landslide recognition and mapping in a mixed forest environment from airborne lidar data abstract a precise accurate and complete landslide inventory is indispensable for the establishment of reliable landslide susceptibility and hazard maps in the preparation of landslide inventories dense vegetation cover is the major obstacle that confounds the topographic signature of landslides today the growing usage of light detection and ranging lidar technology in the field of geoscience illuminates the mystery of the landscapes cloaked in dense vegetation by providing a new visual acuity to researchers turkey similar to many mid latitude mountainous countries suffering from landslides is still continuing landslide inventory mapping with conventional methods such as aerial photo interpretations api although 68 of landslide events occurred under dense forest cover in the north of the country despite the country wide medium scaled landslide catalogs the number and the abundance of landslides covered by forests remain largely unknown regardless of the increasing availability of high resolution remote sensing data from these motivating insights and drawbacks the study s focus is to evaluate the capability of mapping landslides by visually analyzing airborne lidar dtm derivatives and compare the results with the 1 25 000 scaled api based inventory to understand the potential contribution of lidar technology in europe s deadliest country turkey in terms of landslides the landslide mapping results for a test area located in the densely forested ulus basin western black sea region reveal that the extent and the number of the mapped landslides n 902 from the airborne lidar data are much higher than those of the available api based landslide inventory which includes 67 landslides comparative analysis on topographic signatures of landslides is also underpinned on a distinct discrepancy of slope failure diagnostic indicators captured by the two available dems derived from lidar and 1 25 000 scaled topographic maps emphasizing the success rate of lidar derived dem in recognition and mapping landslides with higher precision and accuracy together with all analysis results the landslide recognizability degree assessment based on the forest cover percentage and slope height differences of landslides highlights that the lidar data enable landslides to be defined up to 100 m2 while this value is 20 times lower than that of estimated values from api based landslides in addition to underlining the contribution of lidar technology to the recognition of landslides hidden under dense vegetation these findings stress the importance of lidar data on complete and accurate landslide inventories for production of reliable susceptibility and hazard maps and further a better understanding of the landslide processes and reducing related losses

bayesian framework for mapping and classifying shallow landslides exploiting remote sensing and topographic data abstract we propose a semi automatic approach to detect map and classify rainfall induced shallow landslides the approach combines the classification of a post event multispectral satellite image with information on the morphometric signature of landslides in a bayesian framework we apply the approach in two steps first we detect and map the rainfall induced landslides separating the stable ground from the failed areas next we classify internally the landslides separating the source from the run out areas we obtain the prior probability from the mahalanobis discriminant function used to classify the satellite image and the likelihood from the frequency distribution of terrain slope and cross section convexity in the pre existing shallow landslides we tested the approach in southern taiwan in a catchment where typhoon morakot caused abundant landslides in august 2009 using the semi automatic approach we obtained a detailed event landslide inventory map that we compared to an inventory obtained through the visual interpretation of post event ortho photographs taken a few days after the landslide triggering rainfall event quantitative comparison in a geographical information system revealed a degree of matching between the two event inventories exceeding 90 the approach is general and flexible and can be used with different satellite imagery and topographic data best suited in landscapes where shallow landslides leave distinct radiometric and topographic signatures the approach is expected to facilitate the production of event landslide inventory maps with positive consequences for geomorphological investigations landslide hazard and risk modeling and for post event recovery efforts

holocene history of deep seated landsliding in the north fork stillaguamish river valley from surface roughness analysis radiocarbon dating and numerical landscape evolution modeling documenting spatial and temporal patterns of past landsliding is a challenging step in quantifying the effect of landslides on landscape evolution while landslide inventories can map spatial distributions lack of dateable material landslide reactivations or time access and cost constraints generally limit dating large numbers of landslides to analyze temporal patterns here we quantify the record of the holocene history of deep seated landsliding along a 25 km stretch of the north fork stillaguamish river valley washington state usa including the 2014 oso landslide which killed 43 people we estimate the ages of more than 200 deep seated landslides in glacial sediment by defining an empirical relationship between landslide deposit age from radiocarbon dating and landslide deposit surface roughness we show that roughness systematically decreases with age as a function of topographic wavelength consistent with models of disturbance driven soil transport the age roughness model predicts a peak in landslide frequency 1 000 ybp with very few landslide deposits older than 7 000 ybp or younger than 100 ybp likely reflecting a combination of preservation bias and a complex history of changing climate base level and seismic shaking in the study area most recent landslides have occurred where channels actively interact with the toes of hillslopes composed of glacial sediments suggesting that lateral channel migration is a primary control on the location of large deep seated landslides in the valley

objective landslide detection and surface morphology mapping using high resolution airborne laser altimetry a map of extant slope failures is the most basic element of any landslide assessment without an accurate inventory of slope instability it is not possible to analyze the controls on the spatial and temporal patterns of mass movement or the environmental human or geomorphic consequences of slides landslide inventory maps are tedious to compile difficult to make in vegetated terrain using conventional techniques and tend to be subjective in addition most landslide inventories simply outline landslide boundaries and do not offer information about landslide mechanics as manifested by internal deformation features in an alternative approach we constructed accurate high resolution dems from airborne laser altimetry lidar data to characterize a large landslide complex and surrounding terrain near christchurch new zealand one dimensional circular 2 d and spherical 3 d statistics are used to map the local topographic roughness in the dems over a spatial scale of 1 5 to 10 m the bedrock landslide is rougher than adjacent unfailed terrain and any of the statistics can be employed to automatically detect and map the overall slide complex furthermore statistics that include a measure of the local variability of aspect successfully delineate four kinematic units within the gently sloping lower half of the slide features with a minimum size of surface folds that have a wavelength of about 11 to 12 m and amplitude of about 1 m are readily mapped two adjacent earthflows within the landslide complex are distinguished by a contrast in median roughness and texture and continuity of roughness elements the less active of the earthflows has a surface morphology that presumably has been smoothed by surface processes the laplacian operator also accurately maps the kinematic units and the folds and longitudinal levees within and at the margins of the units finally two dimensional power spectra analyses are used to quantify how roughness varies with length scale these results indicate that no dominant length scale of roughness exists for smooth unfailed terrain in contrast zones with different styles of landslide deformation exhibit distinctive spectral peaks that correspond to the scale of deformation features such as the compression folds the topographic based analyses described here may be used to objectively delineate landslide features generate mechanical inferences about landslide behavior and evaluate relatively the recent activity of slides published by elsevier science b v

