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The state of Amapá within the Amazon biome has a high complexity of ecosystems formed by forests, savannas, seasonally flooded vegetation, mangroves, and different land uses. The present research aimed to map the vegetation from the phenological behavior of the Sentinel-1 time series, which has the advantage of not having atmospheric interference and cloud cover. Furthermore, the study compared three different sets of images (vertical–vertical co-polarization (VV) only, vertical–horizontal cross-polarization (VH) only, and both VV and VH) and different classifiers based on deep learning (long short-term memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent Units (GRU), Bidirectional GRU (Bi-GRU)) and machine learning (Random Forest, Extreme Gradient Boosting (XGBoost), k-Nearest Neighbors, Support Vector Machines (SVMs), and Multilayer Perceptron). The time series englobed four years (2017–2020) with a 12-day revisit, totaling 122 images for each VV and VH polarization. The methodology presented the following steps: image pre-processing, temporal filtering using the Savitsky–Golay smoothing method, collection of samples considering 17 classes, classification using different methods and polarization datasets, and accuracy analysis. The combinations of the VV and VH pooled dataset with the Bidirectional Recurrent Neuron Networks methods led to the greatest F1 scores, Bi-GRU (93.53) and Bi-LSTM (93.29), followed by the other deep learning methods, GRU (93.30) and LSTM (93.15). Among machine learning, the two methods with the highest F1-score values were SVM (92.18) and XGBoost (91.98). Therefore, phenological variations based on long Synthetic Aperture Radar (SAR) time series allow the detailed representation of land cover/land use and water dynamics.

Sheep production is present on all continents and has been practiced in Brazil since the colonization. In this study, the multitemporal dynamics of sheep production in Brazil is examined using official government data (Brazilian Institute for Geography and Statistics-IBGE) from 1976 to 2010. Maps of flock growth rates and growth acceleration maps by municipality were elaborated. The Southern states are seen to show a reduction in production mainly due to the wool crisis in the 1970s and 80s. The Northeast is seen to be important for meat production. More recently, centerwest and northern states have shown an increase in growth rates but this is still incipient. The maps of growth, acceleration and midpoint for sheep production showed a noticeable return to an increase in production in the South in recent years. The midpoint of production flow was in the northeast direction, which has stagnated. There was great dynamics in sheep production over the whole Brazilian territory, which affected supply chains due to the expansion of domestic and foreign markets. Areas with higher fluctuations in production are more vulnerable in terms of investment policies.

Movement of livestock production within a country or region has implications for genetics, adaptation, well-being, nutrition, and production logistics, particularly in continental-sized countries, such as Brazil. Cattle production in Brazil from 1977 to 2011 was spatialized, and the annual midpoint of production was calculated. Changes in the relative production and acceleration of production were calculated and spatialized using ARCGIS®. Cluster and canonical discriminant analyses were performed to further highlight differences between regions in terms of cattle production. The mean production point has moved from the Center of Minas Gerais State (in the southeast region) to the North of Goiás State (in the Midwest region). This reflects changes in environmental factors, such as pasture type, temperature and humidity. Acceleration in production in the northern region of Brazil has remained strong over the years. More recently, "traditional" cattle-rearing regions, such as the south and southeast, showed a reduction in growth rates as well as a reduction in herd size or internal migration over the period studied. These maps showed that this movement tends to be gradual, with few regions showing high acceleration or deceleration rates.

The objective of this paper was to evaluate the relationship between NDVI and the patterns of the dominant species in three fragments of seasonally deciduous forest (SDF) in the Parana Valley in Goias State, Brazil. Landsat 7 ETM+ images from the year 2001 were used. The study showed a relation between NDVI and floristic patterns during the dry and rainy seasons for the three fragments studied. Exclusive species showed greater influence in the spectral response measured by NDVI than did the total species. The results confirmed the three fragments as SDF showing that even within the same physiognomy there were small phenological variations.

The objective of this paper was to evaluate the relationship between NDVI and the patterns of the dominant species in three fragments of seasonally deciduous forest (SDF) in the Parana Valley in Goias State, Brazil. Landsat 7 ETM+ images from the year 2001 were used. The study showed a relation between NDVI and floristic patterns during the dry and rainy seasons for the three fragments studied. Exclusive species showed greater influence in the spectral response measured by NDVI than did the total species. The results confirmed the three fragments as SDF showing that even within the samephysiognomy there were small phenological variations.

