Scatterer identification and analysis using combined InSAR and laser data

Ramon F. Hanssen, Adriaan van Natijne, Roderik C. Lindenbergh, Prabu Dheenathayalan, Mengshi Yang, Ling Chang, Freek van Leijen, Paco Lopez-Dekker, Jipper van der Maaden, Peter van Oosterom, Hanjiang Xiong, Pingbo Hu, Zhang Zhang, Bisheng Yang

Research output: Contribution to conferenceAbstractOther research output

Abstract

The geolocation of coherent radar scatterers, used for InSAR deformation analysis, is often not accurate enough to associate them to physical geo-objects. The imaging geometry of satellite InSAR results in (i) biases in the entire point field, and (ii) quite elongated and skewed confidence ellipsoids in the range, azimuth and cross-range direction. The metric defined by the covariance matrix of the InSAR results defines the optimal way to associate scatterers with geo-objects. Laser scanning point clouds, stemming from aerial or terrestrial laser surveys, yield very dense geometry of geo-objects and topography. Here we combine InSAR and laser point clouds, taking the covariance metrics of the InSAR data into account. This enables us to correct the positions of InSAR data, to provide a geometric match with geo-objects. We demonstrate how this allows for adding contextual information as attributes to individual scatterers, which improves the interpretation of the InSAR results.
Original languageEnglish
Publication statusPublished - 2018
EventEGU General Assembly 2018 - Vienna, Austria
Duration: 8 Apr 201813 Apr 2018
https://www.egu2018.eu/

Conference

ConferenceEGU General Assembly 2018
Abbreviated titleEGU 2018
CountryAustria
CityVienna
Period8/04/1813/04/18
Internet address

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laser
geometry
azimuth
radar
topography
matrix
analysis
attribute

Cite this

Hanssen, R. F., van Natijne, A., Lindenbergh, R. C., Dheenathayalan, P., Yang, M., Chang, L., ... Yang, B. (2018). Scatterer identification and analysis using combined InSAR and laser data. Abstract from EGU General Assembly 2018, Vienna, Austria.
Hanssen, Ramon F. ; van Natijne, Adriaan ; Lindenbergh, Roderik C. ; Dheenathayalan, Prabu ; Yang, Mengshi ; Chang, Ling ; van Leijen, Freek ; Lopez-Dekker, Paco ; van der Maaden, Jipper ; van Oosterom, Peter ; Xiong, Hanjiang ; Hu, Pingbo ; Zhang, Zhang ; Yang, Bisheng. / Scatterer identification and analysis using combined InSAR and laser data. Abstract from EGU General Assembly 2018, Vienna, Austria.
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title = "Scatterer identification and analysis using combined InSAR and laser data",
abstract = "The geolocation of coherent radar scatterers, used for InSAR deformation analysis, is often not accurate enough to associate them to physical geo-objects. The imaging geometry of satellite InSAR results in (i) biases in the entire point field, and (ii) quite elongated and skewed confidence ellipsoids in the range, azimuth and cross-range direction. The metric defined by the covariance matrix of the InSAR results defines the optimal way to associate scatterers with geo-objects. Laser scanning point clouds, stemming from aerial or terrestrial laser surveys, yield very dense geometry of geo-objects and topography. Here we combine InSAR and laser point clouds, taking the covariance metrics of the InSAR data into account. This enables us to correct the positions of InSAR data, to provide a geometric match with geo-objects. We demonstrate how this allows for adding contextual information as attributes to individual scatterers, which improves the interpretation of the InSAR results.",
author = "Hanssen, {Ramon F.} and {van Natijne}, Adriaan and Lindenbergh, {Roderik C.} and Prabu Dheenathayalan and Mengshi Yang and Ling Chang and {van Leijen}, Freek and Paco Lopez-Dekker and {van der Maaden}, Jipper and {van Oosterom}, Peter and Hanjiang Xiong and Pingbo Hu and Zhang Zhang and Bisheng Yang",
note = "Geophysical Research Abstracts (online) EGU2018-17008; EGU General Assembly 2018, EGU 2018 ; Conference date: 08-04-2018 Through 13-04-2018",
year = "2018",
language = "English",
url = "https://www.egu2018.eu/",

