Landslide susceptibility estimations in the Gerecse Hills ...Bikol HUNGARY Tata Epöl D Landslides...
1
0% 10% 20% 30% 40% 50% 60% 70% Cemented sediments (tertiary and older) Fluvial sediments Cemented carbonates (quaternary) Loess Older carbonates Quaternary slope deposits Distribution of geologic landslide area non-landslide area Figure 3: Surface geology features were sorted into 6 categories. Loess and fluvial sediments are overhelmingly present in the Gerecse and equally represented in both areas, however older cemented sediments and older carbonates are significantly less prone to slope movements. 6 3.6 22.5 23.1 1.2 1.1 62.7 57.2 3.8 9.9 3.8 5.1 Statistics (E) proportion of total area B i k o l B iko l Által-ér Tata Lake r é - l a t l Á r C e t e k ó j a B Ú n y C r e e k C s á k á ny C reek C y r n e e á k k á s C St. L á s z l ó C r e ek Field survey, Map 2 Környe Kecskéd Vértessomló Szárliget Nagyegyháza Nagyegyháza Mány Gyermely Epöl Bajna Nagysáp Héreg Tarján Vértestolna Tardos Vértesszőlős Baj Szomód Neszmély Dunaalmás Dunaszentmiklós Süttő Lábatlan Nyergesújfalu Tát TATA TATABÁNYA Agostyán Bajót Mogyorósbánya Gerecse 633 Öreg-Kovács 555 447 Somlyó Halyagos 445 Built-up area Stream Lake River Country border Relative landslide hazard 99–100% 95–99% 90–95% 75–90% below 75% o l k i B HUNGARY Epöl Tata D Landslides in NLC 0 m 2500 m 5000 m 47.55° 47.6° 47.65° 47.7° 47.75° 18.6° 18.55° 18.5° 18.45° 18.4° 18.35° Gerecse 633 Peak (m) Map 2: The used landslide inventory (NLC) stores the state of activity (active, inactive, unknown) for each site. For many it's stated as unknown. The goal of the field survey was to gather up-to-date information about the slope movement activity in 3 stream valleys descending towards the Danube. We found that most of the slope movements in the surveyed area are still active. In the other parts of the Gerecse many site's activity is still unknown. Estimated landslide hazard values in the Gerecse Hills Map 1 : The map shows how certain area is similar to the areas already affected by slope movements according to the four predictor variables. The most hazardous areas are the steeper loess slopes facing north or northwest. These areas include the riverside bluffs and the narrow stream valleys descending towards the Danube in the northern part of the Gerecse Hills. 0% 1% 2% 3% 4% 5% 6% Distribution of slope values 0° 10° 20° 30° 40° 60° 50° landslide area non-landslide area 14° or greater slopes are more likely in landslide areas Goal and motivation (A) Slope movement processes are constantly posing threat to property in populated and agricultural areas in the Gerecse Hills (Hungary). These processes have been studied for a long time in the Gerecse, however, a comprehensive geostatistic based analysis has not yet been made for the whole area. Our goal was to create a landslide-hazard map by using four predictor variables. We achieved this by applying Chung’s (2005) „likelihood ratio function model” with thematic data aquired from local landslide inventory and geologic maps and geomorphometric parameters derived from global coverage SRTM-1 DEM. DATA SOURCES DEM SRTM-1 30x30 m Geologic features The geologic map of Hungary 1 : 100 000 Landslide inventory National Landslides Cadastre (Hungary) Methods (B) Figure 1 : Creating the relative hazard map using the „ likelihood ratio function model ”. Q Q ź Elevation (ele) ź Slope (slo) ź Aspect (asp) Geologic features in 6 categories (geo) ź landslide () L ź non-landslide areas ( ) NL Computing the distribution of the 4 variables for both areas ; L (ele), L (slo), L (asp), L (geo) NL (ele), NL (slo), NL (asp), NL (geo) (Slope: Figure 2 , geologic features: Figure 3 ) R by comparing the distributions in the separate areas R for each cell, higher is more hazardous R shows the cell’s place as percentage in their ranking by H values higher means more hazardous Figure 2: Nearly half of the slopes in the non-landslide area are less steep than 10°. The landslide area has much steeper slopes. The two curves incline after 14°, steeper slopes are considered hazardous (P >1). slo P ele = L(ele) NL(ele) P slo = L(slo) NL(slo) P asp = L(asp) NL(asp) P geo = L(geo) NL(geo) H =P ele ×P slo ×P asp ×P geo ( Map 1 ) 2.2 0.8 0.8 3.2 9.2 17.2 19.5 12.8 21.3 12.8 8.8 4.6 4.6 13.8 23.0 22.9 13.6 4.5 3.5 0.8 0-1 1-5 5-10 10-25 25-50 50-75 75-90 90-95 95-99 99-100 Relave hazard values (H) Distribution of relative hazard (H) values Figure 4: We compared the distributions of the relative hazard values (H) in the landslide and the non-landslide areas. The proportion of landslide cells in the more hazardous categories (75%<H) provides information about the accuracy of the results. More than 66% of the landslide affected area is in the more hazardous categories. landslide area non-landslide area proportion of total area 0% 5% 10% 15% 20% 25% State of activity in the total study area: unknown 31% inactive 29% active 40% active-inactive overlapping previously unknown 0 500 1000 m 18° 20' 18° 21' 47° 43' 18° 22' 18° 23' 47° 44' Suggested changes in the landslide inventory after the field survey Neszmély Dunaalmás DANUBE Meleges-hegy 255 m Kozma-hegy 300 m Kőpite-hegy 292 m Nagy-hegy 280 m Vörös-kő 260 m Új-hegy 300 190 250 Reference Chung, C. (2005). Using likelihood ratio functions for modeling the conditional probability of occurrence of future landslides for risk assessment. Computers & Geosciences, 32. , pp. 1052-1068. Acknowledgement The conference participation was partly subsidised by the Talented Student Program of Eötvös Loránd University , Budapest. Conclusion (D) The relative hazard map (Map 1) we created: ź marks the areas similar to the study area by elevation, slope, aspect and surface geology as hazardous (Figure 4). ź can help the reambulation of the existing landslide inventory database. ź can serve as a base for more complex landslide vulnerability studies. The field survey (Map 2) showed: ź slope movement processes are still active in the area. ź it’s important to have an up-to-date landslide inventory. Results – the Landslide Hazard Map (C) Landslide susceptibility estimations in the Gerecse Hills (Hungary) 1 2 Dávid Gerzsenyi and Gáspár Albert 1 Eötvös Loránd University, Cartography Msc, Budapest, Hungary ([email protected]) 2 Eötvös Loránd University, Department of Cartography and Geoinformatics, Budapest, Hungary ([email protected]) HU RO MD UA PL SK SL HR AT CZ DE IT BG RS BA GERECSE EGU Figure 0: Location of study area
Transcript of Landslide susceptibility estimations in the Gerecse Hills ...Bikol HUNGARY Tata Epöl D Landslides...
0%
10%
20%
30%
40%
50%
60%
70%
Cemented sediments(tertiary and older)
Fluvial sediments
Cementedcarbonates(quaternary)
Loess Older carbonates Quaternaryslope deposits
Distribution of geologic
landslide area
non-landslide area
Figure 3: Surface geology features were sorted into 6 categories. Loess and fluvial sediments are overhelmingly present in the Gerecse and equally represented in both areas, however older cemented sediments and older carbonates are significantly less prone to slope movements.
6 3.6
22.5 23.1
1.2 1.1
62.7
57.2
3.8
9.9
3.8 5.1
Statistics (E)
pro
po
rtio
n o
f to
tal are
a
Bikol
Bikol
Által-ér
������
������
Tata Lake
ré-latlÁ
rC e t ekójaB
Ú
ny Creek
Csákány Creek
Cy rn eeá kkásC
St. László Creek
���������������
���������������
Field survey, Map 2
Környe
Kecskéd
Vértessomló Szárliget
Nagyegyháza
Nagyegyháza
Mány
Gyermely
EpölBajna
Nagysáp
Héreg
Tarján
Vértestolna
Tardos
Vértesszőlős
Baj
Szomód
NeszmélyDunaalmás
Dunaszentmiklós
SüttőLábatlan Nyergesújfalu
Tát
TATA
TATABÁNYA
Agostyán
Bajót Mogyorósbánya
Gerecse
633
Öreg-Kovács
555
447
Somlyó
Halyagos
445
Built-up area
Stream
Lake
River
Country border Relative landslide hazard99–100%95–99%90–95%75–90%below 75%
olkiB HUNGARY
EpölTata
D����� Landslides in NLC
0 m 2500 m 5000 m
47.55°
47.6°
47.65°
47.7°
47.75°
18.6°18.55°18.5°18.45°18.4°18.35°
Gerecse
633 Peak(m)
Map 2: The used landslide inventory (NLC) stores the state of activity (active, inactive, unknown) for each site. For many it's stated as unknown. The goal of the field survey was to gather up-to-date information about the slope movement activity in 3 stream valleys descending towards the Danube. We found that most of the slope movements in the surveyed area are still active. In the other parts of the Gerecse many site's activity is still unknown.
Estimated landslide hazard values in the Gerecse Hills
Map 1: The map shows how certain area is similar to the areas already affected by slope movements according to the four predictor variables. The most hazardous areas are the steeper loess slopes facing north or northwest. These areas include the riverside bluffs and the narrow stream valleys descending towards the Danube in the northern part of the Gerecse Hills.