The understanding of spatial dependence and distribution of agricultural production factors is a key issue for the territorial planning and regional development. This study evaluates the spatial-temporal dynamics of bean crops in Brazil over the period 1990–2013. Common bean (Phaseolus vulgaris L.) is one of the staple foods for the Brazilian population, with nationwide production and cultivated mostly by family farmers. The analyzed variables of this crop included harvested area, produced quantity, and average crop yield. We investigated spatial autocorrelations using the Global and Local Moran Index. The global spatial autocorrelation statistics demonstrated a general spatial dependence of bean production over Brazil, while the local spatial autocorrelation statistics detect statistically significant zones of high and low bean-production attributes. Maps of growth and acceleration rate of the variables were constructed, showing the areas that increased, decreased, or stagnated during the time series. The results showed a considerable reduction of the bean harvested area, but there were significant increases in produced quantity and average crop yield. Results showed distinct and significant patterns of bean-production variables in Brazilian territory over the different years. Regional differences and peculiarities are evident, emphasizing the need for directing investments to agricultural research and public policy.

A localização de todos os rebanhos de cabras de raça pura no Brasil foi espacializada de acordo com os controles climáticos (Indice de Temmperatura e Umidade, precipitação, topografia, umidade relativa do ar) e controles ambientais (altitude, tipo de pastagem). Os dados foram analisados através de uma análise de regressão, análise da variância e análise de cluster. Matrizes de distância foram construídas de acordo com a longitude/ latitude e os controles ambientais foram correlacionados por meio do teste de Mantel. O ponto médio para a maioria das raças foi encontrado no estado da Bahia, mas no estado de Pernambuco encontraram-se as raças localmente adaptadas. A Anglonubiana foi a raça comercial com o ponto médio mais ao norte, enquanto as raças Toggenburg, Saanen e Alpina tiveram o ponto médio de produção mais ao sul do país. Houve pouca diferença entre os controles ambientais para a raça localamente adaptada e comercial, mas raças dupla aptidão encontraram-se nas regiões com menor precipitação e o Indice de Vegetação Diferença Normalizado (Normalized Difference Vegetation Index), mas com as temperaturas mais elevadas e o Indice de Desenvolvimento Humano. As raças comerciais são mais difundidas no Brasil do que raças locais, sendo que as últimas ocorrem um maior risco de extinção devido a doenças, seca ou cruzamento com outras raças.

The present study aims to evaluate the multitemporal dynamics of sheep production in Brazil, considering the Federal Government's official data from 1976 to 2010. Principal Component Analysis (PCA) and Self-Organizing Maps (SOFM) were used. PCA reduced data redundancy and the colour composition of the first three principal components evidenced temporal patterns. In the SOFM classification, a type of Artificial Neural Network (ANN) with non-supervised training, different dimensions of the Kohonen map were tested. The results obtained by the two methods are complementary, evidencing the development of sheep production in the country. The southern and northeast maintained the tradition of sheep production over the analyzed period. The municipalities in the Midwest showed production growth. The techniques used were effective in multitemporal analysis, providing a greater understanding of the dynamics of sheep production in Brazil and providing subsidies for the development of appropriate public policies for its expansion.

Atualmente, as áreas de Floresta Estacional Decidual (FED) na região do Vão do Paranã, Goiás, estão bastante fragmentadas principalmente em função das atividades antrópicas relacionadas com as fazendas de gado e coleta seletiva de madeira. O objetivo do presente trabalho é identificar a possibilidade de discriminar FED no Vão do Paranã por meio da análise espectral multitemporal de imagens Landsat. Imagens de abril a julho de 2001 (desde o final da estação chuvosa ao início da estação seca) foram convertidas em reflectância na superfície terrestre e somadas uma a uma (abril + maio, abril + maio + junho e abril + maio + junho + julho). Os resultados mostraram que houve melhora na identificação da FED na medida em que um maior número de imagens multitemporais foram consideradas. O mapa de distribuição da FED indicou um total de aproximadamente 190.000 ha distribuídos essencialmente na região centro-norte da área de estudo. Conclui-se que a técnica de reflectância acumulada considerada no presente estudo, é uma alternativa promissora para a melhor discriminação das áreas de FED.

O presente trabalho apresenta uma análise dos condicionantes ambientais do município de Jataí – GO, a partir de seus compartimentos morfopedológicos, como subsídio ao planejamento do uso do solo. A metodologia contou com quatro etapas complementares: definição dos compart imentos morfopedológicos; avaliação da suscetibilidade à erosão Linear; análise da capacidade de uso das terras; e avaliação dos conflitos existentes quanto ao uso atual do solo em relação à referida capacidade de uso. O trabalho mostrou que não existem conflitos no uso atual do solo considerados altos no município.

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