MultiscaleDTM : an open‐source R package for multiscale geomorphometric analysis

Digital terrain models (DTMs) are datasets containing altitude values above or below a reference level, such as a reference ellipsoid or a tidal datum over geographic space, often in the form of a regularly gridded raster. They can be used to calculate terrain attributes that describe the shape and characteristics of topographic surfaces. Calculating these terrain attributes often requires multiple software packages that can be expensive and specialized. We have created a free, open‐source R package, MultiscaleDTM , that allows for the calculation of members from each of the five major thematic groups of terrain attributes: slope, aspect, curvature, relative position, and roughness, from a regularly gridded DTM. Furthermore, these attributes can be calculated at multiple spatial scales of analysis, a key feature that is missing from many other packages. Here, we demonstrate the functionality of the package and provide a simulation exploring the relationship between slope and roughness. When roughness measures do not account for slope, these attributes exhibit a strong positive correlation. To minimize this correlation, we propose a new roughness measure called adjusted standard deviation. In most scenarios tested, this measure produced the lowest rank correlation with slope out of all the roughness measures tested. Lastly, the simulation shows that some existing roughness measures from the literature that are supposed to be independent of slope can actually exhibit a strong inverse relationship with the slope in some cases

Land-Surface Parameters for Spatial Predictive Mapping and Modeling

Land-surface parameters derived from digital land surface models (DLSMs) (for example, slope, surface curvature, topographic position, topographic roughness, aspect, heat load index, and topographic moisture index) can serve as key predictor variables in a wide variety of mapping and modeling tasks relating to geomorphic processes, landform delineation, ecological and habitat characterization, and geohazard, soil, wetland, and general thematic mapping and modeling. However, selecting features from the large number of potential derivatives that may be predictive for a specific feature or process can be complicated, and existing literature may offer contradictory or incomplete guidance. The availability of multiple data sources and the need to define moving window shapes, sizes, and cell weightings further complicate selecting and optimizing the feature space. This review focuses on the calculation and use of DLSM parameters for empirical spatial predictive modeling applications, which rely on training data and explanatory variables to make predictions of landscape features and processes over a defined geographic extent. The target audience for this review is researchers and analysts undertaking predictive modeling tasks that make use of the most widely used terrain variables. To outline best practices and highlight future research needs, we review a range of land-surface parameters relating to steepness, local relief, rugosity, slope orientation, solar insolation, and moisture and characterize their relationship to geomorphic processes. We then discuss important considerations when selecting such parameters for predictive mapping and modeling tasks to assist analysts in answering two critical questions: What landscape conditions or processes does a given measure characterize? How might a particular metric relate to the phenomenon or features being mapped, modeled, or studied? We recommend the use of landscape- and problem-specific pilot studies to answer, to the extent possible, these questions for potential features of interest in a mapping or modeling task. We describe existing techniques to reduce the size of the feature space using feature selection and feature reduction methods, assess the importance or contribution of specific metrics, and parameterize moving windows or characterize the landscape at varying scales using alternative methods while highlighting strengths, drawbacks, and knowledge gaps for specific techniques. Recent developments, such as explainable machine learning and convolutional neural network (CNN)-based deep learning, may guide and/or minimize the need for feature space engineering and ease the use of DLSMs in predictive modeling tasks

Software development for the optimization of the influence of wind flows within energy applications and sustainable town planning

