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Jun Tanii - One of the best experts on this subject based on the ideXlab platform.
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Pre-Launch Activity for Flight model of HISUI Hyperspectral Sensor onboard International Space Station
Light Energy and the Environment 2018 (E2 FTS HISE SOLAR SSL), 2018Co-Authors: Jun Tanii, Osamu Kashimura, Yoshiyuki Ito, Akira IwasakiAbstract:HISUI Hyperspectral Sensor to be mounted on International Space Station obtains the earth’s images of 185 bands from the visible to shortwave-infrared wavelength region with the ground sampling distance of 20x31 meters. Pre-launch evaluation activities of a Flight Model are reported.
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Flight model performances of HISUI Hyperspectral Sensor onboard ISS (International Space Station)
Sensors Systems and Next-Generation Satellites XX, 2016Co-Authors: Jun Tanii, Osamu Kashimura, Yoshiyuki Ito, Akira IwasakiAbstract:Hyperspectral Imager Suite (HISUI) is a next-generation Japanese Sensor that will be mounted on Japanese Experiment Module (JEM) of ISS (International Space Station) in 2019 as timeframe. HISUI Hyperspectral Sensor obtains spectral images of 185 bands with the ground sampling distance of 20x31 meter from the visible to shortwave-infrared region. The Sensor system is the follow-on mission of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) in the visible to shortwave infrared region. The critical design review of the instrument was accomplished in 2014. Integration and tests of an flight model of HISUI Hyperspectral Sensor is being carried out. Simultaneously, the development of JEM-External Facility (EF) Payload system for the instrument started. The system includes the structure, the thermal control system, the electrical system and the pointing mechanism. The development status and the performances including some of the tests results of Instrument flight model, such as optical performance, optical distortion and radiometric performance are reported.
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effective observation planning and its simulation of a japanese spaceborne Sensor Hyperspectral imager suite hisui
International Geoscience and Remote Sensing Symposium, 2014Co-Authors: Kenta Ogawa, Jun Tanii, Osamu Kashimura, Tsuneo Matsunaga, S Yamamoto, Tetsushi Tachikawa, Satoshi Tsuchida, Shuichi RokugawaAbstract:Hyperspectral Imager Suite (HISUI) is a Japanese future spaceborne Hyperspectral instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be launched in 2017 or later. In HISUI project, observation strategy is important especially for Hyperspectral Sensor, and relationship between the limitations of Sensor operation and the planned observation scenarios have to be studied. Using observation coverage simulation program and we estimate progress of observation coverage of image with days after launch. We found that HISUI can make 4 times repeated observations for protected area (20 million km2 in the world). And about 70 % of land surface can be observed over 5 years. We also found that the developed rules to avoid cloudy are will improve the area coverage up to 2.4 %.
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Effect of temperature on onboard calibration reference material for spectral response function retrieval of the Hyperspectral Sensor of HISUI-SWIR spectral case
Sensors Systems and Next-Generation Satellites XVI, 2012Co-Authors: Kenji Tatsumi, Hitomi Inada, Jun Tanii, Takahiro Kawashima, Hisashi Harada, Toneo Kawanishi, Fumihiro Sakuma, Akira IwasakiAbstract:HISUI (Hyperspectral Imager SUIte) is the next Japanese earth observation Sensor, which consists of Hyperspectral and multispectral Sensors. The Hyperspectral Sensor is an imaging spectrometer with the VNIR (400-970nm) and the SWIR (900-2500nm) spectral channels. Spatial resolution is 30 m with swath width of 30km. The spectral resolution will be better than 10nm in the VNIR and 12.5nm in the SWIR. The multispectral Sensor has four VNIR spectral bands with spatial resolution of 5m and swath width of 90km. HISUI will be installed in ALOS-3 that is an earth observing satellite by JAXA. It will be launched in FY 2015. This paper is concerned with the effect of temperature on onboard calibration reference material (NIST SRM2065) for spectral response functions (SRFs) retrieval of the Hyperspectral Sensor. Since the location and intensity of absorption features are sensitive to material temperature, the estimated center wavelength and bandwidth of the SRFs may include the uncertainty. Therefore, it is necessary to estimate the deviation of the wavelength and the bandwidth broadening of the SRFs when the material temperature changes. In this paper we describe the evaluation of uncertainty of the SRF’s parameters retrieval and show some simulation’s results.