automated object based classification of topography from srtm data we introduce an object based method to automatically classify topography from srtm data the new method relies on the concept of decomposing land surface complexity into more homogeneous domains an elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self adaptive data driven techniques for each domain scales in the data are detected with the help of local variance and segmentation is performed at these appropriate scales objects resulting from segmentation are partitioned into sub domains based on thresholds given by the mean values of elevation and standard deviation of elevation respectively results resemble reasonably patterns of existing global and regional classifications displaying a level of detail close to manually drawn maps statistical evaluation indicates that most of classes satisfy the regionalization requirements of maximizing internal homogeneity while minimizing external homogeneity most objects have boundaries matching natural discontinuities at regional level the method is simple and fully automated the input data consist of only one layer which does not need any pre processing both segmentation and classification rely on only two parameters elevation and standard deviation of elevation the methodology is implemented as a customized process for the ecognition software available as online download the results are embedded in a web application with functionalities of visualization and download

quantifying temporal changes in gully erosion areas with object oriented analysis abstract mapping gully systems and quantifying their changes over time are essential for implementing soil conservation measures the aim of this study is to analyze the changes in the gully systems in the context of land management image analysis of remotely sensed data in combination with field verification has proven to be a good and practical approach for mapping gully features over large areas given the variability in gully size shape and occurrence recent work has shown object based image analysis also termed as object oriented analysis ooa to be superior to pixel based methods for the identification and characterization of gullies this study presents an improved procedure to map gully features one that has been extended to assess and quantify erosion area dynamics in addition to the convention of using suitable topographic and spectral thresholds in the method the use of contrast and edge filter information and process knowledge of erosion by overland flow was incorporated in the rule set to help recognize potential gullies in ikonos 2 and geoeye 1 data changes in the area enclosed by the gully system boundary estimated for three different sub watersheds sw1 sw2 and sw3 observed over a period of eight years ranged from moderate 11 in sw2 and 21 in sw1 to a very high increase 91 in sw3 however the changes seen in gully system density were much higher than the changes in the area enclosed by the gully system boundary 81 104 and 109 in the respective sws the complex gully systems were better identified semi automatically than was possible by manual digitization in particular the finer edges of the gully systems which in turn led to better quantification of changes in the gully systems the study also determined that the rule set developed for gully feature extraction is more sensitive to the spatial resolution of the imagery used than the quality or resolution of the digital terrain model and its derivatives determining suitable segmentation parameters selecting appropriate object features for the classification the thresholds used retain the trial error aspects in this analysis this limits its application to a regional scale the rule set developed is generic and transferable to other region imagery with adaptation the rule set will be made available on our website www itc nl ooa group

forested landslide detection using lidar data and the random forest algorithm a case study of the three gorges china abstract the three gorges region of central western china is one of the most landslide prone regions in the world however landslide detection based on field surveys and optical remote sensing and synthetic aperture radar sar techniques remains difficult owing to the dense vegetation cover and mountain shadow in the present study an area of zigui county in the three gorges region was selected to test the feasibility of detecting landslides by employing novel features extracted from a lidar derived dtm additionally two small sites site 1 and site 2 were selected for training and were used to classify each other in addition to the aspect dtm and slope images the following feature sets were proposed to improve the accuracy of landslide detection 1 the mean aspect dtm and slope textures based on four texture directions 2 aspect dtm and slope textures based on aspect and 3 the moving average and standard deviation stdev filter of aspect dtm and slope by combining a feature selection method and the rf algorithm the classification accuracy was evaluated and landslide boundaries were determined the results can be summarized as follows 1 the feature selection method demonstrated that the proposed features provided information useful for effective landslide identification 2 feature selection achieved an improvement of about 0 44 in the overall classification accuracy with the feature set reduced by 74 from 39 to 10 this can speed up the training of the rf model 3 when fifty randomly selected 20 of landslide pixels pls and 20 of non landslide pixels pnls i e 20 of pls and pnls were utilized in addition to the selected feature subsets for training the test sets i e the remaining 80 of pls and pnls yielded an average overall classification accuracy of 78 24 the cross training and classification for site 1 and site 2 provided overall classification accuracies of 62 65 and 64 50 respectively this shows that the random sampling design which suffered some of the effects of spatial auto correlation and the proposed method in this present study contribute jointly to the classification accuracy 4 using the canny operator to delineate landslide boundaries based on the classification results of pls and pnls we obtained results consistent with the referenced landslide inventory maps thus the proposed procedure which combines lidar data a feature selection method and the rf algorithm can identify forested landslides effectively in the three gorges region

gis techniques and statistical models in evaluating landslide hazard geographical information systems gis and numerical cartography may greatly facilitate the development and use of statistical models for the assessment of regional landslide hazard from a small drainage basin located in central italy relevant geological and geomorphological factors were collected and processed by applying gis technology in particular modules were used which both generate high fidelity digital terrain models and automatically partition the terrain into main slope units the resulting information was then analysed by discriminant analysis which enabled landslide hazard and risk to be evaluated in each slope unit although not lacking drawbacks the method proved to be a feasible and cost effective approach to landslide susceptibility assessment and mapping

automated landslide mapping using spectral analysis and high resolution topographic data puget sound lowlands washington and portland hills oregon abstract landslide inventory maps are necessary for assessing landslide hazards and addressing the role slope stability plays in landscape evolution over geologic timescales however landslide inventory maps produced with traditional methods aerial photograph interpretation topographic map analysis and field inspection are often subjective and incomplete the increasing availability of high resolution topographic data acquired via airborne light detection and ranging lidar over broad swaths of terrain invites new automated landslide mapping procedures we present two methods of spectral analysis that utilize lidar derived digital elevation models of the puget sound lowlands washington and the tualatin mountains oregon to quantify and automatically map the topographic signatures of deep seated landslides power spectra produced using the two dimensional discrete fourier transform and the two dimensional continuous wavelet transform identify the characteristic spatial frequencies of deep seated landslide morphologic features such as hummocky topography scarps and displaced blocks of material spatial patterns in the amount of spectral power concentrated in these characteristic frequency bands highlight past slope instabilities and allow the delineation of landslide terrain when calibrated by comparison with detailed independently compiled landslide inventory maps our algorithms correctly classify an average of 82 of the terrain in our five study areas spectral analysis also allows the creation of dominant wavelength maps which prove useful in analyzing meter scale topographic expressions of landslide mechanics past landslide activity and landslide modifying geomorphic processes these results suggest that our automated landslide mapping methods can create accurate landslide maps and serve as effective objective and efficient tools for digital terrain analysis

