두 개의 기하학적 관찰 구성을 통합하는 자동화된 지상 기반 초 분광 시스템 개발

학위논문(석사) -- 서울대학교대학원 : 농업생명과학대학 협동과정 농림기상학, 2022. 8. 류영렬.Hyperspectral remote sensing is becoming a powerful tool for monitoring vegetation structure and functions. Especially, Sun-Induced chlorophyll fluorescence (SIF) and canopy reflectance monitoring have been widely used to understand physiological and structural changes in plants, and field spectroscopy has become established as an important technique for providing high spectral-, temporal resolution in-situ data as well as providing a means of scaling-up measurements from small areas to large areas. Recently, several tower-based remote sensing systems have been developed. However, in-situ studies have only monitored either BRF or BHR and there is still a lack of understanding of the geometric and optical differences in remote sensing observations, particularly between hemispheric-conical and bi-hemispheric configurations. Here, we developed an automated ground-based field spectroscopy system measuring far-red SIF and canopy hyperspectral reflectance (400–900 nm) with hemispherical-conical as well as bi-hemispherical configuration. To measure both bi-hemispherical and hemispherical-conical reflectance, we adopted a rotating prism by using a servo motor to face three types of ports that measure incoming-, outgoing irradiance and outgoing radiance. A white diffuse glass and collimating lens were used to measure the irradiance, and a collimating lens was used to measure the radiance with a field of view of 20 degrees. Additionally, we developed data management protocol that includes radiometric-, and wavelength calibrations. Finally, we report how BRF and BHR data differ in this system and investigated SIF and vegetation index from both hemispherical-conical and bi-hemispherical observation configurations for their ability to track GPP in the growing seasons of a deciduous broad-leaved forests.초 분광 원격 감지는 식생 구조와 기능을 모니터링하는 강력한 도구가 되고 있다. 특히, 식물의 생리적, 구조적 변화를 이해하기 위해 태양광 유도 엽록소 형광 (SIF)과 캐노피 반사율 모니터링이 널리 이용되고 있다. 현장 분광법은 높은 스펙트럼, 시간 분해능 현장 데이터를 제공하고 작은 영역에서 큰 영역으로 측정을 확장하는 수단을 제공하기 위한 중요한 기술로 확립되었다. 그러나, 수많은 연구가 현장 분광 시스템을 개발했지만, 반구-원추형 및 양 반구 구성 간의 원격 감지 관찰의 기하학적 및 광학적 차이에 대한 이해가 부족할 뿐만 아니라 초 분광 데이터를 지속적으로 수집하는 것은 여전히 어렵다. 우리는 반구형-원추형 및 이중 반구형 구성으로 원적외선 태양광 유도 엽록소 형광 및 캐노피 초 분광 반사율(400–900nm)을 측정하는 자동화된 지상 기반 필드 분광 시스템을 개발했다. 양방향 반사율과 반구형 원추형 반사율을 모두 측정하기 위해 서보 모터를 사용하여 프리즘을 회전하여 세가지 타입의 포트를 측정한다. 각 포트는 들어오는 복사 조도, 나가는 복사 조도 및 나가는 복사를 측정하는 세 가지 유형의 포트다. 조사조도는 백색확산유리와 굴절 렌즈를 사용하였고, 굴절 렌즈를 이용하여 조도를 측정하였다. 또한, 우리는 방사 측정 및 파장 교정을 포함하는 데이터 관리 프로토콜을 개발했다. 마지막으로, 우리는 낙엽 활엽수림의 성장기에 이 시스템에서 측정된 BRF와 BHR 데이터가 어떻게 다른지 보고하였다.Chapter 1. Introduction １ 1.1. Study Background １ 1.2. Purpose of Research ４ Chapter 2. Developing and Testing of Hyperspectral System ５ 2.1 Development of Hyperspectral System and Data Collecting ５ 2.1.1 The Central Control Unit and Spectrometer ５ 2.1.2 RotaPrism ７ 2.1.3 Data Collection ９ 2.3 Data Managing and Processing １１ 2.3.1 Preprocessing of Spectra １１ 2.3.2 Radiometric Calibration １３ 2.3.3 Retrieval of SIF and Vegetation Indices １５ 2.4 Ancillary Measurements to Monitoring Ecosystem. １７ Chapter 3. Application of Hyperspectral System １９ 3.1 Study Site １９ 3.2 Diurnal and Variation of Spectral Reflectance and SIF ２０ 3.3 Seasonal Variation of Vegetation Index and SIF ２２ 3.4 Broader Implications ２４ Chapter 4. Summary and Conclusions ２６ Bibliography ２８석

