Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north‐eastern Sicily, Italy)

This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north‐eastern sector of Sicily (southern Italy), as test site. On 1 October 2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence‐only‐based statistical method was applied to obtain susceptibility models capable of distinguishing future activation sites of debris flow and debris slide, which where the main source of failure mechanisms for flow or avalanche type propagation. The set of predictors used in this experiment comprised primary and secondary topographic attributes, derived by processing a high resolution digital elevation model, CORINE land cover data and a set of vegetation and mineral indices obtained by processing multispectral ASTER images. All the selected data sources are dated before the disaster. A spatially random partition technique was adopted for validation, generating 50 replicates for each of the two considered movement typologies in order to assess accuracy, precision and reliability of the models. The debris slide and debris flow susceptibility models produced high performances with the first type being the best fit. The evaluation of the probability estimates around the mean value for each mapped pixel shows an inverted relation, with the most robust models corresponding to the debris flows. With respect to the role of each predictor within the modelling phase, debris flows appeared to be primarily controlled by topographic attributes whilst the debris slides were better explained by remotely sensed derived indices, particularly by the occurrence of previous wildfires across the slope. The overall excellent performances of the two models suggest promising perspectives for the application of presence‐only methods and remote sensing derived predictors. Copyright © 2016 John Wiley & Sons, Ltd.

[1]  E. Jaynes.  Information Theory and Statistical Mechanics , 1957 .

[2]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .

[3]  W. H. Wischmeier,et al.  Predicting rainfall erosion losses : a guide to conservation planning , 1978 .

[4]  K. Beven,et al.  A physically based, variable contributing area model of basin hydrology , 1979 .

[5]  R. Heerdegen,et al.  Quantifying source areas through land surface curvature and shape , 1982 .

[6]  C. Thorne,et al.  Quantitative analysis of land surface topography , 1987 .

[7]  David W. Hosmer,et al.  Applied Logistic Regression , 1991 .

[8]  Henry A. Froehlich,et al.  Infiltration, water repellency, and soil moisture content after broadcast burning a forest site in southwest Oregon , 1989 .

[9]  I. Moore,et al.  Digital terrain modelling: A review of hydrological, geomorphological, and biological applications , 1991 .

[10]  C. J. van Westen,et al.  GISSIZ : training package for Geographic Information Systems in slope instability zonation : Part 1. theory Part 2. exercises , 1993 .

[11]  Hiroyuki Fujisada,et al.  Design and performance of ASTER instrument , 1995, Remote Sensing.

[12]  P. Reichenbach,et al.  Gis Technology in Mapping Landslide Hazard , 1995 .

[13]  A. Roli.  Artificial Neural Networks , 2012, Lecture Notes in Computer Science.

[14]  Gerard Govers,et al.  A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units , 1996 .

[15]  A. Kleber.  Cover-beds as soil parent materials in midlatitude regions , 1997 .

[16]  M. Terlien,et al.  Prediction of the occurrence of slope instability phenomenal through GIS-based hazard zonation , 1997 .

[17]  G. R. Foster,et al.  Predicting soil erosion by water : a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE) , 1997 .

[18]  P. G. Luckman,et al.  Landslide erosion risk to New Zealand pastoral steeplands productivity , 1999 .

[19]  P. Reichenbach,et al.  Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy , 1999 .

[20]  Leonard F. DeBano,et al.  The role of fire and soil heating on water repellency in wildland environments: a review , 2000 .

[21]  P. Robichaud,et al.  Water repellency by laboratory burning of four northern Rocky Mountain forest soils , 2000 .

[22]  J. N. Hutchinson,et al.  A review of the classification of landslides of the flow type , 2001 .

[23]  J. Huntington,et al.  Geologic and alteration mapping at Mt Fitton, South Australia, using ASTER satellite-borne data , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[24]  Thomas H Meyer,et al.  Terrain Analysis: Principles and Applications , 2001 .

[25]  Infrared Spaceborne Remote Sensing X , 2002 .

[26]  Akira Iwasaki,et al.  Enhancement of spectral separation performance for ASTER/SWIR , 2002, SPIE Optics + Photonics.

[27]  A. Peterson,et al.  Niche Modeling Perspective on Geographic Range Predictions in the Marine Environment Using a Machine-learning Algorithm , 2003 .

[28]  A. Peterson,et al.  Niche Modeling and Geographic Range Predictions in the Marine Environment Using a Machine-learning Algorithm , 2003 .

