Enhancing Transpiration Estimates: A Novel Approach Using SIF Partitioning and the TL-LUE Model DOI Creative Commons
Tewekel Melese Gemechu, Baozhang Chen, Huifang Zhang

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(21), P. 3924 - 3924

Published: Oct. 22, 2024

Accurate evapotranspiration (ET) estimation is crucial for understanding ecosystem dynamics and managing water resources. Existing methodologies, including traditional techniques like the Penman–Monteith model, remote sensing approaches utilizing Solar-Induced Fluorescence (SIF), machine learning algorithms, have demonstrated varying levels of effectiveness in ET estimation. However, these methods often face significant challenges, such as reliance on empirical coefficients, inadequate representation canopy dynamics, limitations due to cloud cover sensor constraints. These issues can lead inaccuracies capturing ET’s spatial temporal variability, highlighting need improved techniques. This study introduces a novel approach enhance by integrating SIF partitioning with Photosynthetically Active Radiation (PAR) leaf area index (LAI) data, TL-LUE model (Two-Leaf Light Use Efficiency). Partitioning data into sunlit shaded components allows more detailed canopy’s functional significantly improving modelling. Our analysis reveals advancements modelling through partitioning. At Xiaotangshan Station, correlation between modelled SIFsu 0.71, while SIFsh 0.65. The overall (R2) combined (SIF(P)) 0.69, indicating strong positive relationship at Station. correlations show notable patterns, R2 values 0.89 0.88 Heihe Daman, respectively. findings highlight its impact Comparing observed (PM model) demonstrates substantial improvements. against were 0.68, 0.76, across HuaiLai, Shangqiu, Yunxiao Stations. Modelled PM 0.75, 0.73, 0.90, respectively, three stations. results underscore model’s capability estimations physiological data. innovative SIF-partitioning offers nuanced perspective photosynthesis, providing accurate comprehensive method diverse environments.

Language: Английский

Increasing susceptibility and shortening response time of vegetation productivity to drought from 2001 to 2021 DOI
Jiwang Tang, Ben Niu, Z. Hu

et al.

Agricultural and Forest Meteorology, Journal Year: 2024, Volume and Issue: 352, P. 110025 - 110025

Published: April 26, 2024

Language: Английский

Citations

20
Satellite-Observed Arid Vegetation Greening and Terrestrial Water Storage Decline in the Hexi Corridor, Northwest China DOI Creative Commons

Chunyan Cao,

Xiaoyu Zhu,

Kedi Liu

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(8), P. 1361 - 1361

Published: April 11, 2025

The interplay between terrestrial water storage and vegetation dynamics in arid regions is critical for understanding ecohydrological responses to climate change human activities. This study examines the coupling total anomaly (TWSA) greenness changes Hexi Corridor, an region northwestern China consisting of three inland river basins—Shule, Heihe, Shiyang—from 2002 2022. Utilizing TWSA data from GRACE/GRACE-FO satellites MODIS Enhanced Vegetation Index (EVI) data, we applied a trend analysis partial correlation statistical techniques assess spatiotemporal patterns their drivers across varying aridity gradients land cover types. results reveal significant decline Corridor (−0.10 cm/year, p < 0.01), despite modest increase precipitation (1.69 mm/year, = 0.114). spatial shows that deficits are most pronounced northern Shiyang Basin (−600 −300 cm cumulative TWSA), while southern Qilian Mountain exhibit accumulation (0 800 cm). greening strongest irrigated croplands, particularly hyper-arid area. highlights distinct drivers: wetter semi-humid semi-arid regions, plays dominant role driving trends. Such rainfall dominance gives way temperature- human-dominated regions. decoupling importance irrigation activities warming-induced atmospheric demand co-driving These findings suggest expansion cause satellite-observed greening, it exacerbates stress through increased evapotranspiration groundwater depletion, water-limited zones. reveals complex drylands, emphasizing need holistic view dryland context global warming, escalating freshwater resources, efforts achieving sustainable development.

Language: Английский

Citations

1
Comparison between computer recognition and manual measurement methods for the estimation of leaf area DOI
Youying Mu, Ke He, Peijian Shi

et al.

Annals of Botany, Journal Year: 2024, Volume and Issue: 134(3), P. 501 - 510

Published: June 3, 2024

Abstract Background and Aims Leaf area (A) is a crucial indicator of the photosynthetic capacity plants. The Montgomery equation (ME), which hypothesizes that A proportional to product leaf length (L) width (W), valid tool for non-destructively measuring many broadleaved At present, methods used compute L W ME can be broadly divided into two kinds: using computer recognition manually. However, potential difference in prediction accuracy either method has not been thoroughly examined previous studies. Methods In present study, we measured 540 Alangium chinense leaves, 489 Liquidambar formosana leaves 215 Liriodendron × sinoamericanum utilizing manual measurement determine W. was fit data determined by methods, goodness fits were compared. errors analysed examining correlations with symmetry indices (areal ratio left side right side, standardized index bilateral asymmetry), as well shape complexity (the dissection index). Key Results results indicate there neglectable estimation between methods. This further validates an effective estimating tree species, including those lobes. Additionally, significantly influenced A. Conclusions These show use field are both feasible, although influence should considered when applying estimate future.

Language: Английский

Citations

7
Multi-Feature Driver Variable Fusion Downscaling TROPOMI Solar-Induced Chlorophyll Fluorescence Approach DOI Creative Commons

Jinrui Fan,

Xiaoping Lu, Guosheng Cai

et al.

