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The use of suitable pseudo-invariant targets for MIVIS data calibration by the empirical line method

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2016年第0期114卷 102-114页

作者： Mei, Alessandro Bassani, Cristiana Fontinovo, Giuliano Salvatori, Rosamaria Allegrini, Alessia Natl Res Council Italy Inst Atmospher Pollut Res Via Salaria Km 29300 Monterotondo RM Italy

The empirical line method (ELM) enables the calibration of multi- and hyper-airborne/satellite image converting DN or radiance to reflectance values performed by using at ground data. High quality outcome can be reached with the selection of appropriate Pseudo-Invariant Targets (PIT). In this paper, spectral variability of "usual" (asphalt and concrete) and "unusual" (calcareous gravel, basaltic paving, concrete bricks, tartan paving and artificial turf) PITs is retrieved for ELM application. Such PITs are used to calibrate the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) airborne sensor in 12 different Runs. Firstly, processing of field spectral data enables the evaluation of pseudo-invariance of targets by studying their spectral changes in space and in time. Finally, these surfaces are used as Ground Calibration (GCT) and Validation Targets (GVT) in ELM. High calibration accuracy values are observed in Visible (VIS) range (98.9%) while a general decrease of accuracy in Near-InfraRed (NIR) (96.6%) and Middle-InfraRed (SWIR) (88.1%) are reached. Outcomes show that "usual" surfaces as asphalt and concrete and "unusual" surfaces such as tartan can be successfully used for MIVIS image calibration. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

关键词： empirical line method Pseudo-invariant target MIVIS

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Application of the empirical line method ( ELM) to calibrate the airborne Daedalus-CZCS scanner

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EUROPEAN JOURNAL OF REMOTE SENSING 2018年第1期51卷 33-46页

作者： Pompilio, Loredana Marinangeli, Lucia Amitrano, Luigi Pacci, Giacomo D'andrea, Salvatore Iacullo, Salvatore Monaco, Enrico Univ G DAnnunzio Dipartimento Sci Psicol Chieti Italy Serv Telerilevamento Ambientale Nucleo Aereo Guardia Costiera Pescara 3 Pescara Italy

The present investigation aims at providing a reliable evaluation of the geometric and radiometric accuracy of the airborne Daedalus-Coastal Zone Color Scanner (CZCS), through cal/val techniques. To this aim, on November 2014, we accomplished a remote sensing campaign over the Peligna Valley (Italy). Together with the personnel of the III Nucleo Aereo of the Italian Coast Guard, based at the Pescara Airport, we deployed the Daedalus AA1268EM1 CZCS scanner on board the fixed-wing aircraft type ATR42MP and a ASD FieldSpec spectroradiometer for a simultaneous field survey. We used vicarious calibration and secondary non-parametric geometric correction to achieve absolute atmospheric correction and geometric calibration, respectively. Although the validation and calibration targets used in this study were similar in nature, correlation coefficients of the prediction equations between at-sensor radiance and ground reflectance were > 0.90 for each of the 10 CZCS wavebands and the independent error assessment demonstrate that the empirical line method can be applied to correct CZCS imagery with satisfactory results.

关键词： Airborne data in field data acquisition multispectral data empirical line method

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Preliminary Evaluation of the Mirror-based empirical line method using FLARE System 27

Preliminary Evaluation of the Mirror-based Empirical Line Me...

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Conference on Earth Observing Systems XXVII

作者： Pinto, Cibele Teixeira de Carvalho e Oliveira, Pedro Valle Aaron, David Holt, Jeff Russell, Brandon Durell, Chris Leigh, Larry South Dakota State Univ Image Proc Lab Brookings SD 57007 USA Labsphere Inc North Sutton NH USA

