Balancing food production with climate change mitigation and biodiversity conservation in the Brazilian Amazon.

Climate change mitigation and biodiversity conservation are two major environmental actions that need to be effectively performed this century, alongside ensuring food supply for a growing global human population. These three issues are highly interlinked through land management systems. Thus, major global food production regions located in biodiversity hotpots and with potential for carbon sequestration face trade-offs between these valuable land-based ecosystem services.

Socioeconomic and environmental effects of soybean production in metacoupled systems.

Human-environment interactions within and across borders are now more influential than ever, posing unprecedented sustainability challenges. The framework of metacoupling (interactions within and across adjacent and distant coupled human-environment systems) provides a useful tool to evaluate them at diverse temporal and spatial scales. While most metacoupling studies have so far addressed the impacts of distant interactions (telecouplings), few have addressed the complementary and interdependent effects of the interactions within coupled systems (intracouplings) and between adjacent systems (pericouplings).

Transport cost to port though Brazilian federal roads network: Dataset for years 2000, 2005, 2010 and 2017.

Transport costs can play a significant role in agricultural exports and businesses profitability. It can also influence farmers' decisions regarding cropland expansion, intensification or land abandonment. Thus, transport is useful to take into account when modeling and evaluating land use and cover change related to agriculture production.

Land use change emission scenarios: anticipating a forest transition process in the Brazilian Amazon.

Following an intense occupation process that was initiated in the 1960s, deforestation rates in the Brazilian Amazon have decreased significantly since 2004, stabilizing around 6000 km(2) yr(-1) in the last 5 years. A convergence of conditions contributed to this, including the creation of protected areas, the use of effective monitoring systems, and credit restriction mechanisms. Nevertheless, other threats remain, including the rapidly expanding global markets for agricultural commodities, large-scale transportation and energy infrastructure projects, and weak institutions.

A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network.

Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede Amazônia Sustentável, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions.

Land use/cover classification in the Brazilian Amazon using satellite images.

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade.

Integration of Landsat TM and SPOT HRG Images for Vegetation Change Detection in the Brazilian Amazon.

Traditional change detection approaches have been proven to be difficult in detecting vegetation changes in the moist tropical regions with multitemporal images. This paper explores the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data for vegetation change detection in the Brazilian Amazon. A principal component analysis was used to integrate TM and HRG panchromatic data.

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon.

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps.