ANALYSIS OF ASAR POLARISATION SIGNATURES FROM URBAN AREAS (AO-434)
|
|
- Myles Richardson
- 6 years ago
- Views:
Transcription
1 ANALYSIS OF ASAR POLARISATION SIGNATURES FROM URBAN AREAS (AO-434) Dan Johan Weydahl and Richard Olsen Norwegian Defence Research Establishment (FFI), P.O. Box 25, NO-2027 Kjeller, NORWAY, ABSTRACT This project focuses on ASAR backscatter change from urban categories as a function of polarisation and incidence angle. Results show more bright scattering points from manmade objects in like-pol than in cross-pol. ASAR AP data acquired with several incidence angles may be used with success to obtain more knowledge about structural properties of certain man-made objects. 1. INTRODUCTION Satellite synthetic aperture radar (SAR) is an interesting sensor for mapping urban areas and manmade objects. Now, SAR backscatter from urban type objects may change significantly as a function of the radar viewing geometry (e.g. aspect angle and incidence angle). For satellite SAR, ascending/descending satellite pass directions mainly govern aspect angle differences, while incidence angle differences can be achieved using a SAR system with a steerable antenna. RADARSAT-1 gives the opportunity to acquire SAR data using a wide range of incidence angles (20-59 ). Results from an urban area shows that RADARSAT-1 images acquired with different incidence angles can give complimentary information about man-made objects [1]. The objective of ESA AO-434 ( Analysis of ASAR polarisation signatures from urban areas using multiple incidence angles ) is to extend this research by also taking into account different polarisations. The data source in this respect is ENVISAT ASAR. 2. DATA SET AND METHODOLOGY Many ASAR alternating polarisation (AP) data sets were ordered over the Oslo region in Norway from July 2003 to March 2004 as part of ESA AO-434. The AP data were processed to single-look-complex (APS) at ESA PAF s. The APS data are calibrated in the sense that an absolute calibration factor (K) is Proc. of the 2004 Envisat & ERS Symposium, Salzburg, Austria 6-10 September 2004 (ESA SP-572, April 2005) estimated for every product type. This value is found in the accompanying ASAR image header. However, the APS data are not corrected for range-spreading-loss or elevation-antenna-pattern-gain. On the World-Wide- Web, ESA has published auxiliary data files that can be used to estimate the elevation-antenna-pattern-gain. Together with data found in the ASAR header, both the range and antenna pattern were corrected for at FFI using procedures described in the ESA technical notes [2] and [3]. Sigma-nought backscatter values were then estimated for several land surface cover types using the calibrated APS data. A block averaging was performed on the ASAR APS data for several test areas. An averaging window of 16x48 or 32x96 pixels (in range and azimuth respectively) was used. This leads to a more or less square area (in meters) being investigated. Results are shown in Table 1 and Table 2 in the next section where backscatter response for the various polarisation modes are given as a function of increasing incidence angle. 3. RESULTS 3.1 Industrial Table 1 a) shows the ASAR backscatter estimated from an industrial area where a large chemical plant (Dynea ASA) is located. A lot of pipes and metal tanks are present. The like-pol channels (both HH and VV) are always around 10 db above the cross-pol channel. See also area no.1 in the ASAR image in Fig.1. This result seems to be independent of incidence angle variations, or radar aspect angle. The cardinal direction effect (see [4] and [5]) is therefore not very noticeable for this industrial site. We may therefore deduce that this area mainly are made up of two kind of man-made objects: Objects with a lot of corners or complex structures that very likely will give a strong SAR backscatter regardless of radar viewing directions. Simple spherical objects (also including pipes and tanks) that are more or less omnidirectional in nature.
2 3.2 City centre Lillestrøm city centre consists of concrete office houses, shops, parking areas and residential houses in wood (see area no.2 in Fig.1). Results in Table 1 b) show neither extreme differences between the like- and cross-pol channels, nor stable inter-channel differences as for the chemical plant in Table 1 a). From this, we may deduce that the city area is a mixture of simple objects, complex objects and objects that are influenced by the cardinal direction effect. 3.3 Residential A residential area in Lillestrøm is investigated in particular. The houses are mostly built in wood, and the streets are laid out in a regular pattern. Table 1 c) shows the average backscatter from this area. Ascending mode HH backscatter decreases with increasing incidence angle. At the same time, the crosspol HV is fairly stable around 18.5 db. The AP mode channel difference (last column in table) is between 10.5 and 16.6 db for ascending pass data. This is decreasing to a difference of 6 db for descending pass. This residential area is clearly influenced by the cardinal direction effect (see area no.3 in Fig.1) but not in the extent as some industrial areas holding large warehouses with metal roof or walls (see the evaluation in section 3.4). 3.4 Large buildings Trandum is an Army site with some large rectangular buildings. The ASAR backscatter in Table 1 d) shows a high degree of influence from the cardinal direction effect, but also incidence angle variations. The area is shown in the ASAR image in Fig.2. We notice that an incidence angle change of 6.5 degrees (August IS4 to July IS6) leads to a 9.7 db difference in HH-backscatter. A change in both incidence angle and aspect angle (ascending August IS4 to descending August IS7) is producing a difference of as much as 14.4 db in HH. A remarkable observation in this context is that the cross-pol channels only vary by 5.3 db when evaluating the same three acquisitions (HH: IS4, IS6 and IS7). From Table 1 d) we may also suggest that the presence of the cardinal direction effect will give a large spread of backscatter differences between like-pol and crosspol channels when operating with different radar observation angles. Take IS7 in July and August as an example: the like- cross-pol difference (right most column in table) changed by 9 db (from 17 to 8 db) when changing the observation aspect angle from ascending to descending pass. This is quite contrary to the stable situation noticed for the chemical plant in Table 1 a). 3.5 Coniferous forest A coniferous forest area north of Tien Lake in Fet is evaluated and results given in Table 2 a). Here, the likpol backscatter gives less variation (only 1.5 db) than the cross-pol (6.1 db) for the different radar viewing angles. There are only small differences from HH to VV backscatter. 3.6 Agricultural field Agricultural fields are evaluated in Table 2 b). The ASAR data is given in square no.5 in Fig.1. The HH lik-pol backscatter gives a variation of 2.3 db, while HH cross-pol. gives only 1.8 db variations for the same set of radar acquisition angles. In other words: Fields show larger like-pol variations as a function of incidence angle, than coniferous forest. Fields show smaller cross-pol variations as a function of inc. angle, than coniferous forest. 3.7 Grass land A golf area is having large grass patches. The ASAR data is given in square no.4 in Fig.1. Results are given in Table 2 c) and shows that HH and VV polarisation give very similar backscatter from a grass-covered area. From the present data set, it is not possible to evaluate backscatter changes as a function of incidence angle variations. The cross-pol backscatter is low. 3.8 Asphalt covered ground Results from the asphalt-covered aircraft parking area next to the main terminal building at Gardermoen Airport Oslo, is shown in Table 2 d). As expected, the backscatter is independent of aspect angle differences. We notice that the like-pol backscatter is quite low, but not as low as for the category lake, see Table 2 e). The cross-pol response seems to decrease with larger incidence angle. This needs to be investigated further, especially as the cross-pol backscatter is approaching the system noise level, leading to possible inaccuracies in the ackscatter estimate.