EUROSPEC : at the interface between remote-sensing and ecosystem CO2 flux measurements in Europe

Resolving the spatial and temporal dynamics of gross primary productivity (GPP) of terrestrial ecosystems across different scales remains a challenge. Remote sensing is regarded as the solution to upscale point observations conducted at the ecosystem level, using the eddy covariance (EC) technique, to the landscape and global levels. In addition to traditional vegetation indices, the photochemical reflectance index (PRI) and the emission of solar-induced chlorophyll fluorescence (SIF), now measurable from space, provide a new range of opportunities to monitor the global carbon cycle using remote sensing. However, the scale mismatch between EC observations and the much coarser satellite-derived data complicate the integration of the two sources of data. The solution is to establish a network of in situ spectral measurements that can act as a bridge between EC measurements and remote-sensing data. In situ spectral measurements have already been conducted for many years at EC sites, but using variable instrumentation, setups, and measurement standards. In Europe in particular, in situ spectral measurements remain highly heterogeneous. The goal of EUROSPEC Cost Action ES0930 was to promote the development of common measuring protocols and new instruments towards establishing best practices and standardization of these measurements. In this review we describe the background and main tradeoffs of in situ spectral measurements, review the main results of EUROSPEC Cost Action, and discuss the future challenges and opportunities of in situ spectral measurements for improved estimation of local and global estimates of GPP over terrestrial ecosystems.Peer reviewe

Can upscaling ground nadir SIF to eddy covariance footprint improve the relationship between SIF and GPP in croplands?

Ground solar-induced chlorophyll fluorescence (SIF) is important for the mechanistic understanding of the dynamics of vegetation gross primary production (GPP) at fine spatiotemporal scales. However, eddy covariance (EC) observations generally cover larger footprint areas than ground SIF observations (a bare fiber with nadir), and this footprint mismatch between nadir SIF and GPP could complicate the canopy SIF-GPP relationships. Here, we upscaled nadir SIF observations to EC footprint and investigated the change in SIF-GPP relationships after the upscaling in cropland. We included 13 site-years data in our study, with seven site-years corn, four siteyears soybeans, and two site-years miscanthus, all located in the US Corn Belt. All sites’ crop nadir SIF observations collected from the automated FluoSpec2 system (a hemispheric-nadir system) were upscaled to the GPP footprint-based SIF using vegetation indices (VIs) calculated from high spatiotemporal satellite reflectance data. We found that SIF-GPP relationships were not substantially changed after upscaling nadir SIF to GPP footprint at our crop sites planted with corn, soybean, and miscanthus, with R2 change after the upscaling ranging from -0.007 to 0.051 and root mean square error (RMSE) difference from -0.658 to 0.095 umol m-2 s-1 relative to original nadir SIF-GPP relationships across all the site-years. The variation of the SIF-GPP relationship within each species across different site-years was similar between the original nadir SIF and upscaled SIF. Different VIs, EC footprint models, and satellite data led to marginal differences in the SIF-GPP relationships when upscaling nadir SIF to EC footprint. Our study provided a methodological framework to correct this spatial mismatch between ground nadir SIF and GPP observations for croplands and potentially for other ecosystems. Our results also demonstrated that the spatial mismatch between ground nadir SIF and GPP might not significantly affect the SIF-GPP relationship in cropland that are largely homogeneous

Ground-Based Optical Measurements at European Flux Sites: A Review of Methods, Instruments and Current Controversies

This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903—“Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe” that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites

Modelling, Monitoring and Validation of Plant Phenology Products

Phänologie, die Lehre der periodisch wiederkehrenden Entwicklungserscheinungen in der Natur, hat sich in den letzten Jahrzehnten zu einem wichtigen Teilgebiet der Klimaforschung entwickelt. Einer der Haupteffekte der globalen Erwärmung ist die Veränderung der Wachstumsmuster und Fortpflanzungsgewohnheiten von Pflanzen, und somit veränderte Phänologie. Um die Auswirkungen der Klimaveränderung auf wildwachsende sowie Kulturpflanzen vorherzusagen, werden phänologische Modelle angewendet, verbessert und validiert. Dabei ist Wissen über den aktuellen Stand der Vegetation notwendig, welches aus Beobachtungen und fernerkundliche Messungen gewonnen wird. Die hier präsentierte Arbeit befasst sich mit dem Verständnis der Zusammenhänge zwischen fernerkundlichen Messungen und phänologischen Stadien und somit den Herausforderungen der modernen phänologischen Forschung: Der Vorhersage der Phänologie durch Modellierungsansätze, der Beobachtung der Phänologie mit optischen boden- und satellitengestützten Sensoren und der Validierung phänologischer Produkte.Phenology, the study of recurring life cycle events of plants and animals has emerged as an important part of climate change research within the last decades. One of the main effects of global warming on vegetation is altered phenology, since plants have to modify their growth patterns and reproduction habits as reaction to changing environmental conditions. Forecasting phenology, thus phenological modelling, is a timely challenge given the necessity to predict the impact of global warming on wild-growing species and agricultural crops. However, assessing the present state of vegetation, thus phenological monitoring, is essential to update and validate model results. An improved comprehension of the relationships between plant phenology and remotely sensed products is crucial to interpret these results. Consequently, the presented thesis deals with the main challenges faced in modern phenology research, covering phenological forecasting with a modelling approach, satellite-based phenology extraction, and near-surface long-term monitoring of phenology

Automated proximal sensing for estimation of the bidirectional reflectance distribution function in a Mediterranean tree-grass ecosystem

Premio Extraordinario de Doctorado de la UAH en el año académico 2015-2016Los sistemas automáticos de proximal sensing permiten adquirir información espectral de las cubiertas terrestres elevada frecuencia temporal, que puede relacionarse con observaciones remotas o de otros tipos de sensores como los sistemas de eddy covariance. Si bien inicialmente los sistemas automáticos empleaban sensores multi-banda, en los últimos años se ha incrementado el uso de sensores hiperespectrales. Si bien estos sensores ofrecen información redundante y de alta resolución espectral, las mediciones están sujetas a múltiples fuentes de incertidumbre; tanto instrumentales (dependencias de la temperatura o el nivel de señal) como direccionales (dependencia de la geometría de observación e iluminación). Las dependencias instrumentales pueden ser minimizadas, por ejemplo, controlando la temperatura del instrumento o el nivel de señal registrado. En otros casos, es necesario parametrizar y emplear modelos para corregir los datos. En la presente tesis doctoral los capítulos 1 al 3 presentan la caracterización completa de un espectrómetro de campo instalado en un sistema automático. Los capítulos 1 y 2 analizan las fuentes de no linealidad en este instrumento, una de las cuales no había sido anteriormente descrita en este tipo de instrumentos. El tercer capítulo muestra el conjunto completo de modelos de corrección de los efectos instrumentales y la cadena de procesado correspondiente. Por otro lado, los sistemas automáticos se enfrentan a efectos direccionales ya que adquieren mediciones continuamente durante el ciclo solar diario y bajo cualquier condición de iluminación. Esto maximiza los rangos de los ángulos de iluminación y también de la fracción difusa de la irradiancia. Esta variabilidad de condiciones de iluminación, combinada con una variación de los ángulos de observación permite obtener la información necesaria para caracterizar las respuestas direccionales de la cubierta observada. Algunos sistemas automáticos multi-angulares ya han sido empleados para realizar esta caracterización mediante la estimación de la Función de Distribución de Reflectividad Bidireccional (BRDF) en ecosistemas homogéneos. Sin embargo, esto no se ha conseguido aún en áreas heterogéneas, como es el caso de los ecosistemas tree-grass o de sabana. Así mismo, los trabajos previos no han considerado los efectos de la radiación difusa en el estudio del BRDF. En el capítulo 4 proponemos una metodología que permite desmezclar y caracterizar simultáneamente la función de distribución de reflectividad hemisférica-direccional de las dos cubiertas de vegetación presentes en el ecosistema, pasto y arbolado. También se analizan los efectos de las diferentes características del método. Finalmente, los resultados se escalan y se comparan con productos globales de satélite como el producto BRDF de MODIS. La conclusión obtenida es que se requieren más esfuerzos en el desarrollo y caracterización de sensores hiperespectrales instalados en sistemas automáticos de campo. Estos sistemas deberían adoptar configuraciones multi-angulares de modo que puedan caracterizarse las respuestas direccionales. Para ello, será necesario considerar los efectos de la radiación difusa; y en algunos casos también la heterogeneidad de la escena

