Landslide types and causes1
Introduction to landslidesPart 3: Use of Remote sensing for landslide mapping
Cees van Westen
International Institute for Aerospace Survey and Earth
Sciences (ITC), Enschede, The Netherlands.
E-mail: [email protected]
Landslide types and causes2
Landslide mapping Landslides are directly affecting the ground surface, so the
application of remote sensing techniques is very suited to slope instability studies.
The use of remote sensing images is particular useful when stereo images are used: typical morphological features of landslides.
Also the overall terrain conditions, determining the susceptibility of a site to be subject to sliding, can profitably be interpreted from remote sensing data.
The term remote sensing is used here in its widest sense, including aerial photography, as well as imagery obtained by satellites or any other remote sensing technique.
Landslide types and causes3
Landslide mapping Landslide inventory mapping uses:
aerial photo satellite interpretation, ground survey, and/or a database of historical occurrences of landslides.
The final product gives the spatial distribution of mass movements, represented either at scale or as points. Whenmultitemporal airborne or satellite image analysis was performed, these maps can also show landslide activity.
Landslide types and causes4
Short repetition: EM spectrum
1 2 3 4 5 6 8 970.4 0.7 10 11 12 13Wavelengh (M)METEOSAT
NOAA
LANDSAT
SPOT
VIR
AVHRR
MSS
TM
PAN
XS
VISIBLE NEAR IR MEDIUM IR THERMAL IR
VIS TIRWV
1 2 3 4 5
4 & 5
4 5 6 7
1 2 3 4 5 7 6
1 2 3
1
Landslide types and causes5
Landslide mapping
Current landslide inventory maps are not standardized. They are published at different scales with various levels of details.
Attention should be paid to the image specifications required for an adequate interpretation: Spatial resolution Spectral resolution Temporal resolution
Landslide types and causes6
Spatial resolution (1) The interpretability of landslides from remote sensing
images depends in the first place on the spatial resolutionof the images in relation to the size of the features which are characterising the slope movement and which can be recognised or identified.
The following aspects are important for recognizing landslides from remote sensing images: Contrast Size of landslide Interpretation method (Monoscopic / Stereoscopic) Professional experience of the interpreter
Landslide types and causes7
Minimum size of feature that can be identified
Minimum sizes ( in m ) needed for a landslide to be identified or interpreted, depending on the conditions of contrast between theelements of the slide and the background. The data for aerial photographs are somewhat flattered, as optimal photographic conditions and processing are considered.
Landslide types and causes8
Contrast The interpretability is influenced by the existing contrast
between the slope movement and its background.
In image interpretation this contrast may be considered as the spectral or spatial differences that exist between the object of interest (landslide) and its surroundings.
In the case of slope failures, the contrast of the feature with its surroundings depends on:
the period elapsed since the failure, as erosional processes and the recovery of the vegetation are tending to obscure the cicatriceswhich the landslide has left in the surface, and,
the severity with which the morphology, drainage and vegetationalconditions have been affected by the landslide.
Landslide types and causes9
Contrast (2) The before mentioned contrast of the feature against its
background is a variable defining the amount of pixels needed
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Example: contrast Example 1: Low contrast
A landslide scar that is in shadow (low contrast) in the central upper part of the picture and a depositional area of landslide debris in the central to lower part of the picture. The pictures show how the same landslide would be displayed on aerial photos , SPOT Pan, SPOT XS, and LANDSAT TM.
Conclusion ?
Example 2: High contrastThe figures show pictures with varyinggroundresolution cells of a landslide in the Spanish Pyrenees The landslide scar is now artificially enhanced and shown in very high contrast.
Conclusion?
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Interpretability For the evaluation of the suitability of remote sensing images for
landslide inventory mapping the size of individual slope failures in relation to the ground resolution cell is of crucial importance.
For example: typical area involved in a failure of 42000 m2. 20 x 20 pixels on a SPOT Pan image 10 x 10 pixels on SPOT multispectral images, sufficient to identify a landslide displaying a high contrast but insufficient for a proper analysis of the elements
pertaining to the failure to establish characteristics and type of landslide.
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Interpretability
Most appropriate photoscale for analysis is 1:15.000. 1:25.000 should be considered as the smallest scale to
analyze slope instability Using smaller scales a slope failure may be recognised as
such, if size and contrast are sufficiently large. The amount of analytical information, enabling the
interpreter to make conclusions on type and causes of the landslide, will be very limited at scales smaller than 1:25.000.
A considerable amount of slope movements may be overlooked at smaller scales.
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Size of the landslide
Relative suitabilities of different scales of aerial photographs for different elements in slope instability mapping.0 = less adequate, 1 = limited use, 2 = useful, 3 = very useful.
Landslide types and causes14
Conclusions : spatial resolution
Large photoscales allow for the inventory and analysis of landslides and the interpretation of the possible causal factors,
Small scale photographs are enabling the determination of the spatial distribution of the variables involved in the mass movement.
Smaller scales are more useful to analyze the overall geological and geomorphological setting.
For landslide interpretation you need airphotos
Landslide types and causes15
Spectral information Satellite data is useful, only when features are large.
It can be used when: spectral information is used in conjunction to other data related to slope
failures, based on terrain evidences, a direct relationship is known between slope
instability and vegetation or drainage anomalies.
