpolated because the average degree of spatial dependence found for all models was 12.23%. Lastly, 2080 could only be interpolated using the Gaussian model in the Legal Amazon.

The objective of this study was to characterize the physical parameters of the Cachimbal River Watershed, located in Pinheiral, Rio de Janeiro State, Brazil, and to use the resulting data to identify degradation risks. To achieve this purpose, a Hydrologically Consistent Digital Elevation Model (HCDEM) was generated using contour line, river path, and area boundary data extracted from topographic maps of the cities of Volta Redonda (Page SF-23-ZAV-2) and Piraí (Page SF-23-Z-VI-1). These maps were obtained from the Brazilian Institute of Geography and Statistics, and were rendered at a scale of 1:50,000 ArcGISs version 10.5 software was used to generate the HCDEM, from which the physical parameters were extracted. Results showed that the altitude of the area ranges from 360 m to 740 m, while the slope varies heterogeneously from 6% to 28%. The sub-basin has a total area of 104.15 km², a perimeter of 63.41 km, a main channel length of 21.79 km, and a 5th-order dendritic drainage network. Other parameters include a compactness coefficient of 1.74, a form factor of 0.34, and a circularity ratio of 0.33. These values indicate that the sub-basin is not prone to floods because of its elongated shape. Meanwhile, drainage density was 2.60 km km-2, while river density was 5.5 channels km-2; these parameters indicate excellent performance and high potential to generate new channels. Although the roughness coefficient indicates that the area is suitable for agricultural development, the roughness index demonstrates the need to adopt more nuanced agricultural practices that account for the particular features of the area, such as topographic variation and soil characteristics.

Este trabalho avaliou o comportamento da floresta e demais classes espectrais do Projeto de Assentamento Dirigido Santa Luzia, utilizando os recursos do Geoprocessamento e Sensoriamento Remoto. O período avaliado estende-se entre o ano de 2005 a2010, e procurouavaliar o comportamento da evolução espacial de áreas como a floresta, pastagens e áreas utilizadas para agricultura, assim como demais benfeitorias realizadasno perímetro do assentamento. Neste sentido, os objetivos gerais deste trabalho foram: caracterizar a contração ou a expansão de classes de floresta, pastagens, regeneração da floresta e áreas alagadas, no PAD Santa Luzia, AC. Os resultados encontrados mostraram um significativo aumento do índice de regeneração da floresta e conversão de áreas de pastagens e cultivos em capoeira, considerando que esta tipologia florestal é essencial para o processo de transição de áreas desflorestadas em sua reestruturaçãoà condição de floresta novamente. São ainda apresentados dados que demonstraram a elevação dos valores referentes a corpos d’água, embora as imagens tenham sido adquiridas em períodos de estiagem (período seco amazônico) na região. Os dados obtidos pelo algoritmo de Mahalanobis, evidenciaram um significativo aumento destes recursos na superfície estudada. Os dados apresentaram o comportamento de leve decréscimo para a floresta durante o período avaliado.

Foram avaliados a dinâmica espaço-temporal do uso e cobertura da terra entre os anos de 1990 e 2010 no município de Seropédica, Região Metropolitana do Rio de Janeiro (RMRJ). Foram utilizadas imagens TM (Thematic Mapper) Landsat 5 e os métodos de classificações supervisionadas baseado nos algoritmos da Mínima Distância (MINIDIST), Máxima Verossimilhança (MAXVER) e distância de Mahalanobis (MAHAL). Os resultados obtidos de 1990 mostraram que a classificação MINIDIST superestimou as classes de áreas de água (5,02%), mata (8,94%), solo exposto (16,05%) e pastagem (59,33%), respectivamente. O MINIDIST em 1990 subestimou a classe área urbana (10,66%) comparado com os demais métodos. As classespastagem (59%), mata (20,68%) e água (2,25%) foram superestimadas pelo MINIDIST, enquanto que para as classes espectrais de solo exposto (0,92%), área urbana (11,54%) e eucalipto (5,81%) ocorreram subestimativa comparado aos métodos MAHAL e MAXVER em 2010. O viés médio mostrou que os valores de área para ambos os classificadores foram superestimados em relação aos dados do projeto SOS Mata Atlântica. Os índices de vegetação mostraram-se compatíveis com a literatura, às exceções foram às discrepâncias na estimativa de área atribuídas à transição de períodos secos e chuvosos que ocorreram antes da passagem do satélite sobre a região. Ressalta-se que todos os classificadores utilizados neste estudo são passíveis de erro, ou seja, os classificadores foram desenvolvidos na tentativa de aperfeiçoarem os trabalhos de interpretação visual em Seropédica.

