The potential of optical remote sensing data to identify, map and monitor croplands is well recognized. However, clouds strongly limit the usefulness of optical imagery for these applications. This paper aims at assessing cloud cover conditions over four states in the tropical and sub-tropical Center-South region of Brazil to guide the development of an appropriate agricultural monitoring system based on Landsat-like imagery. Cloudiness was assessed during overlapping four months periods to match the typical length of crop cycles in the study area. The percentage of clear sky occurrence was computed from the 1 km resolution MODIS Cloud Mask product (MOD35) considering 14 years of data between July 2000 and June 2014. Results showed high seasonality of cloud occurrence within the crop year with strong variations across the study area. The maximum seasonality was observed for the two states in the northern part of the study area (i.e., the ones closer to the Equator line), which also presented the lowest averaged values (15%) of clear sky occurrence during the main (summer) cropping period (November to February). In these locations, optical data faces severe constraints for mapping summer crops. On the other hand, relatively favorable conditions were found in the southern part of the study region. In the South, clear sky values of around 45% were found and no significant clear sky seasonality was observed. Results underpin the challenges to implement an operational crop monitoring system based solely on optical remote sensing imagery in tropical and sub-tropical regions, in particular if short-cycle crops have to be monitored during the cloudy summer months. To cope with cloudiness issues, we recommend the use of new systems with higher repetition rates such as Sentinel-2. For local studies, Unmanned Aircraft Vehicles (UAVs) might be used to augment the observing capability. Multi-sensor approaches combining optical and microwave data can be another option. In cases where wall-to-wall maps are not mandatory, statistical sampling approaches might also be a suitable alternative for obtaining useful crop area information.

The last few decades have been marked by important changes in the Brazilian agriculture, especially with respect to crop-management practices. This study aimed to analyze the dynamics of cropping systems in a typical agricultural river basin in the state of Mato Grosso. Landsat satellite images and time series of Moderate Resolution Imaging Spectroradiometer vegetation index profiles were analyzed from 2000 to 2010. First, we assessed the horizontal expansion that occurred in the agricultural areas. Subsequently, using the product MOD13Q1, some metrics were established to identify the vertical intensification of soil use (single- or double-cropping systems). Results showed stagnation in the expansion of new deforested areas for agriculture in the 2003/2004 growing season, with simultaneous vertical intensification of agriculture. The adoption of the double-cropping system (e.g., soybean/corn and soybean/cotton) expanded by 266% during the studied period and reached 56% of the croplands in the 2009/2010 growing season.

O sensoriamento remoto e o geoprocessamento são geotecnologias importantes no apoio ao levantamento de dados da agricultura, permitindo estudos e o entendimento das relações ambientais em que uma determinada cultura está inserida. Neste trabalho,objetivou-se, relacionar as variáveis físicas, como, altimetria, declividade e tipo de solo com o agrossistema cafeeiro existente no município de Umuarama-PR pelo uso de geotecnologias. Foi utilizada a imagem do satélite LANDSAT 5/TM (Thematic Mapper) com data de passagem em 02/07/2007 e o software SPRING 4.3.3. As bandas 3, 4 e 5 do sensor TM foram restauradas, resultando em imagens de 15 m de resolução espacial e, posteriormente, constituindo a composição colorida RGB, na sequência TM4, TM5, TM3, a qual foi empregada na identificação das lavouras cafeeiras por meio de interpretação visual. Para o estudo do relevo, foram utilizados dados da missão SRTM, os quais possibilitaram o conhecimento da altimetria e declividade da região. A imagem do sensor TM possibilitou a execução da classificação visual e consequente identificação das lavouras cafeeiras com alta precisão. Quanto ao relevo, verificou-se que aproximadamente 99% das lavouras cafeeiras estão localizadas entre 380 e 480 metros de altitude e que 90% destas estão situadas em declividades de até 8% de inclinação. Em relação aos solos, observou-se que 89% dos cafeeiros são cultivados sobre Latossolo Vermelho distrófico, de textura arenosa.