Multi-sensor satellite imagery reveals spatiotemporal changes in peatland water table after restoration

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 306, P. 114144 - 114144

Published: March 30, 2024

Language: Английский

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Using hydrological modelling to improve the Fire Weather Index system over tropical peatlands of peninsular Malaysia, Sumatra and Borneo

International Journal of Wildland Fire, Journal Year: 2025, Volume and Issue: 34(2)

Published: Feb. 19, 2025

Background Tropical peatland fires contribute to global carbon emissions and air pollution. Aims Enhance the globally used Canadian Fire Weather Index (FWI) system specifically over drained undrained tropical peatlands in southeast Asia. Methodology We included simulated hydrology FWI, creating a new peatland-specific version of FWI (FWIpeat). FWIpeat, original (FWIref) drought code (DC) were evaluated against satellite-based active fire occurrence from 2002 2018. Key results The DC shows superior performance explaining peatlands. Over peatlands, FWIpeat show similar results, both outperforming FWIref. A comparison with an earlier study boreal indicates much smaller improvements for possibly due lower accuracy hydrological input data. Conclusions Our highlight importance including information on deeper soil layers, i.e. or groundwater table, when assessing danger. Implications Although this offers promising approach operational management we emphasise need further research refine data explore additional constraints Earth observation

Language: Английский

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Temporal Stability of Grassland Soil Moisture Utilising Sentinel-2 Satellites and Sparse Ground-Based Sensor Networks

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(2), P. 220 - 220

Published: Jan. 5, 2024

Soil moisture is important for understanding climate, water resources, storage, and land use management. This study used Sentinel-2 (S-2) satellite optical data to retrieve surface soil at a 10 m scale on grassland sites with low hydraulic conductivity in climate dominated by heavy rainfall. was estimated after modifying the Optical Trapezoidal Model account mixed cover such conditions. The method uses from short-wave infra-red band, which sensitive moisture, four vegetation indices bands, are overlying vegetation. Scatter plots of these multiple, infrequent passes define range saturated dry edges clearly non-linear, regardless choice index. Land masks generate scatter only over sites. Enhanced Vegetation Index demonstrated advantages other estimation entire In poorly drained soils, time lag between retrievals situ sensor depth must be part validation process. achieved combining an approximate solution Richards’ Equation, along measurements residual samples, optimise correlations satellites sensors 15 cm depth. Time lags 2–4 days resulted reduction root mean square errors volumetric predicted S-2 that measured sensors, ~0.1 m3/m3 <0.06 m3/m3. results two were analysed using statistical concepts based upon temporal stability content, ideal framework intermittent conditions persistent cloud cover. analysis could discriminate different natural drainages textures areas identify sub-surface artificial drainage channels. techniques transferable land-use agricultural management diverse environmental without need extensive expensive networks.

Language: Английский

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Three Decades of Wetland Methane Surface Flux Modeling by Earth System Models‐Advances, Applications, and Challenges

Journal of Geophysical Research Biogeosciences, Journal Year: 2024, Volume and Issue: 129(3)

Published: March 1, 2024

Abstract Earth System Models (ESMs) simulate the exchange of mass and energy between land surface atmosphere, with a key focus on modeling natural greenhouse gas feedbacks. Methane is second most important after carbon dioxide. There are growing concerns over rapidly increasing methane concentration in underscoring need for accurate global its emissions using ESMs. Of multitude sources globally, wetlands largest emitters methane, leading to significant efforts targeting their representation ESMs special emissions. In this review, we first provide historical overview including wetland‐methane components how approaches have evolved time. Second, discuss recent advancements that show promise improvements predictions, namely coupling atmospheric modules ESMs, microtopography transport mechanisms, resolution microbial processes at different spatial‐temporal scales, improved mapping wetland area extent across types. Third, shed light challenges hindering estimations emissions, as shown by consistent discrepancy bottom‐up top‐down models' predictions. Finally, emphasize more detailed biogeochemistry dynamic hydrology while resolving within‐wetland vegetation heterogeneity should improve model especially when coupled expanding ground‐based measurement networks high‐resolution remote sensing methane‐relevant variables, such water elevation, table depth, concentration.

Language: Английский

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Upscaling vascular aboveground biomass and topsoil moisture of subarctic fens from Unoccupied Aerial Vehicles (UAVs) to satellite level

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 933, P. 173049 - 173049

Published: May 10, 2024

Arctic and subarctic ecosystems are experiencing rapid changes in vegetation composition productivity due to global warming. Tundra wetlands especially susceptible these changes, which may trigger shifts soil moisture dynamics. It is therefore essential accurately map plant biomass topsoil moisture. In this study, we mapped total, wood, leaf above ground tundra located between Norway Finland by linking models derived from Unoccupied Aerial Vehicles with multiple satellite data sources using the Extreme Gradient Boosting algorithm. The most accurate predictions for (R

Language: Английский

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Enhancing peatland monitoring through multisource remote sensing: optical and radar data applications

International Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: 45(18), P. 6372 - 6394

Published: Aug. 30, 2024

Peatlands play a pivotal role in global carbon cycling and the conservation of biodiversity even though they cover small fraction Earth's terrestrial surface. These ecosystems are, however, increasingly vulnerable due to climate change impacts anthropogenic activities, leading significant degradation many areas. This review compiles analyses various studies that employ remote sensing for comprehensive peatland mapping monitoring. Remote offers detailed insights into critical features, including classification vegetation, assessment water table dynamics, vegetation condition diversity estimation stocks. Furthermore, delineates utility monitoring recovery processes restored peatlands, highlighting scarcity long-term studies. It also emphasizes potential integrating hyperspectral, multispectral SAR data as well cross-scale analyses. Concluding with future directions, underscores necessity enhanced upscaling techniques, integration multi-sensor application modelling enrich our understanding management ecosystems.

Language: Английский

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LightGBM hybrid model based DEM correction for forested areas

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(10), P. e0309025 - e0309025

Published: Oct. 7, 2024

The accuracy of digital elevation models (DEMs) in forested areas plays a crucial role canopy height monitoring and ecological sensitivity analysis. Despite extensive research on DEMs recent years, significant errors still exist due to factors such as occlusion, terrain complexity, limited penetration, posing challenges for subsequent analyses based DEMs. Therefore, CNN-LightGBM hybrid model is proposed this paper, with four different types forests (tropical rainforest, coniferous forest, mixed broad-leaved forest) selected study sites validate the performance correcting COP30DEM forest area In choice was made use Densenet architecture CNN LightGBM primary model. This LightGBM’s leaf-growth strategy histogram linking methods, which are effective reducing data’s memory footprint utilising more data without sacrificing speed. uses values from ICESat-2 ground truth, covering several parameters including COP30DEM, height, coverage, slope, roughness relief amplitude. To superiority correction compared other models, test model, CNN-SVR SVR conducted within same sample space. prevent issues overfitting or underfitting during training, although common meta-heuristic optimisation algorithms can alleviate these problems certain extent, they have some shortcomings. overcome shortcomings, paper cites an improved SSA search algorithm that incorporates ingestion FA increase diversity solutions global capability, Firefly Algorithm-based Sparrow Search Optimization Algorithm (FA-SSA algorithm) introduced. By comparing multiple validating airborne LiDAR reference dataset, results show R 2 (R-Square) improves by than 0.05 performs better experiments. FA-SSA-CNN-LightGBM has highest accuracy, RMSE 1.09 meters, reduction 30% when models. Compared (such FABDEM GEDI), its 50%, significantly commonly used areas, indicating feasibility method importance advancing topographic mapping.

Language: Английский

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Using earth observation to develop a health index for peatlands

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 970, P. 178956 - 178956

Published: March 1, 2025

Globally peatlands are laterally extensive and represent important stores sinks of atmospheric carbon. The cold humid island hypothesis proposes that damaged can be distinguished from functioning by their relatively dark, bare, dry soils with resulting high daytime low night-time land surface temperatures. Contrasts in bare soil, vegetation cover temperature readily observed satellite so we propose Earth observation, the hypothesis, used to survey, manage monitor peatlands. Using NASA MODIS Observation (EO) products allowed study directly assess both status trajectory over multi-decadal time at a national scale. predictions means EO (albedo, enhanced index - EVI, temperature, diurnal amplitude temperature) without further calibration or correlation other ecosystem variables. Knowledge specific sites within target region it is possible use controls absolute relative status. By considering state expected five British was combine into peat health index. When compared control locations majority (69 %) showed they were on downward trajectory. This primarily driven changes Land Surface Temperature (LST) and, crucially, deviations trends, as indicated

Language: Английский

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Soil Moisture Profiles of Ecosystem Water Use Revealed With ECOSTRESS

Geophysical Research Letters, Journal Year: 2024, Volume and Issue: 51(8)

Published: April 22, 2024

Abstract While remote sensing has provided extensive insights into the global terrestrial water, carbon, and energy cycles, space‐based retrievals remain limited in observing belowground influence of full soil moisture (SM) profile on ecosystem function. We show that this gap can be addressed when coupling 70 m resolution ECOsystem Spaceborne Thermal Radiometer Experiment Space Station land surface temperature (LST) with in‐situ SM measurements. These data sets together reveal water use decreases depth 93% sites showing significant LST shallower than 20 cm while 34% have interactions deeper 50 cm. Furthermore, median peak is estimated to 10 cm, though forests more common layers (50–100 cm) 37% cases. High spatial coupled field‐level thus elucidate role processes behavior.

Language: Английский

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Hyperspectral characterization of vegetation in hemiboreal, boreal and Arctic peatlands using a geographically extensive field dataset

Ecological Informatics, Journal Year: 2024, Volume and Issue: 82, P. 102772 - 102772

Published: Aug. 13, 2024

Language: Английский

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