ISBN: (纸本)9781510654495;9781510654488

The empirical line method (ELM) is a widely applied technique of achieving absolute atmospheric correction assuming a linear relationship between the raw Digital Numbers (DNs) or at-sensor radiance and surface reflectance measurements collected in-situ. The ELM measures reference targets of known reflectance in an image. Labsphere has created an automated vicarious calibration system using the SPecular Array Radiometric Calibration (SPARC) mirror technology in the new Field line-of-sight Automated Radiance Exposure (FLARE) network. In the FLARE system the known reflectance targets are convex mirrors - because of that it is titled Mirror based empirical line method (MELM). In this context, the objective of this work is to present the initial results of the MELM using one the FLARE network system. The FLARE system evaluated in this work is the Alpha Node located at Arlington, SD. Initially, the data collected in 2020 and 2021 with the Alpha FLARE concomitant with the OLI sensor overpass on-board the Landsat-8 satellite were used in the assessment. In summary, the surface reflectance image product available to download for OLI sensor were compared directly with the surface reflectance image resulting from the MELM method. The preliminary results showed the mean absolute error data between the surface reflectance from the OLI Level-2 product image and the surface reflectance from the MELM was lower than 0.01 for the Blue, Green, Red and SWIR-1 bands;lower than 0.03 for the for the NIR and SWIR-2 spectral bands;and around 0.05 for Coastal Aerosol band (all in reflectance units). These results suggest the MELM technique using FLARE has great potential for reflectance surface evaluation of orbital sensors.

关键词： surface reflectance Landsat empirical line method calibration

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Uncertainty Analysis for Surface Reflectance Retrieved from Hyperspectral Remote Sensing Image using empirical line method 9

Uncertainty Analysis for Surface Reflectance Retrieved from ...

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9th Workshop on Hyperspectral Image and Signal Processing - Evolution in Remote Sensing (WHISPERS)

作者： Jia, Guorui Xue, Qian Zhao, Huijie Beihang Univ Sch Instrument Sci & Optoelect Engn Key Lab Precis Optomechatron Technol Minist Educ 37 Xueyuan Rd Beijing 100191 Peoples R China

ISBN: (纸本)9781728115818

The empirical line method (ELM) of atmospheric correction is widely used in retrieving surface reflectance from the earth observation (EO) radiance of optical remote sensors, Traditionally, the errors in the input quantities for ELM are ignored, whereas the accuracy of the retrieved reflectance is assessed using a field reflectance as reference. In fact, field reflectance is merely another measured value of the ground object and measurements always have errors. To accurately assess the quality of the ELM retrieved reflectance, an uncertainty propagation model accounting for the errors in the input quantities is proposed, according to the rules for measurement uncertainty evaluation and expression in metrology. By applying to a set of CASI/SASI hyperspectral images, the interval about the real reflectance and the corresponding level of confidence was reported as a result, which shows the possibility to accurately express the quality of the retrieved reflectance and to further ascertain the major error sources.

关键词： reflectance uncertainty empirical line method metrology

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Atmospheric compensation in the presence of clouds: an adaptive empirical line method (AELM) approach

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JOURNAL OF APPLIED REMOTE SENSING 2009年第1期3卷 033507-033507页

作者： Bartlett, Brent Schott, John R. Rochester Inst Technol Chester F Carlson Ctr Imaging Sci Digital Imaging & Remote Sensing Lab Rochester NY 14623 USA

Many methods exist to invert airborne imagery from units of either radiance or sensor specific digital counts to units of reflectance. These compensation algorithms remove unwanted atmospheric variability allowing objects on the ground to be analyzed. Low error levels in homogenous atmospheric conditions have been demonstrated. In many cases however, clouds are present in the atmosphere which introduce error into the inversion at unacceptable levels. For example, the relationship that is defined between sensor reaching radiance and ground reflectance in a cloud free scene will not be the same as in an adjacent region with clouds in the surround. A novel method has been developed which utilizes ground based measurements to modify the empirical line method (ELM) approach on a per-pixel basis. A physics based model of the atmosphere is used to generate a spatial correction for the ELM. Creation of this model is accomplished by analyzing whole-sky imagery to produce a cloud mask which drives input parameters to the radiative transfer (RT) code MODTRAN. The RT code is run for several different azimuth and zenith orientations to create a three-dimensional representation of the hemisphere. The model is then used to achieve a per-pixel correction by adjusting the ELM slope spatially. This method is applied to real data acquired over the atmospheric radiation measurement (ARM) site in Lamount, OK. Performance of the method is evaluated with the Hyperspectral Digital Imagery Collection Experiment (HYDICE) instrument. The sensitivity to spectral sampling is also assessed by down-sampling the HYDICE data to the spectral response of the multi-spectral system Wildfire Airborne Sensor Program LITE (WASP Lite). Finally a method to utilize this approach when additional sensors (like a sky camera) are not available is suggested.