remote sensing as tool for development of landslide databases the case of the messina province italy geodatabase abstract landslide geodatabases including inventories and thematic data today are fundamental tools for national and or local authorities in susceptibility hazard and risk management a well organized landslide geo database contains different kinds of data such as past information landslide inventory maps ancillary data and updated remote sensing space borne and ground based data which can be integrated in order to produce landslide susceptibility maps updated landslide inventory maps and hazard and risk assessment maps italy is strongly affected by landslide phenomena which cause victims and significant economic damage to buildings and infrastructure loss of productive soils and pasture lands in particular the messina province southern italy represents an area where landslides are recurrent and characterized by high magnitude due to several predisposing factors e g morphology land use lithologies and different triggering mechanisms meteorological conditions seismicity active tectonics and volcanic activity for this area a geodatabase was created by using different monitoring techniques including remote sensing e g sar satellite ers1 2 envisat radarsat 1 terrasar x cosmo skymed data and in situ measurements e g gbinsar damage assessment in this paper a complete landslide geodatabase of the messina province designed following the requirements of the local and national civil protection authorities is presented this geo database was used to produce maps e g susceptibility ground deformation velocities damage assessment risk zonation which today are constantly used by the civil protection authorities to manage the landslide hazard of the messina province

object oriented identification of forested landslides with derivatives of single pulse lidar data in contrast to the many studies that use expert based analysis of lidar derivatives for landslide mapping in forested terrain only few studies have attempted to develop semi automatic methods for extracting landslides from lidar derivatives while all these studies are pixel based it has not yet been tested whether object oriented analysis ooa could be an alternative this study investigates the potential of ooa using only single pulse lidar derivatives such as slope gradient roughness and curvature to map landslides more specifically the focus is on both lidar data segmentation and classification of slow moving landslides in densely vegetated areas where spectral data do not allow accurate landslide identification a multistage procedure has been developed and tested in the flemish ardennes belgium the procedure consists of 1 image binarization and multiresolution segmentation 2 classification of landslide parts main scarps and landslide body segments and non landslide features i e earth banks and cropland fields with supervised support vector machines at the appropriate scale 3 delineation of landslide flanks 4 growing of a landslide body starting from its main scarp and 5 final cleaning of the inventory map the results obtained show that ooa using lidar derivatives allows recognition and characterization of profound morphologic properties of forested deep seated landslides on soil covered hillslopes because more than 90 of the main scarps and 70 of the landslide bodies of an expert based inventory were accurately identified with ooa for mountainous areas with bedrock on the other hand creation of a transferable model is expected to be more difficult

tracking and evolution of complex active landslides by multi temporal airborne lidar data the montaguto landslide southern italy abstract a multi temporal lidar study of an active landslide at montaguto italy is presented four lidar derived digital terrain models acquired on may 2006 july 2009 april 2010 and june 2010 are used the interpretation of selected morphometric parameters surface roughness residual topographic surface and the statistical analysis of the temporal variations of such parameters allowed the reconstruction and tracking of the landslide the landslide boundary monitoring was achieved and zones of uplift and subsidence volumes of removed and or accumulated material and average rates of vertical and horizontal displacement retreat rate of the crown and advancement rate of the toe were estimated deformation structures scarps cracks folds affecting the landslide in different times were also mapped some of such structures represent precursors of impending instability processes or give information on the mechanism of emplacement various types of activity e g rock fall flow and geometry e g channelized flow are recognized and zones whose topographic features change with time due to artificial drainage and earth handling removal work were detected the lidar derived information allows us to decipher the kinematics of the landslide the results provide new insight on the use of airborne lidar in the monitoring strategies of gravity controlled processes

estimating volume of deep seated landslides and mass transport in basihlan river basin taiwan abstract deep seated landslides are often caused by severe rainfall but the displaced potential landslide mass often does not slide downslope entirely in one time evaluation of the mobilized volume of the deep seated landslide and the volume of the remaining potentially unstable landslide mass on the slope is vital for hazard mitigation in this study an integrated method was developed for evaluation of the potential landslide volume and mass transport of deep seated landslides caused by typhoon morakot in basihlan river basin taiwan a combination of various types of remote sensing data including aerial photographs satellite images and light detection and ranging lidar data from before and after the event were used for locating landslides and the deep seated landslides were identified in the basihlan river basin liuoguey district kaohsiung city taiwan a stability analysis and a profile analysis were conducted to determine the critical sliding surface of each deep seated landslide and the volumes masses of the landslides were estimated the total volume of all the deep seated landslides was approximately 6 017 000 m3 in the basihlan river basin a topographic analysis was performed to evaluate the mass transport of the deep seated landslides using lidar derived digital terrain models dtms before and after typhoon morakot the mass transport of deep seated landslides in the basihlan river basin was determined to be approximately 3 527 300 m3 which suggested the volume of the remaining potentially unstable landslide mass on slope of approximately 41 4 the available field data suggested subsequent reactivations of the deep seated landslides after typhoon morakot including debris flow generation which damaged the infrastructure thus a large landslide volume remaining in the basihlan river basin can cause more landslides or debris flow hazards in the future estimation of the potential landslide volume and mass volume remaining on slopes is essential for both short and long term mitigation strategies