O objetivo deste trabalho foi avaliar a dinâmica nouso e cobertura da terra em área de abrangência de Viçosa, Minas Gerais. Para tanto, utilizou-se o algoritmo SEBAL (Surface Energy Balance Algorithm for Land) e o método de classificação não supervisionada por meio do algoritmo ISODATA. Foi utilizada uma série históricade temperatura do ar (ºC), da Estação Meteorológica Convencional (EMC) do Instituto Nacional de Meteorologia (INMET) e imagens do sensor TM Landsat 5 do Instituto Nacional de Pesquisas Espaciais (INPE), noperíodo que compreendeu 16 anos (1994-2010). Os resultados mostraram que nos anosde 1999, 2000, 2003, 2006, 2009 e 2010 mais de 20 mil hectares foram antropizadas, porém, a partir de 1999 inicia-se um acentuado crescimento das áreas classificadas como mata. Os valores demonstraram avanço das áreas antropizadas (58,92% em 1994 para 71,90% em 2010) e uma redução das áreas de pastagens (27,04% em 1994 para 5,90% em 2010). A temperatura da superfície estimada pelo algoritmo SEBAL para os anos de 1994 e 2010, apresentaram valores máximos de 38ºC em áreas antropizadas e valores mínimos de 18ºC em áreas de vegetação. Com base no cálculo do viés médio (VM), o presente estudo mostrou que os dados estimados da temperatura da superfície apresentaram boa correlação de 0,67 com os dados do INMET, já que as temperaturas foram subestimadas e superestimadas com valores mínimos e máximos de -3,83ºC e 2,65ºC em 1994 e 2003. Os resultados obtidos, ainda que em caráter preliminar, indicam a eficiência do Sensoriamento Remoto (SR) por meio da análise das bandas refletivas e termal do satélite Landsat 5 como ferramenta de análise na identificação da dinâmica do uso do solo, mostrando-se eficaz quanto à espacialização dessas anomalias no espaço e no tempo.

RESUMO A Floresta Atlântica é o ecossistema brasileiro submetido a processos de degradação ambiental mais acentuado, mesmo assim, em alguns ambientes o processo de regeneração natural pode ser observado. O objetivo deste estudo foi avaliar o padrão da regeneração natural dos fragmentos florestais do Médio Vale Paraíba do Sul quanto aos fatores topográficos e identificar áreas potenciais ao processo de regeneração. O mapeamento dos fragmentos florestais foi obtido a partir de imagens do sensor Thematic Mapper (1994 e 2011). Para os fatores topográficos foram utilizadas as cartas topográficas do IBGE. O processo de regeneração natural na área de estudo é influenciado pelos fatores topográficos e acontece principalmente nos ambientes com superfície plana, declividade variando de ondulada a forte ondulada, orientação da vertente variando de SE (sudeste) a SW (sudoeste) e radiação solar global entre 150000 e 1700000 Watts. Na sub-bacia do ribeirão Cachimbal, os ambientes favoráveis à regeneração natural não são suficientes para que a sub-bacia tenha sua cobertura florestal original restabelecida, por representar apenas 1,2% da área da sub-bacia hidrográfica, o que remete à necessidade de intervenção antrópica.