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observation planning strategy of a japanese spaceborne Sensor Hyperspectral imager suite hisui
Multispectral Hyperspectral and Ultraspectral Remote Sensing Technology Techniques and Applications IV, 2012Co-Authors: Kenta Ogawa, Jun Tanii, Osamu Kashimura, Tsuneo Matsunaga, Makoto Takenaka, S Yamamoto, Tetsushi Tachikawa, Satoshi Tsuchida, Shuichi RokugawaAbstract:Hyperspectral Imager Suite (HISUI) is a Japanese future spaceborne Hyperspectral instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be launched in 2016 or later. HISUI’s operation strategic study is described in this paper. In HISUI project, Operation Mission Planning (OMP) team will make long- and short-term observation strategy of the Sensor. OMP is important for HISUI especially for Hyperspectral Sensor with narrow swath of 30 km. There are two major limitations on the operation of HISUI Hyperspectral Imager. The first one is the maximum observation time per orbit. This is due to the cooling systems of the instrument to keep the instruments temperature within the design requirements. The maximum observation time per orbit is set to 15 minutes as the current baseline. The second one is maximum data downlink amount per day. This is a limitation given by communication link of the satellite bus and heavily depends on the operation of the platform satellite. The current baseline is 150 GB per day for Hyperspectral Sensor and 550 GB for multispectral Sensor. We have developed observation coverage simulation program and studied the relationship between the limitations of Sensor operation and the planned observation scenarios. The achievements of global mapping or regional monitoring need to be simulated precisely before launch. We have prepared daily global high resolution (30 second in latitude and longitude) cloud coverage data. The results of the simulations shows that HISUI will be able to acquire cloud free image of about 70 % of the terrestrial surface in three years (at the condition of 150 GB/day downlink rate).
Akira Iwasaki - One of the best experts on this subject based on the ideXlab platform.
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Pre-Launch Activity for Flight model of HISUI Hyperspectral Sensor onboard International Space Station
Light Energy and the Environment 2018 (E2 FTS HISE SOLAR SSL), 2018Co-Authors: Jun Tanii, Osamu Kashimura, Yoshiyuki Ito, Akira IwasakiAbstract:HISUI Hyperspectral Sensor to be mounted on International Space Station obtains the earth’s images of 185 bands from the visible to shortwave-infrared wavelength region with the ground sampling distance of 20x31 meters. Pre-launch evaluation activities of a Flight Model are reported.
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Flight model performances of HISUI Hyperspectral Sensor onboard ISS (International Space Station)
Sensors Systems and Next-Generation Satellites XX, 2016Co-Authors: Jun Tanii, Osamu Kashimura, Yoshiyuki Ito, Akira IwasakiAbstract:Hyperspectral Imager Suite (HISUI) is a next-generation Japanese Sensor that will be mounted on Japanese Experiment Module (JEM) of ISS (International Space Station) in 2019 as timeframe. HISUI Hyperspectral Sensor obtains spectral images of 185 bands with the ground sampling distance of 20x31 meter from the visible to shortwave-infrared region. The Sensor system is the follow-on mission of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) in the visible to shortwave infrared region. The critical design review of the instrument was accomplished in 2014. Integration and tests of an flight model of HISUI Hyperspectral Sensor is being carried out. Simultaneously, the development of JEM-External Facility (EF) Payload system for the instrument started. The system includes the structure, the thermal control system, the electrical system and the pointing mechanism. The development status and the performances including some of the tests results of Instrument flight model, such as optical performance, optical distortion and radiometric performance are reported.
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Onboard image processing system for Hyperspectral Sensor
Sensors (Switzerland), 2015Co-Authors: Hiroki Hihara, Yoshihiro Hoshi, Kotaro Moritani, Hitomi Inada, Taeko Seki, Masao Inoue, Akira Iwasaki, Makoto Suzuki, Jun Takada, Satoshi IchikawaAbstract:Onboard image processing systems for a Hyperspectral Sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for Hyperspectral Sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a Sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS) Sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS), which is a hierarchical predictive coding method with resolution scaling. To improve FELICS’s performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing Sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the Sensor system without adding size, weight, power consumption, and fabrication cost.