Automated proximal sensing for estimation of the bidirectional reflectance distribution function in a Mediterranean tree-grass ecosystem

Premio Extraordinario de Doctorado de la UAH en el año académico 2015-2016Los sistemas automáticos de proximal sensing permiten adquirir información espectral de las cubiertas terrestres elevada frecuencia temporal, que puede relacionarse con observaciones remotas o de otros tipos de sensores como los sistemas de eddy covariance. Si bien inicialmente los sistemas automáticos empleaban sensores multi-banda, en los últimos años se ha incrementado el uso de sensores hiperespectrales. Si bien estos sensores ofrecen información redundante y de alta resolución espectral, las mediciones están sujetas a múltiples fuentes de incertidumbre; tanto instrumentales (dependencias de la temperatura o el nivel de señal) como direccionales (dependencia de la geometría de observación e iluminación). Las dependencias instrumentales pueden ser minimizadas, por ejemplo, controlando la temperatura del instrumento o el nivel de señal registrado. En otros casos, es necesario parametrizar y emplear modelos para corregir los datos. En la presente tesis doctoral los capítulos 1 al 3 presentan la caracterización completa de un espectrómetro de campo instalado en un sistema automático. Los capítulos 1 y 2 analizan las fuentes de no linealidad en este instrumento, una de las cuales no había sido anteriormente descrita en este tipo de instrumentos. El tercer capítulo muestra el conjunto completo de modelos de corrección de los efectos instrumentales y la cadena de procesado correspondiente. Por otro lado, los sistemas automáticos se enfrentan a efectos direccionales ya que adquieren mediciones continuamente durante el ciclo solar diario y bajo cualquier condición de iluminación. Esto maximiza los rangos de los ángulos de iluminación y también de la fracción difusa de la irradiancia. Esta variabilidad de condiciones de iluminación, combinada con una variación de los ángulos de observación permite obtener la información necesaria para caracterizar las respuestas direccionales de la cubierta observada. Algunos sistemas automáticos multi-angulares ya han sido empleados para realizar esta caracterización mediante la estimación de la Función de Distribución de Reflectividad Bidireccional (BRDF) en ecosistemas homogéneos. Sin embargo, esto no se ha conseguido aún en áreas heterogéneas, como es el caso de los ecosistemas tree-grass o de sabana. Así mismo, los trabajos previos no han considerado los efectos de la radiación difusa en el estudio del BRDF. En el capítulo 4 proponemos una metodología que permite desmezclar y caracterizar simultáneamente la función de distribución de reflectividad hemisférica-direccional de las dos cubiertas de vegetación presentes en el ecosistema, pasto y arbolado. También se analizan los efectos de las diferentes características del método. Finalmente, los resultados se escalan y se comparan con productos globales de satélite como el producto BRDF de MODIS. La conclusión obtenida es que se requieren más esfuerzos en el desarrollo y caracterización de sensores hiperespectrales instalados en sistemas automáticos de campo. Estos sistemas deberían adoptar configuraciones multi-angulares de modo que puedan caracterizarse las respuestas direccionales. Para ello, será necesario considerar los efectos de la radiación difusa; y en algunos casos también la heterogeneidad de la escena

Measuring and modelling fAPAR for satellite product validation

This thesis presents a comprehensive approach to satellite Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) product validation. This draws on 3D radiative transfer modelling and metrology to characterise the biases associated with a satellite fAPAR algorithm and the uncertainty associated with fAPAR estimates. This extends existing approaches which tend to assume that the in situ measurement technique produces the same fAPAR quantity as the satellite product. The validation procedure involves creating a closure experiment where every aspect of the satellite product definition and its associated assumptions can be tested from the perspective of the in situ and satellite sensors. The intrinsic differences created by the satellite product assumptions are also assessed, where a new reference is created. This is known as the “true” fAPAR since it is perfectly knowable within the context of the radiative transfer model used. Correction factors between the in situ and satellite-derived fAPAR are created to correct data collected over Wytham Woods. The results indicate that the corrections reduce differences of >10% to near zero. However, the uncertainty estimates for the satellite-derived fAPAR show that it does not meet the requirements given by Global Climate Observing System (GCOS) (≤(10% or 0.05)). The wider implications of the retrieved uncertainties are also presented showing that it is unlikely that the GCOS requirements associated with downstream applications that use satellite fAPAR can be met currently. This work represents an important step forward in the validation of satellitederived fAPAR because it is the first time that the absence of satellite and in situ data uncertainty and traceability, and satellite product definition differences have been addressed. This paves the way for the improvement of satellite fAPAR products because their uncertainties can now be quantified effectively and their validation conducted fairly, meaning there is now a benchmark to base improvements on

