. The net flux of carbon from land use and land-cover change (LULCC) accounted for 12.5% of anthropogenic carbon emissions from 1990 to 2010. This net flux is the most uncertain term in the global carbon budget, not only because of uncertainties in rates of deforestation and forestation, but also because of uncertainties in the carbon density of the lands actually undergoing change. Furthermore, there are differences in approaches used to determine the flux that introduce variability into estimates in ways that are difficult to evaluate, and not all analyses consider the same types of management activities. Thirteen recent estimates of net carbon emissions from LULCC are summarized here. In addition to deforestation, all analyses considered changes in the area of agricultural lands (croplands and pastures). Some considered, also, forest management (wood harvest, shifting cultivation). None included emissions from the degradation of tropical peatlands. Means and standard deviations across the thirteen model estimates of annual emissions for the 1980s and 1990s, respectively, are 1.14 ± 0.23 and 1.12 ± 0.25 Pg C yr−1 (1 Pg = 1015 g carbon). Four studies also considered the period 2000–2009, and the mean and standard deviations across these four for the three decades are 1.14 ± 0.39, 1.17 ± 0.32, and 1.10 ± 0.11 Pg C yr−1. For the period 1990–2009 the mean global emissions from LULCC are 1.14 ± 0.18 Pg C yr−1. The standard deviations across model means shown here are smaller than previous estimates of uncertainty as they do not account for the errors that result from data uncertainty and from an incomplete understanding of all the processes affecting the net flux of carbon from LULCC. Although these errors have not been systematically evaluated, based on partial analyses available in the literature and expert opinion, they are estimated to be on the order of ± 0.5 Pg C yr−1.

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Carbon emissions from land use and land-cover change

The carbon balance of tropical ecosystems remains uncertain, with top-down atmospheric studies suggesting an overall sink and bottom-up ecological approaches indicating a modest net source. Here we use 12 years (2003 to 2014) of MODIS pantropical satellite data to quantify net annual changes in the aboveground carbon density of tropical woody live vegetation, providing direct, measurement-based evidence that the world’s tropical forests are a net carbon source of 425.2 ± 92.0 teragrams of carbon per year (Tg C year –1 ). This net release of carbon consists of losses of 861.7 ± 80.2 Tg C year –1 and gains of 436.5 ± 31.0 Tg C year –1 . Gains result from forest growth; losses result from deforestation and from reductions in carbon density within standing forests (degradation or disturbance), with the latter accounting for 68.9% of overall losses.

https://science.sciencemag.org/content/sci/358/6360/230.full.pdf

Tropical forests are a net carbon source based on aboveground measurements of gain and loss

Performance-based payments are key, yet limited. Payments based on performance directly incentivise and compensate forest owners and users. But schemes such as payments for environmental services (PES) depend on conditions, such as secure tenure, solid carbon data and transparent governance, that are often lacking and take time to change. This constraint reinforces the need for broad institutional and policy reforms.

/pdf/realising-redd-national-strategy-and-policy-options-4ja4390cq1.pdf

Realising Redd+: National strategy and policy options

[1] Our knowledge of the distribution and amount of terrestrial biomass is based almost entirely on ground measurements over an extremely small, and possibly biased sample, with many regions still unmeasured. Our understanding of changes in terrestrial biomass is even more rudimentary, although changes in land use, largely tropical deforestation, are estimated to have reduced biomass, globally. At the same time, however, the global carbon balance requires that terrestrial carbon storage has increased, albeit the exact magnitude, location, and causes of this residual terrestrial sink are still not well quantified. A satellite mission capable of measuring aboveground woody biomass could help reduce these uncertainties by delivering three products. First, a global map of aboveground woody biomass density would halve the uncertainty of estimated carbon emissions from land use change. Second, an annual, global map of natural disturbances could define the unknown but potentially large proportion of the residual terrestrial sink attributable to biomass recovery from such disturbances. Third, direct measurement of changes in aboveground biomass density (without classification of land cover or carbon modeling) would indicate the magnitude and distribution of at least the largest carbon sources (from deforestation and degradation) and sinks (from woody growth). The information would increase our understanding of the carbon cycle, including better information on the magnitude, location, and mechanisms responsible for terrestrial sources and sinks of carbon. This paper lays out the accuracy, spatial resolution, and coverage required for a satellite mission that would generate these products.