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Effect of temperature on onboard calibration reference material for spectral response function retrieval of the Hyperspectral Sensor of HISUI-SWIR spectral case
Sensors Systems and Next-Generation Satellites XVI, 2012Co-Authors: Kenji Tatsumi, Hitomi Inada, Jun Tanii, Takahiro Kawashima, Hisashi Harada, Toneo Kawanishi, Fumihiro Sakuma, Akira IwasakiAbstract:HISUI (Hyperspectral Imager SUIte) is the next Japanese earth observation Sensor, which consists of Hyperspectral and multispectral Sensors. The Hyperspectral Sensor is an imaging spectrometer with the VNIR (400-970nm) and the SWIR (900-2500nm) spectral channels. Spatial resolution is 30 m with swath width of 30km. The spectral resolution will be better than 10nm in the VNIR and 12.5nm in the SWIR. The multispectral Sensor has four VNIR spectral bands with spatial resolution of 5m and swath width of 90km. HISUI will be installed in ALOS-3 that is an earth observing satellite by JAXA. It will be launched in FY 2015. This paper is concerned with the effect of temperature on onboard calibration reference material (NIST SRM2065) for spectral response functions (SRFs) retrieval of the Hyperspectral Sensor. Since the location and intensity of absorption features are sensitive to material temperature, the estimated center wavelength and bandwidth of the SRFs may include the uncertainty. Therefore, it is necessary to estimate the deviation of the wavelength and the bandwidth broadening of the SRFs when the material temperature changes. In this paper we describe the evaluation of uncertainty of the SRF’s parameters retrieval and show some simulation’s results.
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Retrieval of spectral response functions for the Hyperspectral Sensor of HISUI (Hyperspectral Imager SUIte) by means of onboard calibration sources
Sensors Systems and Next-Generation Satellites XV, 2011Co-Authors: Kenji Tatsumi, Hitomi Inada, Takahiro Kawashima, Hisashi Harada, Toneo Kawanishi, Fumihiro Sakuma, Nagamitsu Ohgi, Akira IwasakiAbstract:HISUI (Hyper-spectral Imager SUIte), which is the next Japanese earth observation project, has been developed under the contract with Ministry of Economy, Trade and Industry(METI) and New Energy and Industrial Technology Development Organization(NEDO). HISUI is composed of hyper-spectral Sensor and multi-spectral Sensor. The Hyperspectral Sensor is an imaging spectrometer with two separate spectral channels: one for the VNIR range from 400 to 970 nm and the other for the SWIR range from 900 to 2500 nm. Ground sampling distance is 30 m with spatial swath width of 30 km. The spectral sampling will be better than 10 nm in the VNIR and 12.5 nm in the SWIR. The multi-spectral Sensor has four VNIR spectral bands with spatial resolution of 5m and swath width of 90 km. HISUI will be installed in ALOS-3 that is an earth observing satellite in the project formation phase by JAXA in FY 2015. This paper is concerned with the retrieval of spectral response functions (SRF) for the hyper-spectral Sensor. The center wavelength and bandwidth of spectral response functions of hyper-spectral Sensor may shift and broaden due to the distortion in the spectrometer, the optics and the detector assembly. Therefore it is necessary to measure or estimate the deviation of the wavelength and the bandwidth broadening of the SRFs. In this paper, we describe the methods of retrieval of the SRF's parameters (Gaussian functions assumed) by means of onboard calibration sources and we show some simulation's results and the usefulness of this method.
Guijun Yang - One of the best experts on this subject based on the ideXlab platform.
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A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera
Remote Sensing, 2018Co-Authors: Jibo Yue, Haikuan Feng, Xiuliang Jin, Huanhuan Yuan, Chengquan Zhou, Guijun Yang, Qingjiu TianAbstract:Timely and accurate estimates of crop parameters are crucial for agriculture management. Unmanned aerial vehicles (UAVs) carrying sophisticated cameras are very pertinent for this work because they can obtain remote-sensing images with higher temporal, spatial, and ground resolution than satellites. In this study, we evaluated (i) the performance of crop parameters estimates using a near-surface spectroscopy (350~2500 nm, 3 nm at 700 nm, 8.5 nm at 1400 nm, 6.5 nm at 2100 nm), a UAV-mounted snapshot Hyperspectral Sensor (450~950 nm, 8 nm at 532 nm) and a high-definition digital camera (Visible, R, G, B); (ii) the crop surface models (CSMs), RGB-based vegetation indices (VIs), Hyperspectral-based VIs, and methods combined therefrom to make multi-temporal estimates ofcropparametersandtomaptheparameters. Theestimatedleafareaindex(LAI)andabove-ground biomass(AGB)areobtainedbyusinglinearandexponentialequations,randomforest(RF)regression, and partial least squares regression (PLSR) to combine the UAV based spectral VIs and crop heights (from the CSMs). The results show that: (i) spectral VIs correlate strongly with LAI and AGB over single growing stages when crop height correlates positively with AGB over multiple growth stages; (ii) the correlation between the VIs multiplying crop height and AGB is greater than that between a single VI and crop height; (iii) the AGB estimate from the UAV-mounted snapshot Hyperspectral Sensorandhigh-definitiondigitalcameraissimilartotheresultsfromthegroundspectrometerwhen using the combined methods (i.e., using VIs multiplying crop height, RF and PLSR to combine VIs and crop heights); and (iv) the spectral performance of the Sensors is crucial in LAI estimates (the wheatLAIcannotbeaccuratelyestimatedovermultiplegrowingstageswhenusingonlycropheight). The LAI estimates ranked from best to worst are ground spectrometer, UAV snapshot Hyperspectral Sensor, and UAV high-definition digital camera.
