Carating, R.:
PHILIPPINES: Final Report on the Harmonized World Soil Database Project, DigitalSoilMap.Net Project, funded by the Institute of Soil Science Chinese Academy of Science, Nanjing, China,
https://www.academia.edu/20867911/PHILIPPINES_Final_Report_on_the_Harmonized_World_Soil_Database_Project_DigitalSoilMap_Net_Project?auto=download (last access: 14 March 2023), 2013.
DENR-MGB:
Geological Map of Tumauini Quadrangle (1 : 10 000), Sheet 3371 I, Department of Environment and Natural Resources-Mines and Geosciences Bureau, Quezon City, Philippines, 1991a.
DENR-MGB:
Geological Map of Ilagan Quadrangle (1 : 10 000), Sheet 3371 II, Department of Environment and Natural Resources-Mines and Geosciences Bureau, Quezon City, Philippines, 1991b.
DENR-MGB:
Geological Map of Baguio City Quadrangle (1 V 50000), Sheet 3169 III, Department of Environment and Natural Resources-Mines and Geosciences Bureau, Quezon City, Philippines, 1995.
DENR-MGB:
Geological Map of Sison Quadrangle, Sheet 3168 IV, Department of Environment and Natural Resources-Mines and Geosciences Bureau, Quezon City, Philippines, 2000.
Emberson, R., Kirschbaum, D. B., Amatya, P., Tanyas, H., and Marc, O.:
Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories, Nat. Hazards Earth Syst. Sci., 22, 1129–1149, https://doi.org/10.5194/nhess-22-1129-2022, 2022.
Friedman, J., Hastie, T., and Tibshirani, R.:
Regularization paths for generalized linear models via coordinate descent, J. Stat. Softw., 33, 1–22, https://doi.org/10.18637/jss.v033.i01, 2010.
Friedman, J., Hastie, T., Tibshirani, R., Narasimhan, B., Tay, K., Simon, N., Qian, J., and Yang, J.: glmnet: Lasso and Elastic-Net Regularized Generalized Linear Models, CRAN [code],
https://cran.r-project.org/web/packages/glmnet/ (last access: 12 March 2023), 2022.
Froude, M. J. and Petley, D. N.:
Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2161–2181, https://doi.org/10.5194/nhess-18-2161-2018, 2018.
geoportal PH: geoportal PH Soil Type Layer, Geoportal Philippines [data set],
https://www.geoportal.gov.ph/, last access: 12 March 2023.
Gorokhovich, Y. and Vustianiuk, A.:
Implications of slope aspect for landslide risk assessment: A case study of Hurricane Maria in Puerto Rico in 2017, Geomorphology, 391, 107874, https://doi.org/10.1016/J.GEOMORPH.2021.107874, 2021.
Gorsevski, P. V., Gessler, P. E., Boll, J., Elliot, W. J., and Foltz, R. B.:
Spatially and temporally distributed modeling of landslide susceptibility, Geomorphology, 80, 178–198, https://doi.org/10.1016/j.geomorph.2006.02.011, 2006.
IFRC: DREF Final Report, Philippines: Typhoon Kammuri, International Federation of Red Cross and Red Crescent Societies,
https://reliefweb.int/report/philippines/philippines-typhoon-kammuri-dref-final-report-mdrph037 (last access: 14 March 2023), 2020.
Javier, D. N. and Kumar, L.: FREQUENCY RATIO LANDSLIDE SUSCEPTIBILITY ESTIMATION IN A TROPICAL MOUNTAIN REGION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W8, 173–179, https://doi.org/10.5194/isprs-archives-XLII-3-W8-173-2019, 2019.
Jiang, S., Liu, S., Ren, L., Yong, B., Zhang, L., Wang, M, Lu, Y., and He, Y.:
Hydrologic Evaluation of Six High Resolution Satellite Precipitation Products in Capturing Extreme Precipitation and Streamflow over a Medium-Sized Basin in China, Water, 10, 25, https://doi.org/10.3390/W10010025, 2017.
Jones, J. N., Boulton, S. J., Bennett, G. L., Stokes, M., and Whitworth, M. R. Z.:
Temporal Variations in Landslide Distributions Following Extreme Events: Implications for Landslide Susceptibility Modeling, J. Geophys. Res.-Earth, 126, e2021JF006067, https://doi.org/10.1029/2021JF006067, 2021a.
