7 Comparative GIS-Based Assessment …
135
Fayez L, Pazhman D, Pham BT, Dholakia MB, Solanki HA, Khalid M, Prakash I (2018) Application
of frequency ratio model for the development of landslide susceptibility mapping at part of
Uttarakhand state, India. Int J Appl Eng Res 13(9):6846–6854
Fielding AH, Bell JF (1997) A review of methods for the assessment of prediction errors in
conservation presence/absence models. Environ Conserv. 24(01):38–49
Gasim MB, Toriman ME, Juahir H (2015) Phenomenon of slope failure occurrences along Gerik-Jeli
highway. Science Alert, Malaysia
Ghimire M (2011) Landslide occurrence and its relation with terrain factors in the Siwalik Hills,
Nepal: case study of susceptibility assessment in three basins. Nat Hazards 299–320
Guzzetti F (2012) Landslide inventory maps: new tools for an old problem. Earth Sci Rev 42–66
Hosmer DW, Lemeshow S (2000) Special topics. Applied logistic regression, 2nd edn., pp 260–351
https://www.fao.org/asiapacific/forestry-publication. Accessed 25 Sep 2018
IRIN (2013) No early warning for Nepali’s deadly landslides. http://www.irinnews.org/report/
98381/no-early-warning-nepal%E2%80%99s-deadly-landslides
Kalantar B, Pradhan B, Naghibi SA, Motevalli A, Mansor S (2018) Assessment of the effects of
training data selection on the landslide susceptibility mapping: a comparison between support
vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN). Geomatics,
Nat Hazards Risk 9(1):49–69
Lee S, Pradhan B (2007) Landslide hazard mapping at Selangor, Malaysia using frequency ratio
and logistic regression models. Landslides 4(1):33–41
Lee S, Ryu JH, Won JS, Park HJ (2004) Determination and application of the weights for landslide
susceptibility mapping: using an artificial neural network. Eng Geol 71:289–302
Lim KW, Tay LT, Lateh H (2011) Landslide hazard mapping of Penang island using probabilistic
methods and logistic regression. In: Proceedings of the IEEE international conference on imaging
systems and techniques. Penang, Malaysia, pp 273–278, 17–18 May 2011
Meten M, Prakashbhandary N, Yatabe R (2015) Effect of landslide factor combinations on the
prediction accuracy of landslide susceptibility maps in the Blue Nile Gorge of Central Ethiopia.
Geoenviron Disasters 2:9. https://doi.org/10.1186/s40677-0150016-7
MoFE (2010) National Adaptation Programme of Action (NAPA). Government of Nepal, Ministry
of Forest and Environment (previously MoPE). Kathmandu, Nepal
MoHA (2019) Nepal Disaster Report. Ministry of Home Affairs. Government of Nepal
MoHA, DPNet-Nepal (2015) Nepal Disaster Report. Ministry of Home Affairs, Government of
Nepal and Disaster Preparedness Network-Nepal
Mondal S, Mandal S (2018) RS & GIS-based landslide susceptibility mapping of the Balason River
basin, Darjeeling Himalaya, using logistic regression (LR) model. Georisk: Assess Manage Risk
Eng Syst Geohazards 12(1):29–44
Mousavi SZ, Kavian A, Soleimani K, Mousavi SR, Shirzadi A (2011) GIS-based spatial prediction of
landslide susceptibility using logistic regression model. Geomatics, Nat Hazards Risk 2(1):33–50
Ocakoglu F, Gokceoglu C, Ercanoglu M (2002) Dynamics of a complex mass movement triggered
by heavy rainfall: a case study from NW Turkey. Geomorphology 42(3):329–341
Ohlmacher C (2006) The relationship between geology and landslide hazards of Atchison, Kansas,
and vicinity. Kansas Geol Surv
Ojha TK (2009) Magnetostratigraphy, topography and geology of Nepal Himalaya: a GIS and
Paleomagnetic Approach. Ph.D. dissertation. University of Arizona
Paudel U (2016) Landslide susceptibility assessment using machine learning with emphasis
on scaling and topographic representation issues. Ph.D. dissertation. Department of Natural
Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo
(unpublished)
Pokhrel N (2003) Study of areal precipitation distribution pattern in the Chepe catchment, Nepal.
