An atmospheric correction algorithm for FY3/MERSI data over land in China

Feng-Yun (FY-3) is the second generation of the Chinese Polar Orbiting Meteorological Satellites with global, three-dimensional, quantitative, and multispectral capabilities. Medium Resolution Spectral Imager (MERSI) has 20 channels onboard the FY-3A and FY-3B satellites, including five channels (four VIS and one thermal IR) with a spatial resolution of 250m. The top of the atmosphere signal are necessary to be radiometrically calibrated and corrected for atmospheric effects based on surface reflectance, especially in land surface remote sensing and applications. This paper presents an atmospheric correction algorithm for FY3/MERSI data over land in China, taking into account the directional properties of the observed surface by a kernel-based Bi-directional Reflectance Distribution Function (BRDF) model. The comparison with MODGA and ASD reflectance showed that there is a good agreement. Therefore, FY3/MERSI can serve a reliable and new data source for quantifying global environment change

Dust aerosol optical depth retrieval and dust storm detection for Xinjiang Region using Indian National Satellite Observations

The Xinjiang Uyghur Autonomous Region (Xinjiang) is located near the western border of China. Xinjiang has a high frequency of dust storms, especially in late winter and early spring. Geostationary satellite remote sensing offers an ideal way to monitor the regional distribution and intensity of dust storms, which can impact the regional climate. In this study observations from the Indian National Satellite (INSAT) 3D are used for dust storm detection in Xinjiang because of the frequent 30-min observations with six bands. An analysis of the optical properties of dust and its quantitative relationship with dust storms in Xinjiang is presented for dust events in April 2014. The Aerosol Optical Depth (AOD) derived using six predefined aerosol types shows great potential to identify dust events. Cross validation between INSAT-3D retrieved AOD and MODIS AOD shows a high coefficient of determination (R2 = 0.92). Ground validation using AERONET (Aerosol Robotic Network) AOD also shows a good correlation with R2 of 0.77. We combined the apparent reflectance (top-of-atmospheric reflectance) of visible and shortwave infrared bands, brightness temperature of infrared bands and retrieved AOD into a new Enhanced Dust Index (EDI). EDI reveals not only dust extent but also the intensity. EDI performed very well in measuring the intensity of dust storms between 22 and 24 April 2014. A visual comparison between EDI and Feng Yun-2E (FY-2E) Infrared Difference Dust Index (IDDI) also shows a high level of similarity. A good linear correlation (R2 of 0.78) between EDI and visibility on the ground demonstrates good performance of EDI in estimating dust intensity. A simple threshold method was found to have a good performance in delineating the extent of the dust plumes but inadequate for providing information on dust plume intensity

Optical Remote Sensing of Planetary Space Environment

Planetary science is the scientific investigations of the basic characteristics and the formation and evolution processes of the planets, moons, comets, asteroids and other minor bodies of the solar system, the exoplanets, and the planetary systems. Planetary scientific research mainly depends on deep space exploration, and it is highly interdisplinary and is built from Earth science, space science, astronomy and other relevant disciplines. Planetary space, a critical region of mass and energy exchange between the planet and the interplanetary space, is an integral part of the planetary multi-layer coupling system. Atmospheres of different compositions and plasmas of different densities and energies exist in planetary space, where mass transportation at different temporal and spatial scales and various energy deposition and dissipation processes occur. Optical remote sensing overcomes the difficulties of capturing global views and distinguishing spatiotemporal variations in in-situ particle and field detections. This chapter introduces the principles and applications of optical remote sensing in planetary science. The first ground-based planetary observatory in China, the Lenghu Observation Center for Planetary Sciences, will be introduced in detail. Future development of optical remote sensing platforms in Chinese planetary exploration program will also be introduced