0%
1%
2%
3%
4%
5%
6%Distribution of slope values
0° 10° 20° 30° 40° 60°50°
landslide area
non-landslide area
14° or greater slopes aremore likely in landslide areas
Goal and motivation (A)Slope movement processes are constantly posing threat to property in populated and agricultural areas in the Gerecse Hills (Hungary). These processes have been studied for a long time in the Gerecse, however, a comprehensive geostatistic based analysis has not yet been made for the whole area. Our goal was to create a landslide-hazard map by using four predictor variables. We achieved this by applying Chung’s (2005) „likelihood ratio function model” with thematic data aquired from local landslide inventory and geologic maps and geomorphometric parameters derived from global coverage SRTM-1 DEM.
DATA SOURCES
DEMSRTM-130x30 m
Geologic featuresThe geologic map of
Hungary1 : 100 000
Landslide inventory National Landslides
Cadastre (Hungary)
Methods (B)Figure 1: Creating the relative hazard map using the „likelihood ratio function model”.
Q����������� ��������� Q���������� ���������
ź Elevation (ele)ź Slope (slo)ź Aspect (asp)
Geologic features in 6 categories
(geo)
ź landslide ( )Lź non-landslide
areas ( )NL
Computing the distribution of the 4 variables for both areas; L(ele), L(slo), L(asp), L(geo) NL(ele), NL(slo), NL(asp), NL(geo)
(Slope: Figure 2, geologic features: Figure 3)
R������� ����������� ���������by comparing the distributions in the separate areas
R������� ������ ������for each cell, higher is more hazardous
R������� ������ ���shows the cell’s place as percentage in their ranking by H values
higher means more hazardous
Figure 2: Nearly half of the slopes in the non-landslide area are less steep than 10°. The landslide area has much steeper slopes. The two curves incline after 14°, steeper slopes are considered hazardous (P >1). slo
Pele =L(ele)
NL(ele)Pslo =
L(slo)
NL(slo)Pasp =
L(asp)
NL(asp)Pgeo=
L(geo)
NL(geo)
H=Pele × Pslo × Pasp × Pgeo
(Map 1)
2.20.8 0.8
3.2
9.2
17.2
19.5
12.8
21.3
12.8
8.8
4.6 4.6
13.8
23.0 22.9
13.6
4.53.5
0.8
0-1 1-5 5-10 10-25 25-50 50-75 75-90 90-95 95-99 99-100
Rela�ve hazard values (H)
Distribution of relative hazard (H) values
Figure 4: We compared the distributions of the relative hazard values (H) in the landslide and the non-landslide areas. The proportion of landslide cells in the more hazardous categories (75%<H) provides information about the accuracy of the results. More than 66% of the landslide affected area is in the more hazardous categories.
landslide area
non-landslide area
pro
po
rtio
n o
f to
tal are
a
0%
5%
10%
15%
20%
25%
State of activity in the total study area:
unknown 31% inactive 29% active 40% active-inactive overlapping previously unknown
0 500 1000 m
18° 20' 18° 21'
47° 43'
18° 22' 18° 23'
47° 44'
Suggested changes in the landslide inventory after the field survey
NeszmélyDunaalmás
DANUBE
Meleges-hegy
255 m
Kozma-hegy
300 m
Kőpite-hegy292 m
Nagy-hegy
280 m
Vörös-kő
260 m
Új-hegy300
190
250
ReferenceChung, C. (2005). Using likelihood ratio functions for modeling the conditional probability of occurrence of future landslides for risk assessment. Computers & Geosciences, 32., pp. 1052-1068.
AcknowledgementThe conference participation was partly subsidised by the Talented Student Program of Eötvös Loránd University, Budapest.
Conclusion (D)The relative hazard map (Map 1) we created:ź marks the areas similar to the study area by elevation, slope, aspect and surface
geology as hazardous (Figure 4). ź can help the reambulation of the existing landslide inventory database.ź can serve as a base for more complex landslide vulnerability studies.
The field survey (Map 2) showed:ź slope movement processes are still active in the area.ź it’s important to have an up-to-date landslide inventory.
Results – the Landslide Hazard Map (C)
Landslide susceptibility estimations in the Gerecse Hills (Hungary)1 2Dávid Gerzsenyi and Gáspár Albert
1Eötvös Loránd University, Cartography Msc, Budapest, Hungary ([email protected])2 Eötvös Loránd University, Department of Cartography and Geoinformatics, Budapest, Hungary ([email protected])
HU RO
MD
UA
PL
SK
SL HR
AT
CZ
DE
IT
BGRSBA
GERECSEEGU
Figure 0: Location of study area
