Investigating Diurnal and Seasonal Cycles of Vegetation Optical Depth Retrieved From GNSS Signals in a Broadleaf Forest

Geophysical Research Letters, Journal Year: 2024, Volume and Issue: 51(6)

Published: March 19, 2024

Abstract Vegetation Optical Depth (VOD) has emerged as a valuable metric to quantify water stress on vegetation's carbon uptake from remote sensing perspective. However, existing spaceborne microwave platforms face limitations in capturing the diurnal VOD variations and global products lack site‐level validation against plant physiology. To address these challenges, we leveraged Global Navigation Satellite System (GNSS) L‐band signal, measuring its attenuation by canopy of temperate broadleaf forest using pair GNSS receivers. This approach allowed us collect continuous observations at sub‐hourly scale. We found significant seasonal‐scale correlation between leaf potential. The amplitude is affected soil moisture, transpiration surface water. Additionally, can help independently estimate transpiration. Our findings pave way for deeper understanding response vegetation finer temporal scales.

Language: Английский

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Continuous ground monitoring of vegetation optical depth and water content with GPS signals

Biogeosciences, Journal Year: 2023, Volume and Issue: 20(9), P. 1789 - 1811

Published: May 16, 2023

Abstract. Satellite microwave remote sensing techniques can be used to monitor vegetation optical depth (VOD), a metric which is directly linked biomass and water content. However, these large-scale measurements are still difficult reference against either rare or not comparable field observations. So far, in situ estimates of canopy status often rely on infrequent time-consuming destructive samples, necessarily representative the scale. Here, we present simple technique based Global Navigation Systems (GNSS) with potential bridge this persisting scale gap. Because GNSS signals attenuated scattered by liquid water, placing sensor under vegetated measuring changes signal strength over time provide continuous information about VOD thus We test at forested site southern California for period 8 months. show that variations signal-to-noise ratios reflect overall distribution density monitored continuously. For first time, resolve diurnal content hourly sub-hourly steps. Using model transmissivity assess signals, find temperature effects dielectric constant, VOD, may non-negligible during extreme events like heat waves. Sensitivity rainfall dew deposition also suggests interception approach. The presented here has two important knowledge gaps, namely lack ground truth observations satellite-based need reliable proxy extrapolate isolated labor-intensive biomass, content, leaf potential. recommendations deploying such off-the-shelf easy-to-use systems existing ecohydrological monitoring networks as FluxNet SapfluxNet.

Language: Английский

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Modeling forest above-ground biomass using freely available satellite and multisource datasets

Ecological Informatics, Journal Year: 2023, Volume and Issue: 74, P. 101973 - 101973

Published: Jan. 5, 2023

Language: Английский

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Deep ResU-Net Convolutional Neural Networks Segmentation for Smallholder Paddy Rice Mapping Using Sentinel 1 SAR and Sentinel 2 Optical Imagery

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(6), P. 1517 - 1517

Published: March 9, 2023

Rice is a globally significant staple food crop. Therefore, it crucial to have adequate tools for monitoring changes in the extent of rice paddy cultivation. Such system would require sustainable and operational workflow that employs open-source medium high spatial temporal resolution satellite imagery efficient classification techniques. This study used similar phenological data from Sentinel-2 (S2) optical Sentinel-1 (S1) Synthetic Aperture Radar (SAR) identify distribution with deep learning (DL) Using Google Earth Engine (GEE) U-Net Convolutional Neural Networks (CNN) segmentation, accurately delineates smallholder fields using multi-temporal S1 SAR S2 was investigated. The study′s accuracy assessment results showed optimal dataset mapping fusion multispectral bands (visible near infra-red (VNIR), red edge (RE) short-wave infrared (SWIR)), S1-SAR dual polarization (VH VV) captured within crop growing season (i.e., vegetative, reproductive, ripening). Compared random forest (RF) classification, DL model ResU-Net) had an overall 94% (three percent higher than RF prediction). ResU-Net prediction F1-Score 0.92 compared 0.84 generated 500 trees model. classified maps dates analyzed 2016–2020), change detection analysis over two epochs (2016 2018 2020) provided better understanding spatial–temporal dynamics agriculture area. indicated 377,895 8551 hectares were converted other land-use first (2016–2018) second (2018–2020) epochs. These statistics valuable insight into field across selected districts analyzed. proposed framework has potential be upscaled transferred regions. approach could locally, improve decision making, support security region.

Language: Английский

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Radar vegetation indices for monitoring surface vegetation: Developments, challenges, and trends

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 945, P. 173974 - 173974

Published: June 17, 2024

Language: Английский

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1-km soil moisture retrieval using multi-temporal dual-channel SAR data from Sentinel-1 A/B satellites in a semi-arid watershed

Remote Sensing of Environment, Journal Year: 2022, Volume and Issue: 284, P. 113334 - 113334

Published: Nov. 8, 2022

Language: Английский

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The potential of optical and SAR time-series data for the improvement of aboveground biomass carbon estimation in Southwestern China’s evergreen coniferous forests

GIScience & Remote Sensing, Journal Year: 2024, Volume and Issue: 61(1)