Empirical approach to satellite snow detection

Lumipeitteellä on huomattava vaikutus säähän, ilmastoon, luontoon ja yhteiskuntaan. Pelkästään sääasemilla tehtävät lumihavainnot (lumen syvyys ja maanpinnan laatu) eivät anna kattavaa kuvaa lumen peittävyydestä tai muista lumipeitteen ominaisuuksista. Sääasemien tuottamia havaintoja voidaan täydentää satelliiteista tehtävillä havainnoilla. Geostationaariset sääsatelliitit tuottavat havaintoja tihein välein, mutta havaintoresoluutio on heikko monilla alueilla, joilla esiintyy kausittaista lunta. Polaariradoilla sääsatelliittien havaintoresoluutio on napa-alueiden läheisyydessä huomattavasti parempi, mutta silloinkaan satelliitit eivät tuota jatkuvaa havaintopeittoa. Tiheimmän havaintoresoluution tuottavat sääsatelliittiradiometrit, jotka toimivat optisilla aallonpituuksilla (näkyvä valo ja infrapuna). Lumipeitteen kaukokartoitusta satelliiteista vaikeuttavat lumipeitteen oman vaihtelun lisäksi pinnan ominaisuuksien vaihtelu (kasvillisuus, vesistöt, topografia) ja valaistusolojen vaihtelu. Epävarma ja osittain puutteellinen tieto pinnan ja kasvipeitteen ominaisuuksista vaikeuttaa luotettavan automaattisen analyyttisen lumentunnistusmenetelmän kehittämistä ja siksi empiirinen lähestymistapa saattaa olla toimivin vaihtoehto automaattista lumentunnistusmenetelmää kehitettäessä. Tässä työssä esitellään kaksi EUMETSATin osittain rahoittamassa H SAFissa kehitettyä lumituotetta ja niissä käytetyt empiiristä lähestymistapaa soveltaen kehitetyt algoritmit. Geostationaarinen MSG/SEVIRI H31 lumituote on saatavilla vuodesta 2008 alkaen ja polaarituote Metop/AVHRR H32 vuodesta 2015 alkaen. Lisäksi esitellään pintahavaintoihin perustuvat validointitulokset, jotka osoittavat tuotteiden saavuttavan määritellyt tavoitteet.Snow cover plays a significant role in the weather and climate system, ecosystems and many human activities, such as traffic. Weather station snow observations (snow depth and state of the ground) do not provide highresolution continental or global snow coverage data. The satellite observations complement in situ observations from weather stations. Geostationary weather satellites provide observations at high temporal resolution, but the spatial resolution is low, especially in polar regions. Polarorbiting weather satellites provide better spatial resolution in polar regions with limited temporal resolution. The best detection resolution is provided by optical and infra-red radiometers onboard weather satellites. Snow cover in itself is highly variable. Also, the variability of the surface properties (such as vegetation, water bodies, topography) and changing light conditions make satellite snow detection challenging. Much of this variability is in subpixel scales, and this uncertainty creates additional challenges for the development of snow detection methods. Thus, an empirical approach may be the most practical option when developing algorithms for automatic snow detection. In this work, which is a part of the EUMETSAT-funded H SAF project, two new empirically developed snow extent products for the EUMETSAT weather satellites are presented. The geostationary MSG/SEVIRI H32 snow product has been in operational production since 2008. The polar product Metop/AVHRR H32 is available since 2015. In addition, validation results based on weather station snow observations between 2015 and 2019 are presented. The results show that both products achieve the requirements set by the H SAF

Exploring Himawari-8 geostationary observations for the advanced coastal monitoring of the Great Barrier Reef

Larissa developed an algorithm to enable water-quality assessment within the Great Barrier Reef (GBR) using weather satellite observations collected every 10 minutes. This unprecedented temporal resolution records the dynamic nature of water quality fluctuations for the entire GBR, with applications for improved monitoring and management

OAST Space Theme Workshop. Volume 3: Working group summary. 3: Sensors (E-3). A. Statement. B. Technology needs (form 1). C. Priority assessment (form 2). D. Additional assessment

Developments required to support the space power, SETI, solar system exploration and global services programs are identified. Instrumentation and calibration sensors (rather than scientific) are needed for the space power system. Highly sophisticated receivers for narrowband detection of microwave sensors and sensors for automated stellar cataloging to provide a mapping data base for SETI are needed. Various phases of solar system exploration require large area solid state imaging arrays from UV to IR; a long focal plane telescope; high energy particle detectors; advanced spectrometers; a gravitometer; and atmospheric distanalyzer; sensors for penetrometers; in-situ sensors for surface chemical analysis, life detection, spectroscopic and microscopic analyses of surface soils, and for meteorological measurements. Active and passive multiapplication sensors, advanced multispectral scanners with improved resolution in the UV and IR ranges, and laser techniques for advanced probing and oceanographic characterization will enhance for global services

NASA earth science and applications division: The program and plans for FY 1988-1989-1990

Described here are the Division's research goals, priorities and emphases for the next several years and an outline of longer term plans. Included are highlights of recent accomplishments, current activities in FY 1988, research emphases in FY 1989, and longer term future plans. Data and information systems, the Geodynamics Program, the Land Processes Program, the Oceanic Processes Program, the Atmospheric Dynamics and Radiation Program, the Atmospheric Chemistry Program, and space flight programs are among the topic covered

Dust aerosol optical depth retrieval and dust storm detection for Xinjiang Region using Indian national satellite observations

The Xinjiang Uyghur Autonomous Region (Xinjiang) is located near the western border of China. Xinjiang has a high frequency of dust storms, especially in late winter and early spring. Geostationary satellite remote sensing offers an ideal way to monitor the regional distribution and intensity of dust storms, which can impact the regional climate. In this study observations from the Indian National Satellite (INSAT) 3D are used for dust storm detection in Xinjiang because of the frequent 30-min observations with six bands. An analysis of the optical properties of dust and its quantitative relationship with dust storms in Xinjiang is presented for dust events in April 2014. The Aerosol Optical Depth (AOD) derived using six predefined aerosol types shows great potential to identify dust events. Cross validation between INSAT-3D retrieved AOD and MODIS AOD shows a high coefficient of determination (R2 = 0.92). Ground validation using AERONET (Aerosol Robotic Network) AOD also shows a good correlation with R2 of 0.77. We combined the apparent reflectance (top-of-atmospheric reflectance) of visible and shortwave infrared bands, brightness temperature of infrared bands and retrieved AOD into a new Enhanced Dust Index (EDI). EDI reveals not only dust extent but also the intensity. EDI performed very well in measuring the intensity of dust storms between 22 and 24 April 2014. A visual comparison between EDI and Feng Yun-2E (FY-2E) Infrared Difference Dust Index (IDDI) also shows a high level of similarity. A good linear correlation (R2 of 0.78) between EDI and visibility on the ground demonstrates good performance of EDI in estimating dust intensity. A simple threshold method was found to have a good performance in delineating the extent of the dust plumes but inadequate for providing information on dust plume intensity