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estimation of winter wheat above ground biomass using unmanned aerial vehicle based snapshot Hyperspectral Sensor and crop height improved models
Remote Sensing, 2017Co-Authors: Guijun Yang, Haikuan Feng, Changchun Li, Zhenhai Li, Yanjie Wang, Bo XuAbstract:Correct estimation of above-ground biomass (AGB) is necessary for accurate crop growth monitoring and yield prediction. We estimated AGB based on images obtained with a snapshot Hyperspectral Sensor (UHD 185 firefly, Cubert GmbH, Ulm, Baden-Wurttemberg, Germany) mounted on an unmanned aerial vehicle (UAV). The UHD 185 images were used to calculate the crop height and Hyperspectral reflectance of winter wheat canopies from Hyperspectral and panchromatic images. We constructed several single-parameter models for AGB estimation based on spectral parameters, such as specific bands, spectral indices (e.g., Ratio Vegetation Index (RVI), NDVI, Greenness Index (GI) and Wide Dynamic Range VI (WDRVI)) and crop height and several models combined with spectral parameters and crop height. Comparison with experimental results indicated that incorporating crop height into the models improved the accuracy of AGB estimations (the average AGB is 6.45 t/ha). The estimation accuracy of single-parameter models was low (crop height only: R2 = 0.50, RMSE = 1.62 t/ha, MAE = 1.24 t/ha; R670 only: R2 = 0.54, RMSE = 1.55 t/ha, MAE = 1.23 t/ha; NDVI only: R2 = 0.37, RMSE = 1.81 t/ha, MAE = 1.47 t/ha; partial least squares regression R2 = 0.53, RMSE = 1.69, MAE = 1.20), but accuracy increased when crop height and spectral parameters were combined (partial least squares regression modeling: R2 = 0.78, RMSE = 1.08 t/ha, MAE = 0.83 t/ha; verification: R2 = 0.74, RMSE = 1.20 t/ha, MAE = 0.96 t/ha). Our results suggest that crop height determined from the new UAV-based snapshot Hyperspectral Sensor can improve AGB estimation and is advantageous for mapping applications. This new method can be used to guide agricultural management.
Haikuan Feng - One of the best experts on this subject based on the ideXlab platform.
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A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera
Remote Sensing, 2018Co-Authors: Jibo Yue, Haikuan Feng, Xiuliang Jin, Huanhuan Yuan, Chengquan Zhou, Guijun Yang, Qingjiu TianAbstract:Timely and accurate estimates of crop parameters are crucial for agriculture management. Unmanned aerial vehicles (UAVs) carrying sophisticated cameras are very pertinent for this work because they can obtain remote-sensing images with higher temporal, spatial, and ground resolution than satellites. In this study, we evaluated (i) the performance of crop parameters estimates using a near-surface spectroscopy (350~2500 nm, 3 nm at 700 nm, 8.5 nm at 1400 nm, 6.5 nm at 2100 nm), a UAV-mounted snapshot Hyperspectral Sensor (450~950 nm, 8 nm at 532 nm) and a high-definition digital camera (Visible, R, G, B); (ii) the crop surface models (CSMs), RGB-based vegetation indices (VIs), Hyperspectral-based VIs, and methods combined therefrom to make multi-temporal estimates ofcropparametersandtomaptheparameters. Theestimatedleafareaindex(LAI)andabove-ground biomass(AGB)areobtainedbyusinglinearandexponentialequations,randomforest(RF)regression, and partial least squares regression (PLSR) to combine the UAV based spectral VIs and crop heights (from the CSMs). The results show that: (i) spectral VIs correlate strongly with LAI and AGB over single growing stages when crop height correlates positively with AGB over multiple growth stages; (ii) the correlation between the VIs multiplying crop height and AGB is greater than that between a single VI and crop height; (iii) the AGB estimate from the UAV-mounted snapshot Hyperspectral Sensorandhigh-definitiondigitalcameraissimilartotheresultsfromthegroundspectrometerwhen using the combined methods (i.e., using VIs multiplying crop height, RF and PLSR to combine VIs and crop heights); and (iv) the spectral performance of the Sensors is crucial in LAI estimates (the wheatLAIcannotbeaccuratelyestimatedovermultiplegrowingstageswhenusingonlycropheight). The LAI estimates ranked from best to worst are ground spectrometer, UAV snapshot Hyperspectral Sensor, and UAV high-definition digital camera.