Spectral information, in the same way as spatial data, can be used for the delineation of terrain variables (in this case mostly related to vegetation and drainage conditions), which are correlated or assumed to be related with slope movements.
In special cases (high contrast and/or large dimensions) the feature itself may be identified on the basis of spectral information. Seldomly this type of information alone will be sufficient for the analysis of the type of failure.
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Airphotos Panchromatic black and white , Colour films Black and white infrared and false colour infrared
films Excellent spatial resolution, Normally
stereoscopic Spectral resolution is bad in comparison to
multispectral data Organization of a aerial photographic mission is
time consuming Number of days with good climatic conditions are
very limited The temporal resolution is bad in comparison to
satellite imagery.
Landslide types and causes17
Spectral resolution: types of airphotos
Vertical photographyOblique photography
PanchromaticTrue colour Colour infrared
Landslide types and causes18
Infrared
Detection vegetation differences. Optimal differences in the vegetational conditions may be expected in the early or very late stage of the growing season.
Detection differences in water conditions. Differential drainage conditions are optimal shortly after the first rainstorms of the rainy season or in cold and temperate climatesshortly after the snowmelt.
Infrared sensitive film and false colour infrared film, is very useful. Satellite data is useful, only when features are large.
Landslide types and causes19
Temporal resolution Satellite systems give the opportunity to obtain regularly data
from the same areas, allowing for the monitoring of processes in time.
Images obtained shortly after a period of slope instability will show high contrasts between the zones affected by slope instability and the stable surroundings, resulting in clearly detectable spatial and spectral changes.
The interpretation of sequential images allows for the correlation of climatic or seismic events with the occurrence and intensity of slope movements.
For interpretation of landslide activity we dont need a very high temporal resolution.
Also airphotos from different periods (e.g. each decade) are useful for landslide activity mapping.
Multitemporal radar images can be used to detect altitude differences using radar interferometry. However, radar images are not useful for mapping features themselves.
Landslide types and causes20
Temporal resolution
Landslide types and causes21
SPOT
two sensor systems, each one with a 60 kilometers swath width.
The sensors have an off-nadir looking capability: stereoscopy
sidewards looking option: high temporal resolution. wide panchromatic band (10 meter) three narrower spectral bands (green, red and infrared, 20
meter).
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Mapping landslides using SPOT
Comparison of interpretability of large complex landslide in the Sant ArcangeloBasin (Basilicata, Italy) shown on:
stereo SPOT image (scale approx. 1:70,000),
medium scale aerial photographs (1:33,000) and
large-scale aerial photographs
(1:17,000).
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Mapping landslides using SPOT
SPOT Panchromatic: 10 m pixel size
Landslide at Hachimantai in Akita Prefecture, Japan (1997.5)
The landslide was about 350m in width and about 700m in length.
Earth and debris from the landslide destroyed 16 houses and became a debris flow.
Flow was stopped by the Sabo Dam about 2km downstream.
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Mapping landslides using SPOT
Landslide in IZUMI City, Kagoshima Prefecture,Japan(1997.7) A debris flow occurred on July 10, 1997 causing 34 casualties (21
fatalities) and completely destroying19 houses on the alluvial fan. The landslide was about 200 m long, 80 m wide, 27 m deep at
maximum, with an incline of 26 degrees. The volume was about 165000 cubic meters.
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LANDSAT
6 bands covering the visible and the near and middle infrared (30 m)
one band in the thermal infrared. overpass every eighteen days weather conditions are a serious limiting factor lack of an adequate stereovision.
Landslide types and causes26
Mapping landslides using LANDSAT Guanay Landslide
Progression (Bolivia)
LANDSAT MSS (60 x 80 metres),
LANDSAT TM (30 meters except for the thermal infrared band)
spectral resolution with 6 bands covering the whole visible and the near and middle infrared part of the spectrum and with one band in the thermal infrared.
weakest point of the LANDSAT System is the lack of an adequate stereovision
Airphoto1:50.000
1993
Airphoto1:50.0001963
LANDSATMSS1978
LANDSATTM1987
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Mapping landslides using radar
European ERS-1 Japanese JERS, Canadian RADARSAT all weather capability: cloud
penetrating. information on surface roughness
and micromorphology. not been very appropriate for the
application in mountainous terrain.
radar interferometry is very promising
SPOT 16 Nov. 98SPOT 16 Nov. 98
RADARSAT 7 Nov. 98RADARSAT 7 Nov. 98
Data Processing Chain IData Processing Chain I
SAR and optical EO processing
SAR dataoptical RS data
historicaldata
actualdata
(D-)InSAR processing / optical RS data processing
occurenceof landlsides
SARscape SARscape EO processing softwareEO processing software
Landslide in the area of NiceLandslide in the area of Nice-- the phase was converted tothe phase was converted tomovement results in 1movement results in 1--2cm/day2cm/day
data processing: data processing: PolimiPolimi
Phase values of Phase values of KaunertalKaunertal
IMG, Innsbruck IMG, Innsbruck
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Conclusions
The application of presently available satellite remote sensing is limited.
spatial resolution too large often lack of stereo imagery, only stereo SPOT images may be used for small regional hazard zonation. satellite images are used for mapping the spatial distribution of landslide
controlling variables For the inventory mapping and the analytical part of the slope
instability assessment, large scale aerial photography is used. The potentials of radar imagery for landslide hazard zonation still
need further investigations.
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