Butwal Power Company Ltd, Kumaripati Lalitpur, GPO 11728. Kathmandu, Nepal, pp 1–7
Pontius RJ, Schneider LC (2001) Land-cover change model validation by an ROC method for the
Ipswich watershed, Massachusetts, USA. Agr Ecosyst Environ 85:239–248
135
Fayez L, Pazhman D, Pham BT, Dholakia MB, Solanki HA, Khalid M, Prakash I (2018) Application
of frequency ratio model for the development of landslide susceptibility mapping at part of
Uttarakhand state, India. Int J Appl Eng Res 13(9):6846–6854
Fielding AH, Bell JF (1997) A review of methods for the assessment of prediction errors in
conservation presence/absence models. Environ Conserv. 24(01):38–49
Gasim MB, Toriman ME, Juahir H (2015) Phenomenon of slope failure occurrences along Gerik-Jeli
highway. Science Alert, Malaysia
Ghimire M (2011) Landslide occurrence and its relation with terrain factors in the Siwalik Hills,
Nepal: case study of susceptibility assessment in three basins. Nat Hazards 299–320
Guzzetti F (2012) Landslide inventory maps: new tools for an old problem. Earth Sci Rev 42–66
Hosmer DW, Lemeshow S (2000) Special topics. Applied logistic regression, 2nd edn., pp 260–351
https://www.fao.org/asiapacific/forestry-publication. Accessed 25 Sep 2018
IRIN (2013) No early warning for Nepali’s deadly landslides. http://www.irinnews.org/report/
98381/no-early-warning-nepal%E2%80%99s-deadly-landslides
Kalantar B, Pradhan B, Naghibi SA, Motevalli A, Mansor S (2018) Assessment of the effects of
training data selection on the landslide susceptibility mapping: a comparison between support
vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN). Geomatics,
Nat Hazards Risk 9(1):49–69
Lee S, Pradhan B (2007) Landslide hazard mapping at Selangor, Malaysia using frequency ratio
and logistic regression models. Landslides 4(1):33–41
Lee S, Ryu JH, Won JS, Park HJ (2004) Determination and application of the weights for landslide
susceptibility mapping: using an artificial neural network. Eng Geol 71:289–302
Lim KW, Tay LT, Lateh H (2011) Landslide hazard mapping of Penang island using probabilistic
methods and logistic regression. In: Proceedings of the IEEE international conference on imaging
systems and techniques. Penang, Malaysia, pp 273–278, 17–18 May 2011
Meten M, Prakashbhandary N, Yatabe R (2015) Effect of landslide factor combinations on the
prediction accuracy of landslide susceptibility maps in the Blue Nile Gorge of Central Ethiopia.
Geoenviron Disasters 2:9. https://doi.org/10.1186/s40677-0150016-7
MoFE (2010) National Adaptation Programme of Action (NAPA). Government of Nepal, Ministry
of Forest and Environment (previously MoPE). Kathmandu, Nepal
MoHA (2019) Nepal Disaster Report. Ministry of Home Affairs. Government of Nepal
MoHA, DPNet-Nepal (2015) Nepal Disaster Report. Ministry of Home Affairs, Government of
Nepal and Disaster Preparedness Network-Nepal
Mondal S, Mandal S (2018) RS & GIS-based landslide susceptibility mapping of the Balason River
basin, Darjeeling Himalaya, using logistic regression (LR) model. Georisk: Assess Manage Risk
Eng Syst Geohazards 12(1):29–44
Mousavi SZ, Kavian A, Soleimani K, Mousavi SR, Shirzadi A (2011) GIS-based spatial prediction of
landslide susceptibility using logistic regression model. Geomatics, Nat Hazards Risk 2(1):33–50
Ocakoglu F, Gokceoglu C, Ercanoglu M (2002) Dynamics of a complex mass movement triggered
by heavy rainfall: a case study from NW Turkey. Geomorphology 42(3):329–341
Ohlmacher C (2006) The relationship between geology and landslide hazards of Atchison, Kansas,
and vicinity. Kansas Geol Surv
Ojha TK (2009) Magnetostratigraphy, topography and geology of Nepal Himalaya: a GIS and
Paleomagnetic Approach. Ph.D. dissertation. University of Arizona
Paudel U (2016) Landslide susceptibility assessment using machine learning with emphasis
on scaling and topographic representation issues. Ph.D. dissertation. Department of Natural
Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo
(unpublished)
Pokhrel N (2003) Study of areal precipitation distribution pattern in the Chepe catchment, Nepal.
Butwal Power Company Ltd, Kumaripati Lalitpur, GPO 11728. Kathmandu, Nepal, pp 1–7
Pontius RJ, Schneider LC (2001) Land-cover change model validation by an ROC method for the
Ipswich watershed, Massachusetts, USA. Agr Ecosyst Environ 85:239–248