Next Article in Journal
Estimation of Building Density with the Integrated Use of GF-1 PMS and Radarsat-2 Data
Next Article in Special Issue
Exploiting TERRA-AQUA MODIS Relationship in the Reflective Solar Bands for Aerosol Retrieval
Previous Article in Journal
Cloud Extraction from Chinese High Resolution Satellite Imagery by Probabilistic Latent Semantic Analysis and Object-Based Machine Learning
Previous Article in Special Issue
Using Landsat, MODIS, and a Biophysical Model to Evaluate LST in Urban Centers
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle
Remote Sens. 2016, 8(11), 965; doi:10.3390/rs8110965

Interpolation of GPS and Geological Data Using InSAR Deformation Maps: Method and Application to Land Subsidence in the Alto Guadalentín Aquifer (SE Spain)

Geohazards InSAR Laboratory and Modeling Group (InSARlab), Geoscience Research Department, Geological Survey of Spain (IGME), Alenza 1, 28003 Madrid, Spain
Research Partnership Unit IGME-UA on Radar Interferometry Applied to Ground Deformation (UNIRAD), University of Alicante, P.O. Box 99, 03080 Alicante, Spain
Spanish Working Group on Ground Subsidence (SUBTER), UNESCO, 03690 Alicante, Spain
Environmental Geology and Geomathematics, Geoscience Research Department, Geological Survey of Spain (IGME), Alenza 1, 28003 Madrid, Spain
Departamento de Ingeniería Civil, Universidad Católica San Antonio de Murcia, Campus de los Jerónimos, 30107 Murcia, Spain
Earth Observation and Geohazards Expert Group (EOEG), EuroGeoSurveys, the Geological Surveys of Europe, 36-38, Rue Joseph II, 1000 Brussels, Belgium
Centre Tecnològic de les Telecomunicacions de Catalunya (CTTC), 08860 Castelldefels, Barcelona, Spain
Leica Geosystems, s.l. Ctra Fuencarral, 28108 Alcobendas, Madrid, Spain
Department of Earth Sciences, Environment and Resources, Federico II University of Naples, Largo San Marcellino 10, 80138 Naples, Italy
10 Ingeniería Topográfica y Cartografía, Universidad Politécnica de Madrid, 28031 Madrid, Spain
Dpto. de Geología y Geoquímica, Facultad Ciencias, Universidad Autónoma de Madrid, 28049 Madrid, Spain
Author to whom correspondence should be addressed.
Academic Editors: Naser El-Sheimy, Zahra Lari, Adel Moussa, Zhong Lu, Richard Gloaguen and Prasad S. Thenkabail
Received: 30 August 2016 / Revised: 28 October 2016 / Accepted: 16 November 2016 / Published: 23 November 2016
(This article belongs to the Special Issue Multi-Sensor and Multi-Data Integration in Remote Sensing)
View Full-Text   |   Download PDF [7903 KB, uploaded 23 November 2016]   |  


Land subsidence resulting from groundwater extractions is a global phenomenon adversely affecting many regions worldwide. Understanding the governing processes and mitigating associated hazards require knowing the spatial distribution of the implicated factors (piezometric levels, lithology, ground deformation), usually only known at discrete locations. Here, we propose a methodology based on the Kriging with External Drift (KED) approach to interpolate sparse point measurements of variables influencing land subsidence using high density InSAR measurements. In our study, located in the Alto Guadalentín basin, SE Spain, these variables are GPS vertical velocities and the thickness of compressible soils. First, we estimate InSAR and GPS rates of subsidence covering the periods 2003–2010 and 2004–2013, respectively. Then, we apply the KED method to the discrete variables. The resulting continuous GPS velocity map shows maximum subsidence rates of 13 cm/year in the center of the basin, in agreement with previous studies. The compressible deposits thickness map is significantly improved. We also test the coherence of Sentinel-1 data in the study region and evaluate the applicability of this methodology with the new satellite, which will improve the monitoring of aquifer-related subsidence and the mapping of variables governing this phenomenon. View Full-Text
Keywords: InSAR; aquifer; subsidence; interpolation; kriging with external drift InSAR; aquifer; subsidence; interpolation; kriging with external drift

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Béjar-Pizarro, M.; Guardiola-Albert, C.; García-Cárdenas, R.P.; Herrera, G.; Barra, A.; López Molina, A.; Tessitore, S.; Staller, A.; Ortega-Becerril, J.A.; García-García, R.P. Interpolation of GPS and Geological Data Using InSAR Deformation Maps: Method and Application to Land Subsidence in the Alto Guadalentín Aquifer (SE Spain). Remote Sens. 2016, 8, 965.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top