Tesi en modalitat de cotutela: Universitat Politècnica de Catalunya i Università degli Studi Gabriele d'AnnuzioThis thesis aims to propose and validate an innovative, fully open-source framework capable of performing multiscale analysis for the assessment of local wind flows within the urban fabric. Each part of the framework is fully editable and license-free. A crucial aspect of the adopted methodology concerns the coupling between the mesoscale-microscale analysis in order to increase the accuracy of the final results. In detail, the procedure is based on the interaction between the mesoscale values and the microscale values obtained considering different wind directions. The core of the work is the design and development of an open-source application that allows to generate 3D numerical models for microscale analysis in an automatic way and providing only some basic information. The main benefit of such a procedure is the drastic reduction of the time required for the creation of numerical models and the facilitation, in general, of microscale simulations. The process of geodata retrieval and the subsequent 3D modeling phase, in fact, are completely automated. The results obtained with the above application are compared with those obtained with a commercial software, widely used in the sector, in order to test its potential and accuracy. Finally, the airflows estimated through the application of the whole proposed framework are used as input for dynamic energy simulations to identify the energy consumption, divided into heating and cooling, of a real building located in an urban context. The framework has been tested assuming a domain located in the city of Pescara (central Italy). However, it is important to emphasize that its application to different urban contexts does not present any constraint related, for example, to the geographical location of the area of interest and that it is, therefore, possible to replicate the analysis in any part of the world.La presente tesis tiene como objetivo proponer y validar un marco de trabajo innovador y totalmente de código abierto (open-source) capaz de realizar análisis multiescala para evaluar los flujos de vientos locales dentro del tejido urbano. Cada etapa del marco es totalmente editable y libre de licencia. Uno de los aspectos cruciales de la metodología adoptada es el acoplamiento entre las simulaciones mesoescala-microescala, las cuales permiten aumentar la precisión de los resultados finales obtenidos. Concretamente, el procedimiento se basa en la interacción entre los valores mesoescala y microescala obtenidos considerando diferentes direcciones del viento. El núcleo de la tesis es el diseño y desarrollo de una aplicación open-source capaz de generar automáticamente modelos 3D para el análisis microescala, proporcionando únicamente ciertos datos básicos. El principal beneficio de este procedimiento es la drástica reducción del tiempo requerido para la creación de modelos numéricos y la facilidad, en general, de las simulaciones microescala. El proceso de recuperación de datos de carácter geográficos (geodata) y la posterior fase de modelado 3D están, de hecho, completamente automatizados. Los resultados obtenidos con la aplicación desarrollada son comparados con los generados a través de un software comercial, el cual es usado ampliamente en el sector, con el objetivo de validar y probar el potencial y precisión de la aplicación. Finalmente, los flujos de aire calculados a través de la aplicación del marco de trabajo propuesto son usados como datos de entrada para la realización de simulaciones energéticas dinámicas, las cuales permiten identificar el consumo de energía, dividido este en los requisitos de calefacción y refrigeración, de un edificio real ubicado dentro de un contexto urbano. El marco de trabajo y la metodología adoptada han sido testeados asumiendo un dominio local en la ciudad de Pescara, ubicada en el centro de Italia. No obstante, es importante destacar que su aplicación a diferentes contextos urbanos no presenta ninguna restricción, como por ejemplo la ubicación geográfica de interés, siendo por tanto posible replicar el análisis en cualquier parte del mundo independientemente de la ubicación del caso de estudio.La presente tesi intende proporre e validare un framework innovativo, completamente open-source, in grado di eseguire analisi multiscala per la valutazione dei flussi del vento locale all'interno del tessuto urbano. Ogni fase del framework è interamente editabile e a licenza grauita. Aspetto cruciale della metodologia adottata riguarda l’accoppiamento tra le analisi mesoscala-microscala al fine di incrementare l’accuratezza dei risultati finali. Nel dettaglio, la procedura si basa sul far dialogare i valori stimati dalla mesoscala con quelli della microscala ottenuti considerando diverse direzioni del vento in ingresso. Il nucleo principale del lavoro è la progettazione e lo sviluppo di un’applicazione in ambiente open-source che permetta di generare modelli numerici 3D per le analisi microscala in maniera automatica e fornendo solo alcune informazioni basiche. Beneficio principale di una procedura così individuata è la drastica riduzione dei tempi necessari per la realizzazione di modelli numerici e l’agevolazione, in generale, delle simulazioni microscala. Il processo di reperimento dei geodati e la successiva fase di modellazione 3D, infatti, sono completamente automatizzate. I risultati ottenuti con la suddetta applicazione sono confrontati con quelli ottenuti con un software commerciale, largamente utilizzato nel settore, al fine di testarne le potenzialità e l’accuratezza. Infine, i flussi di aria stimati mediante l’applicazione dell’intero framework proposto, sono impiegati come input per le simulazioni energetiche dinamiche per identificare il consumo energetico, suddiviso in riscaldamento e raffrescamento, di un edificio reale localizzato in un contesto urbano. Il framework è stato testato assumendo un dominio situato nella città di Pescara (centro Italia). Tuttavia, è importante sottolineare che, la sua applicazione a diversi contesti urbani non presenta alcun vincolo legato, ad esempio, alla posizione geografica dell’area di interesse e che è quindi possibile replicare le analisi in qualsiasi parte del mondo.Postprint (published version

Modification of the National Weather Service Distributed Hydrologic Model for subsurface water exchanges between grids

