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Some models have been developed using agrometeorological and remote sensing data to estimate agriculture production. However, it is expected that the use of SAR images can improve their performance. The main objective of this study was to estimate the sugarcane production using a multiple linear regression model which considers agronomic data and ALOS/PALSAR images obtained from 2007/08, 2008/09 and 2009/10 cropping seasons. The performance of models was evaluated by coefficient of determination, t-test, Willmott agreement index (d), random error and standard error. The model was able to explain 79%, 12% and 74% of the variation in the observed productions of the 2007/08, 2008/09 and 2009/10 cropping seasons, respectively. Performance of the model for the 2008/09 cropping season was poor because of the occurrence of a long period of drought in that season. When the three seasons were considered all together, the model explained 66% of the variation. Results showed that SAR-based yield prediction models can contribute and assist sugar mill technicians to improve such estimates.

The objective of this work was to develop and validate a mathematical model to estimate the duration of cotton (Gossypium hirsutum L. r. latifolium hutch) cycle in the State of Goiás, Brazil, by applying the method of growing degree-days (GD), and considering, simultaneously, its time-space variation. The model was developed as a linear combination of elevation, latitude, longitude, and Fourier series of time variation. The model parameters were adjusted by using multiple-linear regression to the observed GD accumulated with air temperature in the range of 15°C to 40°C. The minimum and maximum temperature records used to calculate the GD were obtained from 21 meteorological stations, considering data varying from 8 to 20 years of observation. The coefficient of determination, resulting from the comparison between the estimated and calculated GD along the year was 0.84. Model validation was done by comparing estimated and measured crop cycle in the period from cotton germination to the stage when 90 percent of bolls were opened in commercial crop fields. Comparative results showed that the model performed very well, as indicated by the Pearson correlation coefficient of 0.90 and Willmott agreement index of 0.94, resulting in a performance index of 0.85.O objetivo deste trabalho foi desenvolver e validar um modelo matemático para estimar a duração do ciclo do algodoeiro (Gossypium hirsutum L. r. latifolium hutch) no Estado de Goiás, aplicando o método de graus-dia (GD) e considerando sua variação espaçotemporal. O modelo foi desenvolvido por meio de combinação linear entre altitude, latitude, longitude e a variação temporal, representada pela série trigonométrica incompleta de Fourier. Os parâmetros do modelo foram ajustados, por meio de regressão linear múltipla, aos dados de GD para o algodoeiro, acumulados entre 15°C e 40°C. Os dados utilizados de temperaturas máxima e mínima foram obtidos de séries históricas de 21 estações meteorológicas, com períodos de observações variando entre 8 e 24 anos. A validação do modelo foi feita comparando-se a duração da fase entre a emergência e 90% de capulhos abertos de cultivares de algodoeiros plantados em lavouras comerciais. O coeficiente de determinação resultante do ajuste do modelo aos dados observados foi de 0,84. Os resultados dessa comparação mostraram que o modelo proposto teve um desempenho muito bom, conforme indicado pelo coeficiente de correlação de Pearson de 0,90 e o índice de concordância de Willmott de 0,94, que resultaram em um índice de desempenho de 0,85.

O aumento da demanda de água para a irrigação tem sido objeto de constante preocupação dos órgãos de gestão dos recursos hídricos e da população do Distrito Federal. Os objetivos deste trabalho foram determinar a variação da área irrigada por pivôs-centrais no Distrito Federal entre os anos de 1992 e 2002, estimar a demanda hídrica desses sistemas, bem como verificar sua importância em relação ao consumo humano. Utilizando imagens de satélite e ferramentas de geoprocessamento, foram determinadas as áreas irrigadas por pivô-central. O consumo de água dessas áreas irrigadas foi estimado com base em dados da literatura referentes às principais culturas semeadas na região. Entre 1992 e 2002, o número de pivôs-centrais no Distrito Federal passou de 55 para 104, a área irrigada de 3.894 ha para 6.823 ha e o consumo, de 23,36 para 40,94 milhões de m³ ano-1. O consumo de água para irrigação por pivô-central no Distrito Federal é, ainda, menos representativo do que o consumo de água para o abastecimento humano; entretanto, a demanda para a irrigação tem crescido de forma mais acelerada, indicando tendência de alteração desse quadro.The increase in the water demand for irrigation is a matter of concern of water resources management institutions and of the population from the Distrito Federal in Brazil. The objectives of this work were to determine the variation of the irrigated area by center pivot in the Brazilian Distrito Federal in the period between 1992 and 2002, in order to estimate the water demand by these systems of irrigation, as well as to verify its importance in relation to human consumption. Using satellite images and GIS tools, the center pivot irrigated areas were determined and the water consumption by the main irrigated crops in this region was estimated using reference data obtained from the literature. In the period between 1992 and 2002, the number of center pivots in the Distrito Federal increased from 55 to 104 and the corresponding irrigated area changed from 3.894 to 6.823 ha; consequently, the consumption of water increased from 23.36 to 40.94 million m³ year-1. Although the demand of water for irrigation by center pivot in the Federal District is less representative than by human water consumption, the demand for irrigation has been growing in a higher rate, indicating a significant change in this trend.

Este artigo se propõe a apresentar exemplos de questões científicas que puderam ser respondidas no contexto do Projeto LBA (Large Sale Biosphere-Atmosphere Experiment in Amazonia) graças à contribuição de informações derivadas de sensoriamento remoto. Os métodos de sensoriamento remoto permitem integrar informações sobre os vários processos físicos e biológicos em diferentes escalas de tempo e espaço. Nesse artigo, são enfatizados aqueles avanços de conhecimento que jamais seriam alcançados sem a concorrência da informação derivada de sensoriamento.This paper aims to assess the contribution of remote sensing technology in addressing key questions raised by the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). The answers to these questions foster the knowledge on the climatic, biogechemical and hydrologic functioning of the Amazon, as well as on the impact of human activities at regional and global scales. Remote sensing methods allow integrating information on several processes at different temporal and spatial scales. By doing so, it is possible to perceive hidden relations among processes and structures, enhancing their teleconnections. Key advances in the remote sensing science are summarized in this article, which is particularly focused on information that would not be possible to be retrieved without the concurrence of this technology.