Utilizing Landsat Satellite Data (1990-2018) to Detect Water Inundation for the Management of Human Settlements in Coastal Zones
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Use of Remotely Sensed Data to Enhance Estimation of Aboveground Biomass for the Dry Afromontane Forest in South-Central Ethiopia
remote sensing Article Use of Remotely Sensed Data to Enhance Estimation of Aboveground Biomass for the Dry Afromontane Forest in South-Central Ethiopia Habitamu Taddese 1,2,* , Zerihun Asrat 2,3 , Ingunn Burud 1, Terje Gobakken 3 , Hans Ole Ørka 3 , Øystein B. Dick 1 and Erik Næsset 3 1 Faculty of Science and Technology, Norwegian University of Life Sciences, P.O. Box 5003, 1432 Ås, Norway; [email protected] (I.B.); [email protected] (Ø.B.D.) 2 Wondo Genet College of Forestry and Natural Resources, Hawassa University, P.O. Box 128, Shashemene 3870006, Ethiopia; [email protected] 3 Faculty Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, 1432 Ås, Norway; [email protected] (T.G.); [email protected] (H.O.Ø.); [email protected] (E.N.) * Correspondence: [email protected]; Tel.: +47-4671-8534 Received: 31 July 2020; Accepted: 11 October 2020; Published: 13 October 2020 Abstract: Periodic assessment of forest aboveground biomass (AGB) is essential to regulate the impacts of the changing climate. However, AGB estimation using field-based sample survey (FBSS) has limited precision due to cost and accessibility constraints. Fortunately, remote sensing technologies assist to improve AGB estimation precisions. Thus, this study assessed the role of remotely sensed (RS) data in improving the precision of AGB estimation in an Afromontane forest in south-central Ethiopia. The research objectives were to identify RS variables that are useful for estimating AGB and evaluate the extent of improvement in the precision of the remote sensing-assisted AGB estimates beyond the precision of a pure FBSS. -
Seeds of Discovery: Chapters in the Economic History of Innovation Within NASA
Seeds of Discovery: Chapters in the Economic History of Innovation within NASA Edited by Roger D. Launius and Howard E. McCurdy 2015 MASTER FILE AS OF Friday, January 15, 2016 Draft Rev. 20151122sj Seeds of Discovery (Launius & McCurdy eds.) – ToC Link p. 1 of 306 Table of Contents Seeds of Discovery: Chapters in the Economic History of Innovation within NASA .............................. 1 Introduction: Partnerships for Innovation ................................................................................................ 7 A Characterization of Innovation ........................................................................................................... 7 The Innovation Process .......................................................................................................................... 9 The Conventional Model ....................................................................................................................... 10 Exploration without Innovation ........................................................................................................... 12 NASA Attempts to Innovate .................................................................................................................. 16 Pockets of Innovation............................................................................................................................ 20 Things to Come ...................................................................................................................................... 23 -
Space Security Index 2013
SPACE SECURITY INDEX 2013 www.spacesecurity.org 10th Edition SPACE SECURITY INDEX 2013 SPACESECURITY.ORG iii Library and Archives Canada Cataloguing in Publications Data Space Security Index 2013 ISBN: 978-1-927802-05-2 FOR PDF version use this © 2013 SPACESECURITY.ORG ISBN: 978-1-927802-05-2 Edited by Cesar Jaramillo Design and layout by Creative Services, University of Waterloo, Waterloo, Ontario, Canada Cover image: Soyuz TMA-07M Spacecraft ISS034-E-010181 (21 Dec. 2012) As the International Space Station and Soyuz TMA-07M spacecraft were making their relative approaches on Dec. 21, one of the Expedition 34 crew members on the orbital outpost captured this photo of the Soyuz. Credit: NASA. Printed in Canada Printer: Pandora Print Shop, Kitchener, Ontario First published October 