Određivanje pomaka klizišta Kostanjek relativnom statičkom metodom

Projekt studentske radionice određivanje je pomaka klizišta Kostanjek primjenom GNSS (eng. Global Navigation Satellite System) tehnologije. Opažana je mreža stalnih geodetskih točaka uspostavljena na području klizišta 2009. godine. Izmjera je obavljena 2. veljače 2012. Rezultati mjerenja, koordinate točaka u epohi 2012, uspoređeni su s rezultatima mjerenja iz prošlih epoha (listopad 2009. i ožujak 2010.). Rezultati su korisni hrvatsko-japanskom projektu za interpretaciju modela klizišta i planiranje integriranog sustava praćenja pomaka klizišta

The systematization of analytical and numerical methods of landslide stability calculation

Na osnovu analize mnogih naučnih radova, autori su dali prikaz sopstvene originalne sistematizacije analitičkih i numeričkih metoda proračuna stabilnosti klizišta, pri čemu mnoge od njih tek treba dodatno da se unaprede, implementiraju i testiraju na kompleksnim 3D modelima klizišta. Metode proračuna stabilnosti klizišta klasifikovane su u pet grupa: analitičke jednokoračne, analitičke višekoračne (iteracije kliznih površi), numeričke višekoračne (iteracije kliznih površi), numeričke inkrementalno-iterativne (nelinearne) analize i numeričke inkrementalno-iterativne (nelinearne) analize, uz primenu numeričke integracije u vremenskom domenu. Primenom sprovedene sistematizacije metoda proračuna stabilnosti klizišta, može se vrlo efikasno razmotriti koji je tip metode optimalan za analizu klizišta i koji tip metode je potrebno koristiti u fazi preliminarnih i finalnih analiza za naučna istraživanja i stručne projekte.According to the analysis of a large number of scientific papers, the authors of the paper presented their own original systematization of the analytical and numerical methods of landslide stability calculation, with a large part of them still to be further improved, implemented and tested on complex 3D landslide models. Methods for calculating the stability of the landslide are classified into five groups: analytical single-step, analytical multi-step (iterations of sliding surfaces), numerical multi-step (iterations of sliding surfaces), numerical incremental-iterative (nonlinear) analysis and numerical incremental-iterative (nonlinear) analysis, applying numerical integration in the time domain. By using the systematization method of calculating the stability of the landslide it can be very effective to consider which type of method is optimal for landslide analysis and which type of method should be considered in the phase of preliminary and final analysis for scientific research and expert projects

KINEMATIČKI MODEL SPOROGA KLIZIŠTA KOSTANJEK (GRAD ZAGREB, HRVATSKA)

The interpretation of landslide kinematics provides important information for those responsible for the management of landslide risk. This paper presents an interpretation of the kinematics of the slow-moving Kostanjek landslide, located in the urbanized area of the city of Zagreb, Croatia. The sliding material (very weak to weak marls, often covered with clayey topsoil) exhibits plastic, rather than rigid behavior. Due to this reason, and low landslide velocities, landslide features, such as main scarps or lateral flanks, are barely noticeable or do not exist in most of the landslide area. The data used for the kinematic interpretation were obtained from 15 GNSS sensors, for the period of 2013-2019. The monitoring data revealed a different spatial and temporal distribution of landslide velocities, resulting as a consequence of geomorphological conditions and forces that govern the landslide movements. Temporally, eight periods of faster movements and seven periods of slower movements were determined. Spatially, velocities measured in the central part of the landslide were higher than on its boundaries. The interpretation of the surface (horizontal and vertical) displacements and the direction of movement reveal a new insight into the engineering geological model and provide important information for the management of the Kostanjek landslide risk.Interpretacija kinematičkoga modela klizišta važan je podatak pri procjeni ugroženosti za stanovnike, građevine i infrastrukturu na području klizišta. Ovaj članak opisuje interpretaciju kinematičkoga modela sporoga klizišta Kostanjek, koje se nalazi u gradu Zagrebu. Materijali u klizanju (vrlo slabi do slabi lapori, često prekriveni glinovitim pokrivačem) uglavnom pokazuju plastično ponašanje. Zbog toga, a i zbog male brzine klizišta, dijelovi klizišta kao što su glavna pukotina ili bokovi klizišta izostaju ili nisu jasno izraženi na površini terena. Podatci korišteni za interpretaciju kinematičkoga modela prikupljeni su s 15 GNSS uređaja, u razdoblju između 2013. i 2019. godine. Podatci praćenja upućuju na različitu prostornu i vremensku raspodjelu brzina, koja je posljedica geomorfoloških uvjeta te sila koje uzrokuju gibanje klizišta. Vremenski je moguće raspoznati osam razdoblja bržega gibanja i sedam razdoblja sporijega gibanja, dok su prostorno veće brzine izmjerene u središnjemu dijelu klizišta nego na njegovim rubovima. Rezultati interpretacije horizontalnih i vertikalnih pomaka te smjerova gibanja upućuju na novi inženjerskogeološki model klizišta te pružaju važne podatke za prostorno planiranje i civilnu zaštitu