Published: April 26, 2024

Accurate assessments of forest biomass carbon are invaluable for managing resources, evaluating effects on ecological protection, and achieving goals related to climate change sustainable development. Currently, the integration optical synthetic aperture radar (SAR) data has been extensively utilized in estimating aboveground (AGC), while it is limited by using single-phase remote sensing images. Time-series data, which capture interannual dynamic growth seasonal variations photosynthetic phenology forests, can sufficiently describe characteristics. However, there remains a gap research focusing utilizing satellite-based time-series AGC estimation, especially SAR sensors. This study investigated potential AGC. Here, we undertook nine quantitative experiments estimation from Landsat 8 Sentinel-1 tested several regression algorithms (including multiple linear (MLR), random forests (RF), artificial neural network (ANN), extreme gradient boosting (XGBoost)) explore contributions spatiotemporal features estimation. The results suggested that XGBoost algorithm was suitable with explanatory solid power stable performance. temporal representing trends periodic characteristics (such as coefficients continuous wavelet transform) were more valuable than spatial both sensor types, accounting around 40% ~50% variance compared 17% ~25%. combination produced best performance (R2 = 0.814, RMSE 18.789 Mg C/ha, rRMSE 26.235%), when or alone (optical: R2 0.657 35.317%; SAR: 0.672 34.701%). Feature importance analysis also verified vegetation indices, SWIR 1/2 bands, backscatter VV polarization most critical variables Furthermore, incorporating into modeling illustrated be effective reducing saturation within high-biomass forests. demonstrated superiority While applicability this methodology only evergreen coniferous may provide viable approach needed make full use increasingly better free satellite estimate high accuracy, supporting policy making management

Language: Английский

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Intercomparison of very high-resolution surface soil moisture products over Catalonia (Spain)

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 309, P. 114225 - 114225

Published: May 28, 2024

The surface soil moisture (SSM) is a key variable for monitoring hydrological, meteorological and agricultural processes. It can be estimated from active passive microwave remote sensing data. While coarse-resolution SSM products (> 1 km) have already been evaluated large range of ecosystems, such assessments lack very high-spatial-resolution products, although they are increasingly available thanks to high-resolution radar data or disaggregation methods applied coarse-scale products. Within this context, the aim current study carry out, first time, an intercomparison high-spatial resolution using in situ database collected 33 fields located Ebro basin (Spain) that were cultivated with different crops irrigated techniques. Three considered: (i) SSMTheia at field scale derived Sentinel-1 Sentinel-2 machine learning algorithm; ii) SSMρ 50-m both backscattering coefficient interferometric coherence based on inversion simple radiative transfer model; iii) SSMSMAP20m 20-m obtained by disaggregating SMAP Sentinel-3 statistical metrics computed whole show two outperform disaggregated approach product exhibits better than product. This mainly attributed inability retrieve >0.3 m3/m3. correlation coefficients >0.4 (up 0.8) 72%, 40% 27% SSMρ, SSMSMAP20m, respectively. Similarly, 80% had RMSE values between 0.06 m3/m3 0.1 against 36% SSMSMAP20m. In addition, time series analysis showed was able detect large-scale wetting events as rainfall impacted pixel while irrigation not detected, because used land temperature related hydric status surface. results perform reasonably well cereals and, lesser extent, annuals, drastic drop observed tree crops. Finally, spatial pattern over area also depicted comparison airborne GLORI GNSS-R (Global Navigation Satellite System Reflectometry) maps. highlights limitations provides insights improving scheduling scale.

Language: Английский

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Application of Thresholding Method using Sentinel-1 for Shoreline Stability Analysis around Bangkalan Coast

IOP Conference Series Earth and Environmental Science, Journal Year: 2025, Volume and Issue: 1472(1), P. 012019 - 012019

Published: April 1, 2025

Abstract Shorelines change due to physical, natural, and artificial properties. Shoreline are dynamic interesting analysis, specially around Bangkalan coastal areas. Although the characteristic is dominated by mud substrates, dynamics of shoreline in several locations show significant changes. Sentinel-1 imagery an alternative for studies because it has high spatial resolution temporal frequency applied thresholding method separate land water profiles. This study aims analyze changes coastline using based on method. The results analysis that some areas along have changes, both abrasion accretion.

Language: Английский

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The influence of vegetation water dynamics on the ASCAT backscatter–incidence angle relationship in the Amazon

Hydrology and earth system sciences, Journal Year: 2022, Volume and Issue: 26(11), P. 2997 - 3019

Published: June 15, 2022

Abstract. Microwave observations are sensitive to plant water content and could therefore provide essential information on biomass status in ecological agricultural applications. The combined data record of the C-band scatterometers European Remote-Sensing Satellites (ERS)-1/2, Metop (Meteorological Operational satellite) series, planned Second Generation satellites will span over 40 years, which would a long-term perspective role vegetation climate system. Recent research has indicated that unique viewing geometry Advanced SCATterometer (ASCAT) be exploited observe dynamics. incidence angle dependence backscatter can described with second order polynomial, slope curvature related vegetation. In study limited grasslands, seasonal cycles, spatial patterns, interannual variability were found vary among grassland types attributed differences moisture availability, growing season length phenological changes. To exploit ASCAT for global monitoring, their dynamics wider range needs quantified explained terms Here, we compare meteorological GRACE equivalent thickness (EWT) explain backscatter, slope, availability demand. We consider cycle, diurnal differences, response 2010 2015 droughts across ecoregions Amazon basin surroundings. Results show temporal patterns reflect by EWT. Slope considerably ecoregions. evergreen forests, often used as calibration target, exhibit very stable behavior, even under drought conditions. variation follows changes radiation cycle may indicate such litterfall. contrast, diversity land cover within Cerrado region results considerable heterogeneity influence both curvature. Seasonal flooding forest savanna areas also produced distinctive signature function angle. This improved understanding behavior increases our ability interpret make optimal use optical depth products monitoring.

Language: Английский

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