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Albedo retrieval From Multispectral Landsat 8 Observation in Urban Environment: algorithm Validation by in situ Measurements

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2017年第10期10卷 4504-4511页

作者： Baldinelli, Giorgio Bonafoni, Stefania Rotili, Antonella Univ Perugia Dept Engn I-06125 Perugia Italy

The surface albedo in urban environment represents one of the most influencing parameters in the formation of the Urban Heat Island (UHI). Its assessment is therefore strategic to undertake actions for the UHI mitigation: the increase of urban surface reflectivity is an example of cooling strategies increasingly proposed and developed. Spaceborne observations could give a significant contribution supplying albedo maps, and different retrieval algorithms estimating broadband albedo from narrowband reflectivities provided by satellite sensors were proposed and validated in literature. In this study, the accuracy of two well-known retrieval algorithms applied to Landsat 8 OLI reflectivities was assessed in a city of Central Italy (Perugia), selecting test sites having different land cover types. Since the root mean square error of the estimated albedo was quite high (0.07-0.08), a custom retrieval algorithm was developed to evaluate the potential improvement in the narrowband reflectivity-broadband albedo conversion for the case study. This analysis was made possible thanks to an in situ measurement campaign, carried out during the summer months of 2016. The selected sites, having quite homogenous features inside the urban environment, also demonstrated that the albedo values are not significantly affected by the hour of the day, if measurements are taken near noon (variation less than 7%). Spaceborne observations showed once again a powerful tool for monitoring large areas with a quite good spatial resolution (30 m), even if an improvement of the literature albedo retrieval algorithms is required and possible in an urban context.

关键词： Albedo ground measurements retrieval algorithm satellite observations urban heat island (UHI)

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EOF-based regression algorithm for the fast retrieval of atmospheric CO₂ total column amount from the GOSAT observations

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JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER 2017年 189卷 258-266页

作者： Bril, Andrey Maksyutov, Shamil Belikov, Dmitry Oshchepkov, Sergey Yoshida, Yukio Deutscher, Nicholas M. Griffith, David Hase, Frank Kivi, Rigel Morino, Isamu Notholt, Justus Pollard, David F. Sussmann, Ralf Velazco, Voltaire A. Warneke, Thorsten IPNASB 68 Nezavisimosti Ave Minsk 220072 BELARUS Natl Inst Environm Studies Ctr Global Environm Res 16-2 Onogawa Tsukuba Ibaraki 3058506 Japan Tomsk State Univ 36 Lenin Ave Tomsk 634050 Russia Univ Wollongong Sch Chem Ctr Atmospher Chem Wollongong NSW 2522 Australia Univ Bremen Inst Environm Phys D-28334 Bremen Germany Univ Wollongong Sch Chem Northfields Ave Wollongong NSW 2522 Australia Karlsruhe Inst Technol IMK ASP D-76344 Karlsruhe Germany FMI Arctic Res Ctr Tiihteltintie 62 FIN-99600 Sodankyla Finland Natl Inst Water & Atmospher Res NIWA Private Bag 50061 Omakau Central Otago New Zealand Karlsruhe Inst Technol IMK IFU D-82467 Garmisch Partenkirchen Germany

This paper presents a novel retrieval algorithm for the rapid retrieval of the carbon dioxide total column amounts from high resolution spectra in the short wave infrared (SWIR) range observations by the Greenhouse gases Observing Satellite (GOSAT). The algorithm performs EOF (Empirical Orthogonal Function)-based decomposition of the measured spectral radiance and derives the relationship of limited number of the decomposition coefficients in terms of the principal components with target gas amount and a priori data such as airmass, surface pressure, etc. The regression formulae for retrieving target gas amounts are derived using training sets of collocated GOSAT and ground -based observations. The precision/accuracy characteristics of the algorithm are analyzed by the comparison of the retrievals with those from the Total Carbon Column Observing Network (TCCON) measurements and with the modeled data, and appear similar to those achieved by full-physics retrieval algorithms. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Carbon dioxide retrieval algorithm Empirical orthogonal function GOSAT TCCON

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Application of a Markov Chain Monte Carlo algorithm for snow water equivalent retrieval from passive microwave measurements

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REMOTE SENSING OF ENVIRONMENT 2017年 192卷 150-165页

