Extraction of flood-modelling related base-data from multisource remote sensing imagery

Flooding is one of the most destructive natural hazards, accounting for over a third of all disaster damage worldwide. In particular in less developed countries (LDCs) this is typically attributed to poor planning, lack of warning systems and limited awareness of the hazard. A number of flood risk models have been developed, but have as yet contributed little to mapping and quantifying the risk in LDCs, for several reasons. In addition to limited human and technical capacity, these models require considerable amounts of current spatial information that is widely lacking, such as landcover, elevation and elements at risk basedata. Collecting those with ground-based methods is difficult, but remote sensing technologies have the potential to acquire them economically. To account for the variety of required information, data from different sensors are needed, some of which may not be available or affordable. Therefore, data interchangeability needs to be considered. Thus we test the potential of high spatial resolution optical imagery and laser scanning data to provide the information required to run such flood risk models as SOBEK. Using segmentation-based analysis in eCognition, Quickbird and laser scanning data were used to extract building footprints as well as the boundaries of informal settlements. Additionally, a landcover map to provide roughness values for the model was derived from the Quickbird image. These basedata were used in model simulations to assess their actual utility, as well as the sensitivity of the model to variations in basedata quality. The project shows that existing remote sensing data and image analysis methods can match the input requirements for flood models, and that, given the unavailability of one dataset, alternative images can fill the gap.</p

TOWARDS A MORE EFFICIENT DETECTION OF EARTHQUAKE INDUCED FAÇADE DAMAGES USING OBLIQUE UAV IMAGERY

Urban search and rescue (USaR) teams require a fast and thorough building damage assessment, to focus their rescue efforts accordingly. Unmanned aerial vehicles (UAV) are able to capture relevant data in a short time frame and survey otherwise inaccessible areas after a disaster, and have thus been identified as useful when coupled with RGB cameras for façade damage detection. Existing literature focuses on the extraction of 3D and/or image features as cues for damage. However, little attention has been given to the efficiency of the proposed methods which hinders its use in an urban search and rescue context. The framework proposed in this paper aims at a more efficient façade damage detection using UAV multi-view imagery. This was achieved directing all damage classification computations only to the image regions containing the façades, hence discarding the irrelevant areas of the acquired images and consequently reducing the time needed for such task. To accomplish this, a three-step approach is proposed: i) building extraction from the sparse point cloud computed from the nadir images collected in an initial flight; ii) use of the latter as proxy for façade location in the oblique images captured in subsequent flights, and iii) selection of the façade image regions to be fed to a damage classification routine. The results show that the proposed framework successfully reduces the extracted façade image regions to be assessed for damage 6 fold, hence increasing the efficiency of subsequent damage detection routines. The framework was tested on a set of UAV multi-view images over a neighborhood of the city of L’Aquila, Italy, affected in 2009 by an earthquake

DAMAGE DETECTION ON BUILDING FAÇADES USING MULTI-TEMPORAL AERIAL OBLIQUE IMAGERY

Over the past decades, a special interest has been given to remote-sensing imagery to automate the detection of damaged buildings. Given the large areas it may cover and the possibility of automation of the damage detection process, when comparing with lengthy and costly ground observations. Currently, most image-based damage detection approaches rely on Convolutional Neural Networks (CNN). These are used to determine if a given image patch shows damage or not in a binary classification approach. However, such approaches are often trained using image samples containing only debris and rubble piles. Since such approaches often aim at detecting partial or totally collapsed buildings from remote-sensing imagery. Hence, such approaches might not be applicable when the aim is to detect façade damages. This is due to the fact that façade damages also include spalling, cracks and other small signs of damage. Only a few studies focus their damage analysis on the façade and a multi-temporal approach is still missing. In this paper, a multi-temporal approach specifically designed for the image classification of façade damages is presented. To this end, three multi-temporal approaches are compared with two mono-temporal approaches. Regarding the multi-temporal approaches the objective is to understand the optimal fusion between the two imagery epochs within a CNN. The results show that the multi-temporal approaches outperform the mono-temporal ones by up to 22% in accuracy

3D City Digital Twin Simulation to Mitigate Heat Risk of Urban Heat Islands

Consecutive high-temperature days, a phenomenon known as heatwaves, are becoming more frequent and intense due to anthro- pogenic climate change. Padua City, characterized by significant urban soil sealing, is particularly vulnerable to these changes and the exacerbation of Urban Heat Island effects. This study integrates Urban Digital Twin technology and Internet of Things concepts within a three-dimensional modelling environment to develop a Nature-Based Solutions scenario simulation tool. This tool is designed to address climate-manmade problems in Padua City. Using sensor-derived air temperature and relative humidity data, our approach provides detailed micro-climate information to identify heat-prone areas in Padua City. According to this in- formation, the first pilot project test of scenario development was selected to assess how best to achieve a cooling effect through the use of green-blue infrastructure in order to combat the heat hazard in Padua City. Furthermore, this study addresses the urgency of developing Nature-Based Solutions in Padua City’s planning to reduce the heat effect during heatwaves