the influence of forest cover on landslide occurrence explored with spatio temporal information abstract multi temporal landslide inventories in widely forested landscapes are scarce and further studies are required to face the challenges of producing reliable inventories in woodland areas an elaboration of valuable empirical relationships between shallow landslides and forest cover based on recent remote sensing data alone is often hampered due to constant land cover changes differing ages of landslides within a landslide inventory and the fact that usage of different data sets for mapping might lead to various systematic mapping biases within this study we attempted to overcome these difficulties in order to explore the effect of forest cover on shallow landslide occurrences thus forest dynamics were examined on the basis of 9 orthophoto series from 1950s to 2015 distinguishing 3 forest classes based on the wood type these classes were furthermore distinguished in 12 subclasses considering stand density and age a multi temporal landslide inventory was compiled for the same period based on the aerial photography 2 airborne lidar imageries 8 field surveys and archive data we derived topographical parameters slope topographical positioning index and convergency index from the digital elevation model for areal correction and accounting for topographical confounders within a logistic regression model empirical relationships were assessed by means of a areal changes of forests and logged areas b spatio temporal distribution of shallow translational landslides c frequency ratios and d logistic regression analysis the findings revealed that forests increased by 16 2 from 1950s to 2015 311 landslides of 351 in total that where mapped in total could be assigned to the observed time series and were considered for our analyses frequency ratios and odds ratios indicated a stabilising effect of all forest classes on landslide occurrences odds ratios observed for the models based on aggregated data sets 3 forest classes indicated provided evidence that forest was constantly estimated to be less prone to slope failure than their non forested counterparts the chances for forest classes to be affected by shallow landslides were estimated to be considerably lower whenever topographic predictors were as well included in the model a detailed inspection of the statistical results suggests that the obtained empirical relationships should be interpreted with care challenges in the mapping procedures of forests and landslides implications of the applied methods and potential pitfalls are discussed

local variance for multi scale analysis in geomorphometry increasing availability of high resolution digital elevation models dems is leading to a paradigm shift regarding scale issues in geomorphometry prompting new solutions to cope with multi scale analysis and detection of characteristic scales we tested the suitability of the local variance lv method originally developed for image analysis for multi scale analysis in geomorphometry the method consists of 1 up scaling land surface parameters derived from a dem 2 calculating lv as the average standard deviation sd within a 3 3 moving window for each scale level 3 calculating the rate of change of lv roc lv from one level to another and 4 plotting values so obtained against scale levels we interpreted peaks in the roc lv graphs as markers of scale levels where cells or segments match types of pattern elements characterized by relatively equal degrees of homogeneity the proposed method has been applied to lidar dems in two test areas different in terms of roughness low relief and mountainous respectively for each test area scale levels for slope gradient plan and profile curvatures were produced at constant increments with either resampling cell based or image segmentation object based visual assessment revealed homogeneous areas that convincingly associate into patterns of land surface parameters well differentiated across scales we found that the lv method performed better on scale levels generated through segmentation as compared to up scaling through resampling the results indicate that coupling multi scale pattern analysis with delineation of morphometric primitives is possible this approach could be further used for developing hierarchical classifications of landform elements

investigating the effects of different landslide positioning techniques landslide partitioning approaches and presence absence balances on landslide susceptibility mapping the ziarat watershed located in the south of the golestan province iran has witnessed several destructive landslide episodes prompting a number of researchers to aspire to improve landslide susceptibility modeling lsm techniques we constructed three scenarios focusing on landslide positioning techniques pixel based centroid crown and toe training test sampling strategies mahalanobis distance md and random sampling rs with alternative landslide non landslide data balances 1 1 1 2 and 1 3 the data mining boosted regression trees brt model was used for the landslide susceptibility modeling using landslide data and 13 landslide controlling factors for the ziarat watershed the performance of the scenarios was assessed using the areas under the success and prediction rate curves ausrc and auprc a combination of pixel based md 1 2 showed the highest learning capability and goodness of fit with an ausrc value of 0 87 and the highest predictive power and generalization capacity with an auprc value of 0 79 conversely centroid based 1 3 rs crown based 1 3 rs and toe based 1 3 rs performed less well comparatively the pixel based md and 1 2 data balance scenarios surpassed their counterparts and outperformed the other models the results indicated a high spatial differentiation with a significant chi square value of 4549 46 at 95 confidence level moreover 15 21 of the study area containing almost 50 of the landslides was found to have a high susceptibility to landslides according to the premier scenario pixel based md 1 2 lithological formation distance from roads and ndvi with respective contributions of 31 4 12 9 and 12 are the main spatial controlling factors leading to landslide occurrences in the study area

landslide inventory maps new tools for an old problem landslides are present in all continents and play an important role in the evolution of landscapes they also represent a serious hazard in many areas of the world despite their importance we estimate that landslide maps cover less than 1 of the slopes in the landmasses and systematic information on the type abundance and distribution of landslides is lacking preparing landslide maps is important to document the extent of landslide phenomena in a region to investigate the distribution types pattern recurrence and statistics of slope failures to determine landslide susceptibility hazard vulnerability and risk and to study the evolution of landscapes dominated by mass wasting processes conventional methods for the production of landslide maps rely chiefly on the visual interpretation of stereoscopic aerial photography aided by field surveys these methods are time consuming and resource intensive new and emerging techniques based on satellite airborne and terrestrial remote sensing technologies promise to facilitate the production of landslide maps reducing the time and resources required for their compilation and systematic update in this work we first outline the principles for landslide mapping and we review the conventional methods for the preparation of landslide maps including geomorphological event seasonal and multi temporal inventories next we examine recent and new technologies for landslide mapping considering i the exploitation of very high resolution digital elevation models to analyze surface morphology ii the visual interpretation and semi automatic analysis of different types of satellite images including panchromatic multispectral and synthetic aperture radar images and iii tools that facilitate landslide field mapping next we discuss the advantages and the limitations of the new remote sensing data and technology for the production of geomorphological event seasonal and multi temporal inventory maps we conclude by arguing that the new tools will help to improve the quality of landslide maps with positive effects on all derivative products and analyses including erosion studies and landscape modeling susceptibility and hazard assessments and risk evaluations

high resolution topography for understanding earth surface processes opportunities and challenges abstract in the last decade a range of new remote sensing techniques has led to a dramatic increase in terrain information providing new opportunities for a better understanding of earth surface processes based on geomorphic signatures technologies such as airborne and terrestrial lidar light detection and ranging to obtain high resolution topography have opened avenues for the analysis of landslides hillslope and channellization processes river morphology active tectonics volcanic landforms and anthropogenic signatures on topography this review provides an overview of the recent flourishing literature on high resolution topographic analyses underlining their opportunities and critical issues such as their limitations the goal is to provide answers to questions such as what kind of processes can be analyzed through high resolution topographic data and how to do it the review focuses on two different environments natural and engineered landscapes in both contexts high resolution topography offers opportunities to better understand geomorphic processes from topographic signatures particular attention is given to engineered landscapes in which the direct anthropic alteration of processes is significant the last part of the review discusses future challenges

