Mapping aboveground carbon density (ACD) in tropical forests can enhance large-scale ecological studies and support CO2 emissions monitoring. Light Detection and Ranging (LiDAR) has proven useful for ...estimating carbon density patterns outside of field plot inventory networks. However, the accuracy and generality of calibrations between LiDAR-assisted ACD predictions (EACDLiDAR) and estimated ACD based on field inventory techniques (EACDfield) must be increased in order to make tropical forest carbon mapping more widely available. Using a network of 804 field inventory plots distributed across a wide range of tropical vegetation types, climates and successional states, we present a general conceptual and technical approach for linking tropical forest EACDfield to LiDAR top-of-canopy height (TCH) using regional-scale inputs of basal area and wood density. With this approach, we show that EACDLiDAR and EACDfield reach nearly 90% agreement at 1-ha resolution for a wide array of tropical vegetation types. We also show that Lorey's Height – a common metric used to calibrate LiDAR measurements to biomass – is severely flawed in open canopy forests that are common to the tropics. Our proposed approach can advance the use of airborne and space-based LiDAR measurements for estimation of tropical forest carbon stocks.
•The accuracy and generality of LiDAR-assisted carbon mapping remains uncertain in tropical forests.•An approach is developed to calibrate LiDAR top-of-canopy height to field-estimated aboveground carbon density.•At 1-ha resolution, LiDAR estimates of aboveground carbon density approach 90% agreement with field-estimated carbon density.•This approach will reduce cost and effort to calibrate LiDAR metrics to field estimates of tropical forest carbon stocks.
We identify canopy species in a Hawaiian tropical forest using supervised classification applied to airborne hyperspectral imagery acquired with the Carnegie Airborne Observatory-Alpha system. ...Nonparametric methods (linear and radial basis function support vector machine, artificial neural network, and k-nearest neighbor) and parametric methods (linear, quadratic, and regularized discriminant analysis) are compared for a range of species richness values and training sample sizes. We find a clear advantage in using regularized discriminant analysis, linear discriminant analysis, and support vector machines. No unique optimal classifier was found for all conditions tested, but we highlight the possibility of improving support vector machine classification with a better optimization of its free parameters. We also confirm that a combination of spectral and spatial information increases accuracy of species classification: we combine segmentation and species classification from regularized discriminant analysis to produce a map of the 17 discriminated species. Finally, we compare different methods to assess spectral separability and find a better ability of Bhattacharyya distance to assess separability within and among species. The results indicate that species mapping is tractable in tropical forests when using high-fidelity imaging spectroscopy.
Developing countries are increasingly decentralizing forest governance by granting indigenous groups and other local communities formal legal title to land. However, the effects of titling on forest ...cover are unclear. Rigorous analyses of titling campaigns are rare, and related theoretical and empirical research suggests that they could either stemor spur forest damage. We analyze such a campaign in the Peruvian Amazon, where more than 1,200 indigenous communities comprising some 11 million ha have been titled since the mid-1970s. We use community-level longitudinal data derived from high-resolution satellite images to estimate the effect of titling between 2002 and 2005 on contemporaneous forest clearing and disturbance. Our results indicate that titling reduces clearing by more than three-quarters and forest disturbance by roughly two-thirds in a 2-y window spanning the year title is awarded and the year afterward. These results suggest that awarding formal land titles to local communities can advance forest conservation.