2013 Please direct enquiries to: Cesar Jaramillo Project Ploughshares 57 Erb Street West Waterloo, Ontario N2L 6C2 Canada Telephone: 519-888-6541, ext. 7708 Fax: 519-888-0018 Email: [email protected] Governance Group Julie Crôteau Foreign Aairs and International Trade Canada Peter Hays Eisenhower Center for Space and Defense Studies Ram Jakhu Institute of Air and Space Law, McGill University Ajey Lele Institute for Defence Studies and Analyses Paul Meyer The Simons Foundation John Siebert Project Ploughshares Ray Williamson Secure World Foundation Advisory Board Richard DalBello Intelsat General Corporation Theresa Hitchens United Nations Institute for Disarmament Research John Logsdon The George Washington University Lucy Stojak HEC Montréal Project Manager Cesar Jaramillo Project Ploughshares Table of Contents TABLE OF CONTENTS TABLE PAGE 1 Acronyms and Abbreviations PAGE 5 Introduction PAGE 9 Acknowledgements PAGE 10 Executive Summary PAGE 23 Theme 1: Condition of the space environment: This theme examines the security and sustainability of the space environment, with an emphasis on space debris; the potential threats posed by near-Earth objects; the allocation of scarce space resources; and the ability to detect, track, identify, and catalog objects in outer space. -
Landsat 4, 5 and 7 (1982 to 2017) Analysis Ready Data (ARD) Observation Coverage Over the Conterminous United States and Implications for Terrestrial Monitoring
remote sensing Article Landsat 4, 5 and 7 (1982 to 2017) Analysis Ready Data (ARD) Observation Coverage over the Conterminous United States and Implications for Terrestrial Monitoring Alexey V. Egorov 1 , David P. Roy 2,* , Hankui K. Zhang 1 , Zhongbin Li 1, Lin Yan 1 and Haiyan Huang 1 1 Geospatial Sciences Center of Excellence, South Dakota State University, Brookings, SD 57007, USA; [email protected] (A.V.E.); [email protected] (H.K.Z.); [email protected] (Z.L.); [email protected] (L.Y.); [email protected] (H.H.) 2 Department of Geography, Environment & Spatial Sciences and Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI 48824, USA * Correspondence: [email protected]; Tel.: +1-517-355-3898 Received: 28 January 2019; Accepted: 17 February 2019; Published: 21 February 2019 Abstract: The Landsat Analysis Ready Data (ARD) are designed to make the U.S. Landsat archive straightforward to use. In this paper, the availability of the Landsat 4 and 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) ARD over the conterminous United States (CONUS) are quantified for a 36-year period (1 January 1982 to 31 December 2017). Complex patterns of ARD availability occur due to the satellite orbit and sensor geometry, cloud, sensor acquisition and health issues and because of changing relative orientation of the ARD tiles with respect to the Landsat orbit paths. Quantitative per-pixel and summary ARD tile results are reported. Within the CONUS, the average annual number of non-cloudy observations in each 150 × 150 km ARD tile varies from 0.53 to 16.80 (Landsat 4 TM), 11.08 to 22.83 (Landsat 5 TM), 9.73 to 21.72 (Landsat 7 ETM+) and 14.23 to 30.07 (all three sensors). -
The 2019 Joint Agency Commercial Imagery Evaluation—Land Remote
2019 Joint Agency Commercial Imagery Evaluation— Land Remote Sensing Satellite Compendium Joint Agency Commercial Imagery Evaluation NASA • NGA • NOAA • USDA • USGS Circular 1455 U.S. Department of the Interior U.S. Geological Survey Cover. Image of Landsat 8 satellite over North America. Source: AGI’s System Tool Kit. Facing page. In shallow waters surrounding the Tyuleniy Archipelago in the Caspian Sea, chunks of ice were the artists. The 3-meter-deep water makes the dark green vegetation on the sea bottom visible. The lines scratched in that vegetation were caused by ice chunks, pushed upward and downward by wind and currents, scouring the sea floor. 2019 Joint Agency Commercial Imagery Evaluation—Land Remote Sensing Satellite Compendium By Jon B. Christopherson, Shankar N. Ramaseri Chandra, and Joel Q. Quanbeck Circular 1455 U.S. Department of the Interior U.S. Geological Survey U.S. Department of the Interior DAVID BERNHARDT, Secretary U.S. Geological Survey James F. Reilly II, Director U.S. Geological Survey, Reston, Virginia: 2019 For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment—visit https://www.usgs.gov or call 1–888–ASK–USGS. For an overview of USGS information products, including maps, imagery, and publications, visit https://store.usgs.gov. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials JACIE as noted in the text. -
