- 标题
- 摘要
- 关键词
- 实验方案
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Radiometric Cross-Calibration of Tiangong-2 MWI Visible/NIR Channels over Aquatic Environments using MODIS
摘要： The Moderate-Resolution Wide-Wavelength Imager (MWI), onboard the Tiangong-2 (TG-2) Space Lab, is an experimental satellite sensor designed for the next-generation Chinese ocean color satellites. The MWI imagery is not sufficiently radiometrically calibrated, and therefore, the cross-calibration is urgently needed to provide high quality ocean color products for MWI observations. We proposed a simple and effective cross-calibration scheme for MWI data using well calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) imagery over aquatic environments. The path radiance of the MWI was estimated using the quasi-synchronized MODIS images as well as the MODIS Rayleigh and aerosol look up tables (LUTs) from SeaWiFS Data Analysis System 7.4 (SeaDAS 7.4). The results showed that the coefficients of determination (R2) of the calibration coefficients were larger than 0.97, with sufficient matched areas to perform cross-calibration for MWI. Compared with the simulated Top of Atmosphere (TOA) radiance using synchronized MODIS images, all errors calculated with the calibration coefficients retrieved in this paper were less than 5.2%, and lower than the lab calibrated coefficients. The Rayleigh-corrected reflectance (ρrc), remote sensing reflectance (Rrs) and total suspended matter (TSM) products of MWI, MODIS and the Geostationary Ocean Color Imager (GOCI) images for Taihu Lake in China were compared. The distribution of ρrc of MWI, MODIS and GOCI agreed well, except for band 667 nm of MODIS, which might have been saturated in relatively turbid waters. Besides, the Rrs used to retrieve TSM among MWI, MODIS and GOCI was also consistent. The root mean square errors (RMSE), mean biases (MB) and mean ratios (MR) between MWI Rrs and MODIS Rrs (or GOCI Rrs) were less than 0.20 sr?1, 5.52% and within 1 ± 0.023, respectively. In addition, the derived TSM from MWI and GOCI also agreed with a R2 of 0.90, MB of 13.75%, MR of 0.97 and RMSE of 9.43 mg/L. Cross-calibration coefficients retrieved in this paper will contribute to quantitative applications of MWI. This method can be extended easily to other similar ocean color satellite missions.
关键词： atmospheric correction,cross calibration,total suspended matter,open oceans,inland water
更新于2025-09-23 15:22:29
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Retrieval of Chlorophyll a from Sentinel-2 MSI Data for the European Union Water Framework Directive Reporting Purposes
摘要： The European Parliament and The Council of the European Union have established the Water Framework Directive (2000/60/EC) for all European Union member states to achieve, at least, 'good' ecological status of all water bodies larger than 50 hectares in Europe. The MultiSpectral Instrument onboard European Space Agency satellite Sentinel-2 has suitable 10, 20, 60 m spatial resolution to monitor most of the Estonian lakes as required by the Water Framework Directive. The study aims to analyze the suitability of Sentinel-2 MultiSpectral Instrument data to monitor water quality in inland waters. This consists of testing various atmospheric correction processors to remove the influence of atmosphere and comparing and developing chlorophyll a algorithms to estimate the ecological status of water in Estonian lakes. This study shows that the Sentinel-2 MultiSpectral Instrument is suitable for estimating chlorophyll a in water bodies and tracking the spatial and temporal dynamics in the lakes. However, atmospheric corrections are sensitive to surrounding land and often fail in narrow and small lakes. Due to that, deriving satellite-based chlorophyll a is not possible in every case, but initial results show the Sentinel-2 MultiSpectral Instrument could still provide complementary information to in situ data to support Water Framework Directive monitoring requirements.
关键词： atmospheric correction,chlorophyll a,optically complex waters,remote sensing,European Union Water Framework Directive (2000/60/EC),ecological status of water bodies,Copernicus,Sentinel-2 MultiSpectral Instrument
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A Study on the Aerosol Optical Property Over Validation Sites in Japan for Hisui Atmospherically Corrected Surface Reflectance
摘要： The HISUI Hyperspectral Imager is being developed by Japanese Ministry of Economy, Trade, and Industry (METI), which will deploy on International Space Station (ISS) Japan Experiment Module (JEM) in FY2019. HISUI Level2 surface reflectance product (L2G) will be also provided for each of the VNIR and SWIR bands as research products. We have a plan of HISUI L2G validation, which includes not only surface reflectance itself also the atmospheric parameters, especially aerosol properties. We already have 3 sites that measures the atmospheric parameters day by day. This research shows the aerosol properties over validation sites in Japan on one of the HISUI calibration and validation activities.