3 there are only small differences between the like-pol and cross-pol channels, but this can change considerable if a strong wind is blowing on the lake. Generally speaking, the backscatter from this lake is very low, almost into the system noise region for both like-pol and cross-pol. Fig. 1. ASAR AP colour composite images (Red=HH, Green=HV, Blue=HH) over Lillestrøm city area. The marked squares show the location of the following test areas: 1=Industry area, 2=City centre, 3=Residential area, 4=Golf area, 5=Agricultural field. 3.9 Lake surface Table 2 e) shows results from ASAR backscatter evaluated over Maridalen lake outside Oslo. In our case, Fig. 2. ASAR AP colour composite images (Red=HH, Green=HV, Blue=HH) over Gardermoen Airport. The marked squares show the location of the Trandum test area holding a large building complex (see section 3.4).
4 Table 1. ENVISAT ASAR AP backscatter values from various land surface covers and object types. Green colour is ascending and yellow is descending satellite pass. a) Industry area with tanks/ pipes (Dynea) b) Lillestrøm city centre c) Residential area d) Large building complex (Trandum) Aug, IS Dec, IS July, IS Aug, IS July, IS Aug, IS Dec, IS July, IS Aug, IS July, IS Angl( deg) Aug, IS Dec, IS July, IS Aug, IS July, IS Dec, IS Aug, IS July, IS Aug, IS Dec, IS July, IS
5 Table 2. ENVISAT ASAR AP backscatter values from various land surface covers and object types. Green colour is ascending and yellow is descending satellite pass. a) Dec, IS Aug, IS July, IS Aug, IS Forest (Garderåsen) July, IS b) Agriculture (Jølsen) Dec, IS Aug, IS July, IS Aug, IS July, IS c) Grass (golf area) Dec, IS Aug, IS July, IS Aug, IS July, IS d) Asphalt Aug, IS covered Dec, IS (aircraft July, IS parking) Aug, IS area July, IS e) Lake (Mari-dalsvatn) Aug, IS Dec, IS July, IS July, IS Aug, IS
6 4. CONCLUSIONS Omni-directional scattering objects show stable backscatter difference properties (around 10 db) between the like-pol and cross-pol ASAR AP mode channels, regardless of radar incidence or aspect angles. Buildings prone to the cardinal effect seem to give large inter-channel backscatter variations when comparing the ASAR AP data sets (HH versus HV). The cardinal effect does not seem to have a noticeable effect on the AP mode cross-pol channel. ASAR like-pol and cross-pol backscatter will vary as a function of radar viewing angle for certain man-made objects. This may be used to set up rules in a classification procedure. 6. REFERENCES 1. Weydahl D. J., Backscatter changes of urban features using multiple incidence angle RADARSAT images, Can. J. Remote Sensing, Vol. 28, , Absolute Calibration of ASAR Level 1 Products Generated with PF-ASAR, ESA Technical Note, revision 4, January ASAR Product Handbook, ESA, revision 20 August Levine, D., Radargrammetry. New York: McGraw-Hill Book Co, Hardaway G. and Gustafson G. C., Cardinal effect on SEASAT images of urban areas. Photogrammetric Engineering and Remote Sensing, Vol. 48, , Fields show larger like-pol variation as a function of incidence angle, than coniferous forest. Fields show smaller cross-pol variations as a function of incidence angle, than coniferous forest. It seems to be a trend that shorter vegetation will give lower cross-pol signatures: forest > fields > grass The AP inter-channel difference between copol and cross-pol is more stable for forest areas than for agriculture when evaluating ASAR images acquired in different swaths throughout the growing/harvest season. 5. AKNOWLEDGEMENT The ENVISAT ASAR data were ordered as part of ESA AO-434.