This article aimed to evaluate land surface temperature using MOD11A2 (Terra satellite) with spatial resolution of one kilometre, compares its findings with land surface temperature data gathered by conventional meteorological stations, and, finally, investigates relations between land surface temperature and synoptic systems events that occurred in Rio de Janeiro State between January until December of 2009. The highest surface temperatures recorded by the MOD11A2 product, derived from the MODIS sensor, were found in the Metropolitana, Baixadas Litorâneas, Norte Fluminense and Noroeste Fluminense regions of Rio de Janeiro State and were recorded during the summer, winter and spring seasons. Autumn was the only exception, and this was due to the influence of the coastal environment. The following synoptic systems interfered with the estimated surface temperature produced by the MOD11A2 product for Rio de Janeiro State in 2009: the Madden Julian Oscillation and South Atlantic Convergence Zone in the summer; and Frontal Systems, the South Atlantic Convergence Zone, the Madden Julian Oscillation and the Upper Tropospheric Cyclonic Vortex in spring. The land use and occupation types with the highest surface temperature are: forest, urban area and pasture land in the summer; forest, urban area, agriculture and pasture land in autumn; and urban area and agriculture during spring. The MOD11A2 product showed a drastic decrease of the surface temperature for all land types during winter, especially for forested land.

The aim of this study was to determine the probable monthly rainfall for the state of Mato Grosso do Sul, considering the level of 75% probability, and study the spatial distribution associated with its different biomes. The rainfall data of 32 stations (sites) in the state of Mato Grosso do Sul were collected in the period 1954-2013. In each of the 384 series, the average monthly rainfall was calculated, for at least 30 years of observation. The Kolmogorov-Smirnov adhesion test was applied to the rainfall time series to check the fit of the data to a normal distribution. The likely fallout was estimated at 75% probability, using the normal probability distribution and, subsequently, it was adopted the method of Ordinary Kriging interpolation mathematics to spatial data. Based on the likely monthly precipitation estimated, the State of Mato Grosso do Sul possess three distinct periods, with the precipitation associated with different biomes: the rainy season (between the months November to March, where increased precipitation occurred in the Savanna biome), dry season (between the months from June to August, when the highest rainfall occurred in the Atlantic Forest) and transition period (April and May and September and October).

Identifying homogeneous regions regarding the monthly rainfall is relevant in agricultural planning, especially in relation to the installation of crops. Thus, the aim of this study was to apply the cluster analysis using Ward's algorithm to identify homogeneous regions in Tocantins State. Rainfall database of 34 stations (sites) of Tocantins, from 1976 to 2012, it were obtained of the Database of the Agência Nacional de Águas, Instituto Nacional de Meteorologia and Serviço Meteorológico do Brasil. Thus, were formed 408 time series (12 months × 34 sites) wherein AA technique was applied in conjunction with Ward's algorithm. Three homogeneous regions in relation to monthly rainfall were identified. Group 1, located in the extreme north of the state, has intermediate average values (135.58 mm) to the other groups. Group 2 showed the greatest variance (13,543.68 mm²) and higher average (162.19 mm) for the studied period. On the other hand, group 3 has the lowest average rainfall (117.93 mm) among the homogeneous groups. Separating the groups followed a north-south alignment which suggests that latitude is the physiographic factor that most influences the occurrence of monthly rainfall in the State of Tocantins.

Evidence of environmental impact on the Cerrado is characterised by the presence of large homogeneous pastures and agricultural areas, with the presence of very fragmented and scattered forest fragments. When these areas are abandoned due to low productivity, natural regeneration begins, which is influenced by environmental factors. The goal of the present study was to evaluate the forest cover temporal dynamics in anthropogenic areas and the influence of climate on natural regeneration in the Cerrado. The study site was an anthropogenic area that has been protected against the entrance of domestic animals and agriculture since 2002. Environments were identified, and natural regeneration dynamics were analysed by the use of vegetation indices calculated from satellite images. Statistical analysis Non-parametric Mann-Kendall was used to check the trend of the rain and the Normalized Difference Vegetation Index, multivariate analysis to verify the correlations and groups between the years of occurrence of El Niño and La Niña and the values of Normalized Difference Index. Natural regeneration in the Cerrado increased over time and was positively correlated with rainfall incidence. The process of recovery of degraded areas by natural regeneration technique proved efficient in the Cerrado, however, natural regeneration is negatively influenced by the weather phenomenon El Niño.