关键词： Validation,Skyradiometer,Atmospheric correction,HISUI Hyperspectral Imager,SKYNET
更新于2025-09-23 15:21:21
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Coupled retrieval of the three phases of water from spaceborne imaging spectroscopy measurements
摘要： Measurements of reflected solar radiation by imaging spectrometers can quantify water in different states (solid, liquid, gas) thanks to the discriminative absorption shapes. We developed a retrieval method to quantify the amount of water in each of the three states from spaceborne imaging spectroscopy data, such as those from the German EnMAP mission. The retrieval couples atmospheric radiative transfer simulations from the MODTRAN5 radiative transfer code to a surface reflectance model based on the Beer-Lambert law. The model is inverted on a per-pixel basis using a maximum likelihood estimation formalism. Based on a unique coupling of the canopy reflectance model HySimCaR and the EnMAP end-to-end simulation tool EeteS, we performed a sensitivity analysis by comparing the retrieved values with the simulation input leading to an R2 of 0.991 for water vapor and 0.965 for liquid water. Furthermore, we applied the algorithm to airborne AVIRIS-C data to demonstrate the ability to map snow/ice extent as well as to a CHRIS-PROBA dataset for which concurrent field measurements of canopy water content were available. The comparison between the retrievals and the ground measurements showed an overall R2 of 0.80 for multiple crop types and a remarkable clustering in the regression analysis indicating a dependency of the retrieved water content from the physical structure of the vegetation. In addition, the algorithm is able to produce smoother and more physically-plausible water vapor maps than the ones from the band ratio approaches used for multispectral data, since biases due to background reflectance are reduced. The demonstrated potential of imaging spectroscopy to provide accurate quantitative measures of water from space will be further exploited using upcoming spaceborne imaging spectroscopy missions like PRISMA or EnMAP.
关键词： Atmospheric correction,EnMAP,Canopy water content,Water vapor,Imaging spectroscopy
更新于2025-09-23 15:21:01
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A Sensor Invariant Atmospheric Correction Method for Satellite Images
摘要： Land surface re?ectance is the fundamental variable for the most of earth observation (EO) missions, and corrections of the atmospheric disturbs from the cloud, gaseous, aerosol help to get accurate spectral description of earth surface. Unlike the previous empirical ways of atmospheric correction, we propose a data fusion method for atmospheric correction of satellite images, with an initial attempt to include the uncertainty information from different data source. It takes advantage of the high temporal resolution of MODIS observations to get BRDF description of the earth surface as the prior information of the earth surface property, uses the ECMWF CAMS Near-real-time as the prior information of the atmospheric sates, to get optimal estimations of the atmospheric parameters. It guarantees the correction is consistent cross different satellites image tiles and even cross different sensors. The validations against the AERONET sites are also show high correlation at around 0.9, with a RMSE of about 0.02.
关键词： uncertainty,data fusion,Atmospheric correction
更新于2025-09-10 09:29:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A Temperature and Emissivity Separation Algortihm for Chinese Gaofen-5 Satelltie Data
摘要： In this paper, we proposed a temperature and emissivity separation (TES) algorithm for the simultaneous retrieval of land surface temperature and emissivity (LST&E) from the thermal infrared data of Chinese GaoFen-5 (GF-5) satellite’s Multiple Spectral-Imager (MSI) payload. In order to improve the accuracy of the TES algorithm, a water vapor scaling (WVS) method for atmospheric correction was adopted. The Seebor V5.0 global atmospheric profile database and MODTRAN 5 were used to simulate the WVS coefficients. A total of 11 ASTER scenes were used to simulate the MSI images and concurrent ground measurements acquired in the HiWATER experiment were used to validate the algorithm. The results showed that the bias and root mean square error (RMSE) in the retrieved LST were 0.47 K and 1.70 K, respectively, and the absolute emissivity differences between MSI and the ground measurements were smaller than 0.01 for the four MSI TIR bands, which demonstrated that the proposed algorithm can be used to retrieve high accurate and high spatial resolution LST&E from GF-5 MSI data.
