Empirical Approach to Satellite Snow Detection

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 high-resolution 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. Polar-orbiting 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.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

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

Remote Sensing of Environmental Changes in Cold Regions

This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing

Automated dust storm detection using satellite images. Development of a computer system for the detection of dust storms from MODIS satellite images and the creation of a new dust storm database.

Dust storms are one of the natural hazards, which have increased in frequency in the recent years over Sahara desert, Australia, the Arabian Desert, Turkmenistan and northern China, which have worsened during the last decade. Dust storms increase air pollution, impact on urban areas and farms as well as affecting ground and air traffic. They cause damage to human health, reduce the temperature, cause damage to communication facilities, reduce visibility which delays both road and air traffic and impact on both urban and rural areas. Thus, it is important to know the causation, movement and radiation effects of dust storms. The monitoring and forecasting of dust storms is increasing in order to help governments reduce the negative impact of these storms. Satellite remote sensing is the most common method but its use over sandy ground is still limited as the two share similar characteristics. However, satellite remote sensing using true-colour images or estimates of aerosol optical thickness (AOT) and algorithms such as the deep blue algorithm have limitations for identifying dust storms. Many researchers have studied the detection of dust storms during daytime in a number of different regions of the world including China, Australia, America, and North Africa using a variety of satellite data but fewer studies have focused on detecting dust storms at night. The key elements of this present study are to use data from the Moderate Resolution Imaging Spectroradiometers on the Terra and Aqua satellites to develop more effective automated method for detecting dust storms during both day and night and generate a MODIS dust storm database.Libyan Centre for Remote Sensing and Space ScienceAppendix A was submitted with extra data files which are not available online

Effects of boreal forest on multi-scale optical remote sensing observations for snow-covered landscape