Jones, J. N., Boulton, S. J., Bennett, G. L., Stokes, M., and Whitworth, M. R. Z.:
30-year record of Himalaya mass-wasting reveals landscape perturbations by extreme events, Nat. Commun., 12, 6701, https://doi.org/10.1038/s41467-021-26964-8, 2021b.
Kim, K. G., Emmanuel Q. Angeles, J., Lim, P. K. I., Buluran, J. S., and Tan, F. J.: Slope Stability Analysis as Applied to Rainfall-triggered Landslide in Itogon, Benguet Province, Philippines, 2021 IEEE Conference on Technologies for Sustainability, SusTech 2021, 22–24 April 2021, Irvine, CA, USA, IEEE, Institute of Electrical and Electronics Engineers, https://doi.org/10.1109/SUSTECH51236.2021.9467461, 2021.
Kirschbaum, D., Stanley, T., and Zhou, Y.:
Spatial and temporal analysis of a global landslide catalog, Geomorphology, 249, 4–15, https://doi.org/10.1016/J.GEOMORPH.2015.03.016, 2015.
Lagmay, A. M. F. and Eco, R. N.:
Shallow Landslide Hazard Mapping for Davao Oriental, Philippines Using a Deterministic GIS Model, in: Communicating Climate Change a
nd Natural Hazard Risk and Cultivating Resilience: Case Studies for a Multidisciplinary Approach, edited by: Kontar, Y. Y., Springer, Cham, ISBN 978-3-319-20160-3, https://doi.org/10.1007/978-3-319-20161-0_9, 2016.
LeComte, D.:
International Weather Events 2019: Historic Heat, Hurricanes, and Fires, Weatherwise, 73, 24–31, https://doi.org/10.1080/00431672.2020.1736467, 2020.
Lin, L., Lin, Q., and Wang, Y.:
Landslide susceptibility mapping on a global scale using the method of logistic regression, Nat. Hazards Earth Syst. Sci., 17, 1411–1424, https://doi.org/10.5194/nhess-17-1411-2017, 2017.
Liou, Y. A. and Pandey, R. S.:
Interactions between typhoons Parma and Melor (2009) in North West Pacific Ocean, Weather and Climate Extremes, 29, 100272, https://doi.org/10.1016/J.WACE.2020.100272, 2020.
Lombardo, L. and Mai, P. M.:
Presenting logistic regression-based landslide susceptibility results, Eng. Geol., 244, 14–24, https://doi.org/10.1016/j.enggeo.2018.07.019, 2018.
Lombardo, L., Opitz, T., Ardizzone, F., Guzzetti, F., and Huser, R.:
Space-time landslide predictive modelling, Earth-Sci. Rev., 209, 103318, https://doi.org/10.1016/j.earscirev.2020.103318, 2020.
Luzon, P. K., Montalbo, K., Galang, J., Sabado, J. M., Escape, C. M., Felix, R., and Lagmay, A. M. F.:
Hazard mapping related to structurally controlled landslides in Southern Leyte, Philippines, Nat. Hazards Earth Syst. Sci., 16, 875–883, https://doi.org/10.5194/nhess-16-875-2016, 2016.
Marc, O. and Hovius, N.:
Amalgamation in landslide maps: effects and automatic detection, Nat. Hazards Earth Syst. Sci., 15, 723–733, https://doi.org/10.5194/nhess-15-723-2015, 2015.
Marjanović, M.:
Comparing the performance of different landslide susceptibility models in ROC space, in: Landslide Science and Practice: Landslide Inventory and Susceptibility and Hazard Zoning, edited by: Margottini, C., Canuti, P., and Sassa, K., Springer Science and Business Media Deutschland GmbH, 579–584, https://doi.org/10.1007/978-3-642-31325-7_76, 2013.
Meusburger, K. and Alewell, C.:
On the influence of temporal change on the validity of landslide susceptibility maps, Nat. Hazards Earth Syst. Sci., 9, 1495–1507, https://doi.org/10.5194/nhess-9-1495-2009, 2009.