deep seated gravitational slope deformations controlled by the structure of flysch nappe outliers insights from large scale electrical resistivity tomography survey and lidar mapping abstract the flysch nappe outliers represent a structural setting prone to the development of deep seated gravitational slope deformations dsgsds the study area of the palkovicke h rky hills represents an isolated outlier of the carpathians flysch nappes czech republic geomorphological mapping based on field surveys and interpretation of lidar data reveals the occurrence of various types of slope deformations including two dsgsds with the aim of detecting the main controlling factors of the dsgsds a multiapproach investigation combining surface and underground studies has been performed structural measurement points to a brachysynclinal structure composed of jointed and lithologically diverse strata with step like topography high resolution lidar data suggest strong tectonic disruption caused by conjugated transtensional and en echelon tectonic faults controlling the course of slope segments river valleys and landslide scarps four specific localities have been subjected to geophysical surveying kilometre scale electrical resistivity tomography ert profiles that have depths of penetration reaching the limits of the method 150 m were acquired across the gravitationally deformed nappe outlier the data show the overall structural conditions of the nappe outlier consisting of alternating lithological units affected by folds and fault zones a local subordinate anticline within the central part of the brachysynclinal structure has controlled the origin of the most morphologically pronounced dsgsds other large scale dsgsds related to the inherited fault system potentially affect the entire n nw segment of the studied elevation data integration indicate that structural conditions including lithological boundaries tectonic disruption and local folding to be the main controlling factors of the dsgsds evolution

regional mapping and characterisation of old landslides in hilly regions using lidar based imagery in southern flanders abstract analysis of lidar derived imagery led to the discovery of more than 330 pre holocene to recent landslides in southern flanders 4850 km 2 the morphology of three landslides including the 266 5 ha deep seated gravitational slope deformation in alden biesen was investigated in more detail the analysis of the morphological and topographical characteristics width length relation frequency area distribution and topographical threshold of the landslides revealed important differences compared to the characteristics reported in other landslide studies and helped understanding possible landslide triggering mechanisms especially the possibility of a seismic origin of the landslides was investigated finally a heuristic model for region wide landslide susceptibility mapping was successfully tested the susceptibility model and map allow prediction of future landslide locations and contribute to better understanding the role of individual causal factors on landslide location and spatial density the results suggest that landslides on low gradient soil mantled hills are a more important contributor to landscape evolution of hilly areas than was hitherto thought the morphology of all hilly regions of flanders is clearly marked by landslide processes and higher landslide densities often coincide with the presence of quaternary active faults this study further shows that high resolution topographical data such as lidar significantly contributes to a better detection of old previously unknown landslides

delineation of alluvial fans from digital elevation models with a gis algorithm for the geomorphological mapping of the earth and mars alluvial fans are prominent depositional geomorphic features present in nearly all global climates on earth and also found on mars in this study we present a geographic information system gis algorithm designed for the semi automated detection of alluvial fans that are connected to their contributing upstream drainage network from the analysis of digital elevation models dems through a combination of spatial analysis procedures the gis algorithm generates maps of alluvial fans and their upstream source drainage and watersheds tests of the algorithm in areas with well known alluvial fans indicate that this new gis procedure is capable of high accuracy mapping of the fan apexes and correct delineation of fan deposits in both arid and humid climates possible future applications of the gis algorithm presented in this study include the systematic survey of alluvial fans at the local regional and planetary scales important for geologic hazard assessment studies on the evolution of climate analysis of continental sedimentary environments understanding of the interplay between the endogenous dynamics and exogenous processes and the evaluation of natural resources

evaluating fuzzy operators of an object based image analysis for detecting landslides and their changes abstract this article presents a method of object based image analysis obia for landslide delineation and landslide related change detection from multi temporal satellite images it uses both spatial and spectral information on landslides through spectral analysis shape analysis textural measurements using a gray level co occurrence matrix glcm and fuzzy logic membership functionality following an initial segmentation step particular combinations of various information layers were investigated to generate objects this was achieved by applying multi resolution segmentation to irs 1d spot 5 and alos satellite imagery in sequential steps of feature selection and object classification and using slope and flow direction derivatives from a digital elevation model together with topographically oriented gray level co occurrence matrices fuzzy membership values were calculated for 11 different membership functions using 20 landslide objects from a landslide training data six fuzzy operators were used for the final classification and the accuracies of the resulting landslide maps were compared a fuzzy synthetic evaluation fse approach was adapted for validation of the results and for an accuracy assessment using the landslide inventory database the fse approach revealed that the and operator performed best with an accuracy of 93 87 for 2005 and 94 74 for 2011 closely followed by the mean arithmetic operator while the or and and operators yielded relatively low accuracies an object based change detection was then applied to monitor landslide related changes that occurred in northern iran between 2005 and 2011 knowledge rules to detect possible landslide related changes were developed by evaluating all possible landslide related objects for both time steps

the effectiveness of hillshade maps and expert knowledge in mapping old deep seated landslides large deep seated landslides with a shear surface deeper than 3 m and a mean affected area of 4 2 ha are common features in the flemish ardennes none of these deep seated landslides are dated but they are assumed to be rather old 100 years because most of these landslides are located under forest aerial photo interpretation commonly used for the creation of landslide inventories is not a suitable tool to map the landslides in the flemish ardennes therefore an intensive 100 day field survey was carried out by two geomorphologists in a 430 km 2 study area this resulted in a landslide inventory map indicating the location of 135 large deep seated landslides but field surveys are time consuming and thus very expensive therefore a cheaper and faster mapping technique was tested a hillshade map was constructed for the study area in a gis idris132 from a 5 m resolution digital elevation model dem seven experts were given 1 h to indicate all the hillslope sections which they suspected to be possible landslides on a copy of the aforementioned map scale 1 100 000 in total this exercise took only 1 day i e 7 person hours large differences in the number of presumed landslides and the extent of the hillslopes thought to be affected by landslides were reported among the seven experts the polygon and pixel efficiency were introduced to estimate the quality of the landslide maps based on hillshade maps and expert knowledge compared to the field survey based landslide inventory the quality of the landslide inventories based on the hillshade maps and expert knowledge was relatively low experts familiar with the study area obtained somewhat better results than experts who visited the study area only once a combination of the seven expert maps did not result in a good inventory map because too many unaffected hillslopes were incorrectly indicated as affected by landslides the results obtained in this study are comparable to an investigation carried out by wills c j mccrink t p 2002 comparing landslide inventories the map depends on the method environmental and engineering geoscience 8 279 293 although the tested method can never replace a detailed field survey taking into account the proposed improvements it can be used for the creation of a regional inventory map of old landslides in a densely forested area where light detection and ranging lidar data are unavailable c 2004 elsevier b v all rights reserved

