The High-Performance Airborne Imaging Spectrometer HyPlant—From Raw Images to Top-of-Canopy Reflectance and Fluorescence Products: Introduction of an Automatized Processing Chain

Siegmann, Bastian; Alonso, Luis; Celesti, Marco; Cogliati, Sergio; Colombo, R.; Damm, Alexander; Douglas, Sarah; Guanter, Luis; Hanuš, Jan; Kataja, Kari; Kraska, Thorsten; Matveeva, Maria; Moreno, José; Muller, Onno; Pikl, Miroslav; Pinto, Francisco; Quiros-Vargas, Juan; Rademske, Patrick; Rodriguez-Morene, Fernando; Sabater, Neus; Schickling, Anke; Schüttemeyer, Dirk; Zemek, František; Rascher, Uwe

doi:10.3390/rs11232760

Cited by 66 publications

(55 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Surface reflectance and vegetation indices were calculated after an atmospheric correction using the MODTRAN software package was applied. The atmospheric correction was performed using the MODTRAN software package (for an overview of the data processing of HyPlant, see Siegmann et al, 2019). For the reason of easier comparison of SIF values with other methods of this paper, the commonly used SIF units (mW m −2 sr −1 nm −1 ) were replaced by a substitute (nmol m −2 sr −1 s −1 ) using conversion factors of 6.35 for and 5.74 for F 687 and F 760 , respectively.…”

Section: Regional Level Measurements Of Reflectance and Sun-induced Fmentioning

confidence: 99%

CloudRoots: integration of advanced instrumental techniques and process modelling of sub-hourly and sub-kilometre land–atmosphere interactions

Arellano

Ney²,

Hartogensis

et al. 2020

Biogeosciences

Self Cite

View full text Add to dashboard Cite

Abstract. The CloudRoots field experiment was designed to obtain a comprehensive observational dataset that includes soil, plant, and atmospheric variables to investigate the interaction between a heterogeneous land surface and its overlying atmospheric boundary layer at the sub-hourly and sub-kilometre scale. Our findings demonstrate the need to include measurements at leaf level to better understand the relations between stomatal aperture and evapotranspiration (ET) during the growing season at the diurnal scale. Based on these observations, we obtain accurate parameters for the mechanistic representation of photosynthesis and stomatal aperture. Once the new parameters are implemented, the model reproduces the stomatal leaf conductance and the leaf-level photosynthesis satisfactorily. At the canopy scale, we find a consistent diurnal pattern on the contributions of plant transpiration and soil evaporation using different measurement techniques. From highly resolved vertical profile measurements of carbon dioxide (CO2) and other state variables, we infer a profile of the CO2 assimilation in the canopy with non-linear variations with height. Observations taken with a laser scintillometer allow us to quantify the non-steadiness of the surface turbulent fluxes during the rapid changes driven by perturbation of photosynthetically active radiation by cloud flecks. More specifically, we find 2 min delays between the cloud radiation perturbation and ET. To study the relevance of advection and surface heterogeneity for the land–atmosphere interaction, we employ a coupled surface–atmospheric conceptual model that integrates the surface and upper-air observations made at different scales from leaf to the landscape. At the landscape scale, we calculate a composite sensible heat flux by weighting measured fluxes with two different land use categories, which is consistent with the diurnal evolution of the boundary layer depth. Using sun-induced fluorescence measurements, we also quantify the spatial variability of ET and find large variations at the sub-kilometre scale around the CloudRoots site. Our study shows that throughout the entire growing season, the wide variations in stomatal opening and photosynthesis lead to large diurnal variations of plant transpiration at the leaf, plant, canopy, and landscape scales. Integrating different advanced instrumental techniques with modelling also enables us to determine variations of ET that depend on the scale where the measurement were taken and on the plant growing stage.

show abstract

Section: Regional Level Measurements Of Reflectance and Sun-induced Fmentioning

confidence: 99%

CloudRoots: integration of advanced instrumental techniques and process modelling of sub-hourly and sub-kilometre land–atmosphere interactions

Arellano

Ney²,

Hartogensis

et al. 2020

Biogeosciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…The georeferencing accuracy of the images is 1 pixel, i.e., 1 m. For this study, only data of the DUAL module, which covers the spectral range of 380-2500 nm, was used. Top-of-canopy radiances and relative reflectance was calculated using the laboratory calibration with the GalliGeo software package (SPECIM, Oulu, Finland) and radiative transfer modelling using MODTRAN 5 (for details on the processing of HyPlant imagery see [27]).…”