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Hanssen, RF, van Natijne, A, Lindenbergh, RC, Dheenathayalan, P, Yang, M, Chang, L, van Leijen, F, Lopez-Dekker, P, van der Maaden, J, van Oosterom, P, Xiong, H, Hu, P, Zhang, Z & Yang, B 2018, 'Scatterer identification and analysis using combined InSAR and laser data' EGU General Assembly 2018, Vienna, Austria, 8/04/18 - 13/04/18, .

Scatterer identification and analysis using combined InSAR and laser data. / Hanssen, Ramon F.; van Natijne, Adriaan; Lindenbergh, Roderik C.; Dheenathayalan, Prabu; Yang, Mengshi; Chang, Ling ; van Leijen, Freek ; Lopez-Dekker, Paco; van der Maaden, Jipper; van Oosterom, Peter; Xiong, Hanjiang; Hu, Pingbo; Zhang, Zhang; Yang, Bisheng.

2018. Abstract from EGU General Assembly 2018, Vienna, Austria.

Research output: Contribution to conferenceAbstractOther research output

TY - CONF

T1 - Scatterer identification and analysis using combined InSAR and laser data

AU - Hanssen, Ramon F.

AU - van Natijne, Adriaan

AU - Lindenbergh, Roderik C.

AU - Dheenathayalan, Prabu

AU - Yang, Mengshi

AU - Chang, Ling

AU - van Leijen, Freek

AU - Lopez-Dekker, Paco

AU - van der Maaden, Jipper

AU - van Oosterom, Peter

AU - Xiong, Hanjiang

AU - Hu, Pingbo

AU - Zhang, Zhang

AU - Yang, Bisheng

N1 - Geophysical Research Abstracts (online) EGU2018-17008

PY - 2018

Y1 - 2018

N2 - The geolocation of coherent radar scatterers, used for InSAR deformation analysis, is often not accurate enough to associate them to physical geo-objects. The imaging geometry of satellite InSAR results in (i) biases in the entire point field, and (ii) quite elongated and skewed confidence ellipsoids in the range, azimuth and cross-range direction. The metric defined by the covariance matrix of the InSAR results defines the optimal way to associate scatterers with geo-objects. Laser scanning point clouds, stemming from aerial or terrestrial laser surveys, yield very dense geometry of geo-objects and topography. Here we combine InSAR and laser point clouds, taking the covariance metrics of the InSAR data into account. This enables us to correct the positions of InSAR data, to provide a geometric match with geo-objects. We demonstrate how this allows for adding contextual information as attributes to individual scatterers, which improves the interpretation of the InSAR results.

AB - The geolocation of coherent radar scatterers, used for InSAR deformation analysis, is often not accurate enough to associate them to physical geo-objects. The imaging geometry of satellite InSAR results in (i) biases in the entire point field, and (ii) quite elongated and skewed confidence ellipsoids in the range, azimuth and cross-range direction. The metric defined by the covariance matrix of the InSAR results defines the optimal way to associate scatterers with geo-objects. Laser scanning point clouds, stemming from aerial or terrestrial laser surveys, yield very dense geometry of geo-objects and topography. Here we combine InSAR and laser point clouds, taking the covariance metrics of the InSAR data into account. This enables us to correct the positions of InSAR data, to provide a geometric match with geo-objects. We demonstrate how this allows for adding contextual information as attributes to individual scatterers, which improves the interpretation of the InSAR results.

UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2018/pres/chang_sca.pdf

M3 - Abstract

ER -

Hanssen RF, van Natijne A, Lindenbergh RC, Dheenathayalan P, Yang M, Chang L et al. Scatterer identification and analysis using combined InSAR and laser data. 2018. Abstract from EGU General Assembly 2018, Vienna, Austria.