MULTI-POLARISATION MEASUREMENTS OF SNOW SIGNATURES WITH AIR- AND SATELLITEBORNE SAR
EARSeL eproceedings 5, 1/2006 111 MULTI-POLARISATION MEASUREMENTS OF SNOW SIGNATURES WITH AIR- AND SATELLITEBORNE SAR Eirik Malnes 1, Rune Storvold 1, Inge Lauknes 1 and Simone Pettinato 2 1. Norut IT,
More informationEXTRACTION OF FLOODED AREAS DUE THE 2015 KANTO-TOHOKU HEAVY RAINFALL IN JAPAN USING PALSAR-2 IMAGES
EXTRACTION OF FLOODED AREAS DUE THE 2015 KANTO-TOHOKU HEAVY RAINFALL IN JAPAN USING PALSAR-2 IMAGES F. Yamazaki a, *, W. Liu a a Chiba University, Graduate School of Engineering, Chiba 263-8522, Japan
More informationERS-ENVISAT CROSS-INTERFEROMETRY SIGNATURES OVER DESERTS. Urs Wegmüller, Maurizio Santoro and Christian Mätzler
ERS-ENVISAT CROSS-INTERFEROMETRY SIGNATURES OVER DESERTS Urs Wegmüller, Maurizio Santoro and Christian Mätzler Gamma Remote Sensing AG, Worbstrasse 225, CH-3073 Gümligen, Switzerland, http://www.gamma-rs.ch,
More informationASAR LEVEL 0 PRODUCT ANALYSIS FOR ALTERNATING POLARISATION AND GLOBAL MONITORING MODE
ASAR LEVEL 0 PRODUCT ANALYSIS FOR ALTERNATING POLARISATION AND GLOBAL MONITORING MODE Birgit Schättler Remote Sensing Technology Institute German Aerospace Center (DLR) Münchner Str. 20, 82234 Weßling,
More informationLAND COVER CLASSIFICATION BASED ON SAR DATA IN SOUTHEAST CHINA
LAND COVER CLASSIFICATION BASED ON SAR DATA IN SOUTHEAST CHINA Mr. Feilong Ling, Dr. Xiaoqin Wang, Mr.Xiaoming Shi Fuzhou University, Level 13, Science Building,No.53 Gongye Rd., 35, Fuzhou, China Email:
More informationAnalysis of ERS Tandem SAR Coherence From Glaciers, Valleys, and Fjord Ice on Svalbard
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 39, NO. 9, SEPTEMBER 2001 2029 Analysis of ERS Tandem SAR Coherence From Glaciers, Valleys, and Fjord Ice on Svalbard Dan Johan Weydahl Abstract
More informationMAPPING OF LAKE ICE IN NORTHERN EUROPE USING DUAL-POLARIZATION RADARSAT-2 DATA
MAPPING OF LAKE ICE IN NORTHERN EUROPE USING DUAL-POLARIZATION RADARSAT-2 DATA Hindberg, Heidi and Malnes, Eirik Northern Research Institute (Norut), PO Box 6434 Tromsø Science Park, N9291 Tromsø, Email:
More informationCHAPTER-7 INTERFEROMETRIC ANALYSIS OF SPACEBORNE ENVISAT-ASAR DATA FOR VEGETATION CLASSIFICATION
147 CHAPTER-7 INTERFEROMETRIC ANALYSIS OF SPACEBORNE ENVISAT-ASAR DATA FOR VEGETATION CLASSIFICATION 7.1 INTRODUCTION: Interferometric synthetic aperture radar (InSAR) is a rapidly evolving SAR remote
More informationUSE OF INTERFEROMETRIC SATELLITE SAR FOR EARTHQUAKE DAMAGE DETECTION ABSTRACT
USE OF INTERFEROMETRIC SATELLITE SAR FOR EARTHQUAKE DAMAGE DETECTION Masashi Matsuoka 1 and Fumio Yamazaki 2 ABSTRACT Synthetic Aperture Radar (SAR) is one of the most promising remote sensing technologies
More informationTowards the use of SAR observations from Sentinel-1 to study snowpack properties in Alpine regions
Towards the use of SAR observations from Sentinel-1 to study snowpack properties in Alpine regions Gaëlle Veyssière, Fatima Karbou, Samuel Morin et Vincent Vionnet CNRM-GAME /Centre d Etude de la Neige
More informationShashi Kumar. Indian Institute of Remote Sensing. (Indian Space Research Organisation)
Practical-1 SAR Image Interpretation Shashi Kumar Indian Institute of Remote Sensing (Indian Space Research Organisation) Department of Space, Government of India 04 Kalidas Road, Dehradun - 248 001, U.K.
More informationPOLARIMETRY-BASED LAND COVER CLASSIFICATION WITH SENTINEL-1 DATA
POLARIMETRY-BASED LAND COVER CLASSIFICATION WITH SENTINEL-1 DATA Xavier Banqué (1), Juan M Lopez-Sanchez (2), Daniel Monells (1), David Ballester (2), Javier Duro (1), Fifame Koudogbo (1) (1) Altamira
More informationC-BAND MULTIPLE POLARIZATION SAR FOR ICE MONITORING WHAT CAN IT DO FOR THE CANADIAN ICE SERVICE
C-BAND MULTIPLE POLARIZATION SAR FOR ICE MONITORING WHAT CAN IT DO FOR THE CANADIAN ICE SERVICE Matt Arkett, Dean Flett, and Roger De Abreu Canadian Ice Service, Meteorological Service of Canada, Environment
More informationUsing MERIS and MODIS for Land Cover Mapping in the Netherlands
Using MERIS and for Land Cover Mapping in the Netherlands Raul Zurita Milla, Michael Schaepman and Jan Clevers Wageningen University, Centre for Geo-Information, NL Introduction Actual and reliable information
More informationIII. Publication III. c 2004 Authors
III Publication III J-P. Kärnä, J. Pulliainen, K. Luojus, N. Patrikainen, M. Hallikainen, S. Metsämäki, and M. Huttunen. 2004. Mapping of snow covered area using combined SAR and optical data. In: Proceedings
More informationSNOW COVER MONITORING IN ALPINE REGIONS WITH COSMO-SKYMED IMAGES BY USING A MULTITEMPORAL APPROACH AND DEPOLARIZATION RATIO
SNOW COVER MONITORING IN ALPINE REGIONS WITH COSMO-SKYMED IMAGES BY USING A MULTITEMPORAL APPROACH AND DEPOLARIZATION RATIO B. Ventura 1, T. Schellenberger 1, C. Notarnicola 1, M. Zebisch 1, T. Nagler
More informationDetecting an area affected by forest fires using ALOS PALSAR