O objetivo deste trabalho foi avaliar a dinâmica nouso e cobertura da terra em área de abrangência de Viçosa, Minas Gerais. Para tanto, utilizou-se o algoritmo SEBAL (Surface Energy Balance Algorithm for Land) e o método de classificação não supervisionada por meio do algoritmo ISODATA. Foi utilizada uma série históricade temperatura do ar (ºC), da Estação Meteorológica Convencional (EMC) do Instituto Nacional de Meteorologia (INMET) e imagens do sensor TM Landsat 5 do Instituto Nacional de Pesquisas Espaciais (INPE), noperíodo que compreendeu 16 anos (1994-2010). Os resultados mostraram que nos anosde 1999, 2000, 2003, 2006, 2009 e 2010 mais de 20 mil hectares foram antropizadas, porém, a partir de 1999 inicia-se um acentuado crescimento das áreas classificadas como mata. Os valores demonstraram avanço das áreas antropizadas (58,92% em 1994 para 71,90% em 2010) e uma redução das áreas de pastagens (27,04% em 1994 para 5,90% em 2010). A temperatura da superfície estimada pelo algoritmo SEBAL para os anos de 1994 e 2010, apresentaram valores máximos de 38ºC em áreas antropizadas e valores mínimos de 18ºC em áreas de vegetação. Com base no cálculo do viés médio (VM), o presente estudo mostrou que os dados estimados da temperatura da superfície apresentaram boa correlação de 0,67 com os dados do INMET, já que as temperaturas foram subestimadas e superestimadas com valores mínimos e máximos de -3,83ºC e 2,65ºC em 1994 e 2003. Os resultados obtidos, ainda que em caráter preliminar, indicam a eficiência do Sensoriamento Remoto (SR) por meio da análise das bandas refletivas e termal do satélite Landsat 5 como ferramenta de análise na identificação da dinâmica do uso do solo, mostrando-se eficaz quanto à espacialização dessas anomalias no espaço e no tempo.

The aim of this study was (a) to assess and evaluate the net radiation (Rn) by SEBAL algorithm and (b) to assess the net radiation (Rn) by the landscape's spatial temporal dynamic using ISODATA algorithm, in entire city of Rio de Janeiro. Has been calculated the Rn by using the TM sensor images and orbital platform Landsat 5 and by Penman-Monteith method (FAO 56) with the conventional meteorological station data (EMC). The Rn values obtained with the SEBAL algorithm to the EMC cut area were slightly smaller than those obtained by the Penman-Monteith method (FAO 56), with VM = -36 (Wm-2) and EPE = 84.44 Wm-2. The Rn obtained by SEBAL has a high correlation with the values obtained in the surface. The Rn values obtained with the algorithm for the land use and occupation classes in the city of Rio de Janeiro were similar to those reported by other authors for the same classes.

Este trabalho avaliou a eficiência do algoritmo Máxima Verossimilhança (MAXVER), do município de Quixeramobim, Ceará, Brasil, utilizando imagens do satélite Landsat 8 sensor OLI para o mapeamento do uso e cobertura do solo. Para a aferição como verdade de campo utilizou-se o GPS (GARMIN Etrex LEGEND Cx), amostrando as diferentes classes de uso e cobertura do solo. As classes amostradas em campo foram: área urbana, solo exposto, pastagem, caatinga e água. Os resultados encontrados mostraram que a classificação geral da imagem teve um valor razoável, indicando acurácia global de 57,50%, o que indica uma maior necessidade de coleta de dados de amostras para a área classificada. O índice Kappa, quando observado por classe, apresentou valores baixos para áreas de solo exposto e pastagem (14% e 30%), obtiveram baixíssimos índices Kappa mostrando que a amostragem foi inadequada para classificação da resposta espectral destas feições. As classes área urbana e água (50% e 54%) apresentaram valores medianos de Kappa para suas feições em relação a amostragem para a classificação de sua resposta espectral. No entanto, a classe caatinga foi a única que apresentou valor representativo de acordo com o índice Kappa (77%). Deve-se aumentar a amostragem em campo das feições, já que o Kappa Global foi muito baixo.

