Matthew C. Hansen’s research while affiliated with University of Maryland Global Campus and other places

Forest restoration is gaining momentum as a natural climate solution to provide carbon dioxide removal while also addressing the biodiversity crisis. Globally, three primary restoration strategies—natural regeneration, assisted natural regeneration, and active restoration—have been adopted. However, inconsistent monitoring of forest dynamics mean large uncertainties remain over their long-term potential to enhance carbon (C) removal. We examined over 30 years of forest aboveground carbon (AGC) estimates from high-resolution lidar, Landsat imagery, and field data across East Africa. Our study shows that assisted natural regeneration and active restoration outperform natural regeneration in enhancing forest C removal capacity, with long-term implementation (over 9 years) needed to overcome the initial lags in AGC accumulation. Restoring 14.24 million hectares of suitable areas available in East Africa, representing 2.1% of suitable restoration areas globally, could enhance forest C removal by 2.85 ± 0.82 gigatons of C (Gt C) by 2050. However, less than one quarter of this potential would be achieved by 2030. This research advances our understanding of forest restoration’s potential for enhancing C removal and the time scale for meeting climate targets. We demonstrate that long-term commitments in implementation and investment are critical for restoring forests effectively for climate mitigation.

PlanetScope and Sentinel-2 data to quantify the extent and drivers of global forest loss: sample-based analysis Previously global drivers of forest loss have been quantified only in coarse spatial resolution (Curtis et al. 2018). Here we aim to utilize the high resolution (circa 3m) PlanetScope data, acquired through the NASA's Commercial Smallsat Data Acquisition program, combined with the freely available 10m resolution Sentinel-2 data, to quantify the extent of forest loss and loss drivers for the year 2018. The analysis is sample-based, using the stratified random sample of 600 reference blocks, each 5x5 km in size, to estimate the area of forest loss. Each block is mapped using the combined PlanetScope-Sentinel-2 image stack to produce the reference yes/no maps for the target year. This mapped reference loss is then attributed to the initial disturbance type, proximate cause of forest loss, and pre-disturbance forest type. Identified forest types are natural forests, timber and non-timber tree plantations. Initial disturbance type is identified from year 2018 reference imagery, and includes mechanical forest clearing (manual vs. mechanized) and natural disturbances (fire, insects, floods, hurricanes, windfalls). Proximate cause (driver) of forest loss (Geist and Lambin 2002) is based on the reference imagery three years after disturbance (PlanetScope and Google Earth), and includes the following categories: forestry operations in natural forests (clearcuts with natural regeneration vs. planted, selective logging), tree plantation management (timber vs. non-timber plantations), forest rotation in shifting cultivation, natural disturbances (fire, insects) and conversion of forests to other land uses (pasture, cropland, tree plantations, construction, mining). This is an ongoing project, but preliminary mapping of 425 blocks out of 600 yields a standard error of a global forest loss area estimate of 9.5%, and standard errors of major driver proportions (forestry, shifting cultivation, conversion to pasture and cropland) under 28%. Regression estimator of global forest loss area with per block percent of 2018 forest loss from the global map (Hansen et al. 2013) as an auxiliary variable, yields the standard error of 8.4%. Further steps of the project include assessing the accuracy of reference Planet-based block maps, and producing continental and climate-domain scale forest loss area estimates.

Indonesia has experienced rapid primary forest loss, second only to Brazil in modern history. We examined the fates of Indonesian deforested areas, immediately after clearing and over time, to quantify deforestation drivers in Indonesia. Using time-series satellite data, we tracked degradation and clearing events in intact and degraded natural forests from 1991 to 2020, as well as land use trajectories after forest loss. While an estimated 7.8 Mha (SE = 0.4) of forest cleared during this period had been planted with oil palms by 2020, another 8.8 Mha (SE = 0.4) remained unused. Of the 28.4 Mha (SE = 0.7) deforested, over half were either initially left idle or experienced crop failure before a land use could be detected, and 44% remained unused for 5 y or more. A majority (54%) of these areas were cleared mechanically (not by escaped fires), and in cases where idle lands were eventually converted to productive uses, oil palm plantations were by far the most common outcome. The apparent deliberate creation of idle deforested land in Indonesia and subsequent conversion of idle areas to oil palm plantations indicates that speculation and land banking for palm oil substantially contribute to forest loss, although failed plantations could also contribute to this dynamic. We also found that in Sumatra, few lowland forests remained, suggesting that a lack of remaining forest appropriate for palm oil production, together with an extensive area of banked deforested land, may partially explain slowing forest loss in Indonesia in recent years.

Nature-based climate solutions, such as forest landscape restoration, offer a promising approach to mitigate the effects of global climate change, conserve biodiversity, and enhance rural livelihoods. Heinrich et al. (Nature, 2023) used satellite observation products to assess rates and drivers of aboveground carbon accumulation in tropical recovering forests, which is knowledge essential for understanding their climate mitigation potential. They used a tropical moist forest cover change dataset developed by the European Commission’s Joint Research Centre (JRC) to identify tree cover gains on former agricultural lands, and they referred to these gains as “secondary forests” assuming that all the gains were natural forest regrowth. However, tropical tree cover gains on former agricultural lands also include managed tree systems, e.g., timber plantations, oil palm plantations, and agroforestry. Ignoring the contribution of gains due to managed tree systems likely leads to a significant underestimation of the impact of management practices on tropical carbon sequestration; such impacts might either increase or decrease the rate of carbon sequestration by tropical tree-based systems on former agricultural lands, compared with natural forest recovery solely.

European forests are among the most extensively studied ecosystems in the world, yet there are still debates about their recent dynamics. We modeled the changes in tree canopy height across Europe from 2001 to 2021 using the multidecadal spectral data from the Landsat archive and calibration data from Airborne Laser Scanning (ALS) and spaceborne Global Ecosystem Dynamics Investigation (GEDI) lidars. Annual tree canopy height was modeled using regression tree ensembles and integrated with annual tree canopy removal maps to produce harmonized tree height map time series. From these time series, we derived annual tree canopy extent maps using a ≥ 5 m tree height threshold. The root-mean-square error (RMSE) for both ALS-calibrated and GEDI-calibrated tree canopy height maps was ≤4 m. The user's and producer's accuracies estimated using reference sample data are ≥94% for the tree canopy extent maps and ≥ 80% for the annual tree canopy removal maps. Analyzing the map time series, we found that the European tree canopy extent area increased by nearly 1% overall during the past two decades, with the largest increase observed in Eastern Europe, Southern Europe, and the British Isles. However, after the year 2016, the tree canopy extent in Europe declined. Some regions reduced their tree canopy extent between 2001 and 2021, with the highest reduction observed in Fennoscandia (3.5% net decrease). The continental extent of tall tree canopy forests (≥ 15 m height) decreased by 3% from 2001 to 2021. The recent decline in tree canopy extent agrees with the FAO statistics on timber harvesting intensification and with the increasing extent and severity of natural disturbances. The observed decreasing tree canopy height indicates a reduction in forest carbon storage capacity in Europe.