Nearly 20% of tropical forests are within 100 m of a nonforest edge, a consequence of rapid deforestation for agriculture. Despite widespread conversion, roughly 1.2 billion ha of tropical forest ...remain, constituting the largest terrestrial component of the global carbon budget. Effects of deforestation on carbon dynamics in remnant forests, and spatial variation in underlying changes in structure and function at the plant scale, remain highly uncertain. Using airborne imaging spectroscopy and light detection and ranging (LiDAR) data, we mapped and quantified changes in forest structure and foliar characteristics along forest/oil palm boundaries in Malaysian Borneo to understand spatial and temporal variation in the influence of edges on aboveground carbon and associated changes in ecosystem structure and function. We uncovered declines in aboveground carbon averaging 22% along edges that extended over 100 m into the forest. Aboveground carbon losses were correlated with significant reductions in canopy height and leaf mass per area and increased foliar phosphorus, three plant traits related to light capture and growth. Carbon declines amplified with edge age. Our results indicate that carbon losses along forest edges can arise from multiple, distinct effects on canopy structure and function that vary with edge age and environmental conditions, pointing to a need for consideration of differences in ecosystem sensitivity when developing land-use and conservation strategies. Our findings reveal that, although edge effects on ecosystem structure and function vary, forests neighboring agricultural plantations are consistently vulnerable to long-lasting negative effects on fundamental ecosystem characteristics controlling primary productivity and carbon storage.
Gold mining in Amazonia involves forest removal, soil excavation, and the use of liquid mercury, which together pose a major threat to biodiversity, water quality, forest carbon stocks, and human ...health. Within the global biodiversity hotspot of Madre de Dios, Peru, gold mining has continued despite numerous 2012 government decrees and enforcement actions against it. Mining is now also thought to have entered federally protected areas, but the rates of miner encroachment are unknown. Here, we utilize high-resolution remote sensing to assess annual changes in gold mining extent from 1999 to 2016 throughout the Madre de Dios region, including the high-diversity Tambopata National Reserve and buffer zone. Regionally, gold mining-related losses of forest averaged 4437 ha yr−1. A temporary downward inflection in the annual growth rate of mining-related forest loss following 2012 government action was followed by a near doubling of the deforestation rate from mining in 2013-2014. The total estimated area of gold mining throughout the region increased about 40% between 2012 and 2016, including in the Tambopata National Reserve. Our results reveal an urgent need for more socio-environmental effort and law enforcement action to combat illegal gold mining in the Peruvian Amazon.
Monitoring aboveground carbon stocks and fluxes from tropical deforestation and forest degradation is important for mitigating climate change and improving forest management. However, high temporal ...and spatial resolution analyses are rare. This study presents the most detailed tracking of aboveground carbon over time, with yearly, quarterly and monthly estimations of emissions using the stock-difference approach and masked by the forest loss layer of Global Forest Watch. We generated high spatial resolution (1-ha) monitoring of aboveground carbon density (ACD) and emissions (ACE) in Peru by incorporating hundreds of thousands of Planet Dove satellite images, Sentinel-1 radar, topography and airborne LiDAR, embedded into a deep learning regression workflow using high-performance computing. Consistent ACD results were obtained for all quarters and months analyzed, with R2 values of 0.75-0.78, and root mean square errors (RMSE) between 20.6 and 22.0 Mg C ha-1. A total of 7.138 Pg C was estimated for Peru with annual ACE of 20.08 Tg C between the third quarters of 2017 and 2018, respectively, or 23.4% higher than estimates from the FAO Global Forest Resources Assessment. Analyzed quarterly, the spatial evolution of ACE revealed 11.5 Tg C, 6.6 Tg C, 8.6 Tg C, and 10.1 Tg C lost between the third quarters of 2017 and 2018. Moreover, our monthly analysis for the dry season reveals the evolution of ACE at unprecedented temporal detail. We discuss environmental controls over ACE and provide a spatially explicit tool for enhanced forest carbon management at scale.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Savannahs and woodlands are among the most important biomes in Africa: they cover half of sub-Saharan Africa, provide vital ecosystem services to the rural communities, and play a major part in the ...carbon budget. Despite their importance and their fragility, they are much less studied than other ecosystems like rainforests. In particular, the distribution and amount of the above-ground woody biomass (AGB) is largely unknown. In this paper, we produce the first continental map of the AGB of African savannahs and woodlands at a resolution of 25 m. The map is built from the 2010 L-band PALSAR mosaic produced by JAXA, along the following steps: a) stratification into wet/dry season areas in order to account for seasonal effects, b) development of a direct model relating the PALSAR backscatter to AGB, with the help of in situ and ancillary data, c) Bayesian inversion of the direct model. A value of AGB and its uncertainty has been assigned to each pixel. This approach allows estimating AGB until 85 Mg·ha− 1 approximately, while dense forests and non-vegetated areas are masked out using the ESA CCI Land Cover dataset. The resulting map is visually compared with existing AGB maps and is validated using a cross-validation approach and a comparison with AGB estimates obtained from LiDAR datasets, leading to an RMSD of 8 to 17 Mg·ha− 1. Finally, carbon stocks for savannahs in Africa and in 50 countries are estimated and compared with estimates by FAO and from AGB maps available over Africa.