The study aimed to assess the growth and decrease in vegetation trend by Enhanced Vegetation Index (EVI2) through the application of statistical tests and Markov's chain in the state of Rio de Janeiro (SRJ). Monthly data from EVI2 were calculated for the vegetations of the State of Rio de Janeiro (SRJ) from 2001 to 2012. Mann-Kendall (MK), Pettitt (P) and Estimator of Curvature Slope Sen (Se) tests assessed EVI2 trend, while the future scenarios were evaluated by Markov chain. Overall, there is an insignificant trend in vegetation growth in 75%, followed by a significant trend of decreasing in 25% of the regions. Pettitt's test showed that there is not significant (NS) abrupt changes, both growth and decreasing vegetation, and significant (S) abrupt changes of decreasing vegetation in the others Government regions. Spatial analysis from EVI2 in the regions Médio Paraíba amd Serrana showed the occurrence of NS abrupt change in the vegetation in November 2007 and 2003. Norte Fluminense and Metropolitana showed a NS vegetation increase in October 2003 and 2005. Noroeste Fluminense and Centro Sul Fluminense revealed an NS and S abrupt change of decreasing vegetation in April 2006. In Costa Verde and Baixadas Litorâneas NS and S abrupt changes in decreasing vegetation were observed in May 2004. Future scenarios showed changes in vegetation trend in SRJ with indication of decreasing. Predictions of changes in future scenarios ranging from 1 to 2 years in constant intervals (3 to 10 years) were observed in all future scenarios analyzed in the SRJ.

Incident solar radiation (Rs) is usually used as an input variable in growth simulation models and yield of agricultural crops, in the design of alternative energy systems, buildings desing, weather, irrigation projects and food preservation, among others. However, in Brazil, there are few studies that evaluated the performance of different models in estimating Rs. Therefore, the aim of the study is to evaluate the Hargreaves-Samani, Thornton-Running and Weiss models to estimate Rs in the municipality of Seropédica, Rio de Janeiro. We used hourly measurements of solar radiation (Rs, KJ m-2) and maximum (tx,°C) and minimum (tn,°C) air temperature obtained from Ecologia Agrícola station (EA), between January/2008 to December/2013. Normality (Shapiro-Wilks and Jarque-Bera) and homogeneity of variance (Bartlett) tests were applied to the data set. The performance of the models was evaluated based on different statistical parameters (r2 RMSE, d, Ïs and Student's t-test). The results indicated the rejection of the variance normality hypothesis of the standardized residuals by Shapiro-Wilks and Jarque-Bera tests. Bartlett's test indicated the presence of heterogeneity of model estimates. Hargreaves-Samani and Thornton-Running models obtained high values forr2 and low values for d. Hargreaves-Samani (coastal) model excelled in relation to other, being more suitable for estimating the Rs in the municipality of Seropédica, Rio de Janeiro.

Os objetivos principais do presente trabalho foram: 1) estimar a temperatura da superfície continental, 2) os índices de vegetação e albedo da superfície e posteriormente 3) comparar a evolução espaço-temporal destas imagens com a climatologia local do Instituto Nacional de Meteorologia (INMET) em Rio Branco, AC. As técnicas de sensoriamento remoto (SR), permitiram uma análise temporal de uso e ocupação do solo, especialmente com vistas a identificar e monitorar as alterações na paisagem. Com base no cálculo do viés médio (VM), o presente estudo mostrou que, em áreas densamente verdes, onde a falta de estações meteorológicas ocorrem, o algoritmo que estimou a temperatura da superfície, pode ser utilizado para o preenchimento de falhas, já que os valores foram ligeiramente subestimados, com valor deste indicador de -0,32ºC para o ano de 1994. Foi verificado também uma superestimativa dos resultados, com valor de viés médio de 0,31ºC para o ano de 1996. Os resultados mostraram um acréscimo de temperatura de faxia média de 1,12ºC de 1990 a 2010. O albedo da superfície aumentou significativamente em Rio Branco, principalmente onde ocorreram as maiores porcentagens da classe “área urbana”. Verificou-se que os valores médios do NDVI, SAVI e IAF apresentaram maiores oscilações, principalmente nos anos de maiores aumento das áreas antropizadas (2005, 2009 e 2010). Os resultados obtidos, ainda que em caráter preliminar, indicam a eficiência do SR por meio da análise da banda termal do satélite Landsat-5 como ferramenta de análise na identificação de ilhas de calor urbanas, mostrando-se eficaz quanto à espacialização dessas anomalias espacial e temporalmente.