Section: Datasetmentioning

confidence: 99%

Multi-Scale Evaluation of Drone-Based Multispectral Surface Reflectance and Vegetation Indices in Operational Conditions

et al. 2020

Self Cite

View full text Add to dashboard Cite

Compact multi-spectral sensors that can be mounted on lightweight drones are now widely available and applied within the geo- and environmental sciences. However; the spatial consistency and radiometric quality of data from such sensors is relatively poorly explored beyond the lab; in operational settings and against other sensors. This study explores the extent to which accurate hemispherical-conical reflectance factors (HCRF) and vegetation indices (specifically: normalised difference vegetation index (NDVI) and chlorophyll red-edge index (CHL)) can be derived from a low-cost multispectral drone-mounted sensor (Parrot Sequoia). The drone datasets were assessed using reference panels and a high quality 1 m resolution reference dataset collected near-simultaneously by an airborne imaging spectrometer (HyPlant). Relative errors relating to the radiometric calibration to HCRF values were in the 4 to 15% range whereas deviations assessed for a maize field case study were larger (5 to 28%). Drone-derived vegetation indices showed relatively good agreement for NDVI with both HyPlant and Sentinel 2 products (R2 = 0.91). The HCRF; NDVI and CHL products from the Sequoia showed bias for high and low reflective surfaces. The spatial consistency of the products was high with minimal view angle effects in visible bands. In summary; compact multi-spectral sensors such as the Parrot Sequoia show good potential for use in index-based vegetation monitoring studies across scales but care must be taken when assuming derived HCRF to represent the true optical properties of the imaged surface.

show abstract

“…The results showed a good agreement between airborne SIF maps with ground observations, and the spatial diversity of SIF was clearly detected at the regional scale. Recently, the technical aspects of a unique HyPlant sensor such as the spectrometer, its processing chain, details about the modules, and different processing steps for final data products were covered by Siegmann et al [115].…”

Section: Hyplant-related Sif Studiesmentioning

confidence: 99%

Review of Top-of-Canopy Sun-Induced Fluorescence (SIF) Studies from Ground, UAV, Airborne to Spaceborne Observations

Bandopadhyay

Rastogi

Juszczak

2020

Sensors

View full text Add to dashboard Cite

Remote sensing (RS) of sun-induced fluorescence (SIF) has emerged as a promising indicator of photosynthetic activity and related stress from the leaf to the ecosystem level. The implementation of modern RS technology on SIF is highly motivated by the direct link of SIF to the core of photosynthetic machinery. In the last few decades, a lot of studies have been conducted on SIF measurement techniques, retrieval algorithms, modeling, application, validation, and radiative transfer processes, incorporating different RS observations (i.e., ground, unmanned aerial vehicle (UAV), airborne, and spaceborne). These studies have made a significant contribution to the enrichment of SIF science over time. However, to realize the potential of SIF and to explore its full spectrum using different RS observations, a complete document of existing SIF studies is needed. Considering this gap, we have performed a detailed review of current SIF studies from the ground, UAV, airborne, and spaceborne observations. In this review, we have discussed the in-depth interpretation of each SIF study using four RS platforms. The limitations and challenges of SIF studies have also been discussed to motivate future research and subsequently overcome them. This detailed review of SIF studies will help, support, and inspire the researchers and application-based users to consider SIF science with confidence.

show abstract

The High-Performance Airborne Imaging Spectrometer HyPlant—From Raw Images to Top-of-Canopy Reflectance and Fluorescence Products: Introduction of an Automatized Processing Chain

Cited by 66 publications

References 82 publications

CloudRoots: integration of advanced instrumental techniques and process modelling of sub-hourly and sub-kilometre land–atmosphere interactions

CloudRoots: integration of advanced instrumental techniques and process modelling of sub-hourly and sub-kilometre land–atmosphere interactions

Multi-Scale Evaluation of Drone-Based Multispectral Surface Reflectance and Vegetation Indices in Operational Conditions

Review of Top-of-Canopy Sun-Induced Fluorescence (SIF) Studies from Ground, UAV, Airborne to Spaceborne Observations

Contact Info

Product

Resources

About