NDCC:
Final Report on Tropical Storm Ondoy (Ketsana) and Typhoon Pepeng (Parma), National Disaster Coordinating Council, The Government of the Philippines, https://reliefweb.int/report/philippines/philippines-ndcc-update-final-report-tropical-storm-ondoy-and-typhoon-pepeng (last access: 14 March 2023), 2009.
NDRRMC: Situational Report No. 19 Regarding Response Actions and Effects of Typhoon “Tisoy” (i.n. Kammuri), National Disaster Coordinating Council, The Government of the Philippines, https://reliefweb.int/report/philippines/ndrrmc-update-situational-report-no-19-regarding-response-actions-and-effects (last access: 14 March 2023), 2019.
Niu, Y., Fang, J., Chen, R., Xia, Z., and Xu, H.:
Network Modeling and Dynamic Mechanisms of Multi-Hazards – A Case Study of Typhoon Mangkhut, Water, 12, 2198, https://doi.org/10.3390/W12082198, 2020.
Nolasco-Javier, D. and Kumar, L.:
Landslide Susceptibility Assessment Using Binary Logistic Regression in Northern Philippines, in: Understanding and Reducing Landslide Disaster Risk, edited by: Guzzetti, F., Mihalić Arbanas, S., Reichenbach, P., Sassa, K., Bobrowsky, P. T., and Takara, K., WLF 2020, ICL Contribution to Landslide Disaster Risk Reduction, Springer, Cham, ISBN 978-3-030-60226-0, https://doi.org/10.1007/978-3-030-60227-7_20, 2021.
Nolasco-Javier, D., Kumar, L., and Tengonciang, A. M. P.:
Rapid appraisal of rainfall threshold and selected landslides in Baguio, Philippines, Nat. Hazards, 78, 1587–1607, https://doi.org/10.1007/s11069-015-1790-y, 2015.
Oh, H. J. and Lee, S.:
Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system, Environ. Earth Sci., 62, 935–951, https://doi.org/10.1007/s12665-010-0579-2, 2011.
Ozturk, U., Saito, H., Matsushi, Y., Crisologo, I., and Schwanghart, W.:
Can global rainfall estimates (satellite and reanalysis) aid landslide hindcasting?, Landslides, 18, 3119–3133, https://doi.org/10.1007/s10346-021-01689-3, 2021a.
Ozturk, U., Pittore, M., Behling, R., Roessner, S., Andreani, L., and Korup, O.: How robust are landslide susceptibility estimates?, Landslides, 18, 681–695, https://doi.org/10.1007/s10346-020-01485-5, 2021b.
PAGASA:
DOST-PAGASA Annual Report on Philippine Tropical Cyclones, Philippine Atmospheric, Geophysical and Astronomical Services Administration,
https://pubfiles.pagasa.dost.gov.ph/pagasaweb/files/tamss/weather/tcsummary/ARTC2018.pdf (last access: 12 March 2023), 2018.
PAGASA:
Annual Report on Philippine Tropical Cyclones, Philippine Atmospheric, Geophysical and Astronomical Services Administration,
https://pubfiles.pagasa.dost.gov.ph/pagasaweb/files/tamss/weather/tcsummary/ARTC2019_web.pdf (last access: 12 March 2023), 2019.
PAGASA:
Climate Change in the Philippines, Philippine Atmospheric, Geophysical and Astronomical Services Administration,
https://www.pagasa.dost.gov.ph/information/climate-change-in-the-philippines (last access: 12 March 2023), 2022.
Palau, R. M., Hürlimann, M., Berenguer, M., and Sempere-Torres, D.:
Influence of the mapping unit for regional landslide early warning systems: comparison between pixels and polygons in Catalonia (NE Spain), Landslides, 17, 2067–2083, https://doi.org/10.1007/s10346-020-01425-3, 2020.
Pourghasemi, H. R., Teimoori Yansari, Z., Panagos, P., and Pradhan, B.:
Analysis and evaluation of landslide susceptibility: a review on articles published during 2005–2016 (periods of 2005–2012 and 2013–2016), Arab. J. Geosci., 11, 1–12, https://doi.org/10.1007/s12517-018-3531-5, 2018.