We evaluated the potential of a multi-temporal Multiple Endmember Spectral Mixture Analysis (MESMA) for invasive species mapping in Hawaiian rainforests. Earth Observing-1 Hyperion time series data ...were compiled in a single image cube and ingested into MESMA. While the temporal analysis provided a way to incorporate species phenology, a feature selection technique automatically identified the best time and best spectral feature set to optimize the separability among the native and invasive tree species in our study area. We initiated an alternative Separability Index (SI)-based feature selection approach in which a boundary condition reduced the amount of correlation in the selected spectral subset. We hypothesized that redundant spectral information could be avoided, and improved plant detection accuracy could be achieved, with reduced computational time due to the selection of fewer bands in the mixture analysis. Our analysis showed a systematic increase in the invasive species detection success when we compared the output of multi-temporal MESMA (Kappa=0.78) with that of the traditional unitemporal approach (Kappa=0.51–0.69). Even for unitemporal MESMA, in which only a single input image was used, the band selection strategy was beneficial both in plant detection accuracy and computational time. We could further demonstrate that, despite a lack of imagery covering all phenological events, a proper band selection strategy can emphasize subtle spectral and phenological differences between species and can thereby partly compensate for this lack of data. This creates opportunities for mapping in areas where cloud cover is a limiting factor for building extended spectral image time series. This approach is sufficiently general and inherently adaptive, thereby supporting species mapping using Hyperion and forthcoming space-borne imaging spectrometers.
•We used a time series of Hyperion to detect invasive species in Hawaiian forests.•We ingested the time series into MESMA improving detection success.•Band selection was needed to optimize CPU efficiency and detection success.•We proposed an automated technique forcing the selection of uncorrelated bands.•The selected bands optimized the separability between the targeted tree species.
Gold mining has rapidly increased in western Amazonia, but the rates and ecological impacts of mining remain poorly known and potentially underestimated. We combined field surveys, airborne mapping, ...and high-resolution satellite imaging to assess road- and river-based gold mining in the Madre de Dios region of the Peruvian Amazon from 1999 to 2012. In this period, the geographic extent of gold mining increased 400%. The average annual rate of forest loss as a result of gold mining tripled in 2008 following the global economic recession, closely associated with increased gold prices. Small clandestine operations now comprise more than half of all gold mining activities throughout the region. These rates of gold mining are far higher than previous estimates that were based on traditional satellite mapping techniques. Our results prove that gold mining is growing more rapidly than previously thought, and that high-resolution monitoring approaches are required to accurately quantify human impacts on tropical forests.
Large-scale carbon mapping is needed to support the UNFCCC program to reduce deforestation and forest degradation (REDD). Managers of forested land can potentially increase their carbon credits via ...detailed monitoring of forest cover, loss and gain (hectares), and periodic estimates of changes in forest carbon density (tonsha−1). Satellites provide an opportunity to monitor changes in forest carbon caused by deforestation and degradation, but only after initial carbon densities have been assessed. New airborne approaches, especially light detection and ranging (LiDAR), provide a means to estimate forest carbon density over large areas, which greatly assists in the development of practical baselines. Here I present an integrated satellite–airborne mapping approach that supports high-resolution carbon stock assessment and monitoring in tropical forest regions. The approach yields a spatially resolved, regional state-of-the-forest carbon baseline, followed by high-resolution monitoring of forest cover and disturbance to estimate carbon emissions. Rapid advances and decreasing costs in the satellite and airborne mapping sectors are already making high-resolution carbon stock and emissions assessments viable anywhere in the world.
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