[29]  Yoshiki Ninomiya,et al.  A stabilized vegetation index and several mineralogic indices defined for ASTER VNIR and SWIR data , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[30]  S. Catalano,et al.  Late Quaternary uplift of northeastern Sicily: relation with the active normal faulting deformation , 2003 .

[31]  L. Rowan,et al.  Lithologic mapping in the Mountain Pass, California area using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data , 2003 .

[32]  C. Monaco,et al.  Long-term behaviour of the late Quaternary normal faults in the Straits of Messina area (Calabrian arc): structural and morphological constraints , 2003 .

[33]  Simon J. Hook,et al.  Mapping Hydrothermally Altered Rocks at Cuprite, Nevada, Using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), a New Satellite-Imaging System , 2003 .

[34]  Yasushi Yamaguchi,et al.  Spectral indices for lithologic discrimination and mapping by using the ASTER SWIR bands , 2003 .

[35]  V. Perrone,et al.  Oligocene-to-Early Miocene depositional and structural evolution of the Calabria-Peloritani Arc southern terrane (Italy) and geodynamic correlations with the Spain Betics and Morocco Rif , 2003 .

[36]  L. Debano.  The role of fire and soil heating on water repellency , 2003 .

[37]  Peloritani continental crust composition (southern Italy); geological and petrochemical evidence , 2004 .

[38]  S. Weiss,et al.  GLM versus CCA spatial modeling of plant species distribution , 1999, Plant Ecology.

[39]  Peter R. Robichaud,et al.  Field validation of Burned Area Reflectance Classification (BARC) products for post fire assessment , 2004 .

[40]  L. Macdonald,et al.  Post-fire Soil Water Repellency : Persistence and Soil Moisture Thresholds , 2004 .

[41]  L. Macdonald,et al.  Post-fire Soil Water Repellency , 2004 .

[42]  Miroslav Dudík,et al.  A maximum entropy approach to species distribution modeling , 2004, ICML.

[43]  T. Cudahy,et al.  Seamless geological map generation using ASTER in the Broken Hill-Curnamona province of Australia , 2005 .

[44]  L. Ermini,et al.  Artificial Neural Networks applied to landslide susceptibility assessment , 2005 .

[45]  Francesco M. Guadagno,et al.  Some aspects of the initiation of debris avalanches in the Campania Region: The role of morphological slope discontinuities and the development of failure , 2005 .

[46]  P. Reichenbach,et al.  Estimating the quality of landslide susceptibility models , 2006 .

[47]  Robert P. Anderson,et al.  Maximum entropy modeling of species geographic distributions , 2006 .

[48]  M. Araújo,et al.  Five (or so) challenges for species distribution modelling , 2006 .

[49]  G. Ohlmacher.  Plan curvature and landslide probability in regions dominated by earth flows and earth slides , 2007 .

[50]  O. Hungr.  Dynamics of Rapid Landslides , 2007 .

[51]  Y. Martin.  Wildfire disturbance and shallow landsliding in coastal British Columbia over millennial time scales: A numerical modelling study , 2007 .

[52]  Jr-Chuan Huang,et al.  Influence of Specific Contributing Area algorithms on slope failure prediction in landslide modeling , 2007 .

[53]  G. Rossi,et al.  Toward improved species niche modelling: Arnica montana in the Alps as a case study , 2008 .

[54]  Miroslav Dudík,et al.  Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation , 2008 .

[55]  J. E. Gartner,et al.  Storm rainfall conditions for floods and debris flows from recently burned areas in southwestern Colorado and southern California , 2008 .

[56]  L. Senelick.  It (review) , 2008 .

[57]  Robert E. Wolfe,et al.  Automated registration and orthorectification package for Landsat and Landsat-like data processing , 2009 .

[58]  S. Cannon,et al.  The Increasing Wildfire and Post-Fire Debris-Flow Threat in Western USA, and Implications for Consequences of Climate Change , 2009 .

[59]  J. Roering,et al.  Post-fire geomorphic response in steep, forested landscapes: Oregon Coast Range, USA , 2009 .

[60]  Lawrence C. Rowan,et al.  Spectral assessment of new ASTER SWIR surface reflectance data products for spectroscopic mapping of rocks and minerals , 2010 .

[61]  B. Pradhan,et al.  Weights-of-evidence model applied to landslide susceptibility mapping in a tropical hilly area , 2010 .

[62]  Giuseppe Tito Aronica,et al.  Flash floods and debris flow in the city area of Messina, north-east part of Sicily, Italy in October 2009: the case of the Giampilieri catchment , 2010 .