Improving the Performance of 3-D Radiative Transfer Model FLIGHT to Simulate Optical Properties of a Tree-Grass Ecosystem

The 3-D Radiative Transfer Model (RTM) FLIGHT can represent scattering in open forest or savannas featuring underlying bare soils. However, FLIGHT might not be suitable for multilayered tree-grass ecosystems (TGE), where a grass understory can dominate the reflectance factor (RF) dynamics due to strong seasonal variability and low tree fractional cover. To address this issue, we coupled FLIGHT with the 1-D RTM PROSAIL. The model is evaluated against spectral observations of proximal and remote sensing sensors: the ASD Fieldspec® 3 spectroradiometer, the Airborne Spectrographic Imager (CASI) and the MultiSpectral Instrument (MSI) onboard Sentinel-2. We tested the capability of both PROSAIL and PROSAIL+FLIGHT to reproduce the variability of different phenological stages determined by 16-year time series analysis of Moderate Resolution Imaging Spectroradiometer-Normalized Difference Vegetation Index (MODIS-NDVI). Then, we combined concomitant observations of biophysical variables and RF to test the capability of the models to reproduce observed RF. PROSAIL achieved a Relative Root Mean Square Error (RRMSE) between 6% to 32% at proximal sensing scale. PROSAIL+FLIGHT RRMSE ranged between 7% to 31% at remote sensing scales. RRMSE increased in periods when large fractions of standing dead material mixed with emergent green grasses —especially in autumn—; suggesting that the model cannot represent the spectral features of this material. PROSAIL+FLIGHT improves RF simulation especially in summer and at mid-high view angles.This research was funded by Ministerio de Economía y Competitividad, CGL2012-34383 and CGL2015-G9095-R and Ministerio de Educación, Cultura y Deporte, FPU15/03558.Peer reviewe

Passive direct measurement of sun-induced chlorophyll fluorescence spectrum from in vivo leaves

The fluorescence of chlorophyll in vegetation is a weak signal emitted between 650 and 850 nm that is mixed with the much more intense light reflected by the leaf, which is why active methods are commonly used (through the additional contribution of controlled artificial light) or using indirect measurements instead. So, the measurement is provided just in relative units in the first case, or the accuracy of the estimate in the second case is uncertain without proper direct validation. The Thesis presents a new device, called FluoWat, for passive measurement that allows direct measurement of the fluorescence emission of leaves in vivo under natural conditions in the field with sunlight. And it is part of the activities supporting the preparation of ESA’s FLEX mission for the global monitoring of vegetation fluorescence. The device consists of a small dark chamber implemented as a clip, so that the leaf can be housed inside without damaging it, with an opening to illuminate the sample by pointing at the sun, and a sliding filter holder with a low-pass filter that blocks sunlight in the same spectral range as fluorescence is emitted while allowing the excitation light to pass through, then a spectroradiometer connected to the clip measures the fluorescence spectrum without interference from sunlight. In addition, it is possible to measure the reflectance and transmittance factors of the leaf, which allows determining the absorptance, necessary to determine the photosynthetically active radiation (PAR) that has been absorbed (APAR). An essential parameter to properly interpret the fluorescence signal in relation to photosynthesis. Similarly, the reflectance and transmittance spectra in the visible range make it possible to determine the degree of photoprotection of the leaf and/or its chlorophyll content. A sensitivity analysis of different factors likely to affect the measurement has been carried out, such as the residual light that passes through the filter, or the effect of transients on fluorescence emission, among others. Processing methods have been developed to mitigate their effects on the fluorescence measurement, increasing the accuracy of the results. Finally, a series of experiments are presented in which the system is put to the test and that illustrate how, with the measurements provided by this new device, a better understanding of the dynamics of fluorescence emission while the vegetation adapts to different illumination changes, levels of stress and changing environmental conditions