semi automatic classification of glaciovolcanic landforms an object based mapping approach based on geomorphometry abstract a new object oriented approach is developed to classify glaciovolcanic landforms procedure a and their landform elements boundaries procedure b it utilizes the principle that glaciovolcanic edifices are geomorphometrically distinct from lava shields and plains pedersen and grosse 2014 and the approach is tested on data from reykjanes peninsula iceland the outlined procedures utilize slope and profile curvature attribute maps 20 m pixel and the classified results are evaluated quantitatively through error matrix maps procedure a and visual inspection procedure b in procedure a the highest obtained accuracy is 94 1 but even simple mapping procedures provide good results 90 accuracy successful classification of glaciovolcanic landform element boundaries procedure b is also achieved and this technique has the potential to delineate the transition from intraglacial to subaerial volcanic activity in orthographic view this object oriented approach based on geomorphometry overcomes issues with vegetation cover which has been typically problematic for classification schemes utilizing spectral data furthermore it handles complex edifice outlines well and is easily incorporated into a gis environment where results can be edited or fused with other mapping results the approach outlined here is designed to map glaciovolcanic edifices within the icelandic neovolcanic zone but may also be applied to similar subaerial or submarine volcanic settings where steep volcanic edifices are surrounded by flat plains

potential of airborne lidar data analysis to detect subtle landforms of slope failure portaine central pyrenees abstract slope failures have been traditionally detected by field inspection and aerial photo interpretation these approaches are generally insufficient to identify subtle landforms especially those generated during the early stages of failures and particularly where the site is located in forested and remote terrains we present the identification and characterization of several large and medium size slope failures previously undetected within the orri massif central pyrenees around 130 scarps were interpreted as being part of rock slope failures rsfs while other smaller and more superficial failures were interpreted as complex movements combining colluvium slow flow slope creep and rsfs except for one of them these slope failures had not been previously detected albeit they extend across a 15 of the studied region the failures were identified through the analysis of a high resolution 1 m lidar derived bare earth digital elevation model dem most of the scarps are undetectable either by fieldwork photo interpretation or 5 m resolution topography analysis owing to their small heights 0 5 to 2 m and their location within forest areas in many cases these landforms are not evident in the field due to the presence of other minor irregularities in the slope and the lack of open views due to the forest 2d and 3d visualization of hillshade maps with different sun azimuths provided an overall picture of the scarp assemblage and permitted a more complete analysis of the geometry of the scarps with respect to the slope and the structural fabric the sharpness of some of the landforms suggests ongoing activity which should be explored in future detailed studies in order to assess potential hazards affecting the portaine ski resort our results reveal that close analysis of the 1 m lidar derived dem can significantly help to detect early stage slope deformations in high mountain regions and that expert judgment of the dem is essential when dealing with subtle landforms the incorporation of this approach in regional mapping represents a great advance in completing the catalogue of slope failures and will eventually contribute to a better understanding of the spatial factors controlling them

object representations at multiple scales from digital elevation models in the last decade landform classification and mapping has developed as one of the most active areas of geomorphometry however translation from continuous models of elevation and its derivatives slope aspect and curvatures to landform divisions landforms and landform elements is filtered by two important concepts scale and object ontology although acknowledged as being important these two issues have received surprisingly little attention this contribution provides an overview and prospects of object representation from dems as a function of scale relationships between object delineation and classification or regionalization are explored in the context of differences between general and specific geomorphometry a review of scales issues in geomorphometry ranging from scale effects to scale optimization techniques is followed by an analysis of pros and cons of using cells and objects in dem analysis prospects for coupling multi scale analysis and object delineation are then discussed within this context we propose discrete geomorphometry as a possible approach between general and specific geomorphometry discrete geomorphometry would apply to and describe land surface divisions defined solely by the criteria of homogeneity in respect to a given land surface parameter or a combination of several parameters homogeneity in its turn should always be relative to scale

expert driven semi automated geomorphological mapping for a mountainous area using a laser dtm in this paper a semi automated method is presented to recognize and spatially delineate geomorphological units in mountainous forested ecosystems using statistical information extracted from a 1 m resolution laser digital elevation dataset the method was applied to a mountainous area in austria first slope angle and elevation characteristics were determined for each key geomorphological unit occurring in the study area second a map of slope classes derived from the laser dtm was used in an expert driven multilevel object oriented approach the resulting classes represent units corresponding to landforms and processes commonly recognized in mountain areas fluvial terrace alluvial fan slope with mass movement talus slope rock cliff glacial landform shallow incised channel and deep incised channel the classification result was compared with a validation dataset of geomorphological units derived from an analogue geomorphological map for the above mentioned classes the percentages of correctly classified grid cells are 69 79 50 64 32 61 23 and 70 respectively the lower values of 32 and 23 are mainly related to inaccurate mapping of rock cliffs and shallow incised channels in the analogue geomorphological map the accuracy increased to 76 and 54 respectively if a buffer is applied to these specific units it is concluded that high resolution topographical data derived from laser dtms are useful for the extraction of geomorphological units in mountain areas