Percentage maps of forest cover derived from the annual product MOD44B were compared with the annual deforestation data from PRODES. PRODES data were used to calibrate the MOD44B (sub-pixel-level representation of surface vegetation cover estimates globally) annual images with the aim of evaluating the annual characterization of the deforestation dynamics and forest regeneration in the municipality of Bujari - Acre, Brazil, from 2000 to 2010. The percentage rates from MODIS were divided into forest cover categories (forested and deforested areas) by means of the Mann-Kendall (MK) non-parametric test used in each category. The results were satisfactory when compared with PRODES. The analysis of MOD44B product in the municipality, during the years 2001, 2004 and 2009, shows that there was an increase of the pixel frequency in the "Extremely High" category, which indicates regeneration of the area in the municipality of Bujari. Validations in situ should be done primarily to the regenerate areas.

Este trabalho avaliou o comportamento da floresta e demais classes espectrais do Projeto de Assentamento Dirigido Santa Luzia, utilizando os recursos do Geoprocessamento e Sensoriamento Remoto. O período avaliado estende-se entre o ano de 2005 a2010, e procurouavaliar o comportamento da evolução espacial de áreas como a floresta, pastagens e áreas utilizadas para agricultura, assim como demais benfeitorias realizadas no perímetro do assentamento. Neste sentido, os objetivos gerais deste trabalho foram: caracterizar a contração ou a expansão de classes de floresta, pastagens, regeneração da floresta e áreas alagadas, no PAD Santa Luzia, AC. Os resultados encontrados mostraram um significativo aumento do índice de regeneração da floresta e conversão de áreas de pastagens e cultivos em capoeira, considerando que esta tipologia florestal é essencial para o processo de transição de áreas desflorestadas em sua reestruturaçãoà condição de floresta novamente. São ainda apresentados dados que demonstraram a elevação dos valores referentes a corpos d’água, embora as imagens tenham sido adquiridas em períodos de estiagem (período seco amazônico) na região. Os dados obtidos pelo algoritmo de Mahalanobis, evidenciaram um significativo aumento destes recursos na superfície estudada. Os dados apresentaram o comportamento de leve decréscimo para a floresta durante o período avaliado.

Foram avaliados a dinâmica espaço-temporal do uso e cobertura da terra entre os anos de 1990 e 2010 no município de Seropédica, Região Metropolitana do Rio de Janeiro (RMRJ). Foram utilizadas imagens TM (Thematic Mapper) Landsat 5 e os métodos de classificações supervisionadas baseado nos algoritmos da Mínima Distância (MINIDIST), Máxima Verossimilhança (MAXVER) e distância de Mahalanobis (MAHAL). Os resultados obtidos de 1990 mostraram que a classificação MINIDIST superestimou as classes de áreas de água (5,02%), mata (8,94%), solo exposto (16,05%) e pastagem (59,33%), respectivamente. O MINIDIST em 1990 subestimou a classe área urbana (10,66%) comparado com os demais métodos. As classespastagem (59%), mata (20,68%) e água (2,25%) foram superestimadas pelo MINIDIST, enquanto que para as classes espectrais de solo exposto (0,92%), área urbana (11,54%) e eucalipto (5,81%) ocorreram subestimativa comparado aos métodos MAHAL e MAXVER em 2010. O viés médio mostrou que os valores de área para ambos os classificadores foram superestimados em relação aos dados do projeto SOS Mata Atlântica. Os índices de vegetação mostraram-se compatíveis com a literatura, às exceções foram às discrepâncias na estimativa de área atribuídas à transição de períodos secos e chuvosos que ocorreram antes da passagem do satélite sobre a região. Ressalta-se que todos os classificadores utilizados neste estudo são passíveis de erro, ou seja, os classificadores foram desenvolvidos na tentativa de aperfeiçoarem os trabalhos de interpretação visual em Seropédica.