Developments in Landsat Land Cover Classification Methods: a Review
remote sensing Review Developments in Landsat Land Cover Classification Methods: A Review Darius Phiri * and Justin Morgenroth ID New Zealand School of Forestry, University of Canterbury, Christchurch 8140, New Zealand; [email protected] * Correspondence: [email protected]; Tel.: +64-22-621-4280 Received: 1 August 2017; Accepted: 13 September 2017; Published: 19 September 2017 Abstract: Land cover classification of Landsat images is one of the most important applications developed from Earth observation satellites. The last four decades were marked by different developments in land cover classification methods of Landsat images. This paper reviews the developments in land cover classification methods for Landsat images from the 1970s to date and highlights key ways to optimize analysis of Landsat images in order to attain the desired results. This review suggests that the development of land cover classification methods grew alongside the launches of a new series of Landsat sensors and advancements in computer science. Most classification methods were initially developed in the 1970s and 1980s; however, many advancements in specific classifiers and algorithms have occurred in the last decade. The first methods of land cover classification to be applied to Landsat images were visual analyses in the early 1970s, followed by unsupervised and supervised pixel-based classification methods using maximum likelihood, K-means and Iterative Self-Organizing Data Analysis Technique (ISODAT) classifiers. After 1980, other methods such as sub-pixel, knowledge-based, contextual-based, object-based image analysis (OBIA) and hybrid approaches became common in land cover classification. Attaining the best classification results with Landsat images demands particular attention to the specifications of each classification method such as selecting the right training samples, choosing the appropriate segmentation scale for OBIA, pre-processing calibration, choosing the right classifier and using suitable Landsat images. -
A Conversation with Jack Hild, VP, Digitalglobe
Worldwide Satellite Magazine July/August 2011 SatMagazine Imagery + Earth Observation DigitalGlobe ImageSat NASA SSTL Plus HPA Roundtable Chris Forrester Jos Heyman Advantech Comtech AeroAstro iDirect Spacecom Space Foundation SSC Prisma sIRG/GVF and more... SatMagazine Vol. 4, No. 5 — July/August 2011 Silvano Payne, Publisher + Author Hartley G. Lesser, Editorial Director Pattie Waldt, Editor Jill Durfee, Sales Director, Editorial Assistant Donald McGee, Production Manager Simon Payne, Development Manager Chris Forrester, Associate Editor Richard Dutchik, Contributing Editor Alan Gottlieb, Contributing Editor Dan Makinster, Technical Advisor Authors Michael Carlowicz Chris Forrester Hadass Geyfman Rani Hellerman Jos Heyman David Hodgson Eugene Keane Mark Lambert Hartley Lesser Pattie Waldt Published monthly by Satnews Publishers 800 Siesta Way Sonoma, CA 95476 USA Phone: (707) 939-9306 Fax: (707) 838-9235 © 2011 Satnews Publishers We reserve the right to edit all submitted materials to meet our content guidelines, as well as for grammar and spelling consistency. Articles may be moved to an alternative issue to accommodate publication space requirements or removed due to space restrictions. Submission of content does not constitute acceptance of said material by SatNews Publishers. Edited materials may, or may not, be returned to author and/or company for review prior to publication. The views expressed in our various publications do not necessarily reflect the views or opinions of SatNews Publishers. All included imagery is courtesy of, and copyright to, the respective companies. SatMagazine — July/August 2011 — Payload Cover photo: Qatar, Dohar, “The Pearl” — courtesy of DigitalGlobe A Case In Point Forrester’s Focus 48 Developing Satellite Formation Flying Software 86 by Chris Forrester by SSC + Mathworks’ Engineering Team Focus On The Hosted Payload Alliance 54 Executive Spotlight With Jim Mitchell, Boeing / Don Thomas, Iridium, Stanley O. -
Landsat and the Data Continuity Mission