作者： Pan, Jinmei Durand, Michael T. Vander Jagt, Benjamin J. Liu, Desheng Ohio State Univ Sch Earth Sci Columbus OH 43210 USA Ohio State Univ Byrd Polar & Climate Res Ctr Columbus OH 43210 USA Ohio State Univ Dept Geog Columbus OH 43210 USA

Recent applications of passive microwave remote sensing techniques to estimate snow water equivalent (SWE) increasingly rely on the comprehension of microwave emission theories, instead of traditional empirical fitting approaches. In this study, an advanced SWE retrieval algorithm based on the Markov Chain Monte Carlo method was developed. This method samples the posterior multiple-layer snow properties according to the likelihood of the brightness temperature (TB) simulation with the actual TB observations. The Microwave Emission Model of Layered Snowpacks with improved Born approximation (MEMLS-IBA) was used as the observation model. Using a globally applicable method to produce prior estimates of snow properties, the retrieval approach is called the Bayesian algorithm for SWE Estimation with Passive Microwave measurements (BASE-PM), and was applied on 48 snowpits at Sodanlcyla, Finland;Churchill, Canada and Colorado, US. The result shows that the root mean squared (RMS) error of the retrieved SWE is 42.7 mm excluding two outliers, and is 30.8 mm if the outliers as well as six deep snowpits from Colorado are excluded. This accuracy approximately meets the 30-mm requirement of Integrated Global Observing Strategy for shallow snow. The poor performance for the outlier and deep snowpits is explained. Additional experiments using more accurate priors show that SWE retrieval accuracy can be improved with local snowcover knowledge, e.g. if historical snowpit measurements or snow process model simulations are available. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Passive microwave remote sensing Snow water equivalent retrieval algorithm

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retrieval of Barometric Pressure from Satellite Passive Microwave Observations over the Oceans

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JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS 2018年第6期123卷 4360-4372页

作者： Zhang, Zijin Dong, Xiaolong Liu, Liling He, Jieying Chinese Acad Sci Natl Space Sci Ctr Key Lab Microwave Remote Sensing Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China China Univ Min & Technol Sch Mech Elect & Informat Engn Beijing Peoples R China

Sea surface barometric pressure is one of the few key geophysical variables has not been derived from satellite observations. In this study, we investigate the retrieval of sea surface barometric pressure from passive microwave observations. The direct relationship between surface barometric pressure and upward-emitted brightness temperature observed by a microwave radiometer is deduced and validated. A statistical retrieval algorithm based on the back-propagation (BP) neural networks is proposed to estimate sea surface barometric pressure using the observations from the Advanced Technology Microwave Sounder (ATMS) onboard the Suomi-National Polar-Orbiting Operational Environmental Satellite System Preparatory Project (SNPP) satellite. In situ buoy measurements and reanalysis data are used to assess the retrieval performance. Experimental results show that the proposed retrieval algorithm can estimate sea surface barometric pressure over mid-to-low latitude areas ( 40 degrees S-40 degrees N) with the root mean square errors of less than 2.0, 3.0, and 3.5 hPa for clear-sky, cloudy, and rainy conditions, respectively. Several tropical cyclone retrieval experiments also show that the proposed retrieval algorithm behaves well under high wind conditions (15 m/s

关键词： sea surface barometric pressure retrieval algorithm passive microwave ATMS tropical cyclone analysis

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Remote Sensing of Sea Surface Salinity: Comparison of Satellite and In Situ Observations and Impact of retrieval Parameters

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REMOTE SENSING 2019年第7期11卷 750-750页

作者： Dinnat, Emmanuel P. Le Vine, David M. Boutin, Jacqueline Meissner, Thomas Lagerloef, Gary NASA Goddard Space Flight Ctr Greenbelt MD 20771 USA Chapman Univ CEESMO Orange CA 92866 USA Sorbonne Univ CNRS MNHN LOCEANIRD F-75005 Paris France Remote Sensing Syst Santa Rosa CA 95401 USA Earth & Space Res Seattle WA 98121 USA

