2,345 research outputs found

    Diurnal and Seasonal Solar Induced Chlorophyll Fluorescence and Photosynthesis in a Boreal Scots Pine Canopy

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    Solar induced chlorophyll fluorescence has been shown to be increasingly an useful proxy for the estimation of gross primary productivity (GPP), at a range of spatial scales. Here, we explore the seasonality in a continuous time series of canopy solar induced fluorescence (hereafter SiF) and its relation to canopy gross primary production (GPP), canopy light use efficiency (LUE), and direct estimates of leaf level photochemical efficiency in an evergreen canopy. SiF was calculated using infilling in two bands from the incoming and reflected radiance using a pair of Ocean Optics USB2000+ spectrometers operated in a dual field of view mode, sampling at a 30 min time step using custom written automated software, from early spring through until autumn in 2011. The optical system was mounted on a tower of 18 m height adjacent to an eddy covariance system, to observe a boreal forest ecosystem dominated by Scots pine. (Pinus sylvestris) A Walz MONITORING-PAM, multi fluorimeter system, was simultaneously mounted within the canopy adjacent to the footprint sampled by the optical system. Following correction of the SiF data for O2 and structural effects, SiF, SiF yield, LUE, the photochemicsl reflectance index (PRI), and the normalized difference vegetation index (NDVI) exhibited a seasonal pattern that followed GPP sampled by the eddy covariance system. Due to the complexities of solar azimuth and zenith angle (SZA) over the season on the SiF signal, correlations between SiF, SiF yield, GPP, and LUE were assessed on SZ

