REMOTE SENSING DATA FOR USE IN REGIONAL DIKE INSPECTION SHARON CUNDILL1, ROBERT HACK1, MARK VAN DER MEIJDE1,
JOOST VAN DER SCHRIER2 & DOMINIQUE NGAN-TILLARD3
1UNIVERSITY TWENTE, FACULTY OF GEO-INFORMATION SCIENCE AND EARTH OBSERVATION (ITC), ENSCHEDE, THE NETHERLANDS 2ROYAL HASKONING, NIJMEGEN, THE NETHERLANDS 3DELFT UNIVERSITY OF TECHNOLOGY, FACULTY OF CIVIL ENGINEERING &GEOSCIENCES, GEO-ENGINEERING SECTION, DELFT, THE NETHERLANDS
HOW ARE REGIONAL DIKES CURRENTLY MONITORED?
Inspected visually in person Looking for irregularities About 14 000 km of regional dikes in the Netherlands
http://www.ctv.ca/CTVNews/World/20120106/dutch-villages-rain-dike-120105/
Current method of dike inspection is: slow man-hour intensive subjective limited by accessibility to the areas to be inspected
THE IDEA
Remote sensing has been proposed as a possible tool for dike inspection: To identify possible problematic areas for further investigation Rapid collection and processing of data Large coverage (of specified areas) Relatively low costs Access to flooded and difficult/dangerous to reach areas Objective Regular surveys
BUT has not been fully researched
WHAT IS REMOTE SENSING?
Remote sensing is the acquisition of information about an object without making physical contact with the object
Objects reflect or emit different amounts of energy in different wavelengths
This electromagnetic energy is measured by a sensor Data most often collected in image form Sensor maybe on plane, helicopter, satellite, etc
Diagrams from http://www.univie.ac.at/geographie/fachdidaktik/FD/site/external_htmls/imagers.gsfc.nasa.gov/adventure/rs_lesson.html
THE ELECTROMAGNETIC SPECTRUM
Modified from http://www.kollewin.com/blog/electromagnetic-spectrum/
BACKGROUND
2 key inspection features
Quality of dike covering
Phtotographs from http://www.inspectiewaterkeringen.nl/content.asp?h=4&s=39
Soil moisture of the dike
Weeds
Bare patches
Cracks due to dryness
Wet patches
DIKE COVERING
Most regional dikes – grass covering Remote sensing vegetation studies % vegetation cover Plant health and vigour Species differentiation
SOIL MOISTURE
Thermal inertia of water Wet areas take longer to heat up and longer to cool down than
dry areas
Vegetation response Plant temperature affected by available soil moisture Healthy vs stressed affects spectral response (reflect different
amounts of energy in different wavelengths)
STUDY SITE
STUDY SITE
FIELD CAMPAIGN
15 to 16 July 2010 – over 24 hour period 54 point locations
Remote sensing data: Thermal Visible Multispectral Hyperspectral
Validation data: Soil moisture Grass cover quality
FIELD CAMPAIGN
15 to 16 July 2010 – over 24 hour period 54 point locations
Remote sensing data: Thermal Visible Multispectral Hyperspectral
Validation data: Soil moisture Grass cover quality
Apparent Temperature
Blue, green and red
Few broad bands
Many narrow bands
RESULTS: SOIL MOISTURE
Soil moisture Daytime thermal
RESULTS: SOIL MOISTURE
Soil moisture Near infrared
RESULTS: SOIL MOISTURE
Pearson correlation Soil moisture Significancea
Daytime - Thermal -0.668 0.000
Near infrared - Multispectral -0.614
0.000
a Significant at the 0.01 probability level
RESULTS: THERMAL TIME SERIES
Normalised thermal values for selected locations (normalised to the mean). Apparent solar noon: 13h38. Apparent sunset: 21h30. Apparent sunrise: 05h46. Rain event (in grey) at around 16h00.
RESULTS: COVER QUALITY
RESULTS: COVER QUALITY
Spearman's rho Cover quality Significancea
Green:Red ratio – Visible -0.593 0.000
NIR:Red ratio – Multispectral
-0.583 0.000
a Significant at the 0.01 probability level
RESULTS: COVER QUALITY
CONCLUSIONS
Soil moisture conditions can be observed in daytime thermal and multispectral remote sensing data
Visible and multispectral ratios can also be used to evaluate dike grass cover quality
Hyperspectral data is particularly useful for evaluating the quality of grass cover
Thermal measurements are strongly affected by local conditions. Optimal conditions are dry days with clear skies. Optimal time is apparent noon so as to reduce illumination effects.
THANK YOU
Contact: Sharon Cundill Email: [email protected] This research is part of the RSDYK project of the Flood Control 2015 programme