assessing debris flows using lidar differencing 18 may 2005 matata event new zealand the town of matata in the eastern bay of plenty new zealand experienced an extreme rainfall event on the 18 may 2005 this event triggered widespread landslips and large debris flows in the awatarariki and waitepuru catchments behind matata the light detection and ranging technology lidar data sets flown prior to and following this event have been differenced and used in conjunction with a detailed field study to identify the distribution of debris and major sediment pathways which from the awatarariki catchment transported at least 350 000 50 000 m3 of debris debris flows were initially confined to stream valleys and controlled by the density and hydraulic thrust of the currents before emerging onto the awatarariki debris fan where a complex system of unconfined sediment pathways developed here large boulders clasts logs and entire homes were deposited as the flows decelerated downstream from the debris fan the pre existing coastal foredune topography played a significant role in deflecting the more dilute currents that in filled lagoonal swale systems in both directions the differenced lidar data have revealed several sectors characterised by significant variation in clast size thickness and volume of debris as well as areas where post debris flow cleanup and grading operations have resulted in man made levees sediment dumps scoured channels and substantial graded areas the application of differenced lidar data to a debris flow event demonstrates the techniques potential as a precise and powerful tool for hazard mapping and assessment

characterising spectral spatial and morphometric properties of landslides for semi automatic detection using object oriented methods recognition and classification of landslides is a critical requirement in pre and post disaster hazard analysis this has been primarily done through field mapping or manual image interpretation however image interpretation can also be done semi automatically by creating a routine in object based classification using the spectral spatial and morphometric properties of landslides and by incorporating expert knowledge this is a difficult task since a fresh landslide has spectral properties that are nearly identical to those of other natural objects such as river sand and rocky outcrops and they also do not have unique shapes this paper investigates the use of a combination of spectral shape and contextual information to detect landslides the algorithm is tested with a 5 8 m multispectral data from resourcesat 1 and a 10 m digital terrain model generated from 2 5 m cartosat 1 imagery for an area in the rugged himalayas in india it uses objects derived from the segmentation of a multispectral image as classifying units for object oriented analysis spectral information together with shape and morphometric characteristics was used initially to separate landslides from false positives objects recognised as landslides were subsequently classified based on material type and movement as debris slides debris flows and rock slides using adjacency and morphometric criteria they were further classified for their failure mechanism using terrain curvature the procedure was developed for a training catchment and then applied without further modification on an independent catchment a total of five landslide types were detected by this method with 76 4 recognition and 69 1 classification accuracies this method detects landslides relatively quickly and hence has the potential to aid risk analysis disaster management and decision making processes in the aftermath of an earthquake or an extreme rainfall event

high resolution broad scale mapping of soil parent material using object based image analysis obia of lidar elevation data abstract precise mapping of subsurface properties especially soil parent material spm is critical to understanding most geomorphic and hydrologic processes because spatial variability of the subsurface properties is highly correlated to the morphology of the earth s surface dems and aerial satellite imagery have been used successfully for lithological mapping however most of the studies using this approach have used either coarse resolution dems or covered limited areas lidar derived topographic attributes may provide an opportunity for finer resolution mapping of subsurface properties at much larger spatial scales here we present an approach that uses object based image analysis obia the process of clustering pixels into homogeneous objects paired with a classification tree ct algorithm to map spm at 1 m resolution and at a regional spatial scale using lidar derived topographic attributes combining obia of topographic attributes with the ct method proved to be an efficient approach for mapping of spm at fine resolution and broad scales using field acquired spm samples we found that this approach was able to explain 73 5 of the variance of three spm classes i e bedrock glacial till sands using only four common topographic metrics i e slope topographic wetness index terrain ruggedness index multi resolution topographic positioning index when comparing our approach to other classification methods and to other studies that have mapped spm we obtain the highest overall accuracy with a value of 85 this approach allowed us to produce a fine resolution 185 km2 spm map in a heterogeneous post glaciation precambrian shield setting

use of lidar derived images for mapping old landslides under forest large deep seated landslides are common features in the flemish ardennes belgium as most of these old 100 years landslides are located under forest in this hilly region aerial photograph interpretation is not an appropriate landslide mapping method this study tested the potential of lidar light detection and ranging images for mapping old landslides under forest landslide inventory maps were created for a 125 km2 area by applying the expert knowledge of seven geomorphologists to lidar derived hillshade slope and contour line maps in a gis environment each of the seven lidar based landslide inventories was compared i with the other six ii with a detailed field survey based inventory and iii with a comparable study in which topographic data were extracted from a topographical map the combination of the percentage of field landslides indicated by an expert and the percentage of positional discrepancies expressed in terms of positional mismatch were used to evaluate the quality of the lidar based inventory maps high quality lidar derived landslide inventory maps contain more than 70 per cent of the landslides mapped during the field survey and have positional discrepancies smaller than 70 per cent when compared with the field survey based inventory map four experts and the combination map of all experts satisfied these criteria together the seven experts indicated all landslides mapped in the field importantly lidar enabled the experts to find ten new landslides and to correct the boundaries of eleven of the 77 landslides mapped during the field survey hence this study showed that large scale lidar derived maps analysed by experienced geomorphologists can significantly improve field survey based inventories of landslides with a subdued morphology in hilly regions copyright 2006 john wiley sons ltd

parametrization of momentum transport by convection i theory and cloud modelling results summary the theory of the mass flux approach to parametrization of convective momentum transport is presented a cloud resolving model is used to simulate momentum transport by ensembles of deep convective clouds in two very different regimes a mid latitude cold air outbreak and tropical convection forced by convergence idealized unidirectional wind profiles are used to simplify interpretation of the results diagnostics relevant to the parametrization problem are presented and it is shown that for both regimes the approximations inherent in the parametrization equations are reasonable the pressure gradients inside clouds play an important role in determining horizontal velocities in the clouds for the cold air outbreak with linear shear the results suggest that these pressure gradients are proportional to the shear and to the up downdraught mass fluxes sensitivity studies suggest that the results are not very sensitive to resolution or parametrization of subgrid scale processes giving some confidence that the results are reasonably accurate for the tropical case with a low level jet the pressure gradients change sign with the wind shear in part i1 of this paper these results will be used to develop and validate a mass flux parametrization of convective momentum transport which is tested in single column and global versions of the meteorological office unified model