Foram propostos dois cenários futuros para a Amazônia Ocidental, utilizando-se a saída do Modelo de circulação regional HadRM3 para radiação solar global (Rg), para o Estado do Acre. Os cenários A2 (pessimista) e B2 (otimista) são baseados no relatório do IPCC (Intergovernmental Panel on Climate Change). Foram definidas duas estações distintas para ambos os cenários: a estação seca, de abril a setembro, e a estação chuvosa, de outubro a março. O período de 1961 a 1990, "baselines", e para os cenários A2 e B2, a simulação ocorreu entre 2070 e 2100. A conversão da grade pontual do modelo HadRM3 foi baseada no método de Krigagem Ordinária. Os menores valores de R g abrangem a parte oeste do Estado do Acre, na estação seca, em ambos os cenários. Os valores intermediários de R g são na direção norte-sul, seguidos dos maiores valores de R g, que são na porção leste do Estado; houve um aumento significativo de Rg na estação chuvosa no período de 2080 a 2090, em ambos os cenários adotados no estudo. Com base na estatística descritiva e exploratória dos cenários otimista, pessimista e "baseline" mostrou-se que a forçante radiativa (positivo) tende a aquecer a superfície continental e, ao contrário, situação negativa tende a esfriar, sendo identificado tal quadro na formação do gradiente entre as direções leste-oeste do Estado do Acre, para ambas as estações no período de estudo.

ABSTRACT In Brazil, the remaining areas of Atlantic Forest are intensely fragmented. The connection of forest fragments through ecological corridors is an important step in biodiversity conservation. Certain areas are more resilient, and in those areas, natural forest regeneration, for example, can be encouraged. The aim of this study was to identify areas of greater resilience in order to support the connection of Atlantic Forest fragments with ecological corridors. Forest fragments in the municipality of Paraíba do Sul, in the state of Rio de Janeiro, were mapped using the supervised maximum likelihood classification of an Operational Land Imager (OLI)/Landsat-8 sensor image. Next, we analyzed the influence of terrain attributes (aspect, incident solar radiation, slope, and curvature profile) on natural regeneration. The areas with the greatest potential to achieve natural regeneration and to form ecological corridors were indicated through fuzzy membership functions. Within Paraíba do Sul, 31% of the territory is covered by vegetation in different stages of regeneration. Recordings were made of 1,251 forest fragments in a middle or advanced stage of regeneration. These fragments are usually situated in the southeast, south, and southwest aspects, in areas that receive the least amount of global solar radiation (Wh·m-2) per year, and on slopes with an angle of inclination greater than 20%. The adjustment of fuzzy functions identified 17,327.5 ha with a tendency to recover, and which are therefore strategic areas in the development of ecological corridors.

RESUMOPara avaliar os dados de precipitação pluvial via satélite no estado do Amazonas, compararam-se as estimativas do produto 3B43 do satélite TRMM (2004-2008) com dados de sete Estações Meteorológicas Convencionais (EMC). A comparação foi baseada nos seguintes parâmetros estatísticos: Erro Médio (EM), Raiz do Erro Médio Quadrático (REMQ), coeficiente de correlação linear (r) e índice de concordância de Wilmott (d). As estimativas do TRMM foram similares aos dados de superfície e representaram bem a variabilidade sazonal das chuvas. Os dados apresentaram alta correlação linear (r = 0,83), alto índice de concordância (d = 0,85) e REMQ satisfatório (66,6 mm/mês). Dessa forma, as estimativas de precipitação pluvial do produto 3B43 podem ser utilizadas como uma fonte alternativa de dados de qualidade.