Optical snow monitoring methods have tendency to underestimate snow cover beneath the evergreen forest canopy due to the masking effect of trees. There is need to develop method for providing more reliable snow products and enhance their use e.g. in hydrological and climatological models. The main objective of this thesis is to provide information to improve the accuracy of snow mapping by algorithm development and its regional parameterization. This thesis exploits reflectance data derived from ground-based, mast-borne, airborne and space-borne sensors. Each datatype with different ground resolutions has specific strengths and weaknesses. Together this dataset provides valuable information to advance knowledge of reflectance properties of snow-covered forests and supports the interpretation of satellite-borne reflectance observations. Improvement of satellite-based snow cover mapping is essential because it is the only way to monitor snow cover spatially, temporally and economically effectively. To obtain information about certain geophysical variable using satellite data, a model for interpreting the satellite signal must be developed. The feasibility of satellite-borne observations in describing geophysical variables depends on the reliability of the model used. Here simple reflectance models based on the zeroth order radiative transfer equation and lineal mixing models are investigated. They are found to reliably describe the observed surface reflectances from snow-covered terrain, both in forests and in open areas. Additionally, to improve methods for seasonal snow cover monitoring in forests, the high spatial resolution observations are required to describe spectral properties and their temporal behaviour of different targets inside the investigated scene. It is also important to combine these target-specific reflectances with the in situ data to describe the characteristics of the target area. In this thesis the datasets complement each other so that while mast-borne data provides information on the temporal behaviour of the scene reflectance of the specific location where measurement conditions are well known, the airborne data provides information during a very short time (~1 hour) on the spatial variation of scene reflectance from the areas where land cover, forest characteristics and snow conditions are well defined. The results demonstrate the notable effect of forest on observed reflectance in both the temporal (changes in illumination geometry) and on the spatial (changes in forest structure) scale. The presence of tree canopy also weakens the capability of the Normalized Difference Snow Index (NDSI) to detect snow-covered areas. Additionally, the effect of melting snow cover on reflectances and NDSI is significant in all land covers producing high variation inside individual land cover types too.Boreaalisen havumetsän vaikutus lumipeitteisen maaston optisiin kaukokartoitusmittauksiin Laaja osa pohjoisen pallonpuoliskon maa-alasta kuuluu kausittaisen lumipeitteen vyöhykkeeseen. Kausittainen lumipeite on herkkä lämpötilan vaihteluille ja siksi se on hyvä ilmastonmuutoksen indikaattori. Sulaessaan kausittainen lumipeite vapauttaa valtavan määrän talven ajaksi varastoitunutta vettä. Vapautuvan veden määrän ennakoiminen on tärkeässä roolissa tulvavahinkojen minimoimisessa sekä vesivoiman säännöstelyssä. Suuri osa lumipeitteisistä alueista on harvaan asuttua ja satelliitit tarjoavat ainoan vaihtoehdon saada ajallisesti ja paikallisesti kattavaa tietoa. Kuitenkin samalla suuri osa kausittaisen lumipeitteen alasta kuuluu boreaaliseen metsävyöhykkeeseen, jossa optisilla kaukokartoitusmenetelmillä on vaikeuksia tunnistaa lumipeite ikivihreän kasvillisuuden alla. Tämän väitöskirjatyön tavoite on tutkia valon käyttäytymistä boreaalisella metsävyöhykkeellä lumipeitteisenä aikana. Tätä tietoa voidaan suoraan hyödyntää lumen kaukokartoitusmenetelmien kehittämisessä, huomioiden eri satelliittisensorien maastoerotuskyky ja aallonpituuskanavat. Näin saatu entistä tarkempi tieto lumipeitteestä parantaa myös niiden ilmasto- ja hydrologisten mallien tarkkuutta, jotka hyödyntävät lumipeitetietoa laskennassaan. Jotta satelliitin välityksellä voidaan saada tietoa jostakin tietystä geofysikaalisesta parametrista, on kehitettävä malli satelliitti-instrumentin mittaaman signaalin tulkitsemiseksi. Tässä työssä tutkitaan säteilynkuljetusyhtälöön ja lineaariseen mallinnukseen perustuvia yksinkertaisia heijastusmalleja. Työn kannalta oleellisia ovat tarkasti määritetyt heijastusmittaukset luonnon kohteista, joiden ominaisuudet vaihtelevat ajallisesti ja paikallisesti. Työssä hyödynnetään 1) maastossa, 2) mastosta ja 3) lentäen mitattuja valon heijastussuhteita optisella aallonpituusalueella sekä aktiivisella tutkasensorilla määritettyjä tarkkoja tietoja puuston peittämästä alasta ja puuston korkeudesta. Tämä kolmitasoinen lähestymistapa antaa tärkeää tietoa erotuskyvyn (ts. mittakaavan) merkityksestä satelliittihavainnon mallintamisessa ja tulkinnassa. Tulokset osoittavat, että semi-empiirinen säteilynkuljetusyhtälöön perustuva heijastusmalli on pätevä lumipeitteen kaukokartoitukseen myös metsäisillä alueilla. Puustolla on merkittävä vaikutus lumipeitteisen maaston heijastuskykyyn sekä ajallisesti (muutokset kuvaus- ja valaistusgeometriassa) että paikallisesti (muutokset puuston ominaisuuksissa), mikä tulee huomioida mallinnuksessa. Puusto heikentää myös lumipeitteen kaukokartoituksessa paljon hyödynnetyn lumi-indeksin (Normalized Difference Snow Index) kykyä havaita lumiset alueet. Myös ohuella sulavalla lumipeitteellä on merkittävä vaikutus heijastussuhteisiin ja lumi-indeksiin kaikissa tutkituissa maanpeitetyypeissä, myös aukeilla. Tämä aiheuttaa suuria eroja havaittuihin arvoihin myös yksittäisten maanpeitetyyppien sisällä. Saavutetut tulokset tukevat optisten lumen kaukokartoitusmenetelmien kehitystä, niiden validointia ja alueellista parametrisointia

Aeronautics and space report of the President, 1980 activities

The year's achievements in the areas of communication, Earth resources, environment, space sciences, transportation, and space energy are summarized and current and planned activities in these areas at the various departments and agencies of the Federal Government are summarized. Tables show U.S. and world spacecraft records, spacecraft launchings for 1980, and scientific payload anf probes launched 1975-1980. Budget data are included

Toward an Integrated Regional Research Program on Global Change and the Nation\u27s Major Grasslands: Second Annual Report