extraction of multi scale landslide morphological features based on local g i using airborne lidar derived dem abstract for automatic landslide detection landslide morphological features should be quantitatively expressed and extracted high resolution digital elevation models dems derived from airborne light detection and ranging lidar data allow fine scale morphological features to be extracted but noise in dems influences morphological feature extraction and the multi scale nature of landslide features should be considered this paper proposes a method to extract landslide morphological features characterized by homogeneous spatial patterns both profile and tangential curvature are utilized to quantify land surface morphology and a local gi statistic is calculated for each cell to identify significant patterns of clustering of similar morphometric values the method was tested on both synthetic surfaces simulating natural terrain and airborne lidar data acquired over an area dominated by shallow debris slides and flows the test results of the synthetic data indicate that the concave and convex morphologies of the simulated terrain features at different scales and distinctness could be recognized using the proposed method even when random noise was added to the synthetic data in the test area cells with large local gi values were extracted at a specified significance level from the profile and the tangential curvature image generated from the lidar derived 1 m dem the morphologies of landslide main scarps source areas and trails were clearly indicated and the morphological features were represented by clusters of extracted cells a comparison with the morphological feature extraction method based on curvature thresholds proved the proposed method s robustness to dem noise when verified against a landslide inventory the morphological features of almost all recent 10 years landslides were extracted this finding indicates that the proposed method can facilitate landslide detection although the cell clusters extracted from curvature images should be filtered using a filtering strategy based on supplementary information provided by expert knowledge or other data sources

morphology and internal structure of a dormant landslide in a hilly area the collinabos landslide belgium abstract this study attempts to reconstruct the history of the collinabos landslide a landslide with a fresh morphology that is representative for more than 150 dormant deep seated 3 m landslides in the flemish ardennes belgium a geomorphological map was created based on lidar light detection and ranging derived maps and detailed field surveys the map showed that the landslide consisted of three zones with significant differences in surface topography the northern landslide zone 1 is characterised by at least five reverse slopes whereas zones 2 and 3 the southern landslide zones have only two reverse slopes and a convex foot electric resistivity profiles measured in zones 1 and 2 revealed that the differences in surface topography were not related to differences in internal structure as both parts of the landslide were initiated as a rotational earth slide with a surface of rupture at 15 m deep where the displaced material broke apart in two blocks however two shear surfaces of reactivations within landslide debris were only distinguished in the accumulation area of zone 1 the observed differences in surface morphology can be caused by a temporary conversion of a forest into cropland in zone 2 it is suggested that reverse slopes of smaller reactivations within landslide debris were obliterated during the agricultural activities ams radiocarbon dating of organic material found in ponds located in reverse slopes generally resulted in relatively recent dates i e 1400 1950 cal ad suggesting that several of the small local reactivations occurred in that period one dating at 8700 8440 cal bp of organic matter collected in a reverse slope in zone 1 suggests that an initiation under periglacial conditions cannot be excluded for the collinabos landslide by combining different technologies this study provides valuable information for a better understanding of dormant landslides

producing a landslide inventory map using pixel based and object oriented approaches optimized by taguchi method abstract landslides are considered one of the most important natural hazards mapping landslides and producing landslide inventory maps have received special attention from a wide range of specialists the main objective of this study was to produce landslide inventory maps using advanced pixel based ann and svm and object oriented approaches the most important challenge in this case is to determine the optimum structure of classification methods the taguchi method was to perform optimization of the structure of ann and svm and segmentation process in the object oriented classification method results showed that the taguchi method can be effectively used to cope with this problem it significantly reduces the number of classification tests we also showed that there were no significant differences existed between ann and svm approaches 2 value of 3 33 however we demonstrated that object oriented approaches significantly outperformed the pixel based classification methods z value of 5 70 in producing a landslide inventory map the accurate map produced using an object oriented approach overall accuracy of 0 90 effectively determines the shape of landslides and also efficiently shows the intensifying effects of land use changes in the occurrence of landslides

analysis of lidar derived topographic information for characterizing and differentiating landslide morphology and activity abstract this study used airborne laser altimetry lidar to examine the surface morphology of two canyon rim landslides in southern idaho the high resolution topographic data were used to calculate surface roughness slope semivariance and fractal dimension these data were combined with historical movement data global positioning systems gps and laser theodolite and field observations for the currently active landslide and the results suggest that topographic elements are related to the material types and the type of local motion of the landslide weak unconsolidated materials comprising the toe of the slide which were heavily fractured and locally thrust upward had relatively high surface roughness high fractal dimension and high vertical and lateral movement the body of the slide which predominantly moved laterally and consists mainly of undisturbed older canyon floor materials had relatively lower surface roughness than the toe the upper block consisting of a down dropped section of the canyon rim that has remained largely intact had a low surface roughness on its upper surface and high surface roughness along fractures and on its west face unrelated to landslide motion the upper block also had a higher semivariance than the toe and body the topographic data for a neighboring older and larger landslide complex which failed in 1937 are similarly used to understand surface morphology as well as to compare to the morphology of the active landslide and to understand scale dependent processes the morphometric analyses demonstrate that the active landslide has a similar failure mechanism and is topographically more variable than the 1937 landslide especially at scales 20 m weathering and the larger scale processes of the 1937 slide are hypothesized to cause the lower semivariance values of the 1937 slide at smaller scales

elementary forms for land surface segmentation the theoretical basis of terrain analysis and geomorphological mapping abstract land surface morphology is fundamental to geomorphological mapping and many gis applications review and comparison of various approaches to segmentation of the land surface reveals common features and permits development of a broad theoretical basis for segmentation and for characterization of segments and their boundaries within the context of defining landform units that maximise internal homogeneity and external differences this paper introduces the concept of elementary forms segments units defined by constant values of fundamental morphometric properties and limited by discontinuities of the properties the basic system of form defining properties represents altitude and its derivatives constant values of which provide elementary forms with various types of homogeneity every geometric type of elementary form can be characterized by a defining function which is a specific case of the general polynomial fitted function various types of boundary discontinuity and their connections and transformations into other types of morphological unit boundaries are analysed the wealth of types of elementary forms and their boundaries is potentially unbounded and thus is sufficient to cover the real variety of landforms elementary forms in the basic set proposed here have clear potential for genetic and dynamic interpretation a brief worked example documents the possibility of analytical computation of various models of ideal elementary forms for particular segments of landform ideal elementary forms can be considered as attractors to which the affinity of surface segments can be measured by multivariate statistical methods the use of the concept of elementary forms in landscape segmentation is promising and it could be adapted for elementary segmentation of various other spatial fields