    ๋‘ ๊ฐœ์˜ ๊ธฐํ•˜ํ•™์  ๊ด€์ฐฐ ๊ตฌ์„ฑ์„ ํ†ตํ•ฉํ•˜๋Š” ์ž๋™ํ™”๋œ ์ง€์ƒ ๊ธฐ๋ฐ˜ ์ดˆ ๋ถ„๊ด‘ ์‹œ์Šคํ…œ ๊ฐœ๋ฐœ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๋†์—…์ƒ๋ช…๊ณผํ•™๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ๋†๋ฆผ๊ธฐ์ƒํ•™, 2022. 8. ๋ฅ˜์˜๋ ฌ.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 (400โ€“900โ€ฏnm) 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.์ดˆ ๋ถ„๊ด‘ ์›๊ฒฉ ๊ฐ์ง€๋Š” ์‹์ƒ ๊ตฌ์กฐ์™€ ๊ธฐ๋Šฅ์„ ๋ชจ๋‹ˆํ„ฐ๋งํ•˜๋Š” ๊ฐ•๋ ฅํ•œ ๋„๊ตฌ๊ฐ€ ๋˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, ์‹๋ฌผ์˜ ์ƒ๋ฆฌ์ , ๊ตฌ์กฐ์  ๋ณ€ํ™”๋ฅผ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด ํƒœ์–‘๊ด‘ ์œ ๋„ ์—ฝ๋ก์†Œ ํ˜•๊ด‘ (SIF)๊ณผ ์บ๋…ธํ”ผ ๋ฐ˜์‚ฌ์œจ ๋ชจ๋‹ˆํ„ฐ๋ง์ด ๋„๋ฆฌ ์ด์šฉ๋˜๊ณ  ์žˆ๋‹ค. ํ˜„์žฅ ๋ถ„๊ด‘๋ฒ•์€ ๋†’์€ ์ŠคํŽ™ํŠธ๋Ÿผ, ์‹œ๊ฐ„ ๋ถ„ํ•ด๋Šฅ ํ˜„์žฅ ๋ฐ์ดํ„ฐ๋ฅผ ์ œ๊ณตํ•˜๊ณ  ์ž‘์€ ์˜์—ญ์—์„œ ํฐ ์˜์—ญ์œผ๋กœ ์ธก์ •์„ ํ™•์žฅํ•˜๋Š” ์ˆ˜๋‹จ์„ ์ œ๊ณตํ•˜๊ธฐ ์œ„ํ•œ ์ค‘์š”ํ•œ ๊ธฐ์ˆ ๋กœ ํ™•๋ฆฝ๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์ˆ˜๋งŽ์€ ์—ฐ๊ตฌ๊ฐ€ ํ˜„์žฅ ๋ถ„๊ด‘ ์‹œ์Šคํ…œ์„ ๊ฐœ๋ฐœํ–ˆ์ง€๋งŒ, ๋ฐ˜๊ตฌ-์›์ถ”ํ˜• ๋ฐ ์–‘ ๋ฐ˜๊ตฌ ๊ตฌ์„ฑ ๊ฐ„์˜ ์›๊ฒฉ ๊ฐ์ง€ ๊ด€์ฐฐ์˜ ๊ธฐํ•˜ํ•™์  ๋ฐ ๊ด‘ํ•™์  ์ฐจ์ด์— ๋Œ€ํ•œ ์ดํ•ด๊ฐ€ ๋ถ€์กฑํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ดˆ ๋ถ„๊ด‘ ๋ฐ์ดํ„ฐ๋ฅผ ์ง€์†์ ์œผ๋กœ ์ˆ˜์ง‘ํ•˜๋Š” ๊ฒƒ์€ ์—ฌ์ „ํžˆ ์–ด๋ ต๋‹ค. ์šฐ๋ฆฌ๋Š” ๋ฐ˜๊ตฌํ˜•-์›์ถ”ํ˜• ๋ฐ ์ด์ค‘ ๋ฐ˜๊ตฌํ˜• ๊ตฌ์„ฑ์œผ๋กœ ์›์ ์™ธ์„  ํƒœ์–‘๊ด‘ ์œ ๋„ ์—ฝ๋ก์†Œ ํ˜•๊ด‘ ๋ฐ ์บ๋…ธํ”ผ ์ดˆ ๋ถ„๊ด‘ ๋ฐ˜์‚ฌ์œจ(400โ€“900nm)์„ ์ธก์ •ํ•˜๋Š” ์ž๋™ํ™”๋œ ์ง€์ƒ ๊ธฐ๋ฐ˜ ํ•„๋“œ ๋ถ„๊ด‘ ์‹œ์Šคํ…œ์„ ๊ฐœ๋ฐœํ–ˆ๋‹ค. ์–‘๋ฐฉํ–ฅ ๋ฐ˜์‚ฌ์œจ๊ณผ ๋ฐ˜๊ตฌํ˜• ์›์ถ”ํ˜• ๋ฐ˜์‚ฌ์œจ์„ ๋ชจ๋‘ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•ด ์„œ๋ณด ๋ชจํ„ฐ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ํ”„๋ฆฌ์ฆ˜์„ ํšŒ์ „ํ•˜์—ฌ ์„ธ๊ฐ€์ง€ ํƒ€์ž…์˜ ํฌํŠธ๋ฅผ ์ธก์ •ํ•œ๋‹ค. ๊ฐ ํฌํŠธ๋Š” ๋“ค์–ด์˜ค๋Š” ๋ณต์‚ฌ ์กฐ๋„, ๋‚˜๊ฐ€๋Š” ๋ณต์‚ฌ ์กฐ๋„ ๋ฐ ๋‚˜๊ฐ€๋Š” ๋ณต์‚ฌ๋ฅผ ์ธก์ •ํ•˜๋Š” ์„ธ ๊ฐ€์ง€ ์œ ํ˜•์˜ ํฌํŠธ๋‹ค. ์กฐ์‚ฌ์กฐ๋„๋Š” ๋ฐฑ์ƒ‰ํ™•์‚ฐ์œ ๋ฆฌ์™€ ๊ตด์ ˆ ๋ Œ์ฆˆ๋ฅผ ์‚ฌ์šฉํ•˜์˜€๊ณ , ๊ตด์ ˆ ๋ Œ์ฆˆ๋ฅผ ์ด์šฉํ•˜์—ฌ ์กฐ๋„๋ฅผ ์ธก์ •ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์šฐ๋ฆฌ๋Š” ๋ฐฉ์‚ฌ ์ธก์ • ๋ฐ ํŒŒ์žฅ ๊ต์ •์„ ํฌํ•จํ•˜๋Š” ๋ฐ์ดํ„ฐ ๊ด€๋ฆฌ ํ”„๋กœํ† ์ฝœ์„ ๊ฐœ๋ฐœํ–ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ์šฐ๋ฆฌ๋Š” ๋‚™์—ฝ ํ™œ์—ฝ์ˆ˜๋ฆผ์˜ ์„ฑ์žฅ๊ธฐ์— ์ด ์‹œ์Šคํ…œ์—์„œ ์ธก์ •๋œ BRF์™€ BHR ๋ฐ์ดํ„ฐ๊ฐ€ ์–ด๋–ป๊ฒŒ ๋‹ค๋ฅธ์ง€ ๋ณด๊ณ ํ•˜์˜€๋‹ค.Chapter 1. Introduction ๏ผ‘ 1.1. Study Background ๏ผ‘ 1.2. Purpose of Research ๏ผ” Chapter 2. Developing and Testing of Hyperspectral System ๏ผ• 2.1 Development of Hyperspectral System and Data Collecting ๏ผ• 2.1.1 The Central Control Unit and Spectrometer ๏ผ• 2.1.2 RotaPrism ๏ผ— 2.1.3 Data Collection ๏ผ™ 2.3 Data Managing and Processing ๏ผ‘๏ผ‘ 2.3.1 Preprocessing of Spectra ๏ผ‘๏ผ‘ 2.3.2 Radiometric Calibration ๏ผ‘๏ผ“ 2.3.3 Retrieval of SIF and Vegetation Indices ๏ผ‘๏ผ• 2.4 Ancillary Measurements to Monitoring Ecosystem. ๏ผ‘๏ผ— Chapter 3. Application of Hyperspectral System ๏ผ‘๏ผ™ 3.1 Study Site ๏ผ‘๏ผ™ 3.2 Diurnal and Variation of Spectral Reflectance and SIF ๏ผ’๏ผ 3.3 Seasonal Variation of Vegetation Index and SIF ๏ผ’๏ผ’ 3.4 Broader Implications ๏ผ’๏ผ” Chapter 4. Summary and Conclusions ๏ผ’๏ผ– Bibliography ๏ผ’๏ผ˜์„