RESUMOEste trabalho teve como objetivo ajustar modelos de regressão entre o índice de área foliar (IAF) de plantios de Eucalyptusgrandis x urophylla e índices de vegetação (IVs) de imagens TM - Landsat 5. O estudo foi realizado em plantios com diferentes idades localizados na porção mineira da bacia hidrográfica do rio Doce, entre os anos de 2008 e 2011. O IAF foi medido em campo, de forma não destrutiva, com o equipamento LAI-2000. Os IVs utilizados foram o Normalized Difference Vegetation Index (NDVI), o Soil Adjusted Vegetation Index (SAVI) e o Simple Ratio (SR). O melhor modelo foi ajustado a partir do NDVI, com coeficiente de determinação de 0,73 e erro quadrático médio da raiz de 0,37 m² m–2(19%). Pode-se concluir que os valores de IAF podem ser estimados pelos modelos de regressão ajustados a partir dos IVs derivados do TM - Landsat.

Este trabalho avaliou o uso e a cobertura da terra, e comparou os dados obtidos com aqueles das Áreas de Preservação Permanente (APPs), para identificar conflitos do uso da terra no município de Seropédica-RJ. Utilizaram-se duas cenas do satélite CBERS2 e a classificação supervisionada com o método da mínima distância. As APPs foram delimitadas com o auxílio de geotecnologias, baseando-se na legislação ambiental (Lei n.º 12.651/2012) (Brasil, 2012). Utilizou-se no mapeamento das APPs um Modelo Digital de Elevação (1:25.000) e, para a rede de drenagem, cartas planialtimétricas (1:10.000). Identificaram-se 40,02 km² de APPs, o que correspondeu a 15,01% do município. A APP do rio Guandu apresentou maior área (7,23%) e lagos urbanos, a menor (0,04%). O município não apresentou APPs de declividade (

RESUMO No presente estudo avaliou-se a dinâmica da vegetação de florestas tropicais no período de 2000 a 2010 em áreas desmatadas, utilizando-se os produtos MOD44B, 3B43 e SRTM. Através deles analisou-se, temporal e espacialmente, a ocorrência de regeneração em áreas de desmatamento mapeadas pelo sistema PRODES (Projeto de Estimativa de Desflorestamento da Amazônia) do INPE (Instituto Nacional de Pesquisas Espaciais). Os resultados encontrados mostraram que há regeneração nas áreas desmatadas e que, ao longo do tempo, a densidade da vegetação tende a aumentar. As áreas regeneradas apareceram majoritariamente em áreas mais baixas, seguindo a tendência do desmatamento. O MOD44B mostrou-se eficiente no estudo temporal e espacial da vegetação, indicando haver regeneração ao longo do tempo. O período de maior precipitação coincidiu com o período em que os pixels de menor densidade migraram para classes de maior densidade, sugerindo uma possível relação entre os índices de precipitação e o crescimento da vegetação.

Dados pluviométricos horários da Estação Meteorológica Automática (EMA) foram preenchidos com dados da normal climatológica do INMET e com os dados do satélite TRMM via produto 3B43. Esses dois conjuntos preencheram as falhas e homogeneizaram os dados do período de 2000-2012, e foram comparados com a ocorrência dos sistemas sinóticos (ZCAS, ZCOU e SF) e com os episódios de El Niño e La Niña, em Seropédica-RJ. A avaliação foi dividida em escalas médias, percentuais sazonais e acumulados anuais. Os dados sinóticos foram obtidos da Climanálise (1996-2012). As características médias mostraram alta variabilidade interanual e intrassazonal dos sistemas sinóticos, seguida da interação dos sistemas de mesoescala e locais. Os meses com maior precipitação (> 120 mm) foram dezembro, janeiro e março, e os meses com menor precipitação (< 60 mm) foram maio, junho, julho e agosto. O verão (42%) e inverno (10%) possuem características bem definidas e distintas em seus padrões de chuva.