关键词： Atmospheric inversion empirical line method ground truth MODTRAN cloud cover whole-sky image

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Improved target detection for hyperspectral images using hybrid in-scene calibration

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JOURNAL OF APPLIED REMOTE SENSING 2017年第3期11卷

作者： Zhou, Jin Kwan, Chiman Ayhan, Bulent Signal Proc Inc Rockville MD 20850 USA

This paper presents a practical approach to target detection for hyperspectral images. In target detection, it is normally assumed that the ground truth target signatures collected in a laboratory are available and one then uses them to search for targets in a given image. However, directly applying the laboratory signatures to the real data is not appropriate due to environmental differences between the ground truth data and real data. Conventional atmospheric compensation schemes such as the use of MODTRAN can help to improve the target detection performance. However, the computational load is huge and thus real-time applications may prohibit this compensation approach. We present results of an alternative compensation technique known as in-scene compensation, which is appealing as no complicated techniques such as MODTRAN are needed. Two in-scene methods for visible near-infrared/short-wave infrared range have been developed in the literature: empirical line method (ELM) and vegetation normalization (VN). Both approaches have advantages and disadvantages. We propose a hybrid in-scene compensation method that can be considered as a combination of ELM and VN and we call our method ELM augmented VN (EAVN). One key advantage of EAVN is that it combines the advantages of ELM and VN and eliminates their disadvantages. Compared to ELM, there is no need for two or more known target pixels in the test scene. Compared to VN, there is no need for dark pixels. Extensive experimental results using ground-based sensor data showed that the EAVN algorithm provides excellent compensation to environmental changes. After compensation, the receiver operating characteristics performance of target detection has been significantly improved by orders of magnitude in a number of cases, as compared to two standard compensation methods: quick atmospheric correction and internal average relative reflectance correction. (C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： in-scene calibration hyperspectral visible near-infrared short-wave infrared target detection empirical line method vegetation normalization quick atmospheric correction internal average relative reflectance ground-based sensor

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The use of selected pseudo-invariant targets for the application of atmospheric correction in multi-temporal studies using satellite remotely sensed imagery

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INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 2009年第3期11卷 192-200页

作者： Hadjimitsis, D. G. Clayton, C. R. I. Retalis, A. Cyprus Univ Technol Dept Civil Engn & Geomat Fac Engn & Technol Lemesos Cyprus Univ Southampton Sch Civil & Environm Engn Southampton SO17 1BJ Hants England Natl Observ Athens Inst Environm Res & Sustainable Dev GR-15236 Athens Greece

Because atmospheric effects can have a significant impact on the data obtained from multi-spectral satellite remote sensing, it is frequently necessary to make corrections before any other image processing can be started. This paper describes a robust and relatively simple atmospheric correction method that uses pseudo-invariant targets (PITs) in conjunction with the empirical line method. The method is based on the selection of a number of suitable generic PlTs, on the basis that they are large, distinctive in shape, and occur in many geographical areas. Whereas the multi-temporal normalization method corrects all images to a selected reference image, in this method images are simultaneously corrected using targets with a range of estimated surface reflectance values. The paper describes some applications of the method fora range of environmental studies involving water quality and air pollution monitoring, and mapping land-cover changes. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Atmospheric correction Pseudo-invariant targets empirical line method Dark target Light target Reflectance Remote sensing

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Low-cost system for radiometric calibration of UAV-based multispectral imagery

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JOURNAL OF SPATIAL SCIENCE 2022年第3期67卷 395-409页

作者： Fim Rosas, Jorge Tadeu de Carvalho Pinto, Francisco de Assis de Queiroz, Daniel Marcal de Melo Villar, Flora Maria Martins, Rodrigo Nogueira Silva, Samuel de Assis Univ Sao Paulo USP ESALQ Dept Soil & Plant Nutr Piracicaba Brazil Fed Univ Vicosa UFV Dept Agr Engn Vicosa MG Brazil Univ Fed Espirito Santo Dept Rural Engn Alegre Brazil

This study evaluated the use of low-cost materials for radiometric calibration of multispectral images. Four materials were tested: plywood panels painted with matte paint (M1);plywood panels covered with synthetic nappa leather (M2);Ethylene Vinyl Acetate (EVA) panels (M3), and plywood panels covered with Polyvinyl chloride (PVC) canvas (M4). The useful life of all materials and the errors associated with the calibration was determined. The M1 and M2 panels presented the lowest errors (RMSE), whereas the M4 panels showed the highest errors. Finally, the M3 panels showed the lowest resistance to use, whereas the M1 panels showed the greatest durability.