Landsat and the Data Continuity Mission Carl E. Behrens Specialist in Energy Policy June 7, 2010 Congressional Research Service 7-5700 www.crs.gov R40594 CRS Report for Congress Prepared for Members and Committees of Congress Landsat and the Data Continuity Mission Summary The U.S. Landsat Mission has collected remotely sensed imagery of the Earth’s surface for more than 35 years. At present two satellites—Landsat-5, launched in 1984, and Landsat-7, launched in 1999—are in orbit and continuing to supply images and data for the many users of the information, but they are operating beyond their designed life and may fail at any time. The National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) jointly operate Landsat. The two agencies are developing a follow-on initiative known as the Landsat Data Continuity Mission (LDCM). The LDCM spacecraft (LDCM-1), with its instrument payload, is currently planned for launch in December 2012. NASA completed the Critical Design Review of the LDCM on June 1, 2010, allowing the project to proceed with full- scale fabrication, assembly, integration, and test of the mission elements. Landsat has been used in a wide variety of applications, including climate research, natural resources management, commercial and municipal land development, public safety, homeland security and natural disaster management. Despite its wide use, efforts in the past to commercialize Landsat operations have not been successful. Most of the users of the data are other government agencies. For that reason, funding a replacement for the failing Landsat orbiters has been a federal responsibility. -
Meteoroid-Induced Anomalies on Spacecraft
Meteoroid-Induced Anomalies on Spacecraft Bill Cooke Meteoroid Environment Office, NASA Marshall Space Flight Center [email protected] NASA/MEO/B. Cooke Space Anomalies Workshop, 2014 July 24 Overview • Sporadic meteoroid background is directional (not isotropic) and accounts for 90% of the meteoroid risk to a typical spacecraft. • Meteor showers get all the press, but account for only ~10% of spacecraft risk. – Bias towards assigning meteoroid cause to anomalies during meteor showers. • Vast majority of meteoroids come from comets and have a bulk density of ~ 1 g cm-3 (ice). • High speed meteoroids (~50 km s-1) can induce electrical anomalies in spacecraft through discharging of charged surfaces (also EMP?). NASA/MEO/B. Cooke Space Anomalies Workshop, 2014 July 24 Sporadic Directionality NASA/MEO/B. Cooke Space Anomalies Workshop, 2014 July 24 Meteor Shower Radiants NASA/MEO/B. Cooke Space Anomalies Workshop, 2014 July 24 Could it be a meteoroid? • Are the anomaly characteristics consistent with a particle impact? – Sudden change in attitude most common. • Was there a meteor outburst or storm at the time of the anomaly? – If yes, was the shower radiant visible from the spacecraft? – If yes, did the affected surface “see” the shower radiant? – If yes, shower impact possible. • Compare meteoroid (sporadic + shower) flux to orbital debris flux at spacecraft location to establish likelihood. – If affected surface is sun-fixed, must use a directional meteoroid model to compute flux. NASA/MEO/B. Cooke Space Anomalies Workshop, 2014 July 24 Mariner IV NASA/MEO/B. Cooke Space Anomalies Workshop, 2014 July 24 • Launched 28 November 1964; flew by Mars on 14-15 July 1965. -
TBE Technicalreport CS91-TR-JSC-017 U
Hem |4 W TBE TechnicalReport CS91-TR-JSC-017 u w -Z2- THE FRAGMENTATION OF THE NIMBUS 6 ROCKET BODY i w i David J. Nauer SeniorSystems Analyst Nicholas L. Johnson Advisory Scientist November 1991 Prepared for: t_ NASA Lyndon B. Johnson Space Center Houston, Texas 77058 m Contract NAS9-18209 DRD SE-1432T u Prepared by: Teledyne Brown Engineering ColoradoSprings,Colorado 80910 m I i l Id l II a_wm n IE m m I NI g_ M [] l m IB g II M il m Im mR z M i m The Fragmentation of the Nimbus 6 Rocket Body Abstract: On 1 May 1991 the Nimbus 6 second stage Delta Rocket Body experienced a major breakup at an altitude of approximately 1,100km. There were numerous piecesleftin long- livedorbits,adding to the long-termhazard in this orbitalregime already°presentfrom previousDelta Rocket Body explosions. The assessedcause of the event is an accidentalexplosionof the Delta second stageby documented processesexperiencedby other similar Delta second stages. Background _-£ W Nimbus 6 and the Nimbus 6 Rocket Body (SatelliteNumber 7946, InternationalDesignator i975-052B) were launched from the V_denberg WeStern Test Range on 12 June 1975. The w Delta 2910 launch vehicleloftedthe 830 kg Nimbus 6 Payload into a sun-synchronous,99.6 degree inclination,1,100 km high orbit,leaving one launch fragment and the Delta Second N Stage Rocket Body. This was the 23_ Delta launch of a Second Stage Rocket Body in the Delta 100 or laterseriesofboostersand the 111_ Delta launch overall. k@ On 1 May 1991 the Nimbus 6 Delta second stage broke up into a large,high altitudedebris cloud as reportedby a NAVSPASUR data analysismessage (Appendix 1). -