I DIRECTOR\u27S REPORT: A GPRC Research Framework and Thrusts B FY94 GPRC Grant Competition C Synopsis of Current Projects 1 Thrust 1: Impacts of Climate Change 2 Thrust 2: Measuring and Modeling Net Carbon Exchange 3 Other Projects D Summary and Recommendations of FY94 GPRC PI\u27s Workshop 1 Biogeochemical Cycling Group 2 Climate Scenarios Group 3 Managed and Unmanaged Ecosystem Impacts Group 4 Scaling Group 5 Actions Prompted by the Workshop E Research Integration with ARM-CART: Eco-ARM F Future Directions for the GPRC Appendix I-A: Biogeochemical Cycling Group Workshop Report • Appendix I-B: Climate Change Scenarios Group Workshop Report • Appendix I-C: Managed and Unmanaged Ecosystem Impacts Group Workshop Report • Appendix 1-0: Funded Projects Table • Appendix I-E: Core Research Program Diagram • Appendix I-F: Regional Map II RESEARCH PROGRESS REPORTS (Title, Principal Investigator, Institution): A IMPACTS OF CLIMATE CHANGE 1 Process Studies Effects of Altered Soil Moisture and Temperature on Soil Communities, Primary Producers and Ecological Processes in Grassland Ecosystems · John M Blair, Kansas State University Impacts of global climate change on phytoplankton productivity in lakes along a thermal gradient · Kyle D Hoagland, University of Nebraska-Lincoln Natural Responses of Shallow Lakes and Wetlands for Detecting Climatic/Environmental Change · Donald C Rundquist, University of Nebraska-Lincoln 2 Climate Scenarios for Impact Analysis Space-time Local Hydrology Influenced by Changing Climatology: Disaggregation, Prediction and Comparison · Istvan Bogardi, University of Nebraska-Lincoln Observational and Numerical Study for Interannual and Interdecadel Variabilities of the Atmospheric Circulation · Tsing-Chang Chen, Iowa State University The Effect of Ecosystems on Cloud Microphysics and Aerosol Distribution · Qinghuan Han, South Dakota School of Mines and Technology Development of a Nested Regional Model for the Conterminous United States and Formation of High Resolution Climate Change Scenarios with an Application to Crop Climate Models · Linda Mearns, National Center for Atmospheric Research The detection of Climate Change Using Long Term Daily Climate Records Over Grassland Regions of the Northern Hemisphere · Michael A Palecki, University of Nebraska-Lincoln 3 Modeling Impacts of Climate Change Assessment of Climate Change on a Mixed Agricultural Landscape on the North American Great Plains · James R Brandle, University of Nebraska-Lincoln The Economic and Environmental Impact of Major Shifts in Land Use into Energy Biomass Production for Part of the Great Plains · Paul T Dyke, Texas A&M University Local and Regional Scaling With a Spatially Explicit Ecological Model · George P Malanson, University of Iowa Potential Global Warming Impacts on Vegetation Distribution, Productivity, and Hydrology at Landscape to Regional Scales in the Great Plains Region · Ronald P Neilson, Oregon State University B MEASUREMENT AND MODELING OF NET CARBON EXCHANGE 1 Process Studies Carbon, Water, and Energy Fluxes From a Tallgrass Prairie: A Long-term investigation of Biological, Environmental, and Land Use Factors · Jay M Ham, Kansas State University An Integrated Investigation of Methane and Carbon Dioxide Fluxes in Mid-Latitude Prairie Wetlands: Micrometeorological Measurements, Process-Level Studies and Modeling · Shashi B Verma, University of Nebraska-Lincoln 2 Modeling Studies Regional projections of C Dynamics with Global Change in the Central US Edward T Elliott, Colorado State University Assessment of Climate and Management Induced Directional Changes in Great Plains Vegetation with NDVI and Stable Carbon Isotopes Larry L Tieszen, Augustana College C DETECTION OF CLIMATE CHANGE Climate Change in the Mid-continent of North America William D Gosnold, University of North Dakota 105 Satellite Observation of Lake Ice as a Robust Indicator of Regional Climate Change Thomas M Ullesand, University of Wisconsin-Madison Appendix II-A: Author Index Great Plains Regional Center for Global Environmental Change 20 LW Chase Hall University of Nebraska-Lincoln PO Box 830725 Lincoln, NE 68583-0725 Phone 4021472-7887 Fax 4021472-6614 E-mail agme022@unlvmunledu ACKNOWLEDGEMENT This material is based upon work supported by the US Department of Energy under Cooperative Agreement No DE-FC03-90ER61 01 O Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the US Department of Energ

Aeronautics and space report of the President, 1982 activities

Achievements of the space program are summerized in the area of communication, Earth resources, environment, space sciences, transportation, aeronautics, and space energy. Space program activities of the various deprtments and agencies of the Federal Government are discussed in relation to the agencies' goals and policies. Records of U.S. and world spacecraft launchings, successful U.S. launches for 1982, U.S. launched applications and scientific satellites and space probes since 1975, U.S. and Soviet manned spaceflights since 1961, data on U.S. space launch vehicles, and budget summaries are provided. The national space policy and the aeronautical research and technology policy statements are included

Earth Resources: A continuing bibliography with indexes, issue 33

This bibliography list 436 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution sytems, instrumentation and sensors, and economic analysis