Landslides in the wider area of Našice town

Na širem području grada Našica nalazi se veći broj manjih klizišta. Prikupljeni podaci pomažu u razumijevanju njihova nastanka, ali i njihovoj sanaciji. Geološka struktura, vremenske prilike, vode i neprikladni građevinski zahvati samo su neki od elemenata koji mogu dovesti do nastanka klizišta. U ovom radu prezentiraju se klizišta u centru Našica, kod Donje Motičine te u Orahovici.There are a lot of small landslides in the area of Našice which. Collected data can help understand their origin and can also be very helpful in their recovery. Geological structure, weather, water, interventions on the ground are just some of the causes that can lead to the landslides. In this thesis are presented the landslides in the center of Našice, in Donja Motičina and in Orahovica

PROCJENA PODLOŽNOSTI NA KLIZIŠTA INICIRANA POTRESOM: POTRES OD 7,5 MW U 2018. GODINI U PALUU, SULAWESI, INDONEZIJA

A catastrophic Palu earthquake on September 28th, 2018 with Mw 7.5 triggered countless slope failures, generating numerous landslides. This paper presents a practical method for susceptibility assessment of earthquake-induced landslides in the Palu region and the surrounding area. The statistical weight of evidence (WoE) model was used to assess the relationship between landslides induced by seismic motion and its causative factors to determine the susceptibility level and derive an earthquake-induced landslide susceptibility map of this study area. The 1273 landslides were classified into two data series, training data for modelling (70%) and test data for validation (30%). The six selected thematic maps as landslide causative factors are lithology, land use, peak ground acceleration (PGA), and slope (gradient, aspect, elevation). The selection of causative factors considerably influences the frequency of landslides in the area. The result is satisfactory because the AUC value of the chosen model excelled the minimum limit, which is 0.6 (60%). The estimated success rate of the model is 85.7%, which shows that the relevancy of the model is good with the occurrence of landslides. The prediction rate of 84.6% indicates that the applied model is very good at predicting new landslides.Katastrofalni potres koji se dogodio u Paluu 28. rujna 2018. godine, magnitude 7,5 Mw, izazvao je brojne nestabilnosti na padinama, uključujući nastanak velikoga broja klizišta. Ovaj rad predstavlja praktičnu metodu za definiranje procjene podložnosti na klizišta izazvana potresom u regiji Palu i okolnom području. Metoda Weight of Evidence (WoE) korištena je za procjenu odnosa između klizišta izazvanih seizmičkim kretanjem i preduvjeta kako bi se odredila razina podložnosti i izradila karta podložnosti na klizišta izazvana potresom u istraživanom području. 1273 klizišta podijeljena su u dvije serije podataka: podatci za treniranje modela (70 %) i podatci za validaciju modela (30 %). Korišteno je šest odabranih tematskih karata kao faktora koji utječu na pojavu klizišta: litologija, korištenje zemljišta, vršno ubrzanje tla (PGA), nagib padine, orijentacija padine i nadmorska visina. Odabir uzročnih faktora znatno utječe na učestalost klizišta na tom području. Rezultat modela zadovoljavajući je jer je vrijednost AUC odabranoga modela premašila minimalnu granicu koja iznosi 0,6 (60 %). Procijenjena uspješnost modela iznosi 85,7 %, što pokazuje relevantnost modela kod pojave klizišta. Stopa predviđanja od 84,6 % upućuje na to da je primijenjeni model vrlo dobar u predviđanju novih klizišta

Application of innovative technologies in landslide research in the area of the City of Zagreb (Croatia, Europe)

This paper describes the application of innovative technologies for landslide detection, mapping and monitoring in the City of Zagreb since 2010. Airborne Light Detection and Ranging (LiDAR) data are used to visually identify landslides in the Podsljeme Zone over the area of 180 km2 for the purpose of landslide inventory mapping. The total number of landslides in the analyzed area (approx. 1,600 landslides) is estimated based on the average landslide density (9 landslides per square km) from the most reliable geomorphological historical inventory, which was produced in 1979. Examples of the visual interpretation of very-high-resolution bare-earth DEMs (Digital Elevation Model) are given to show the potential of these innovative techniques to identify the landslide contours of the very small, small and moderately small landslides that are characteristic of the study area, which is composed of engineering soils and/or soft rocks (marls). In the framework of the described landslide research, the biggest landslide in the Podsljeme Zone, the Kostanjek landslide (landslide area of 1 km2), was also equipped with an automated near-real time monitoring system that encompassed approximately 40 sensors to monitor landslide movement and landslide causal factors. Monitoring of this deep and large landslide during multiple extreme hydro-meteorological events from January 2013 to January 2015 enabled collection of data for the analysis of landslide movement on the surface and in the underground and as well as analysis of the relationship between landslide reactivations and its triggers, i.e., changes in groundwater level and precipitation. The final aim of the described scientific research in terms of landslide mapping and monitoring is its practical application in land-use planning and civil protection systems in the City of Zagreb. Namely, the conclusions propose reliable and efficient methods for landslide identification and monitoring, which are necessary to provide data and solutions for hazard and risk reduction to local authorities that are managed by the City

Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia

Landslide Susceptibility Assessment is becoming a very productive re-search area, wherein different modeling approaches are practiced to delineate zones of the high-low likelihood of landslide occurrence. However, there is no strong consensus on which approach is the most adequate. The reason behind the lack of the general view on the performance of different approaches could be partially explained by the particularity of each study. To evaluate the effi-ciency of different approaches they need to be applied under the same conditions for the same study area. Herein, we examined three different approaches, in-cluding expert, deterministic and Machine Learning, on the example of Ljubo-vija Municipality in western Serbia. The study area has been known as suscep-tible to landslides, and represents good ground for assessing the chosen methods. It is represented by complex geology, prone to landslides that are commonly hosted in thick weathering crust of Paleozoic formations, composed of schists and meta-sediments. Under extreme triggering conditions, such as the one that unfolded in May 2014, these thick weathering crusts saturate, and give way to a variety of landslide and flash-flood processes that we will be focusing on in this study. The application of the expert-approach, through Analytical Hierarchy Process provided a rough assessment map. The deterministic model, which couples simple infinite slope and hydrological model, provided us with lower quality results, when compared to the expert-based one. This could be explained by the assumptions used in the model are too simplistic to generically model a wide range of landslide typology. Finally, Machine Learning approach, using the Random Forest algorithm, provided significantly better results and showed that it can cope with versatile landslide typology over larger scales. Its AUC performance is about 0.75 which is considerably outperforming the AUC values of the other two models, which were up to 0.55, i.e. at the level of random gues

NOVI PRISTUP PRAĆENJA POMAKA KLIZIŠTA POMOĆU BESPILOTNIH FOTOGRAMETRIJSKIH SUSTAVA

Landslides represent great dangers that can cause fatalities and huge property damage. To prevent or reduce all possible consequences that landslides cause, it is necessary to know the kinematics of the surface and undersurface sliding masses. Geodetic surveying techniques can be used for landslide monitoring and creating a kinematic model of the landslide. One of the most used surveying techniques for landslide monitoring is the photogrammetric survey by Unmanned Aerial System. The results of the photogrammetric survey are dense point clouds, digital terrain models, and digital orthomosaic maps, where landslide displacements can be determined by comparing these results in two measurement epochs. This paper presents a new data processing method with a novel approach for calculating landslide displacements based on Unmanned Aerial System photogrammetric survey data. The main advantage of the new method is that it does not require the production of dense point clouds, digital terrain models, or digital orthomosaic maps to determine displacements. The applicability and accuracy of the new method were tested in a test field with simulated displacements of known values within the range of 20-40 cm in various directions. The new method successfully determined these displacements with a 3D accuracy of ±1.3 cm.Klizišta predstavljaju velike opasnosti koje mogu uzrokovati katastrofalne ljudske žrtve te nanijeti veliku materijalnu štetu. Da bi se spriječile ili umanjile sve moguće posljedice koje klizišta prouzročuju, važno je poznavati kinematiku kretanja površinskih i podzemnih kliznih masa klizišta. Geodetske tehnike izmjere mogu se koristiti za potrebe praćenja te za izradu kinematičkoga modela klizišta. U današnje vrijeme jedna od najčešće korištenih geodetskih tehnika za potrebe praćenja klizišta jest fotogrametrijsko snimanje pomoću bespilotnih zrakoplovnih sustava. Rezultati su takvih snimanja gusti oblaci točaka, digitalni modeli terena te digitalne ortomozaik karte, a na temelju usporedbe tih rezultata u dvjema mjernim epohama mogu se odrediti pomaci klizišta. Ovaj rad predstavlja novu metodu obrade podataka s novim pristupom za određivanje pomaka klizišta na temelju podataka fotogrametrijskoga snimanja bespilotnim zrakoplovnim sustavima. Glavna je prednost nove metode u tome što ne zahtijeva izradu gustih oblaka točaka, digitalnih modela terena ili digitalnih ortomozaik karata za određivanje pomaka. Primjenjivost i točnost nove metode ispitane su na testnome polju sa simuliranim pomacima poznatih vrijednosti čiji su se iznosi kretali u rasponu od 20 do 40 cm u različitim smjerovima. Nova metoda uspješno je odredila te pomake s 3D točnošću od ±1,3 cm