关键词： Remote sensing empirical line method vegetation indices coffee crop

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Surface reflectance calculation and predictive models of biophysical parameters of maize crop from RG-NIR sensor on board a UAV

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PRECISION AGRICULTURE 2021年第5期22卷 1535-1558页

作者： dos Santos, Robson Argolo Filgueiras, Roberto Mantovani, Everardo Chartuni Fernandes-Filho, Elpidio Inacio Almeida, Thome Simpliciano Venancio, Luan Peroni da Silva, Adelaide Cristielle Barbosa Fed Univ Vicosa UFV Dept Agr Engn Peter Henry Rolfs Ave BR-36570900 Vicosa MG Brazil Fed Univ Vicosa UFV Dept Soil Peter Henry Rolfs Ave BR-36570900 Vicosa MG Brazil Fed Inst Educ Sci & Technol South Minas IFSULDEMI Campus PassosPenha St 394Penha 2 BR-37903358 Passos MG Brazil

Unmanned aerial vehicles (UAVs) present themselves as an alternative to overcome the limitations of satellite sensors in monitoring agricultural crops, motivating many studies with UAVs. They can carry sensors, which need studies for better understanding. The present study aimed to vicariously calibrate a Red-Green-Near infrared (RG-NIR) low-cost sensor on board a UAV, and to develop predictive models of biophysical parameters for a maize crop. To achieve this purpose, 15 sets of images were captured over 61 days after emergence (DAE) of the maize crop plantation. Each set of images was mosaicked and had their digital numbers (DN) converted to reflectance. After calibration, normalized difference vegetation index (NDVI) and cumulative NDVI (cNDVI) were calculated to serve as an independent variable in the models for estimating crop parameters. In the field, 54 plants were collected and evaluated for height, leaf area and dry biomass. It was observed that the NIR band had an influence on the red band, but this influence was attenuated with the empirical line calibration. NDVI was able to detect seasonal and spatial variations in maize. The NDVI model obtained on the collection day to estimate the total dry above ground biomass had better results, generating RMSE of 68.68 g m(-2) and R-2 of 0.81, in comparison with cNDVI. For productivity, the result was satisfactory with cNDVI, showing RMSE of 134.00 g m(-2) and R-2 of 0.63. Calibration of the sensor was shown to be important to attenuate influence between bands.

关键词： Remote sensing Vicarious calibration empirical line method NDVI

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A spectral climatology for atmospheric compensation of hyperspectral imagery 22

A spectral climatology for atmospheric compensation of hyper...

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22nd SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII

作者： Powell, John H. Resmini, Ronald G. George Mason Univ Coll Sci 4400 Univ Dr Fairfax VA 22030 USA

ISBN: (纸本)9781510600812

Most Earth observation hyperspectral imagery (HSI) detection and identification algorithms depend critically upon a robust atmospheric compensation capability to correct for the effects of the atmosphere on the radiance signal. Atmospheric compensation methods typically perform optimally when ancillary ground truth data are available, e.g., high fidelity in situ radiometric observations or atmospheric profile measurements. When ground truth is incomplete or not available, additional assumptions must be made to perform the compensation. Meteorological climatologies are available to provide climatological norms for input into the radiative transfer models;however no such climatologies exist for empirical methods. The success of atmospheric compensation methods such as the empirical line method suggests that remotely sensed HSI scenes contain comprehensive sets of atmospheric state information within the spectral data itself. It is argued that large collections of empirically-derived atmospheric coefficients collected over a range of climatic and atmospheric conditions comprise a resource that can be applied to prospective atmospheric compensation problems. A previous study introduced a new climatological approach to atmospheric compensation in which empirically derived spectral information, rather than sensible atmospheric state variables, is the fundamental datum. The current work expands the approach across an experimental archive of 127 airborne HSI datasets spanning nine physical sites to represent varying climatological conditions. The representative atmospheric compensation coefficients are assembled in a scientific database of spectral observations and modeled data. Improvements to the modeling methods used to standardize the coefficients across varying collection and illumination geometries and the resulting comparisons of adjusted coefficients are presented. The climatological database is analyzed to show that common spectral similarity metrics can be used to

关键词： Hyperspectral HSI atmospheric compensation empirical line method remote sensing climatology

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