Ecophysiological variables retrieval and early stress detection: insights from a synthetic spatial scaling exercise DOI Creative Commons
Javier Pacheco‐Labrador, Maria Pilar Cendrero‐Mateo, Shari Van Wittenberghe

и другие.

International Journal of Remote Sensing, Год журнала: 2024, Номер unknown, С. 1 - 26

Опубликована: Окт. 28, 2024

The ability to access physiologically driven signals, such as surface temperature, photochemical reflectance index (PRI), and sun-induced chlorophyll fluorescence (SIF), through remote sensing (RS) are exciting developments for vegetation studies. Accessing this ecophysiological information requires considering processes operating at scales from the top-of-the-canopy photosystems, adding complexity compared index-based approaches. To investigate maturity knowledge of growing RS community in area, COST Action CA17134 SENSECO organized a Spatial Scaling Challenge (SSC). participants were asked retrieve four key variables field each maize wheat simulated campaign: leaf area (LAI), content (Cab), maximum carboxylation rate (Vcmax,25), non-photochemical quenching (NPQ). campaign data included hyperspectral optical, thermal SIF imagery, together with ground sampling variables. Non-parametric methods that combined multiple spectral domains measurements used most often, thereby indirectly performing photosystem scaling. LAI Cab reliably retrieved cases, whereas Vcmax,25 NPQ less accurately estimated demanded ancillary imagery. factors considered least by biophysical physiological canopy vertical profiles, spatial mismatch between sensors, temporal acquisition, measurement uncertainty. Furthermore, few developed maps into stress or provided deeper analysis their parameter retrievals. SSC shows that, despite advances statistical physically based models, should improve how integrated scaled space time. We expect work will guide newcomers support robust research field.

Язык: Английский

DART-based temporal and spatial retrievals of solar-induced chlorophyll fluorescence quantum efficiency from in-situ and airborne crop observations DOI Creative Commons
Omar Regaieg, Zbyněk Malenovský, Bastian Siegmann

и другие.

Remote Sensing of Environment, Год журнала: 2025, Номер 319, С. 114636 - 114636

Опубликована: Фев. 5, 2025

Язык: Английский

Процитировано

0
Integrating Diurnal Physiological and Structural Variations in SIF for Enhanced Daily Drought Detection in Maize DOI Creative Commons
Jin Wang, Zhigang Liu, Hao Jiang

и другие.

Remote Sensing, Год журнала: 2025, Номер 17(4), С. 565 - 565

Опубликована: Фев. 7, 2025

Daily water stress reflects the status of crops on a specific day, which is crucial for studying drought progression and guiding precision irrigation. However, accurately monitoring daily remains challenging, particularly when eliminating impact historical normal growth. Recent studies have demonstrated that diurnal characteristics crop canopy obtained via remote sensing techniques can be used to assess levels effectively. Remote observations, such as solar-induced chlorophyll fluorescence (SIF) reflectance, offer information structure, physiology, or their combination. sensitivity different structural, physiological, combined variables unclear. We investigated this issue continuous measurements active fluorescence, leaf rolling, spectra maize under irrigation conditions. The results indicated with increasing stress, vegetation exhibited significant coordinated variations in both structure physiology. influence was minimal morning but peaked at noon. morning-to-noon ratio (NMR) apparent SIF yield (SIFy), only effect photosynthetically radiation (PAR) eliminated structural physiological incorporated, highest variations. This NMR SIFy followed by normalized difference index (NDVI) emission efficiency (ΦFcanopy) correction (FCVI) method, primarily reflect information, respectively. study highlights advantages utilizing levels.

Язык: Английский

Процитировано

0
Research on the Red Sif Downscaling Method and its Application Based on Kernel Ndvi DOI
Xia Jing, Jiaqi Zhao, Xinjie Liu

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Improved GPP upscaling from instantaneous measurements to daily sums using the light-use-efficiency-based model DOI
Ruonan Chen, Xinjie Liu, Liangyun Liu

и другие.

Agricultural and Forest Meteorology, Год журнала: 2025, Номер 368, С. 110529 - 110529

Опубликована: Апрель 12, 2025

Язык: Английский

Процитировано

0
Downscaling the full-spectrum solar-induced fluorescence emission signal of a mixed crop canopy to the photosystem level using the hybrid approach DOI Creative Commons

Julie Krämer,

Bastian Siegmann, Antony Oswaldo Castro

и другие.

Remote Sensing of Environment, Год журнала: 2025, Номер 324, С. 114739 - 114739

Опубликована: Апрель 14, 2025

Язык: Английский

Процитировано

0
Improving the accuracy of SIF quantified from moderate spectral resolution airborne hyperspectral imager using SCOPE: assessment with sub-nanometer imagery DOI Creative Commons
A. Belwalkar, T. Poblete, A. Hornero

и другие.

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2024, Номер 134, С. 104198 - 104198

Опубликована: Окт. 7, 2024

Язык: Английский

Процитировано

1
Ecophysiological variables retrieval and early stress detection: insights from a synthetic spatial scaling exercise DOI Creative Commons
Javier Pacheco‐Labrador, Maria Pilar Cendrero‐Mateo, Shari Van Wittenberghe

и другие.

International Journal of Remote Sensing, Год журнала: 2024, Номер unknown, С. 1 - 26

Опубликована: Окт. 28, 2024

The ability to access physiologically driven signals, such as surface temperature, photochemical reflectance index (PRI), and sun-induced chlorophyll fluorescence (SIF), through remote sensing (RS) are exciting developments for vegetation studies. Accessing this ecophysiological information requires considering processes operating at scales from the top-of-the-canopy photosystems, adding complexity compared index-based approaches. To investigate maturity knowledge of growing RS community in area, COST Action CA17134 SENSECO organized a Spatial Scaling Challenge (SSC). participants were asked retrieve four key variables field each maize wheat simulated campaign: leaf area (LAI), content (Cab), maximum carboxylation rate (Vcmax,25), non-photochemical quenching (NPQ). campaign data included hyperspectral optical, thermal SIF imagery, together with ground sampling variables. Non-parametric methods that combined multiple spectral domains measurements used most often, thereby indirectly performing photosystem scaling. LAI Cab reliably retrieved cases, whereas Vcmax,25 NPQ less accurately estimated demanded ancillary imagery. factors considered least by biophysical physiological canopy vertical profiles, spatial mismatch between sensors, temporal acquisition, measurement uncertainty. Furthermore, few developed maps into stress or provided deeper analysis their parameter retrievals. SSC shows that, despite advances statistical physically based models, should improve how integrated scaled space time. We expect work will guide newcomers support robust research field.

Язык: Английский

Процитировано

0