Since 2009, three low frequency microwave sensors have been launched into space with the capability of global monitoring of sea surface salinity (SSS). The European Space Agency's (ESA's) Microwave Imaging Radiometer using Aperture Synthesis (MIRAS), onboard the Soil Moisture and Ocean Salinity mission (SMOS), and National Aeronautics and Space Administration's (NASA's) Aquarius and Soil Moisture Active Passive mission (SMAP) use L-band radiometry to measure SSS. There are notable differences in the instrumental approaches, as well as in the retrieval algorithms. We compare the salinity retrieved from these three spaceborne sensors to in situ observations from the Argo network of drifting floats, and we analyze some possible causes for the differences. We present comparisons of the long-term global spatial distribution, the temporal variability for a set of regions of interest and statistical distributions. We analyze some of the possible causes for the differences between the various satellite SSS products by reprocessing the retrievals from Aquarius brightness temperatures changing the model for the sea water dielectric constant and the ancillary product for the sea surface temperature. We quantify the impact of these changes on the differences in SSS between Aquarius and SMOS. We also identify the impact of the corrections for atmospheric effects recently modified in the Aquarius SSS retrievals. All three satellites exhibit SSS errors with a strong dependence on sea surface temperature, but this dependence varies significantly with the sensor. We show that these differences are first and foremost due to the dielectric constant model, then to atmospheric corrections and to a lesser extent to the ancillary product of the sea surface temperature.

关键词： sea surface salinity microwave radiometry remote sensing calibration retrieval algorithm validation Aquarius SMOS SMAP sea surface temperature

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A retrieval algorithm of Sheet Metal Parts Based on Relationships of Features

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Chinese Journal of Aeronautics 2012年第3期25卷 453-472页

作者： WANG Dawei YAN Guangrong LEI Yi ZHANG Jiaying School of Mechanical Engineering and Automation Beihang University Beijing 100191. China Modern Education Center. Shandong University of Science and Technology. Ta ian 271019. China

With the rapid increase in the number of three-dimensional （3D） models each year, to quickly and easily find the part desired has become a big challenge of enterprises. Meanwhile, many methods and algorithms have been proposed for part retrieval. However, most of the existing methods are designed lbr mechanical parts, and can not be well worked for sheet metal part re- trieval. An approach to feature-based retrieval of sheet metal parts is presented. Firstly, the features frequently used in sheet metal part design are chosen as the ＂＇key words＂ in retrieval. Based on those features, a relative position model is built to express the different relationships of the features in 3D space. Secondly, a description method of the model is studied. With the descrip- tion method the relative position of features in sheet metal parts can be expressed by four location description matrices. Thirdly, based on the relative position model and location description matrices, the equivalent definition of relationships of two feature groups is given which is the basis to calculate the similarity of two sheet metal parts. Next, the tbrmula of retrieval algorithm for sheet metal parts is given. Finally, a prototype system is developed to test and verify the effectiveness of the retrieval method suggested. Experiments verify that the new method is able to meet the requirements of searching sheet metal parts and possesses potentials in practical application.

关键词： CAD sheet metal retrieval algorithm features search 3D model

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EXPLOITATION OF GPM/CLOUDSAT COINCIDENCE DATASET FOR GLOBAL SNOWFALL retrieval 38

EXPLOITATION OF GPM/CLOUDSAT COINCIDENCE DATASET FOR GLOBAL ...

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38th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Panegrossi, Giulia Rysman, Jean-Francois Casella, Daniele Sano, Paolo Marra, Anna Cinzia Dietrich, Stefano Kulie, Mark S. Natl Res Council CNR ISAC Rome Italy SERCO SpA Frascati Italy Michigan Technol Univ Houghton MI 49931 USA

ISBN: (纸本)9781538671504

The assessment of the actual observational capabilities of snowfall by spaceborne microwave radiometers is crucial to develop and improve precipitation retrieval algorithms. Exploiting coincident spaceborne active and passive microwave sensor datasets can effectively enhance our understanding of high-frequency microwave channels sensitivity to snowfall. This study illustrates the results of the analysis of matched Global Precipitation Measurement (GPM) Microwave Imager (GMI) and CloudSat Cloud Profiling Radar (CPR) snowfall observations (mainly found at latitudes between 55 and 65) providing insights on GMI multi-frequency signals associated with different snowfall types. These findings are used to develop a new algorithm to retrieve snow water path associated to surface snowfall from GMI multichannel measurements.