[63]  R. Dickinson,et al.  Modeling the mudslide aftermath of the 2007 Southern California Wildfires , 2011 .

[64]  M. Hashim,et al.  Using spectral mapping techniques on short wave infrared bands of ASTER remote sensing data for alteration mineral mapping in SE Iran , 2011 .

[65]  Christian Conoscenti,et al.  The role of the diagnostic areas in the assessment of landslide susceptibility models: a test in the sicilian chain , 2011 .

[66]  Trevor Hastie,et al.  A statistical explanation of MaxEnt for ecologists , 2011 .

[67]  M. Agate,et al.  Late Quaternary high uplift rates in northeastern Sicily: evidence from calcareous nannofossils and benthic and planktonic foraminifera , 2011, Facies.

[68]  V. L. Mulder,et al.  The use of remote sensing in soil and terrain mapping — A review , 2011 .

[69]  Fausto Guzzetti,et al.  Semi-automatic recognition and mapping of rainfall induced shallow landslides using optical satellite images , 2011 .

[70]  B. Schröder,et al.  A functional entity approach to predict soil erosion processes in a small Plio-Pleistocene Mediterranean catchment in Northern Chianti, Italy , 2011 .

[71]  Bogdan M. Strimbu,et al.  Modeling the travel distances of debris flows and debris slides: quantifying hillside morphology , 2011 .

[72]  Neil C. Mitchell,et al.  Distribution and causes of landslides in the eastern Peloritani of NE Sicily and western Aspromonte of SW Calabria, Italy , 2011 .

[73]  G. Gigli,et al.  Landslide inventory map for the Briga and the Giampilieri catchments, NE Sicily, Italy , 2012 .

[74]  Saro Lee,et al.  Extraction of landslide-related factors from ASTER imagery and its application to landslide susceptibility mapping , 2012 .

[75]  Boris Schröder,et al.  How can statistical models help to determine driving factors of landslides , 2012 .

[76]  Markus Möller,et al.  Plausibility test of conceptual soil maps using relief parameters , 2012 .

[77]  Filippo Catani,et al.  Detecting fingerprints of landslide drivers: A MaxEnt model , 2013 .

[78]  H. Pourghasemi,et al.  Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances , 2013, Natural Hazards.

[79]  C. Irigaray,et al.  Forward logistic regression for earth-flow landslide susceptibility assessment in the Platani river basin (southern Sicily, Italy) , 2014, Landslides.

[80]  T. Hastie,et al.  Finite-Sample Equivalence in Statistical Models for Presence-Only Data. , 2012, The annals of applied statistics.

[81]  Matthew J. Smith,et al.  Protected areas network is not adequate to protect a critically endangered East Africa Chelonian: Modelling distribution of pancake tortoise, Malacochersus tornieri under current and future climates , 2013, bioRxiv.

[82]  Qiang Xu,et al.  Pre-conditioning factors and susceptibility assessments of Wenchuan earthquake landslide at the Zhouqu segment of Bailongjiang basin, China , 2013, Journal of the Geological Society of India.

[83]  S. Leroueil,et al.  The Varnes classification of landslide types, an update , 2014, Landslides.

[84]  Stefania Matteoli,et al.  The PRISMA hyperspectral mission: Science activities and opportunities for agriculture and land monitoring , 2013, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS.

[85]  Jerry D. Davis,et al.  Physical and maximum entropy models applied to inventories of hillslope sediment sources , 2013, Journal of Soils and Sediments.

[86]  Salvatore Scudero,et al.  Landslide susceptibility assessment in the Peloritani Mts. (Sicily, Italy) and clues for tectonic control of relief processes , 2013 .

[87]  A. J. Miller.  ASSESSING LANDSLIDE SUSCEPTIBILITY BY INCORPORATING THE SURFACE COVER INDEX AS A MEASUREMENT OF VEGETATIVE COVER , 2013 .

[88]  Martin Mergili,et al.  Regional-scale analysis of high-mountain multi-hazard and risk indicators in the Pamir (Tajikistan) with GRASS GIS , 2013 .

[89]  S. Vitale,et al.  Tectono-stratigraphic and kinematic evolution of the southern Apennines/Calabria–Peloritani Terrane system (Italy) , 2013 .

[90]  Jean-Philippe Malet,et al.  Climate-physiographically differentiated Pan-European landslide susceptibility assessment using spatial multi-criteria evaluation and transnational landslide information , 2014 .