Effect of Gravity and Confinement on Phase Equilibria: A Density Matrix Renormalization Approach

The phase diagram of the 2D Ising model confined between two infinite walls and subject to opposing surface fields and to a bulk "gravitational" field is calculated by means of density matrix renormalization methods. In absence of gravity two phase coexistence is restricted to temperatures below the wetting temperature. We find that gravity restores the two phase coexistence up to the bulk critical temperature, in agreement with previous mean-field predictions. We calculate the exponents governing the finite size scaling in the temperature and in the gravitational field directions. The former is the exponent which describes the shift of the critical temperature in capillary condensation. The latter agrees, for large surface fields, with a scaling assumption of Van Leeuwen and Sengers. Magnetization profiles in the two phase and in the single phase region are calculated. The profiles in the single phase region, where an interface is present, agree well with magnetization profiles calculated from a simple solid-on-solid interface hamiltonian.Comment: 4 pages, RevTeX and 4 PostScript figures included. Final version as published. To appear in Phys. Rev. Let

A symmetric polymer blend confined into a film with antisymmetric surfaces: interplay between wetting behavior and phase diagram

We study the phase behavior of a symmetric binary polymer blend which is confined into a thin film. The film surfaces interact with the monomers via short range potentials. We calculate the phase behavior within the self-consistent field theory of Gaussian chains. Over a wide range of parameters we find strong first order wetting transitions for the semi-infinite system, and the interplay between the wetting/prewetting behavior and the phase diagram in confined geometry is investigated. Antisymmetric boundaries, where one surface attracts the A component with the same strength than the opposite surface attracts the B component, are applied. The phase transition does not occur close to the bulk critical temperature but in the vicinity of the wetting transition. For very thin films or weak surface fields one finds a single critical point at $\phi_c=1/2$. For thicker films or stronger surface fields the phase diagram exhibits two critical points and two concomitant coexistence regions. Only below a triple point there is a single two phase coexistence region. When we increase the film thickness the two coexistence regions become the prewetting lines of the semi-infinite system, while the triple temperature converges towards the wetting transition temperature from above. The behavior close to the tricritical point, which separates phase diagrams with one and two critical points, is studied in the framework of a Ginzburg-Landau ansatz. Two-dimensional profiles of the interface between the laterally coexisting phases are calculated, and the interfacial and line tensions analyzed. The effect of fluctuations and corrections to the self-consistent field theory are discussed.Comment: Phys.Rev.E in prin

Intrinsic profiles and capillary waves at homopolymer interfaces: a Monte Carlo study

A popular concept which describes the structure of polymer interfaces by ``intrinsic profiles'' centered around a two dimensional surface, the ``local interface position'', is tested by extensive Monte Carlo simulations of interfaces between demixed homopolymer phases in symmetric binary (AB) homopolymer blends, using the bond fluctuation model. The simulations are done in an LxLxD geometry. The interface is forced to run parallel to the LxL planes by imposing periodic boundary conditions in these directions and fixed boundary conditions in the D direction, with one side favoring A and the other side favoring B. Intrinsic profiles are calculated as a function of the ``coarse graining length'' B by splitting the system into columns of size BxBxD and averaging in each column over profiles relative to the local interface position. The results are compared to predictions of the self-consistent field theory. It is shown that the coarse graining length can be chosen such that the interfacial width matches that of the self-consistent field profiles, and that for this choice of B the ``intrinsic'' profiles compare well with the theoretical predictions.Comment: to appear in Phys. Rev.

Interface localisation-delocalisation transition in a symmetric polymer blend: a finite-size scaling Monte Carlo study

Using extensive Monte Carlo simulations we study the phase diagram of a symmetric binary (AB) polymer blend confined into a thin film as a function of the film thickness D. The monomer-wall interactions are short ranged and antisymmetric, i.e, the left wall attracts the A-component of the mixture with the same strength as the right wall the B-component, and give rise to a first order wetting transition in a semi-infinite geometry. The phase diagram and the crossover between different critical behaviors is explored. For large film thicknesses we find a first order interface localisation/delocalisation transition and the phase diagram comprises two critical points, which are the finite film width analogies of the prewetting critical point. Using finite size scaling techniques we locate these critical points and present evidence of 2D Ising critical behavior. When we reduce the film width the two critical points approach the symmetry axis $\phi=1/2$ of the phase diagram and for $D \approx 2 R_g$ we encounter a tricritical point. For even smaller film thickness the interface localisation/delocalisation transition is second order and we find a single critical point at $\phi=1/2$. Measuring the probability distribution of the interface position we determine the effective interaction between the wall and the interface. This effective interface potential depends on the lateral system size even away from the critical points. Its system size dependence stems from the large but finite correlation length of capillary waves. This finding gives direct evidence for a renormalization of the interface potential by capillary waves in the framework of a microscopic model.Comment: Phys.Rev.