Detecting an area affected by forest fires using ALOS PALSAR Keiko Ishii (1), Masanobu Shimada (2), Osamu Isoguchi (2), Kazuo Isono (1) (1)Remote Sensing Technology Center of Japan (2)Japan Aerospace Exploration
More informationSAR Coordination for Snow Products
Polar SAR Coordination Working Meeting 5 SAR Coordination for Snow Products David Small 1, Thomas Nagler 2, David Jäger 1, Christoph Rohner 1, Adrian Schubert 1 1: University of Zurich, Switzerland 2:
More informationSAR Data Analysis: An Useful Tool for Urban Areas Applications
SAR Data Analysis: An Useful Tool for Urban Areas Applications M. Ferri, A. Fanelli, A. Siciliano, A. Vitale Dipartimento di Scienza e Ingegneria dello Spazio Luigi G. Napolitano Università degli Studi
More informationGeneral Four-Component Scattering Power Decomposition with Unitary Transformation of Coherency Matrix
1 General Four-Component Scattering Power Decomposition with Unitary Transformation of Coherency Matrix Gulab Singh, Member, IEEE, Yoshio Yamaguchi, Fellow, IEEE and Sang-Eun Park, Member, IEEE Abstract
More informationAPPEARANCE OF PERSISTENT SCATTERERS FOR DIFFERENT TERRASAR-X ACQUISITION MODES
APPEARANCE OF PERSISTENT SCATTERERS FOR DIFFERENT TERRASAR-X ACQUISITION MODES Stefan Gernhardt a, Nico Adam b, Stefan Hinz c, Richard Bamler a,b a Remote Sensing Technology, TU München, Germany b Remote
More informationDr. Simon Plank. German Remote Sensing Data Center (DFD), German Aerospace Center (DLR)
Pre-survey suitability analysis of the differential and persistent scatterer synthetic ti aperture radar interferometry t method for deformation monitoring of landslides Dr. Simon Plank German Remote Sensing
More informationEVALUATION OF CLASSIFICATION METHODS WITH POLARIMETRIC ALOS/PALSAR DATA
EVALUATION OF CLASSIFICATION METHODS WITH POLARIMETRIC ALOS/PALSAR DATA Anne LÖNNQVIST a, Yrjö RAUSTE a, Heikki AHOLA a, Matthieu MOLINIER a, and Tuomas HÄME a a VTT Technical Research Centre of Finland,
More informationIce Observations on the Churchill River using Satellite Imagery
CGU HS Committee on River Ice Processes and the Environment 15 th Workshop on River Ice St. John s, Newfoundland and Labrador, June 15-17, 2009 Ice Observations on the Churchill River using Satellite Imagery
More informationDIFFERENTIAL INSAR STUDIES IN THE BOREAL FOREST ZONE IN FINLAND
DIFFERENTIAL INSAR STUDIES IN THE BOREAL FOREST ZONE IN FINLAND Kirsi Karila (1,2), Mika Karjalainen (1), Juha Hyyppä (1) (1) Finnish Geodetic Institute, P.O. Box 15, FIN-02431 Masala, Finland, Email:
More informationEE/Ge 157 b. Week 2. Polarimetric Synthetic Aperture Radar (2)
EE/Ge 157 b Week 2 Polarimetric Synthetic Aperture Radar (2) COORDINATE SYSTEMS All matrices and vectors shown in this package are measured using the backscatter alignment coordinate system. This system
More informationINDIVIDUAL WAVE HEIGHT FROM SAR
INDIVIDUAL WAVE HEIGHT FROM SAR W. Rosenthal (1), S.Lehner (2) (1), GKSS, D 2102 Geesthacht, Email:Wolfgang.Rosenthal@gkss.de (2), DLR, D82234 Wessling,, Email:Susanne.Lehner@dlr.de ABSTRACT Safety of
More informationTHE PYLA 2001 EXPERIMENT : EVALUATION OF POLARIMETRIC RADAR CAPABILITIES OVER A FORESTED AREA
THE PYLA 2001 EXPERIMENT : EVALUATION OF POLARIMETRIC RADAR CAPABILITIES OVER A FORESTED AREA M. Dechambre 1, S. Le Hégarat 1, S. Cavelier 1, P. Dreuillet 2, I. Champion 3 1 CETP IPSL (CNRS / Université
More informationImpact of the Envisat Mission Extension on SAR data
Impact of the Envisat Mission Extension on SAR data Impact of Envisat extension on SAR data Prepared by nuno miranda Reference Issue 0.9 Revision Date of Issue 23 August 2010 Status Preliminary version
More informationLinking Different Spatial Scales For Retrieval Of Sea Ice Conditions From SAR Images
Linking Different Spatial Scales For Retrieval Of Sea Ice Conditions From SAR Images Matt Arkett 2, Wolfgang Dierking 1, Jakob Griebel 1, Thomas Hollands 1, Stefanie Linow 1, Eero Rinne 3, Markku Similä
More informationMaking a case for full-polarimetric radar remote sensing
Making a case for full-polarimetric radar remote sensing Jeremy Nicoll Alaska Satellite Facility, University of Alaska Fairbanks 1 Polarization States of a Coherent Plane Wave electric field vector vertically
More informationThe Importance of Microwave Remote Sensing for Operational Sea Ice Services And Challenges
The Importance of Microwave Remote Sensing for Operational Sea Ice Services And Challenges Wolfgang Dierking January 2015 (1) Why is microwave remote sensing important (=useful) for sea ice mapping? Problems
More informationRemote sensing of sea ice
Remote sensing of sea ice Ice concentration/extent Age/type Drift Melting Thickness Christian Haas Remote Sensing Methods Passive: senses shortwave (visible), thermal (infrared) or microwave radiation
More informationRice Monitoring using Simulated Compact SAR. Kun Li, Yun Shao Institute of Remote Sensing and Digital Earth