关键词： Passive microwave radiometer GPM GMI CloudSat snowfall retrieval algorithm

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retrieval OF TYPHOON AND HURRICANE SURFACE BAROMETRIC PRESSURE BY PASSIVE MICROWAVE MEASUREMENTS 38

RETRIEVAL OF TYPHOON AND HURRICANE SURFACE BAROMETRIC PRESSU...

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38th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Zhang, Zijin Dong, Xiaolong Chinese Acad Sci Natl Space Sci Ctr CAS Key Lab Microwave Remote Sensing Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (纸本)9781538671504

The paper investigates the retrieval of typhoon and hurricane surface barometric pressure by passive measurements. The SVR based retrieval algorithm is presented and the passive microwave measurements from the SNPP/ATMS are used for the algorithm training and verification. The assessment of the retrieval performance is done by comparing the case-by-case retrievals with dropsonde measurements and tropical cyclone best track data. The validation results show that the established retrieval algorithm can estimate typhoon and hurricane surface barometric pressure with the accuracy better than 8hpa. As a preliminary conclusion, this method can provide some important sea surface barometric pressure information for typhoon and hurricane structure and dynamic characteristics analysis and offers a new idea for the study of typhoon and hurricane from microwave radiometer data.

关键词： Sea surface barometric pressure typhoon and hurricane analysis retrieval algorithm ATMS

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The TanSat mission： preliminary global observations

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Science Bulletin 2018年第18期63卷 1200-1207页

作者： Yi Liu Jing Wang Lu Yao Xi Chen Zhaonan Cai Dongxu Yang Zengshan Yin Songyan Gu Longfei Tian Naimeng Lu Daren Lyu Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029 China University of Chinese Academy of Sciences Beijing 100049 China Shanghai Engineering Center for Microsatellites Shanghai 201210 China National Satellite Meteorological Center China Meteorological Administration Beijing 100081 China

The Chinese global carbon dioxide monitoring satellite （TanSat） was launched successfully in December 2016 and has completed its on-orbit tests and calibration. TanSat aims to measure the atmospheric column-averaged dry air mole fractions of carbon dioxide （XCO2） with a precision of 4 ppm at the regional scale, and in addition, to derive global and regional CO2 fluxes. Progress towards these objectives is reviewed and the first scientific results from TanSat measurements are presented. TanSat on-orbit tests indicate that the Atmospheric Carbon dioxide GratingSpectrometer is in normal working status and is beginning to produce LIB products. The preliminary TanSat XCO2 products have been retrieved by an algorithm and compared to NASA Orbiting Carbon Observatory-2 （OCO-2） measurements during an over- lapping observation period. Furthermore, the XCO2 retrievals have been validated against eight groundsite measurement datasets from the Total Carbon Column Observing Network, for which the preliminary conclusion is that TanSat has met the precision design requirement, with an average bias of 2.11 ppm. The first scientific observations are presented, namely, the seasonal distributions of XCO2 over land on a global scale.

关键词： TanSat Carbon dioxide retrieval algorithm Carbon flux inversion

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Antenna Pattern retrieval from Measurements in non-ideal Anechoic Chamber

Antenna Pattern Retrieval from Measurements in non-ideal Ane...

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Conference on Systems of Signals Generating and Processing in the Field of on Board Communications

作者： Choni, Yu, I Abuhadma, L. K. T. Danilov, I. Yu Kazan Natl Res Tech Univ Radio Elect & Telecommun Syst Kazan Tatarstan Russia Informat Satellite Syst Reshetnev Co Zheleznogorsk Russia

ISBN: (纸本)9781538656235;9781538656228

The study focuses on the measurement procedure and the algorithm for retrieval of the true radiation pattern of the antenna from data measured in non-ideal environments, which are insufficient distance from the source antenna and scattering from the walls of the chamber. Unlike the previous works, a concept of converging cluster of plane waves used not only to approximate the primary illuminating field, but also to account for waves reflected from the measuring chamber walls. In addition, expansion in the number of basis functions instead of a set of points represents the sought-for antenna pattern. This leads to bettering the reconstruction algorithm stability. The results of modeling various tasks illustrate how interesting can be relief of fields brought forth by clusters of waves inside and outside the test zone.

关键词： antenna radiation pattern anechoic chamber converging cluster of plane waves retrieval algorithm stability

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