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Humid tropical forests provide numerous global ecosystem services, but are under continuing threat of clearing from economic drivers. Here, we report primary humid tropical forest extent for the year 2001, and primary forest loss and distance to loss from 2002-2014 for the largest rainforest countries of Brazil, Democratic Republic of the Congo (DRC), and Indonesia. Brazil's total area of primary forest loss is more than twice that of Indonesia and five times that of DRC. Despite unprecedented success in slowing deforestation along its forest frontier, Brazil's most remote forests are increasingly nearer to loss, as extractive activities such as logging and mining intrude upon previously intact forests. In absolute terms, DRC has the lowest area of primary forest loss; however, its forests are increasingly encroached upon as smallholder agriculturalists move into remaining forests, often to escape conflict and insecurity. The decrease in DRC forests' distance to loss as a function of area of forest loss was five times that of Brazil or Indonesia. In 2014, Indonesia had the least area of remaining primary forest. Despite an announced moratorium on concession licenses in 2011, Indonesia exhibited a rate of primary forest loss twice that of DRC and triple that of Brazil by the end of the study period. Forest loss dynamics in Indonesia range from industrial-scale clearing of coastal peatlands to logging of interior montane rainforests. While results illustrate considerable variation in forest loss dynamics between the three countries, the dominant narrative is of ongoing exploitation of primary humid tropical forests.

Tropical deforestation accounts for almost one-fifth of greenhouse gas emissions and threatens the world's most diverse ecosystems. Much of this deforestation is driven by illegal logging. We use novel satellite data that tracks annual deforestation across eight years of Indonesian institutional change to examine how local officials' incentives affect deforestation. Increases in the number of political jurisdictions lead to increased deforestation and lower timber prices, consistent with Cournot competition between jurisdictions. Illegal logging and local oil and gas rents are short-run substitutes, but this effect disappears over time with political turnover. The results illustrate how local officials' incentives affect deforestation and show how standard economic theories can explain illegal behavior.

Land change is a cause and consequence of global environmental change 1 , 2 . Changes in land use and land cover considerably alter the Earth’s energy balance and biogeochemical cycles, which contributes to climate change and—in turn—affects land surface properties and the provision of ecosystem services 1 – 4 . However, quantification of global land change is lacking. Here we analyse 35 years’ worth of satellite data and provide a comprehensive record of global land-change dynamics during the period 1982–2016. We show that—contrary to the prevailing view that forest area has declined globally 5 —tree cover has increased by 2.24 million km 2 (+7.1% relative to the 1982 level). This overall net gain is the result of a net loss in the tropics being outweighed by a net gain in the extratropics. Global bare ground cover has decreased by 1.16 million km 2 (−3.1%), most notably in agricultural regions in Asia. Of all land changes, 60% are associated with direct human activities and 40% with indirect drivers such as climate change. Land-use change exhibits regional dominance, including tropical deforestation and agricultural expansion, temperate reforestation or afforestation, cropland intensification and urbanization. Consistently across all climate domains, montane systems have gained tree cover and many arid and semi-arid ecosystems have lost vegetation cover. The mapped land changes and the driver attributions reflect a human-dominated Earth system. The dataset we developed may be used to improve the modelling of land-use changes, biogeochemical cycles and vegetation–climate interactions to advance our understanding of global environmental change 1 – 4 , 6 . Satellite data for the period 1982–2016 reveal changes in land use and land cover at global and regional scales that reflect patterns of land change indicative of a human-dominated Earth system.

Extensive clearing of Indonesian primary forests results in increased greenhouse gas emissions and biodiversity loss. However, there is no consensus on the areal extent and temporal trends of primary forest clearing in Indonesia. Here we report a spatially and temporally explicit quantification of Indonesian primary forest loss, which totalled over 6.02 Mha from 2000 to 2012 and increased on average by 47,600 ha per year. By 2012, annual primary forest loss in Indonesia was estimated to be higher than in Brazil (0.84 Mha and 0.46 Mha, respectively). Proportional loss of primary forests in wetland landforms increased and almost all clearing of primary forests occurred within degraded types, meaning logging preceded conversion processes. Loss within official forest land uses that restrict or prohibit clearing totalled 40% of all loss within national forest land. The increasing loss of Indonesian primary forests has significant implications for climate change mitigation and biodiversity conservation efforts. Deforestation affects climate, biodiversity and other ecosystem services. This study quantifies Indonesia’s increasing rate of primary forest loss, which runs counter to the declining rates of loss in Brazil. The results highlight the value of thematically consistent and spatially and temporally explicit information in tracking forest change.