Rice Monitoring using Simulated Compact SAR Kun Li, Yun Shao Institute of Remote Sensing and Digital Earth Outlines Introduction Test site and data Results Rice type discrimination Rice phenology retrieval
More informationRADAR BACKSCATTER AND COHERENCE INFORMATION SUPPORTING HIGH QUALITY URBAN MAPPING
RADAR BACKSCATTER AND COHERENCE INFORMATION SUPPORTING HIGH QUALITY URBAN MAPPING Peter Fischer (1), Zbigniew Perski ( 2), Stefan Wannemacher (1) (1)University of Applied Sciences Trier, Informatics Department,
More informationOpportunities for advanced Remote Sensing; an outsider s perspective
Opportunities for advanced Remote Sensing; an outsider s perspective Ramon Hanssen Delft University of Technology 1 Starting questions Can we do more with the data we are already acquire? What s in stock
More informationEvaluation of sub-kilometric numerical simulations of C-band radar backscatter over the french Alps against Sentinel-1 observations
Evaluation of sub-kilometric numerical simulations of C-band radar backscatter over the french Alps against Sentinel-1 observations Gaëlle Veyssière, Fatima Karbou, Samuel Morin, Matthieu Lafaysse Monterey,
More informationRADAR Remote Sensing Application Examples
RADAR Remote Sensing Application Examples! All-weather capability: Microwave penetrates clouds! Construction of short-interval time series through cloud cover - crop-growth cycle! Roughness - Land cover,
More informationMicrowave Remote Sensing of Soil Moisture. Y.S. Rao CSRE, IIT, Bombay
Microwave Remote Sensing of Soil Moisture Y.S. Rao CSRE, IIT, Bombay Soil Moisture (SM) Agriculture Hydrology Meteorology Measurement Techniques Survey of methods for soil moisture determination, Water
More informationIndonesian seas Numerical Assessment of the Coastal Environment (IndoNACE) Executive Summary
Indonesian seas Numerical Assessment of the Coastal Environment (IndoNACE) Executive Summary Study team members: Dr. Martin Gade, PD Dr. Thomas Pohlmann, Dr. Mutiara Putri Research Centres: Universität
More informationImpact of the Envisat Mission Extension on SAR data
Impact of the Envisat Mission Extension on SAR data Impact of Envisat Mission Extension on SAR data - 1.0 Prepared by Nuno Miranda, Berthyl Duesmann, Monserrat Pinol, Davide Giudici, Davide D Aria Reference
More informationRetrieving 3D deformation pattern of a landslide with hiresolution InSAR and in-situ measurements: Just landslide case-study
Retrieving 3D deformation pattern of a landslide with hiresolution InSAR and in-situ measurements: Just landslide case-study Zbigniew Perski (1), Petar Marinković (2), Yngvar Larsen (3), Tomasz Wojciechowski
More informationCurrent Status of the ALOS-2 Operation and PALSAR-2 Calibration Activities
Current Status of the ALOS-2 Operation and PALSAR-2 Calibration Activities Takeshi Motohka, Ryo Natsuaki, Yukihiro Kankaku, Shinichi Suzuki, Masanobu Shimada (JAXA) Osamu Isoguchi (RESTEC) CEOS SAR CALVAL
More informationSAR data Sensords and examples
SAR data Sensords and examples Sar Technical Training for Forest Mapping 2014/2015 Cédric Lardeux Jean-Paul Rudant Pierre-Louis Frison cedric.lardeux@onfinternational.com rudant@univ-mlv.fr frison@univ-mlv.fr
More informationPREDICTION AND MONITORING OF OCEANIC DISASTERS USING MICROWAVE REMOTE SENSING TECHNIQUES
PREDICTION AND MONITORING OF OCEANIC DISASTERS USING MICROWAVE REMOTE SENSING TECHNIQUES O P N Calla International Centre for Radio Science, OM NIWAS A-23, Shastri Nagar, Jodhpur-342 003 Abstract The disasters
More informationLong term performance monitoring of ASCAT-A
Long term performance monitoring of ASCAT-A Craig Anderson and Julia Figa-Saldaña EUMETSAT, Eumetsat Allee 1, 64295 Darmstadt, Germany. Abstract The Advanced Scatterometer (ASCAT) on the METOP series of
More informationSTUDIES OF OCEAN S SCATTERING PROPERTIES BASED ON AIRSAR DATA
STUDIES OF OCEAN S SCATTERING PROPERTIES BASED ON AIRSAR DATA Wang Wenguang *, Sun Jinping, Wang Jun, Hu Rui School of EIE, Beihang University, Beijing 00083, China- wwenguang@ee.buaa.edu.cn KEY WORDS:
More informationDEMOSS. Title: Development of Marine Oil Spills/slicks Satellite monitoring System elements for the Black Sea, Caspian Sea and /Kara/Barents Seas
DEMOSS Title: Development of Marine Oil Spills/slicks Satellite monitoring System elements for the Black Sea, Caspian Sea and /Kara/Barents Seas INTAS Thematic Call on Earth Sciences and Environment in
More informationDLR s TerraSAR-X contributes to international fleet of radar satellites to map the Arctic and Antarctica
DLR s TerraSAR-X contributes to international fleet of radar satellites to map the Arctic and Antarctica The polar regions play an important role in the Earth system. The snow and ice covered ocean and
More informationMonitoring the ice cover evolution of a medium size river from RADARSAT-1 : preliminary results