SP-1322/2 Sentinel-2
→ Sentinel-2 ESA’s Optical High-Resolution Mission for GMeS Operational Services SP-1322/1 SP-1322/2 March 2012 → Sentinel-2 ESA’s Optical High-Resolution Mission for GMeS Operational Services Acknowledgements In the preparation of this publication, ESA acknowledges the contributions of the following organisations and individuals: GMES programme, ESA Sentinel-2 Project and Science Division Teams at ESTEC, Noordwijk, the Netherlands: F. Bertini, O. Brand, S. Carlier, U. Del Bello, M. Drusch, R. Duca, V. Fernandez, C. Ferrario, M.H. Ferreira, C. Isola, V. Kirschner, P. Laberinti, M. Lambert, G. Mandorlo, P. Marcos, P. Martimort, S. Moon, P. Oldeman, M. Palomba, J. Patterson, M. Prochazka, M.H. Schricke- Didot, C. Schwieso, J. Skoog, F. Spoto, J. Stjernevi, O. Sy, B. Teianu and C. Wildner ESA Sentinel-2 Payload Data Ground Segment and Mission Management Team at ESRIN, Frascati, Italy: O. Arino, P. Bargellini, M. Berger, E. Cadau, O. Colin, F. Gascon, B. Hoersch, H. Laur, B. Lopez Fernandez and E. Monjoux ESA Sentinel-2 Flight Operations Segment Team at ESOC, Darmstadt, Germany: M. Collins, F. Marchese and J. Piñeiro National space agencies working in partnership with ESA: — CNES, Toulouse, France: S. Ballarin, C. Dechoz, P. Henry, S. Lachérade, A. Meygret, B. Petrucci, S. Sylvander and T. Trémas. CNES is in charge of Sentinel-2 image quality activities, including monitoring mission performance and assisting ESA with the prototyping, development and verification of payload data processing and product quality monitoring. — DLR, Bonn, Germany: H. Hauschildt, R. Meyer and S. Phillip-May. DLR is responsible for providing the Optical Communication Payload (OCP), developed by Tesat (Germany), which is expected to enhance the distribution of mission data to receiving and processing stations in real time through Alphasat and later on EDRS. -
Landsat's Role in Ecological Applications of Remote Sensing
Articles Landsat’s Role in Ecological Applications of Remote Sensing WARREN B. COHEN AND SAMUEL N. GOWARD Remote sensing, geographic information systems, and modeling have combined to produce a virtual explosion of growth in ecological investigations and applications that are explicitly spatial and temporal. Of all remotely sensed data, those acquired by Landsat sensors have played the most piv- otal role in spatial and temporal scaling. Modern terrestrial ecology relies on remote sensing for modeling biogeochemical cycles and for characteriz- ing land cover, vegetation biophysical attributes, forest structure, and fragmentation in relation to biodiversity. Given the more than 30-year record of Landsat data, mapping land and vegetation cover change and using the derived surfaces in ecological models is becoming commonplace. In this article, we summarize this large body of work, highlighting the unique role of Landsat. Keywords: remote sensing, Landsat, spectral vegetation indices, vegetation mapping, change detection he discipline of ecology has undergone tremendous of Earth from space, and a discipline known as remote sens- Tgrowth and diversification over the past century. These ing was born. With the launch of the first Landsat satellite in advances were driven by a variety of sociological, political, 1972, scientists could suddenly view tangible human im- environmental, and technological developments that fos- pacts on the whole Earth system on a regular basis. By ne- tered new theory as well as new applications. Public concern cessity, field measurements and experiments focused (and have over the state of the environment, which had been increas- continued to focus) mainly on plots with sizes up to several ing over the decades leading up to the 1960s, led to landmark square meters (m2).