For agronomic, environmental, and economic reasons, the need for spatialized information about agricultural practices is expected to rapidly increase. In this context, we reviewed the literature on remote sensing for mapping cropping practices. The reviewed studies were grouped into three categories of practices: crop succession (crop rotation and fallowing), cropping pattern (single tree crop planting pattern, sequential cropping, and intercropping/agroforestry), and cropping techniques (irrigation, soil tillage, harvest and post-harvest practices, crop varieties, and agro-ecological infrastructures). We observed that the majority of the studies were exploratory investigations, tested on a local scale with a high dependence on ground data, and used only one type of remote sensing sensor. Furthermore, to be correctly implemented, most of the methods relied heavily on local knowledge on the management practices, the environment, and the biological material. These limitations point to future research directions, such as the use of land stratification, multi-sensor data combination, and expert knowledge-driven methods. Finally, the new spatial technologies, and particularly the Sentinel constellation, are expected to improve the monitoring of cropping practices in the challenging context of food security and better management of agro-environmental issues.

Assessing the impact/adaptation of human activities on/to climate change is a key issue, especially in the tropics that concentrate major anthropogenic dynamics such as deforestation and nearly two-thirds of the planetary rainfall. However, this task is often made tough because human activities such as agricultural dynamics are usually analysed at local or regional scale whereas climate related studies are led at large to global scales due to a lack of reliable data, especially in the tropics. In this article we argue that the increased spatial resolution of remote sensing-based rainfall estimates enables assessing the spatiotemporal variability of rainfall regimes at regional and local scales, thus allowing fine analysis of the interactions with human activities. We processed Tropical Rainfall Measuring Mission (TRMM) 3B42 daily rainfall estimates over the state of Mato Grosso (southern Brazilian Amazon) for the 1998–2012 study period in order to compute rainfall metrics such as annual rainfall and duration, onset and end dates of the rainy season based on the Anomalous Accumulation methodology (at a 0.25° spatial resolution). We then crossed these metrics with agricultural maps (produced at a 250 m spatial resolution) and proved that the adoption of intensive agricultural practices such as double cropping systems is partly the result of a strategy to adapt practices to local climatic conditions. Finally, we discuss how such results raise important issues regarding the sustainability of the agricultural development model in the Southern Amazon.

International audienceHighlights • We emphasize the end of the boom-and-bust development pattern in the Brazilian Amazon. • Deforestation and socioeconomic development follow an inverted U-shape relationship. • Household incomes are greater in stabilized areas than in areas undergoing deforestation. • Environmental governance efforts fostered the emergence of EKC. Abstract Socioeconomic development in the Brazilian Amazon is currently reaching national averages although deforestation activity has been declining for a decade. As a consequence, recent studies rejected the widely agreed boom-and-bust development hypothesis that deforestation first generates an economic boom, which is then followed by a collapse as forest resources are depleted. Here, we confirm these studies that there is no boom-bust cycle and suggest that a new pattern of relationship between deforestation and socioeconomic development has emerged following an environmental Kuznets curve (EKC). In this scenario, environmental degradation increases in the early stages of economic development and decreases in later stages as the economy develops and wellbeing increases. To validate this assumption, we conducted the first sub-municipal analysis of socioeconomic development and deforestation in the Brazilian Amazon for the 2000–2010 period. Our results confirm the emergence of an EKC relationship with a turning point beyond which socioeconomic growth does not appear anymore to be a driver of deforestation. We also emphasize that areas subjected to active deforestation in 2010 present lower socio-Author manuscript version economic indicators than stabilized areas, pointing to the precarious socioeconomic situation of areas still undergoing active deforestation. We put these results in perspective by considering Brazilian efforts to ensure a transition in environmental governance with the objective of promoting land use sustainability through control of deforestation at the same time as supporting socioeconomic development