    Remote sensing of photosynthetic-light-use efficiency

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    Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence

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    State-of-the-art optical remote sensing of vegetation canopies is reviewed here to stimulate support from laboratory and field plant research. This overview of recent satellite spectral sensors and the methods used to retrieve remotely quantitative biophysical and biochemical characteristics of vegetation canopies shows that there have been substantial advances in optical remote sensing over the past few decades. Nevertheless, adaptation and transfer of currently available fluorometric methods aboard air- and space-borne platforms can help to eliminate errors and uncertainties in recent remote sensing data interpretation. With this perspective, red and blue-green fluorescence emission as measured in the laboratory and field is reviewed. Remotely sensed plant fluorescence signals have the potential to facilitate a better understanding of vegetation photosynthetic dynamics and primary production on a large scale. The review summarizes several scientific challenges that still need to be resolved to achieve operational fluorescence based remote sensing approache

    Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science

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    Remote sensing methods enable detection of solar-induced chlorophyll a fluorescence. However, to unleash the full potential of this signal, intensive cross-disciplinary work is required to harmonize biophysical and ecophysiological studies. For decades, the dynamic nature of chlorophyll a fluorescence (ChlaF) has provided insight into the biophysics and ecophysiology of the light reactions of photosynthesis from the subcellular to leaf scales. Recent advances in remote sensing methods enable detection of ChlaF induced by sunlight across a range of larger scales, from using instruments mounted on towers above plant canopies to Earth-orbiting satellites. This signal is referred to as solar-induced fluorescence (SIF) and its application promises to overcome spatial constraints on studies of photosynthesis, opening new research directions and opportunities in ecology, ecophysiology, biogeochemistry, agriculture and forestry. However, to unleash the full potential of SIF, intensive cross-disciplinary work is required to harmonize these new advances with the rich history of biophysical and ecophysiological studies of ChlaF, fostering the development of next-generation plant physiological and Earth-system models. Here, we introduce the scale-dependent link between SIF and photosynthesis, with an emphasis on seven remaining scientific challenges, and present a roadmap to facilitate future collaborative research towards new applications of SIF.Peer reviewe

    Earth Observing System. Volume 1, Part 2: Science and Mission Requirements. Working Group Report Appendix

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    Areas of global hydrologic cycles, global biogeochemical cycles geophysical processes are addressed including biological oceanography, inland aquatic resources, land biology, tropospheric chemistry, oceanic transport, polar glaciology, sea ice and atmospheric chemistry

    MODIS: Moderate-resolution imaging spectrometer. Earth observing system, volume 2B

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    The Moderate-Resolution Imaging Spectrometer (MODIS), as presently conceived, is a system of two imaging spectroradiometer components designed for the widest possible applicability to research tasks that require long-term (5 to 10 years), low-resolution (52 channels between 0.4 and 12.0 micrometers) data sets. The system described is preliminary and subject to scientific and technological review and modification, and it is anticipated that both will occur prior to selection of a final system configuration; however, the basic concept outlined is likely to remain unchanged
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