Monitoring the ice cover evolution of a medium size river from RADARSAT-1 : preliminary results Y. Gauthier, T. B.M.J. Ouarda, M. Bernier and A. El Battay INRS-Eau, 2800 Einstein, C.P. 7500, Ste-Foy (Qc)
More informationRADAR TARGETS IN THE CONTEXT OF EARTH OBSERVATION. Dr. A. Bhattacharya
RADAR TARGETS IN THE CONTEXT OF EARTH OBSERVATION Dr. A. Bhattacharya 1 THE RADAR EQUATION The interaction of the incident radiation with the Earth s surface determines the variations in brightness in
More informationCalibrating SeaWinds and QuikSCAT scatterometers using natural land targets
Brigham Young University BYU ScholarsArchive All Faculty Publications 2005-04-01 Calibrating SeaWinds and QuikSCAT scatterometers using natural land targets David G. Long david_long@byu.edu Lucas B. Kunz
More informationApplication of Wavelet Spectrum Analysis to Oil Spill Detection by Using Satellite Observation Data
PAJ Oil Spill Symposium 2008 Application of Wavelet Spectrum Analysis to Oil Spill Detection by Using Satellite Observation Data February 21, 2008 Tokyo, Japan Masanao Hara Dr., VisionTech Inc. 1. Background
More informationAN OBJECT-BASED CLASSIFICATION PROCEDURE FOR THE DERIVATION OF BROAD LAND COVER CLASSES USING OPTICAL AND SAR DATA
AN OBJECT-BASED CLASSIFICATION PROCEDURE FOR THE DERIVATION OF BROAD LAND COVER CLASSES USING OPTICAL AND SAR DATA T. RIEDEL, C. THIEL, C. SCHMULLIUS Friedrich-Schiller-University Jena, Earth Observation,
More informationAnalysis of the Temporal Behavior of Coherent Scatterers (CSs) in ALOS PalSAR Data
Analysis of the Temporal Behavior of Coherent Scatterers (CSs) in ALOS PalSAR Data L. Marotti, R. Zandona-Schneider & K.P. Papathanassiou German Aerospace Center (DLR) Microwaves and Radar Institute0 PO.BOX
More informationGEOGG141 Principles & Practice of Remote Sensing (PPRS) RADAR III: Applications Revision
UCL DEPARTMENT OF GEOGRAPHY GEOGG141 Principles & Practice of Remote Sensing (PPRS) RADAR III: Applications Revision Dr. Mathias (Mat) Disney UCL Geography Office: 113, Pearson Building Tel: 7670 0592
More informationSentinel-1 Long Duration Mutual Interference
MPC-S1 Sentinel-1 Long Duration Mutual Interference Reference: Nomenclature: MPC-0432 DI-MPC-ARC Issue: 1. 0 Date: 2018,Dec.04 MPC-0432 DI-MPC-ARC V1.0 2018,Dec.04 i.1 Chronology Issues: Issue: Date: Reason
More informationMultitemporal RADARSAT 2 Fine Beam Polarimetric SAR for Urban Land Cover Mapping
Multitemporal RADARSAT 2 Fine Beam Polarimetric SAR for Urban Land Cover Mapping Yifang Ban & Xin Niu KTH Royal Institute of Technology Stockholm, Sweden Introduction Urban represents one of the most dynamic
More informationFloating Ice: Progress in Addressing Science Goals
Polar Floating Ice: Progress in Addressing Science Goals Stephen Howell 1, Leif Toudal Pedersen 2 and Roberto Saldo 3 1 Environment Canada, Climate Research Division, Toronto, Canada 2 Danish Meteorological
More informationACHIEVING THE ERS-2 ENVISAT INTER-SATELLITE INTERFEROMETRY TANDEM CONSTELLATION.
ACHIEVING THE ERS-2 ENVISAT INTER-SATELLITE INTERFEROMETRY TANDEM CONSTELLATION M. A. Martín Serrano (1), M. A. García Matatoros (2), M. E. Engdahl (3) (1) VCS-SciSys at ESA/ESOC, Robert-Bosch-Strasse
More informationIce surveys, meteorological and oceanographic data What is available and up-to-date?
Ice surveys, meteorological and oceanographic data What is available and up-to-date? Leader of the Norwegian Ice Service +47 77 62 13 15 - nick.hughes@met.no Norwegian Meteorological Institute met.no 1
More informationSnow Water Equivalent (SWE) of dry snow derived from InSAR -theory and results from ERS Tandem SAR data
Snow Water Equivalent (SWE) of dry snow derived from InSAR -theory and results from ERS Tandem SAR data Tore Guneriussen, Kjell Arild Høgda, Harald Johnsen and Inge Lauknes NORUT IT Ltd., Tromsø Science
More informationDevelopment of wind rose diagrams for Kadapa region of Rayalaseema
International Journal of ChemTech Research CODEN (USA): IJCRGG ISSN: 0974-4290 Vol.9, No.02 pp 60-64, 2016 Development of wind rose diagrams for Kadapa region of Rayalaseema Anil Kumar Reddy ChammiReddy
More informationImproved sea-ice monitoring for the Baltic Sea Project summary
Improved sea-ice monitoring for the Baltic Sea Project summary Leif E.B. Eriksson (1), Karin Borenäs (2), Wolfgang Dierking (3), Anders Berg (1) and Per Pemberton (2) (1) Chalmers University of Technology,
More informationKnowledge-based sea ice classification by polarimetric SAR
Downloaded from orbit.dtu.dk on: Dec 17, 217 Knowledge-based sea ice classification by polarimetric SAR Skriver, Henning; Dierking, Wolfgang Published in: IEEE International Geoscience Remote Sensing Symposium,
More informationDEPENDENCE OF URBAN TEMPERATURE ELEVATION ON LAND COVER TYPES. Ping CHEN, Soo Chin LIEW and Leong Keong KWOH
DEPENDENCE OF URBAN TEMPERATURE ELEVATION ON LAND COVER TYPES Ping CHEN, Soo Chin LIEW and Leong Keong KWOH Centre for Remote Imaging, Sensing and Processing, National University of Singapore, Lower Kent