Agronomy, Journal Year: 2025, Volume and Issue: 15(1), P. 133 - 133

Published: Jan. 8, 2025

Solar-induced chlorophyll fluorescence (SIF), as a direct indicator of vegetation photosynthesis, offers more accurate measure plant photosynthetic dynamics than traditional indices. However, the current SIF satellite products have low spatial resolution, limiting their application in fine-scale agricultural research. To address this, we leveraged MODIS data at 1 km including bands b1, b2, b3, and b4, alongside indices such NDVI, EVI, NIRv, OSAVI, SAVI, LAI, FPAR, LST, covering October 2018 to May 2020 for Shandong Province, China. Using Random Forest (RF) model, downscaled from 0.05° based on invariant scaling theory, focusing winter wheat growth cycle. Various machine learning models, CNN, Stacking, Extreme Trees, AdaBoost, GBDT, were compared, with yielding best performance, achieving R2 = 0.931, RMSE 0.052 mW/m2/nm/sr, MAE 0.031 mW/m2/nm/sr 2018–2019 0.926, 0.058 0.034 2019–2020. The showed strong correlation TanSIF GOSIF (R2 > 0.8), consistent trends GPP further confirmed reliability product. Additionally, time series analysis Province’s wheat-growing areas revealed 0.8) between multiple indices, underscoring its utility regional crop monitoring.

Language: Английский

Citations

0
Solar-induced chlorophyll fluorescence and its relationship with photosynthesis during waterlogging in a maize field DOI
Yunfei Wu, Zhaoying Zhang, Linsheng Wu

et al.

Agricultural and Forest Meteorology, Journal Year: 2025, Volume and Issue: 363, P. 110404 - 110404

Published: Jan. 22, 2025

Language: Английский

Citations

0
The 2020 Heatwave Led to a Larger Enhancement in Annual Gross Primary Production in West Siberia Than in East Siberia DOI
Sung‐Bin Park, Chang‐Eui Park, Jin‐Soo Kim

et al.

Journal of Geophysical Research Biogeosciences, Journal Year: 2025, Volume and Issue: 130(2)

Published: Jan. 29, 2025

Abstract Spring and summer vegetation productivity in Siberia shows opposing responses to warmer spring. warming causes excessive growth earlier start of photosynthesis, enhancing However, this leads reduced the following season (i.e., summer) through soil moisture depletion. To understand how an exceptional spring heatwave (HW) affected ecosystem carbon uptake, we investigated spatiotemporal cascade gross primary production (GPP) multiple climate variables over 2020, using a satellite‐retrieved GPP product (GOSIF‐GPP) ERA5‐Land reanalysis data set for 2001–2020. Results showed positive impact anomalous on annual (GPP ann ). from GOSIF‐GPP West (55°–70°N, 50°–90°E) was enhanced by up 10% above 2001–2019 average despite continued dry conditions May August. In East (55–70°N, 90–130°E), increases June were sufficient compensate marked reduction July due negative anomaly radiation. addition, higher sensitivity temperature than suggests that increase coupled with strong respective might be more pronounced western region, as observed 2020. Our results indicate trend spring, combined possible extreme heat events, could elevate uptake Siberia, particularly Siberia. Further, case study HW event occurred 2020 can provide useful insight understanding future change

Language: Английский

Citations

0
Investigation of factors that affect post-fire recovery of photosynthetic activity at global scale DOI Creative Commons
Yicheng Shen, I. Colin Prentice, Sandy P. Harrison

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 171, P. 113206 - 113206

Published: Feb. 1, 2025

Language: Английский

Citations

0
VPM v3.0 model: improved estimates of terrestrial gross primary production from individual eddy flux tower sites to the globe DOI Creative Commons
Li Pan, Xiangming Xiao,

Baihong Pan

et al.

Journal of Remote Sensing, Journal Year: 2025, Volume and Issue: 5

Published: Jan. 1, 2025

Accurate estimation of gross primary production (GPP) terrestrial vegetation is crucial for comprehending the carbon dynamics. To date, there still no consensus on magnitude and seasonality global GPP among major products, underscoring necessity to improve models higher accuracy estimates. Here, we introduce an improved Vegetation Photosynthesis Model (VPM v3.0), which incorporates site-specific apparent optimum temperature photosynthesis, leaf-trait-based light absorption (flat leaf vs. needle leaf), water stress estimation. The VPM simulation driven by Moderate Resolution Imaging Spectroradiometer images ERA5-Land climate dataset. We evaluate v3.0 using from 205 eddy flux tower sites across 11 land cover types (1,658 site-years) (GPP EC ), as well TROPOspheric monitoring instrument (TROPOMI) solar-induced fluorescence (SIF) product 2018 2021. slope, R 2 , root mean square error between VPM-v3 ) are 0.97, 0.78, 1.46 gC m −2 day −1 respectively. shows high temporal consistency with TROPOMI SIF. provides estimates at most evaluated than v2.0. Comparisons other products reveal both spatial–temporal discrepancies. These findings clearly indicate in estimating GPP, making it suitable generating datasets.

Language: Английский

Citations

0
Increasing susceptibility of vegetation productivity to compound drought from 2001 to 2020 DOI Creative Commons
Jiwang Tang, Ben Niu, Z. Hu

et al.

Global and Planetary Change, Journal Year: 2025, Volume and Issue: unknown, P. 104826 - 104826

Published: April 1, 2025

Language: Английский

Citations

0
Non-uniform climatic responses of land surface phenology derived from optical-, fluorescence-, and microwave-based satellite observations DOI
Wenjun Qu, Lu Hu, Josep Peñuelas

et al.

Remote Sensing of Environment, Journal Year: 2025, Volume and Issue: 325, P. 114793 - 114793

Published: May 4, 2025

Language: Английский

Citations

0