关键词： atmospheric correction,TES,GF-5,Land Surface Emissivity,Land Surface Temperature
更新于2025-09-10 09:29:36
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[Lecture Notes in Electrical Engineering] Microelectronics, Electromagnetics and Telecommunications Volume 521 (Proceedings of the Fourth ICMEET 2018) || Assessment of EO-1 Hyperion Imagery for Crop Discrimination Using Spectral Analysis
摘要： This paper outlines the research objectives to discriminate crop species using pure spectral-spatial reflectance of EO-1 Hyperion imagery. Vigorous encroachment in remote sensing unlocks the new avenues to investigate the hyper-spectral imagery for analysis and implication for crop-type classification and agricultural management. The investigated crop species were namely Sorghum, Wheat, and cotton located in West zone of Aurangabad, Maharashtra, India. The preprocessing algorithm namely quick atmospheric correction (QUAC) was applied to calibrate bad bands and construct precise data for crop discrimination. The machine learning classifiers applied to identify the pixels having a significant difference in pure spectral signatures based on Ground Control Point (GCP) and image spectral responses. The investigation was based on a binary encoding (BE) and support vector machine (SVM) learning approach in order to discriminate crop types. Crop discrimination followed land cover classes gives 73.35% accuracy using BE and SVM with polynomial third-degree order gives overall accuracy 90.44%. These results show that satellite data with 30 m spatial resolution (Hyperion) are able to identify crop species using Environment for Visualizing Images (ENVI) open source software.
关键词： Atmospheric correction,Support vector machine,A spectral signature,Hyperspectral data
更新于2025-09-10 09:29:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Adaptation and Validation of the Swire Algorithm for Sentinel-3 Over Complex Waters of Pearl River Estuary
摘要： Accurate removal of atmospheric interference and precise retrieval of water-leaving reflectance is decisive for subsequent water color applications. As follow-up satellite of Envisat, Sentinel-3 will provide valuable observations of the earth. This study aims to adapt the shortwave infrared extrapolation (SWIRE) atmospheric correction algorithm for Sentinel-3 to derive remote sensing reflectance of turbid waters, and validation it using our in-situ data in Pearl River Estuary. Results showed that SWIRE algorithm could effectively remove atmospheric perturbations, and produced more accurate remote sensing reflectance over complex waters of PRE than NIR and SWIR algorithms.
关键词： Pearl River Estuary,water color remote sensing,atmospheric correction,Sentinel-3
更新于2025-09-09 09:28:46
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Preliminary Evaluation of Sentinel-2 Bottom of Atmosphere Reflectance Using the 6Sv Code in Beijing Area
摘要： In this study, the Sentinel-2A Bottom Of Atmosphere (BOA) reflectance imageries over Beijing area from Dec 2016 to Nov 2017 were generated by the Sen2Cor processor and evaluated using the AERONET measurements and the 6SV code. The result shows a poor correlation between the Sen2Cor retrieved AOT and the ground data with R = 0.289 possibly because of the limitation of the AOT algorithm. The errors of Sen2Cor retrieved AOT and water vapor pressure have a great effect on the BOA reflectance and spectral indices such as NDVI. The highest relative uncertainty of the Sen2Cor BOA reflectance is 37.76% for B01 and the lowest correlation is 0.859 for B09. The result also shows that a high-accuracy atmospheric correction is still crucial and urgent for the Sentinel-2A data.
关键词： 6SV code,atmospheric correction,AERONET,Sentinel-2,uncertainty
更新于2025-09-09 09:28:46
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Bio-optical Modeling and Remote Sensing of Inland Waters || Atmospheric Correction for Inland Waters
摘要： Light received by a passive Earth-observing remote sensor goes through the Earth’s atmosphere twice—from the Sun to the Earth’s surface and from the surface to the sensor—before it reaches the sensor. As such, the light received at the sensor is invariably affected by absorption and scattering by gaseous molecules and particulate matter in the atmosphere. The process of correcting for the atmospheric effects and retrieving the reflectance of a target on the Earth’s surface is called atmospheric correction. The atmospheric effect on the radiance received by a remote sensor is significantly large over water bodies because water is highly absorptive and contributes to only 20% or less of the total at-sensor radiance (e.g., Hovis and Leung, 1977). Correcting for these atmospheric effects is an essential prerequisite to retrieving accurate estimates of water-leaving radiance, which is the basis for deriving quantitative estimates of biophysical parameters from remotely sensed data.
关键词： remote sensing,biophysical parameters,Atmospheric correction,inland waters,water-leaving radiance
更新于2025-09-09 09:28:46