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estimation of winter wheat above ground biomass using unmanned aerial vehicle based snapshot Hyperspectral Sensor and crop height improved models
Remote Sensing, 2017Co-Authors: Guijun Yang, Haikuan Feng, Changchun Li, Zhenhai Li, Yanjie Wang, Bo XuAbstract:Correct estimation of above-ground biomass (AGB) is necessary for accurate crop growth monitoring and yield prediction. We estimated AGB based on images obtained with a snapshot Hyperspectral Sensor (UHD 185 firefly, Cubert GmbH, Ulm, Baden-Wurttemberg, Germany) mounted on an unmanned aerial vehicle (UAV). The UHD 185 images were used to calculate the crop height and Hyperspectral reflectance of winter wheat canopies from Hyperspectral and panchromatic images. We constructed several single-parameter models for AGB estimation based on spectral parameters, such as specific bands, spectral indices (e.g., Ratio Vegetation Index (RVI), NDVI, Greenness Index (GI) and Wide Dynamic Range VI (WDRVI)) and crop height and several models combined with spectral parameters and crop height. Comparison with experimental results indicated that incorporating crop height into the models improved the accuracy of AGB estimations (the average AGB is 6.45 t/ha). The estimation accuracy of single-parameter models was low (crop height only: R2 = 0.50, RMSE = 1.62 t/ha, MAE = 1.24 t/ha; R670 only: R2 = 0.54, RMSE = 1.55 t/ha, MAE = 1.23 t/ha; NDVI only: R2 = 0.37, RMSE = 1.81 t/ha, MAE = 1.47 t/ha; partial least squares regression R2 = 0.53, RMSE = 1.69, MAE = 1.20), but accuracy increased when crop height and spectral parameters were combined (partial least squares regression modeling: R2 = 0.78, RMSE = 1.08 t/ha, MAE = 0.83 t/ha; verification: R2 = 0.74, RMSE = 1.20 t/ha, MAE = 0.96 t/ha). Our results suggest that crop height determined from the new UAV-based snapshot Hyperspectral Sensor can improve AGB estimation and is advantageous for mapping applications. This new method can be used to guide agricultural management.
Qingjiu Tian - One of the best experts on this subject based on the ideXlab platform.
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A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera
Remote Sensing, 2018Co-Authors: Jibo Yue, Haikuan Feng, Xiuliang Jin, Huanhuan Yuan, Chengquan Zhou, Guijun Yang, Qingjiu TianAbstract:Timely and accurate estimates of crop parameters are crucial for agriculture management. Unmanned aerial vehicles (UAVs) carrying sophisticated cameras are very pertinent for this work because they can obtain remote-sensing images with higher temporal, spatial, and ground resolution than satellites. In this study, we evaluated (i) the performance of crop parameters estimates using a near-surface spectroscopy (350~2500 nm, 3 nm at 700 nm, 8.5 nm at 1400 nm, 6.5 nm at 2100 nm), a UAV-mounted snapshot Hyperspectral Sensor (450~950 nm, 8 nm at 532 nm) and a high-definition digital camera (Visible, R, G, B); (ii) the crop surface models (CSMs), RGB-based vegetation indices (VIs), Hyperspectral-based VIs, and methods combined therefrom to make multi-temporal estimates ofcropparametersandtomaptheparameters. Theestimatedleafareaindex(LAI)andabove-ground biomass(AGB)areobtainedbyusinglinearandexponentialequations,randomforest(RF)regression, and partial least squares regression (PLSR) to combine the UAV based spectral VIs and crop heights (from the CSMs). The results show that: (i) spectral VIs correlate strongly with LAI and AGB over single growing stages when crop height correlates positively with AGB over multiple growth stages; (ii) the correlation between the VIs multiplying crop height and AGB is greater than that between a single VI and crop height; (iii) the AGB estimate from the UAV-mounted snapshot Hyperspectral Sensorandhigh-definitiondigitalcameraissimilartotheresultsfromthegroundspectrometerwhen using the combined methods (i.e., using VIs multiplying crop height, RF and PLSR to combine VIs and crop heights); and (iv) the spectral performance of the Sensors is crucial in LAI estimates (the wheatLAIcannotbeaccuratelyestimatedovermultiplegrowingstageswhenusingonlycropheight). The LAI estimates ranked from best to worst are ground spectrometer, UAV snapshot Hyperspectral Sensor, and UAV high-definition digital camera.