Unlike satellite images, which are typically acquired and processed in near-real-time, global land cover products have historically been produced on an annual basis, often with substantial lag times between image processing and dataset release. We developed a new automated approach for globally consistent, high resolution, near real-time (NRT) land use land cover (LULC) classification leveraging deep learning on 10 m Sentinel-2 imagery. We utilize a highly scalable cloud-based system to apply this approach and provide an open, continuous feed of LULC predictions in parallel with Sentinel-2 acquisitions. This first-of-its-kind NRT product, which we collectively refer to as Dynamic World, accommodates a variety of user needs ranging from extremely up-to-date LULC data to custom global composites representing user-specified date ranges. Furthermore, the continuous nature of the product’s outputs enables refinement, extension, and even redefinition of the LULC classification. In combination, these unique attributes enable unprecedented flexibility for a diverse community of users across a variety of disciplines.

A humid tropical forest disturbance alert using Sentinel-1 radar data is presented for the Congo Basin. Radar satellite signals can penetrate through clouds, allowing Sentinel-1 to provide gap-free observations for the tropics consistently every 6–12 days at 10 m spatial scale. In the densely cloud covered Congo Basin, this represents a major advantage for the rapid detection of small-scale forest disturbances such as subsistence agriculture and selective logging. Alerts were detected with latest available Sentinel-1 images and results are presented from January 2019 to July 2020. We mapped 4 million disturbance events during this period, totalling 1.4 million ha with nearly 80% of events smaller than 0.5 ha. Monthly distribution of alert totals varied widely across the Congo Basin countries and can be linked to regional differences in wet and dry season cycles, with more forest disturbances in the dry season. Results indicated high user’s and producer’s accuracies and the rapid confirmation of alerts within a few weeks. Our disturbance alerts provide confident detection of events larger than or equal to 0.2 ha but do not include smaller events, which suggests that disturbance rates in the Congo Basin are even higher than presented in this study. The new alert product can help to better study the forest dynamics in the Congo Basin with improved spatial and temporal detail and near real-time detections, and highlights the value of dense Sentinel-1 time series data for large-area tropical forest monitoring. The research contributes to the Global Forest Watch initiative in providing timely and accurate information to support a wide range of stakeholders in sustainable forest management and law enforcement. The alerts are available via the https://www.globalforestwatch.org and http://radd-alert.wur.nl.

While agriculture is generally recognized to be a major driver of deforestation, few studies have attempted to estimate the role that particular commodities play in global deforestation, and even fewer have been spatially explicit. In this analysis, we estimate the extent to which seven commodities—oil palm, soy, cattle, plantation wood fiber, cocoa, coffee, and plantation rubber—are replacing forests, and map their impacts using the best available spatially explicit data. We report results for these seven commodities globally at the second administrative level (e.g., county, municipality, or other administrative subdivision, depending on the country), though the methods are flexible and could be applied to other commodities and geographic scales of analysis. To identify the specific commodities that have replaced forested land, we analyzed the overlap of current commodity extent with global annual tree cover loss from 2001 to 2018. We used recent, detailed crop and pasture maps for relevant regions and commodities where available, and supplemented them with coarser resolution global data where needed.

Near–real-time monitoring and response are possible

Tropical deforestation continues at alarming rates with profound impacts on ecosystems, climate, and livelihoods, prompting renewed commitments to halt its continuation. Although it is well established that agriculture is a dominant driver of deforestation, rates and mechanisms remain disputed and often lack a clear evidence base. We synthesize the best available pantropical evidence to provide clarity on how agriculture drives deforestation. Although most (90 to 99%) deforestation across the tropics 2011 to 2015 was driven by agriculture, only 45 to 65% of deforested land became productive agriculture within a few years. Therefore, ending deforestation likely requires combining measures to create deforestation-free supply chains with landscape governance interventions. We highlight key remaining evidence gaps including deforestation trends, commodity-specific land-use dynamics, and data from tropical dry forests and forests across Africa.

Many researchers have tested whether protected areas save tropical forest, but generally focus on parks and reserves, management units that have internationally recognized standing and clear objectives. Buffer zones have received considerably less attention because of their ambiguous rules and often informal status. Although buffer zones are frequently dismissed as ineffective, they warrant attention given the need for landscape-level approaches to conservation and their prevalence around the world-in Peru, buffer zones cover >10 % of the country. This study examines the effectiveness of buffer zones in the Peruvian Amazon to (a) prevent deforestation and (b) limit the extent of mining concessions. We employ covariate matching to determine the impact of 13 buffer zones on deforestation and mining concessions from 2007 to 2012. Despite variation between sites, these 13 buffer zones have prevented ~320 km(2) of forest loss within their borders during the study period and ~1739 km(2) of mining concessions, an outcome associated with the special approval process for granting formal concessions in these areas. However, a closer look at the buffer zone around the Tambopata National Reserve reveals the difficulties of controlling illegal and informal activities. According to interviews with NGO employees, government officials, and community leaders, enforcement of conservation is limited by uncertain institutional responsibilities, inadequate budgets, and corruption, although formal and community-based efforts to block illicit mining are on the rise. Landscape-level conservation not only requires clear legal protocol for addressing large-scale, formal extractive activities, but there must also be strategies and coordination to combat illegal activities.

Limiting global warming to 1.5°C requires far-reaching transformations across power generation, buildings, industry, transport, land use, coastal zone management, and agriculture, as well as the immediate scale-up of technological carbon removal and climate finance. This report translates these transitions into 40 targets for 2030 and 2050, with measurable indicators. Transformations, particularly those driven by new technology adoption, often unfold slowly before accelerating after crossing a tipping point. Nearly a quarter of indicators assessed new technology adoption, with some already growing exponentially. This report considers such nonlinear change in its methodology. The transitions required to avoid the worst climate impacts are not happening fast enough. Of the 40 indicators assessed, none are on track to reach 2030 targets. Change is heading in the right direction at a promising but insufficient speed for 8 and in the right direction but well below the required pace for 17. Progress has stagnated for 3, while change for another 3 is heading in the wrong direction entirely. Data are insufficient to evaluate the remaining 9. This report also identifies underlying conditions that enable change—supportive policies, innovations, strong institutions, leadership, and shifts in social norms. Finance for climate action, for example, must increase nearly 13-fold to meet the estimated need in 2030.

Here we present Tambopata: Who Owns Paradise?, a map-centric, multimedia website created to enrich an educational role playing exercise about biodiversity, conservation, and development in the Amazon (www.geography.wisc.edu/tambopata). The exercise assigns students a character from the Tambopata region of the Peruvian Amazon, and asks them to evaluate four proposed zoning plans from their assigned perspective. Using principles of web cartography, we designed the four proposal maps to communicate complex information and allow for increased exploration. Compared to the previously used static maps, the website increases opportunities for student engagement with the material, incorporates multimedia, and clarifies spatial relationships and land use patterns. The website is available publicly and can be integrated freely into other university and high school courses.