Global carbon balance of the forest: satellite-based L-VOD results over the last decade

Frontiers in Remote Sensing, Год журнала: 2024, Номер 5

Опубликована: Май 10, 2024

Monitoring forest carbon (C) stocks is essential to better assess their role in the global balance, and model predict long-term trends inter-annual variability atmospheric CO2 concentrations. On a national scale, inventories (NFIs) can provide estimates of stocks, but these are only available certain countries, limited by time lags due periodic revisits, cannot spatially continuous mapping forests. In this context, remote sensing offers many advantages for monitoring above-ground biomass (AGB) on scale with good spatial (50–100 m) temporal (annual) resolutions. Remote has been used several decades monitor vegetation. However, traditional methods AGB using optical or microwave sensors affected saturation effects moderately densely vegetated canopies, limiting performance. Low-frequency passive less effects: occurs at levels around 400 t/ha L-band (frequency 1.4 GHz). Despite its coarse resolution order 25 km × km, method based L-VOD (vegetation depth L-band) index recently established itself as an approach annual variations continental scale. Thus, applied continents biomes: tropics (especially Amazon Congo basins), boreal regions (Siberia, Canada), Europe, China, Australia, etc. no reference study yet published analyze detail terms capabilities, validation results. This paper fills gap presenting physical principles calculation, analyzing performance reviewing main applications tracking balance vegetation over last decade (2010–2019).

Язык: Английский

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Advanced soil conservation for African drylands: from erosion models to management theories

Pedosphere, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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Dynamics of carbon sequestration in vegetation affected by large-scale surface coal mining and subsequent restoration

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Июнь 12, 2024

Abstract Surface coal development activities include mining and ecological restoration, which significantly impact regional carbon sinks. Quantifying the dynamic impacts on sequestration in vegetation (VCS) during has been challenging. Here, we provided a novel approach to assess dynamics of VCS affected by large-scale surface subsequent restoration. This effectively overcomes limitations imposed lack finer scale long-time series data through transformation. We found that directly decreased 384.63 Gg CO 2 , while restoration increased 192.51 between 2001 2022. As 2022, deficit at areas still had 1966.7 . The study highlights complete requires compensating not only for loss year destruction but also ongoing accumulation losses throughout lifecycle. findings deepen insights into intricate relationship resource environmental protection.

Язык: Английский

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The responses of vegetation water use efficiency to biomass density and CO2 balance in dryland of Central Asia during 21st century

Ecological Indicators, Год журнала: 2025, Номер 171, С. 113070 - 113070

Опубликована: Фев. 1, 2025

Язык: Английский

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State of the art and for remote sensing monitoring of carbon dynamics in African tropical forests

Frontiers in Remote Sensing, Год журнала: 2025, Номер 6

Опубликована: Март 17, 2025

African tropical forests play a crucial role in global carbon dynamics, biodiversity conservation, and climate regulation, yet monitoring their structure, diversity, stocks changes remains challenging. Remote sensing techniques, including multi-spectral data, lidar-based canopy height vertical structure detection, radar interferometry, have significantly improved our ability to map forest composition, estimate biomass, detect degradation deforestation features at finer scale. Machine learning approaches further enhance these capabilities by integrating multiple data sources produce maps of attributes track over time. Despite advancements, uncertainties remain due limited ground-truth validation, the structural complexity large spatial heterogeneity forests. Future developments remote should examine how multi-sensor integration high-resolution from instruments such as Planet, Tandem-X, SPOT AI methods can refine storage function maps, large-scale tree biomass improve detection down level. These advancements will be essential for supporting science-based decision-making conservation mitigation.

Язык: Английский

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Spatiotemporal evolution and risk thresholds of PM2.5 components in China from the human health perspective

Environmental Pollution, Год журнала: 2025, Номер unknown, С. 126194 - 126194

Опубликована: Апрель 1, 2025

Язык: Английский

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Construction and analysis of atmospheric visibility and fog-haze datasets in China (2001−2023) based on machine learning models

Atmospheric Research, Год журнала: 2025, Номер unknown, С. 108160 - 108160

Опубликована: Апрель 1, 2025

Язык: Английский

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Remote Sensing of Forest Above-Ground Biomass Dynamics: A Review

Forests, Год журнала: 2025, Номер 16(5), С. 821 - 821

Опубликована: Май 15, 2025

Recent studies have primarily focused on estimating forest above-ground biomass (AGB) at single time points, with limited attention to temporal changes. However, time-series remote sensing data offer valuable insights into trends, drivers of change, and recovery following disturbance, deepening our understanding dynamics. This review synthesized 166 published between 2010 2024 (15 years) changes or dynamics monitored through sensing, an emphasis datasets both indirect (83.7%) direct (16.3%) methods for AGB changes, as well the key these A meta-analysis change estimates revealed that 81.5% operated spatial resolutions below 100 m, while only a few addressed coarser scales. Notably, just 11.9% used independent validation, 8.8% reported no validation all, underscoring need more rigorous accuracy assessment ensure methodological reliability ecological relevance. also discusses challenges, limitations, future directions improved sensing-based monitoring.

Язык: Английский

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Global L-band equivalent AI-based vegetation optical depth dataset

Scientific Data, Год журнала: 2024, Номер 11(1)

Опубликована: Авг. 28, 2024

The L-band vegetation optical depth data garners significant interest for its ability to effectively monitor vegetation, thanks minimal saturation within this frequency range. However, the existing datasets have limited temporal coverage, constrained by start of respective satellite missions. Global equivalent AI-Based Vegetation Optical Depth or GLAB-VOD is a global long-term consistent microwave dataset created using machine learning expand SMAP-IB VOD coverage from 2015-2020 2002-2020. has an 18-day resolution and 25 km spatial on EASE2 grid covers An auxiliary daily brightness temperature product, called GLAB-TB, developed in parallel ensures consistency product across time periods with different satellites. As result consistency, can be used study regional trends biomass utilized any other applications where necessary. shows excellent correlation globally when compared (up R = 0.92) canopy height (R 0.93), outperforming target dataset, VOD.

Язык: Английский

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Soil Moisture Content Inversion Model on the Basis of Sentinel Multispectral and Radar Satellite Remote Sensing Data

Journal of soil science and plant nutrition, Год журнала: 2024, Номер unknown

Опубликована: Окт. 25, 2024

Язык: Английский

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