More informationGEOSC/METEO 597K Kevin Bowley Kaitlin Walsh
GEOSC/METEO 597K Kevin Bowley Kaitlin Walsh Timeline of Satellites ERS-1 (1991-2000) NSCAT (1996) Envisat (2002) RADARSAT (2007) Seasat (1978) TOPEX/Poseidon (1992-2005) QuikSCAT (1999) Jason-2 (2008)
More informationSAR Data Help Improving the Monitoring of Intertidal Flats on the German North Sea Coast
SAR Data Help Improving the Monitoring of Intertidal Flats on the German North Sea Coast Martin Gade (1), Kerstin Stelzer (2), and Jörn Kohlus (3) (1) Institut für Meereskunde, Universität Hamburg, Hamburg,
More informationDUAL-POLARIZED COSMO SKYMED SAR DATA TO OBSERVE METALLIC TARGETS AT SEA
DUAL-POLARIZED COSMO SKYMED SAR DATA TO OBSERVE METALLIC TARGETS AT SEA F. Nunziata, M. Montuori and M. Migliaccio Università degli Studi di Napoli Parthenope Dipartimento per le Tecnologie Centro Direzionale,
More informationPolarimetry-based land cover classification with Sentinel-1 data
Polarimetry-based land cover classification with Sentinel-1 data Banqué, Xavier (1); Lopez-Sanchez, Juan M (2); Monells, Daniel (1); Ballester, David (2); Duro, Javier (1); Koudogbo, Fifame (1) 1. Altamira-Information
More informationSentinel and ESA Third-Party Mission data access and processing tools
Sentinel and ESA Third-Party Mission data access and processing tools Magdalena Fitrzyk RSAC c/o ESA ESRIN 11/09/2018 Content Copernicus Sentinel missions Copernicus Open Access Hub: Sentinels Data Access
More informationEvaporation Duct Height Climatology for Norwegian Waters Using Hindcast Data
Evaporation Duct Height Climatology for Norwegian Waters Using Hindcast Data Petter Østenstad Norwegian Defence Research Establishment (FFI) Horten NORWAY Petter.Ostenstad@ffi.no Marthe Marie Meltzer Norwegian
More informationInternational Journal of Intellectual Advancements and Research in Engineering Computations
ISSN:2348-2079 Volume-5 Issue-2 International Journal of Intellectual Advancements and Research in Engineering Computations Agricultural land investigation and change detection in Coimbatore district by
More informationJulia Figa-Saldaña & Klaus Scipal
Julia Figa-Saldaña & Klaus Scipal julia.figa@eumetsat.int klaus.scipal@esa.int Meeting, Outline MetOp/EPS status MetOp/EPS Second Generation status 2016 scatterometer conference Other European ocean programme
More informationPolarimetric Calibration of the Ingara Bistatic SAR
Polarimetric Calibration of the Ingara Bistatic SAR Alvin Goh, 1,2 Mark Preiss, 1 Nick Stacy, 1 Doug Gray 2 1. Imaging Radar Systems Group Defence Science and Technology Organisation 2. School of Electrical
More informationEarth Exploration-Satellite Service (EESS)- Active Spaceborne Remote Sensing and Operations
Earth Exploration-Satellite Service (EESS)- Active Spaceborne Remote Sensing and Operations SRTM Radarsat JASON Seawinds TRMM Cloudsat Bryan Huneycutt (USA) Charles Wende (USA) WMO, Geneva, Switzerland
More informationWetland InSAR: A new space-based hydrological monitoring tool of wetlands surface water level changes
Wetland InSAR: A new space-based hydrological monitoring tool of wetlands surface water level changes Shimon Wdowinski (1), Sang-Wan Kim (1), Falk Amelung (1), and Tim Dixon (1) (1) Division of Marine
More informationSentinel-1A SAR Interferometry Verification
Sentinel-1A SAR Interferometry Verification Dirk Geudtner1, Pau Prats2, Nestor Yaguee-Martinez2, Andrea Monti Guarnieri3, Itziar Barat1, Björn Rommen1 and Ramón Torres1 1ESA ESTEC 2DLR, Microwave and Radar
More informationSnow property extraction based on polarimetry and differential SAR interferometry
Snow property extraction based on polarimetry and differential SAR interferometry S. Leinß, I. Hajnsek Earth Observation and Remote Sensing, Institute of Enviromental Science, ETH Zürich TerraSAR X and
More informationCHARACTERISTICS OF SNOW AND ICE MORPHOLOGICAL FEATURES DERIVED FROM MULTI-POLARIZATION TERRASAR-X DATA
CHARACTERISTICS OF SNOW AND ICE MORPHOLOGICAL FEATURES DERIVED FROM MULTI-POLARIZATION TERRASAR-X DATA Dana Floricioiu 1, Helmut Rott 2, Thomas Nagler 2, Markus Heidinger 2 and Michael Eineder 1 1 DLR,
More informationGround surface deformation of L Aquila. earthquake revealed by InSAR time series
Ground surface deformation of L Aquila earthquake revealed by InSAR time series Reporter: Xiangang Meng Institution: First Crust Monitoring and Application Center, CEA Address: 7 Naihuo Road, Hedong District
More informationKimberly J. Mueller Risk Management Solutions, Newark, CA. Dr. Auguste Boissonade Risk Management Solutions, Newark, CA
1.3 The Utility of Surface Roughness Datasets in the Modeling of United States Hurricane Property Losses Kimberly J. Mueller Risk Management Solutions, Newark, CA Dr. Auguste Boissonade Risk Management
More informationCopyright 2015 California Institute of Technology. U.S. Government sponsorship acknowledged.