[91]  B. Pradhan,et al.  Landslide susceptibility mapping at Al-Hasher area, Jizan (Saudi Arabia) using GIS-based frequency ratio and index of entropy models , 2015, Geosciences Journal.

[92]  Jane Elith,et al.  Maxent is not a presence–absence method: a comment on Thibaud et al. , 2014 .

[93]  Wenzhong Shi,et al.  Semi-automatic approach for identifying locations of shallow debris slides/flows based on lidar-derived morphological features , 2014 .

[94]  Marco Borga,et al.  The influence of grid resolution on the prediction of natural and road-related shallow landslides , 2014 .

[95]  Antonino Cancelliere,et al.  Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach , 2014 .

[96]  R. Heinse,et al.  Root Decay and Fire Affect Soil Pipe Formation and Morphology in Forested Hillslopes with Restrictive Horizons , 2014 .

[97]  Spatial probabilistic approach on landslide susceptibility assessment from high resolution sensors derived parameters , 2014 .

[98]  P. Reichenbach,et al.  The Influence of Land Use Change on Landslide Susceptibility Zonation: The Briga Catchment Test Site (Messina, Italy) , 2013, Environmental Management.

[99]  Kang-Tsung Chang,et al.  Combining spectral and geoenvironmental information for probabilistic event landslide mapping , 2014 .

[100]  Birgit Kleinschmit,et al.  Automated Spatiotemporal Landslide Mapping over Large Areas Using RapidEye Time Series Data , 2014, Remote. Sens..

[101]  Ronald Chase,et al.  A Remote Sensing-Based Approach for Debris-Flow Susceptibility Assessment Using Artificial Neural Networks and Logistic Regression Modeling , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[102]  N. Park.  Using maximum entropy modeling for landslide susceptibility mapping with multiple geoenvironmental data sets , 2015, Environmental Earth Sciences.

[103]  E. Rotigliano,et al.  A test of transferability for landslides susceptibility models under extreme climatic events: application to the Messina 2009 disaster , 2014, Natural Hazards.

[104]  Nicola Casagli,et al.  Remote sensing as tool for development of landslide databases: The case of the Messina Province (Italy) geodatabase , 2015 .

[105]  Haluk Akgün,et al.  Evaluation and comparison of landslide susceptibility mapping methods: a case study for the Ulus district, Bartın, northern Turkey , 2015, Int. J. Geogr. Inf. Sci..

[106]  Patrick Hostert,et al.  The EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation , 2015, Remote. Sens..

[107]  Carlo Esposito,et al.  Evaluation of shallow landslide-triggering scenarios through a physically based approach: An example of application in the southern Messina area (northeastern Sicily, Italy) , 2015 .

[108]  T. Glade,et al.  Effectiveness of visually analyzing LiDAR DTM derivatives for earth and debris slide inventory mapping for statistical susceptibility modeling , 2016, Landslides.

[109]  Fausto Guzzetti,et al.  Calibration and validation of rainfall thresholds for shallow landslide forecasting in Sicily, southern Italy. , 2015 .

[110]  Michael Märker,et al.  Comparison of SVM and boosted regression trees for the delineation of lacustrine sediments using multispectral ASTER data and topographic indices in the lake Manyara Basin , 2015 .

[111]  E. Rotigliano,et al.  Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messina (Sicily, southern Italy) , 2015, Natural Hazards.

[112]  E. Rotigliano,et al.  Predicting storm-triggered debris flow events: application to the 2009 Ionian Peloritan disaster (Sicily, Italy) , 2015 .

[113]  Michael Märker,et al.  Multisensoral Topsoil Mapping in the Semiarid Lake Manyara Region, Northern Tanzania , 2015, Remote. Sens..

[114]  G. Fubelli,et al.  Presence-only approach to assess landslide triggering-thickness susceptibility: a test for the Mili catchment (north-eastern Sicily, Italy) , 2015, Natural Hazards.

[115]  L. Lombardo,et al.  Estimation of intrinsic aquifer vulnerability with index-overlay and statistical methods: the case of eastern Kopaida, central Greece , 2017, Applied Water Science.

[116]  E. Rotigliano,et al.  Exploring the effect of absence selection on landslide susceptibility models: A case study in Sicily, Italy , 2016 .

[117]  E. Rotigliano,et al.  Exploring relationships between grid cell size and accuracy for debris-flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy) , 2016, Environmental Earth Sciences.