The conversion of natural land cover into human-dominated land use systems has significant impacts on the environment. Global mapping and monitoring of human-dominated land use extent via satellites provides an empirical basis for assessing land use pressures. Here, we present a novel 2019 global land cover, land use, and ecozone map derived from Landsat satellite imagery and topographical data using derived image feature spaces and algorithms suited per theme. From the map, we estimate the spatial extent and dispersion of land use disaggregated by climate domain and ecozone, where dispersion is the mean distance of land use to all land within a subregion. We find that percent of area under land use and distance to land use follow a power law that depicts an increasingly random spatial distribution of land use as it extends across lands of comparable development potential. For highly developed climate/ecozones, such as temperate and sub-tropical terra firma vegetation on low slopes, area under land use is contiguous and remnant natural land cover have low areal extent and high fragmentation. The tropics generally have the greatest potential for land use expansion, particularly in South America. An exception is Asian humid tropical terra firma vegetated lowland, which has land use intensities comparable to that of temperate breadbaskets such as the United States’ corn belt. Wetland extent is inversely proportional to land use extent within climate domains, indicating historical wetland loss for temperate, sub-tropical, and dry tropical biomes. Results highlight the need for planning efforts to preserve natural systems and associated ecosystem services. The demonstrated methods will be implemented operationally in quantifying global land change, enabling a monitoring framework for systematic assessments of the appropriation and restoration of natural land cover.

Managing forests for climate change mitigation requires action by diverse stakeholders undertaking different activities with overlapping objectives and spatial impacts. To date, several forest carbon monitoring systems have been developed for different regions using various data, methods and assumptions, making it difficult to evaluate mitigation performance consistently across scales. Here, we integrate ground and Earth observation data to map annual forest-related greenhouse gas emissions and removals globally at a spatial resolution of 30 m over the years 2001–2019. We estimate that global forests were a net carbon sink of −7.6 ± 49 GtCO2e yr−1, reflecting a balance between gross carbon removals (−15.6 ± 49 GtCO2e yr−1) and gross emissions from deforestation and other disturbances (8.1 ± 2.5 GtCO2e yr−1). The geospatial monitoring framework introduced here supports climate policy development by promoting alignment and transparency in setting priorities and tracking collective progress towards forest-specific climate mitigation goals with both local detail and global consistency.Forest management for climate mitigation plans requires accurate data on carbon fluxes to monitor policy impacts. Between 2001 and 2019, forests were a net sink of carbon globally, although emissions from disturbances highlight the need to reduce deforestation in tropical countries.

A globally consistent methodology using satellite imagery was implemented to quantify gross forest cover loss (GFCL) from 2000 to 2005 and to compare GFCL among biomes, continents, and countries. GFCL is defined as the area of forest cover removed because of any disturbance, including both natural and human-induced causes. GFCL was estimated to be 1,011,000 km² from 2000 to 2005, representing 3.1% (0.6% per year) of the year 2000 estimated total forest area of 32,688,000 km². The boreal biome experienced the largest area of GFCL, followed by the humid tropical, dry tropical, and temperate biomes. GFCL expressed as the proportion of year 2000 forest cover was highest in the boreal biome and lowest in the humid tropics. Among continents, North America had the largest total area and largest proportion of year 2000 GFCL. At national scales, Brazil experienced the largest area of GFCL over the study period, 165,000 km², followed by Canada at 160,000 km². Of the countries with >1,000,000 km² of forest cover, the United States exhibited the greatest proportional GFCL and the Democratic Republic of Congo the least. Our results illustrate a pervasive global GFCL dynamic. However, GFCL represents only one component of net change, and the processes driving GFCL and rates of recovery from GFCL differ regionally. For example, the majority of estimated GFCL for the boreal biome is due to a naturally induced fire dynamic. To fully characterize global forest change dynamics, remote sensing efforts must extend beyond estimating GFCL to identify proximate causes of forest cover loss and to estimate recovery rates from GFCL.

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring.

Policies to reduce emissions from deforestation would benefit from clearly derived, spatially explicit statistically bounded estimates of carbon emissions. Existing efforts derive carbon impacts of land-use change using broad assumptions, unreliable data, or both. We improve on this approach using satellite observations of gross forest cover loss and a map of forest carbon stocks to estimate gross carbon emissions across tropical regions between 2000 and 2005 as 0.81 petagram of carbon per year, with a 90% prediction interval of 0.57 to 1.22 petagrams of carbon per year. This estimate is 25 to 50% of recently published estimates. By systematically matching areas of forest loss with their carbon stocks before clearing, these results serve as a more accurate benchmark for monitoring global progress on reducing emissions from deforestation.

Brazil has become a global leader in the production of commodity row crops such as soybean, sugarcane, cotton, and corn. Here, we report an increase in Brazilian cropland extent from 26.0 Mha in 2000 to 46.1 Mha in 2014. The states of Maranhão, Tocantins, Piauí, Bahia (collectively MATOPIBA), Mato Grosso, Mato Grosso do Sul, and Pará all more than doubled in cropland extent. The states of Goiás, Minas Gerais, and São Paulo each experienced >50% increases. The vast majority of expansion, 79%, occurred on repurposed pasture lands, and 20% was from the conversion of natural vegetation. Area of converted Cerrado savannas was nearly 2.5 times that of Amazon forests, and accounted for more than half of new cropland in MATOPIBA. Spatiotemporal dynamics of cropland expansion reflect market conditions, land use policies, and other factors. Continued extensification of cropland across Brazil is possible and may be likely under current conditions, with attendant benefits for and challenges to development.