Copyright 2015 California Institute of Technology. U.S. Government sponsorship acknowledged. DOCUMENT CHANGE LOG Revision Date Sections Changed Reason for Change ii Copyright 2015 California Institute
More informationBurst overlapping of ALOS-2 PALSAR-2 ScanSAR-ScanSAR interferometry
Burst overlapping of ALOS-2 PALSAR-2 ScanSAR-ScanSAR interferometry Japan Aerospace Exploration Agency Earth Observation Research Center Ryo Natsuaki, Takeshi Motohka, Shinichi Suzuki and Masanobu Shimada
More informationWind, Slick, and Fishing Boat Observations with Radarsat ScanSAR
Wind, Slick, and Fishing Boat Observations with Radarsat ScanSAR Jim Gower and Simon Skey The wide swath (45 km) of ScanSAR (synthetic aperture radar) images provides a greater opportunity for imaging
More informationSMAP and SMOS Integrated Soil Moisture Validation. T. J. Jackson USDA ARS
SMAP and SMOS Integrated Soil Moisture Validation T. J. Jackson USDA ARS Perspective Linkage of SMOS and SMAP soil moisture calibration and validation will have short and long term benefits for both missions.
More informationLeveraging Sentinel-1 time-series data for mapping agricultural land cover and land use in the tropics
Leveraging Sentinel-1 time-series data for mapping agricultural land cover and land use in the tropics Caitlin Kontgis caitlin@descarteslabs.com @caitlinkontgis Descartes Labs Overview What is Descartes
More informationAATSR Cycle Report Cycle # 21
11111311 AATSR Cycle Report Cycle # 21 20 October 2003, 21:59:29 orbit 8572 24 November 2003, 21:59:29 orbit 9072 This image shows fascinating sea surface temperature patterns off the western coast of
More information1. Regarding the availability of two co-polarized (HH and VV) channels.
Dear Anonymous Referee #2, Thank you for your insightful and stimulating review comments. Modifications based on these comments will significantly improve the quality of this research paper. General Comments:
More informationERS-ENVISAT Cross-interferometry for Coastal DEM Construction
ERS-ENVISAT Cross-interferometry for Coastal DEM Construction Sang-Hoon Hong and Joong-Sun Won Department of Earth System Sciences, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, 120-749, Seoul, Korea
More informationEXPLOITING SUNGLINT SIGNATURES FROM MERIS AND MODIS IMAGERY IN COMBINATION TO SAR DATA TO DETECT OIL SLICKS
EXPLOITING SUNGLINT SIGNATURES FROM MERIS AND MODIS IMAGERY IN COMBINATION TO SAR DATA TO DETECT OIL SLICKS M. Adamo 1, G. De Carolis 2, V. De Pasquale 2, and G. Pasquariello 2 1 Dept. of Physics, University
More informationProspects of microwave remote sensing for snow hydrology
Hydrologie Applications of Space Technology (Proceedings of the Cocoa Beach Workshop, Florida, August 1985). IAHS Publ. no. 160,1986. Prospects of microwave remote sensing for snow hydrology HELMUT ROTT
More informationMajor Point/Area Sources Name Type Major Emissions Distance (m) Direction CFB Cold Lake Air Force Base NOx, PM, HC, TRS 3km to aircraft West
Page 1 of 11 Site Documentation: Cold Lake South Continuous Monitoring Station General Site Information Item Description Site ID (CASA ID) LICA01 Station Name Cold Lake South Continuous Monitoring Station
More informationEvaluating Flood Hazard Potential in Danang City, Vietnam Using FOSS4G
Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings Volume 15 Seoul, South Korea Article 28 2015 Evaluating Flood Hazard Potential in Danang City, Vietnam Using FOSS4G An Tran
More informationEffective Utilization of Synthetic Aperture Radar (SAR) Imagery in Rapid Damage Assessment
Effective Utilization of Synthetic Aperture Radar (SAR) Imagery in Rapid Damage Assessment Case Study Pakistan Floods SUPARCO M. Maisam Raza, Ahmad H. Rabbani SEQUENCE Flood Monitoring using Satellite
More informationCURRENT STATUS OF SCIAMACHY POLARISATION MEASUREMENTS. J.M. Krijger 1 and L.G. Tilstra 2
% % CURRENT STATUS OF SCIAMACHY POLARISATION MEASUREMENTS JM Krijger 1 and LG Tilstra 2 1 SRON (National Institute for Space Research), Sorbonnelaan 2, 3584 CA Utrecht, The Netherlands, krijger@sronnl
More informationApplication of PSI technique to slope stability monitoring in the Daunia mountains, Italy
ESA ESRIN - Frascati 28 November- 2 December Application of PSI technique to slope stability monitoring in the Daunia mountains, Italy F. Bovenga (1) (fabio.bovenga@ba.infn.it) L. Guerriero (1) R. Nutricato
More informationRoadway Traffic Noise Feasibility Assessment. 315 Chapel Street. Ottawa, Ontario
Roadway Traffic Noise Feasibility Assessment 315 Chapel Street Ottawa, Ontario REPORT: GWE17-002 - Traffic Noise Prepared For: Leanne Moussa Allsaints 10 Blackburn Avenue K1N 6P8 Ottawa, Ontario Prepared
More informationEvaluating Urban Vegetation Cover Using LiDAR and High Resolution Imagery
Evaluating Urban Vegetation Cover Using LiDAR and High Resolution Imagery Y.A. Ayad and D. C. Mendez Clarion University of Pennsylvania Abstract One of the key planning factors in urban and built up environments
More informationSAR Remote Sensing of Snow Parameters in Norwegian Areas Current Status and Future Perspective
182 Progress In Electromagnetics Research Symposium 2006, Cambridge, USA, March 26-29 SAR Remote Sensing of Snow Parameters in Norwegian Areas Current Status and Future Perspective R. Storvold, E. Malnes,
More information