Rabonza, M. L., Felix, R. P., Lagmay, A. M. F., Eco, R. N., Ortiz, I. J., ang Aquino, D. K.:
Shallow landslide susceptibility mapping using high-resolution topography for areas devastated by super typhoon Haiyan, Landslides, 13, 201–210, 2015.
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., and Guzzetti, F.:
A review of statistically-based landslide susceptibility models, Earth-Sci. Rev., 180, 60–91, https://doi.org/10.1016/j.earscirev.2018.03.001, 2018.
Samia, J., Temme, A., Bregt, A., Wallinga, J., Guzzetti, F., and Ardizzone, F.:
Dynamic path-dependent landslide susceptibility modelling, Nat. Hazards Earth Syst. Sci., 20, 271–285, https://doi.org/10.5194/nhess-20-271-2020, 2020.
Sassa, K.:
Foreword by Flavia Schlegel for the Journal of the International Consortium on Landslides, Landslides, 16, 1–1, https://doi.org/10.1007/S10346-018-1120-Z, 2018.
Schwanghart, W. and Scherler, D.:
Short Communication: TopoToolbox 2 – MATLAB-based software for topographic analysis and modeling in Earth surface sciences, Earth Surf. Dynam., 2, 1–7, https://doi.org/10.5194/esurf-2-1-2014, 2014.
Sevieri, G. and Galasso, C.:
Typhoon fragility analysis and climate change impact assessment of Filipino cultural heritage asset roofs, in: XI International Conference on Structural Dynamics, 23–26 November 2020, Athens, Greece, edited by: Papadrakakis, M., Fragiadakis, M., and Papadimitriou, C., 4763–4776, 2020.
Shimokawa, S., Iizuka, S., Kayahara, T., Suzuki, S., and Murakami, T.:
Fujiwhara effect; the interaction between T0917 and T0918, Natural Disaster Research Report of the National Research Institute for Earth Science and Disaster Prevention, No. 45, 23–26, 2011.
Steger, S., Brenning, A., Bell, R., and Glade, T.:
The propagation of inventory-based positional errors into statistical landslide susceptibility models, Nat. Hazards Earth Syst. Sci., 16, 2729–2745, https://doi.org/10.5194/nhess-16-2729-2016, 2016.
Steger, S., Brenning, A., Bell, R., and Glade, T.:
The influence of systematically incomplete shallow landslide inventories on statistical susceptibility models and suggestions for improvements, Landslides, 14, 1767–1781, https://doi.org/10.1007/s10346-017-0820-0, 2017.
Steger, S., Mair, V., Kofler, C., Pittore, M., Zebisch, M., and Schneiderbauer, S.:
Correlation does not imply geomorphic causation in data-driven landslide susceptibility modelling – Benefits of exploring landslide data collection effects, Sci. Total Environ., 776, 145935, https://doi.org/10.1016/j.scitotenv.2021.145935, 2021.
Temme, A., Guzzetti, F., Samia, J., and Mirus, B. B.:
The future of landslides' past – A framework for assessing consecutive landsliding systems, Landslides, 17, 1519–1528. https://doi.org/10.1007/s10346-020-01405-7, 2020.
Vakhshoori, V. and Zare, M.:
Is the ROC curve a reliable tool to compare the validity of landslide susceptibility maps?, Geomatics, Natural Hazards and Risk, 9, 249–266, https://doi.org/10.1080/19475705.2018.1424043, 2018.
Yumul, G. P., Dimalanta, C. B., Servando, N. T., and Cruz, N. A.:
Abnormal weather events in 2009, increased precipitation and disastrous impacts in the Philippines, Climatic Change, 118, 715–727, https://doi.org/10.1007/s10584-012-0661-8, 2013.
Zhu, Q., Xuan, W., Liu, L., and Xu, Y. P.:
Evaluation and hydrological application of precipitation estimates derived from PERSIANN-CDR, TRMM 3B42V7, and NCEP-CFSR over humid regions in China, Hydrol. Process., 30, 3061–3083, https://doi.org/10.1002/hyp.10846, 2016.
Zuur, A. F., Ieno, E. N., and Elphick, C. S.:
A protocol for data exploration to avoid common statistical problems, Methods Ecol. Evol., 1, 3–14, https://doi.org/10.1111/j.2041-210x.2009.00001.x, 2010.