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2009JG000935

Importance of biomass in the global carbon cycle

Remote sensing-based methods of aboveground biomass (AGB) estimation in forest ecosystems have gained increased attention, and substantial research has been conducted in the past three decades. This paper provides a survey of current biomass estimation methods using remote sensing data and discusses four critical issues – collection of field-based biomass reference data, extraction and selection of suitable variables from remote sensing data, identification of proper algorithms to develop biomass estimation models, and uncertainty analysis to refine the estimation procedure. Additionally, we discuss the impacts of scales on biomass estimation performance and describe a general biomass estimation procedure. Although optical sensor and radar data have been primary sources for AGB estimation, data saturation is an important factor resulting in estimation uncertainty. LIght Detection and Ranging (lidar) can remove data saturation, but limited availability of lidar data prevents its extensive application. This...

A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems

Mapping and monitoring carbon stocks in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions, and are now included in climate change negotiations. We review the potential for satellites to measure carbon stocks, specifically aboveground biomass (AGB), and provide an overview of a range of approaches that have been developed and used to map AGB across a diverse set of conditions and geographic areas. We provide a summary of types of remote sensing measurements relevant to mapping AGB, and assess the relative merits and limitations of each. We then provide an overview of traditional techniques of mapping AGB based on ascribing field measurements to vegetation or land cover type classes, and describe the merits and limitations of those relative to recent data mining algorithms used in the context of an approach based on direct utilization of remote sensing measurements, whether optical or lidar reflectance, or radar backscatter. We conclude that while satellite remote sensing has often been discounted as inadequate for the task, attempts to map AGB without satellite imagery are insufficient. Moreover, the direct remote sensing approach provided more coherent maps of AGB relative to traditional approaches. We demonstrate this with a case study focused on continental Africa and discuss the work in the context of reducing uncertainty for carbon monitoring and markets.

/pdf/mapping-and-monitoring-carbon-stocks-with-satellite-4x3nc2yz8p.pdf

Mapping and monitoring carbon stocks with satellite observations: a comparison of methods

SUMMARY The role of tropical deforestation in global climate change is a strong justification for its inclusion in the UN's global climate treaty. In order to successfully address deforestation and forest degradation in developing countries, a compensation scheme must include the main actors involved in deforestation and provide incentives for forest stewards who protect forest carbon stores. Since each tropical forest country represents a different mix of public and private tenure of forested land, policies at the UNFCCC level will need to be sufficiently flexible to allow countries to tailor REDD programs to reflect these differences. At the same time, Parties need to negotiate a basic REDD structure that can apply to all countries as a framework under which to build their national programs. We propose an approach that will incorporate the three main actors of deforestation and forest protection in tropical regions: government, private forest owners, and public forest stewards (including indigenous peop...

A Three-Fund Approach to Incorporating Government, Public and Private Forest Stewards into a REDD Funding Mechanism

Vegetation structure mapping is critical for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. Repeat measurements of these data allow for the observation of deforestation or degradation of existing forests, natural forest regeneration, and the implementation of sustainable agricultural practices like agroforestry. Assessments of tree canopy height and crown projected area at a high spatial resolution are also important for monitoring carbon fluxes and assessing tree-based land uses, since forest structures can be highly spatially heterogeneous, especially in agroforestry systems. Very high resolution satellite imagery (less than one meter (1m) ground sample distance) makes it possible to extract information at the tree level while allowing monitoring at a very large scale. This paper presents the first high-resolution canopy height map concurrently produced for multiple sub-national jurisdictions. Specifically, we produce canopy height maps for the states of California and S\~{a}o Paolo, at sub-meter resolution, a significant improvement over the ten meter (10m) resolution of previous Sentinel / GEDI based worldwide maps of canopy height. The maps are generated by applying a vision transformer to features extracted from a self-supervised model in Maxar imagery from 2017 to 2020, and are trained against aerial lidar and GEDI observations. We evaluate the proposed maps with set-aside validation lidar data as well as by comparing with other remotely sensed maps and field-collected data, and find our model produces an average Mean Absolute Error (MAE) within set-aside validation areas of 3.0 meters.

Tracy Johns

Papers

Mapping and monitoring carbon stocks with satellite observations: a comparison of methods

A Three-Fund Approach to Incorporating Government, Public and Private Forest Stewards into a REDD Funding Mechanism

Sub-meter resolution canopy height maps using self-supervised learning and a vision transformer trained on Aerial and GEDI Lidar