Estimating rice leaf area index at multiple growth stages with Sentinel-2 data: An evaluation of different retrieval algorithms DOI
Tongzhou Wu, Zhewei Zhang, Qi Wang

et al.

European Journal of Agronomy, Journal Year: 2024, Volume and Issue: 161, P. 127362 - 127362

Published: Sept. 16, 2024

Language: Английский

Evaluation of spatial and temporal variability in Sentinel-2 surface reflectance on a rice paddy landscape DOI Creative Commons

WonSeok Choi,

Youngryel Ryu, Juwon Kong

et al.

Agricultural and Forest Meteorology, Journal Year: 2025, Volume and Issue: 363, P. 110401 - 110401

Published: Feb. 8, 2025

Language: Английский

Citations

1
Evaluating the sensitivity of vegetation indices to leaf area index variability at individual tree level using multispectral drone acquisitions DOI

Xianchao Tian,

Xingyu Jia,

Yizhuo Da

et al.

Agricultural and Forest Meteorology, Journal Year: 2025, Volume and Issue: 364, P. 110441 - 110441

Published: Feb. 17, 2025

Language: Английский

Citations

0
Geometric Alignment Improves Wheat NDVI Calculation from Ground-Based Multispectral Images DOI Creative Commons
Md Asrakul Haque, Md Nasim Reza, Md Rejaul Karim

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(5), P. 743 - 743

Published: Feb. 20, 2025

Multispectral sensors are integral to vegetation analysis, particularly in the calculation of various indices (VIs). The use integrated multispectral has become prevalent research, although their effectiveness is influenced by several factors. This highlights need for ongoing research into enhancement techniques improve accuracy and reliability status estimation. study investigated impact field view (FOV) variability on normalized differential index (NDVI) using a sensor. Data were collected from wheat at four growth stages (GS) (GS 1, GS 2, 3, 4, 10, 34, 70, 84 days after sowing (DAS), respectively) mounted around 100 cm above crop canopy. An active sensor was used provide reference data assessing measurement. A program developed Python (ver. 3.10) programming language process global navigation satellite system (GNSS) coordinates segment images align with FOV extracting reflectance NDVI calculation. results showed that proper alignment significantly improved regression metrics (R2 RMSE) all stages, R2 improvements ranging 3% 33%, RMSE reductions 0.03 0.06, respectively. high vegetative stage less affected due misalignment. These promising toward improving accuracy, especially during early mid-growth crop.

Language: Английский

Citations

0
Retrieving the chlorophyll content of individual apple trees by reducing canopy shadow impact via a 3D radiative transfer model and UAV multispectral imagery DOI Creative Commons
Chengjian Zhang, Zhibo Chen, Riqiang Chen

et al.

Plant Phenomics, Journal Year: 2025, Volume and Issue: unknown, P. 100015 - 100015

Published: March 1, 2025

Language: Английский

Citations

0
Advancing Ecosystem Monitoring with Global High-Resolution Maps of Vegetation Biophysical Properties DOI
Felix Specker, Anna K. Schweiger, Jean‐Baptiste Féret

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Abstract Environmental restoration projects are crucial for ecosystem recovery and biodiversity conservation but monitoring progress at a global scale poses substantial challenges. Publicly funded satellite missions such as Sentinel-2 have great potential to transform due their high spatial temporal resolution if they can be reliably linked characteristics. Here, we present the first global, analysis-ready, decametric maps three key vegetation biophysical properties on an annual basis, including effective leaf area index (LAIe), fraction of absorbed photosynthetically active radiation (FAPAR), fractional cover (FCOVER). We utilize hybrid retrieval approach physically based radiative transfer model PROSAIL directly estimate variables from multispectral images, making use multiple observations during peak growing season. All retrievals aggregated into mean values, standard deviations, number taken this period. The available 20 m, 100 1000 m years 2019 2024, totaling approximately TB analysis-ready data, validated using in-situ data Ground-Based Observations Validation (GBOV). these provides new opportunities monitoring, enabling more assessments efforts contributing development standardized frameworks.

Language: Английский

Citations

0
On the consistency and stability of vegetation biophysical variables retrievals from Landsat-8/9 and Sentinel-2 DOI
Najib Djamai, Richard Fernandes,

Lixin Sun

et al.

ISPRS Journal of Photogrammetry and Remote Sensing, Journal Year: 2025, Volume and Issue: 224, P. 329 - 347

Published: April 17, 2025

Language: Английский

Citations

0
Estimating rice leaf area index at multiple growth stages with Sentinel-2 data: An evaluation of different retrieval algorithms DOI
Tongzhou Wu, Zhewei Zhang, Qi Wang

et al.

European Journal of Agronomy, Journal Year: 2024, Volume and Issue: 161, P. 127362 - 127362

Published: Sept. 16, 2024

Language: Английский

Citations

3