To account for spatial variability of precipitation, as well as basin physiographic properties, the National Weather Service (NWS) has developed a distributed version of its hydrologic component, termed the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM). Because channels are the only source of water exchange between neighboring computational elements, the absence of such exchange has been identified as a weakness in the model. The primary objective of this paper is to modify the model structure to account for subsurface water exchanges without dramatically altering the conceptual framework of the water balance module. The subsurface exchanges are established by partitioning the slow response components released from the lower layer storages into two parts: the first part involves the grid's conceptual channel, while the second is added to the lower layer storages of the downstream pixel. Realizing the deficiency of the water balance module to locate the lower zone layers in sufficient depths, a complementary study is conducted to test the feasibility of further improvement in the modified model by equally shifting downward the lower zone layers of all pixels over the basin. The Baron Fork at Eldon, Oklahoma, is chosen as the test basin. Ten years of grid-based multisensor precipitation data are used to investigate the effects of the modification, plus shifting the lower zone layers on model performance. The results show that the modified-shifted HL-RDHM can markedly improve the streamflow simulations at the interior point, as well as very high peak-flow simulations at the basin's outlet. Copyright 2011 by the American Geophysical Union

A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures

Change detection and deformation monitoring is an active area of research within the field of engineering surveying as well as overlapping areas such as structural and civil engineering. The application of Terrestrial Laser Scanning (TLS) techniques for change detection and deformation monitoring of concrete structures has increased over the years as illustrated in the past studies. This paper presents a review of literature on TLS application in the monitoring of structures and discusses registration and georeferencing of TLS point cloud data as a critical issue in the process chain of accurate deformation analysis. Past TLS research work has shown some trends in addressing issues such as accurate registration and georeferencing of the scans and the need of a stable reference frame, TLS error modelling and reduction, point cloud processing techniques for deformation analysis, scanner calibration issues and assessing the potential of TLS in detecting sub-centimetre and millimetre deformations. However, several issues are still open to investigation as far as TLS is concerned in change detection and deformation monitoring studies such as rigorous and efficient workflow methodology of point cloud processing for change detection and deformation analysis, incorporation of measurement geometry in deformation measurements of high-rise structures, design of data acquisition and quality assessment for precise measurements and modelling the environmental effects on the performance of laser scanning. Even though some studies have attempted to address these issues, some gaps exist as information is still limited. Some methods reviewed in the case studies have been applied in landslide monitoring and they seem promising to be applied in engineering surveying to monitor structures. Hence the proposal of a three-stage process model for deformation analysis is presented. Furthermore, with technological advancements new TLS instruments with better accuracy are being developed necessitating more research for precise measurements in the monitoring of structures

Geomorphometry 2020. Conference Proceedings

Geomorphometry is the science of quantitative land surface analysis. It gathers various mathematical, statistical and image processing techniques to quantify morphological, hydrological, ecological and other aspects of a land surface. Common synonyms for geomorphometry are geomorphological analysis, terrain morphometry or terrain analysis and land surface analysis. The typical input to geomorphometric analysis is a square-grid representation of the land surface: a digital elevation (or land surface) model. The first Geomorphometry conference dates back to 2009 and it took place in Zürich, Switzerland. Subsequent events were in Redlands (California), Nánjīng (China), Poznan (Poland) and Boulder (Colorado), at about two years intervals. The International Society for Geomorphometry (ISG) and the Organizing Committee scheduled the sixth Geomorphometry conference in Perugia, Italy, June 2020. Worldwide safety measures dictated the event could not be held in presence, and we excluded the possibility to hold the conference remotely. Thus, we postponed the event by one year - it will be organized in June 2021, in Perugia, hosted by the Research Institute for Geo-Hydrological Protection of the Italian National Research Council (CNR IRPI) and the Department of Physics and Geology of the University of Perugia. One of the reasons why we postponed the conference, instead of canceling, was the encouraging number of submitted abstracts. Abstracts are actually short papers consisting of four pages, including figures and references, and they were peer-reviewed by the Scientific Committee of the conference. This book is a collection of the contributions revised by the authors after peer review. We grouped them in seven classes, as follows: • Data and methods (13 abstracts) • Geoheritage (6 abstracts) • Glacial processes (4 abstracts) • LIDAR and high resolution data (8 abstracts) • Morphotectonics (8 abstracts) • Natural hazards (12 abstracts) • Soil erosion and fluvial processes (16 abstracts) The 67 abstracts represent 80% of the initial contributions. The remaining ones were either not accepted after peer review or withdrawn by their Authors. Most of the contributions contain original material, and an extended version of a subset of them will be included in a special issue of a regular journal publication

Soil Spatial Scaling: Modelling variability of soil properties across scales using legacy data

Understanding how soil variability changes with spatial scale is critical to our ability to understand and model soil processes at scales relevant to decision makers. This thesis uses legacy data to address the ongoing challenge of understanding soil spatial variability in a number of complementary ways. We use a range of information: precision agriculture studies; compiled point datasets; and remotely observed raster datasets. We use classical geostatistics, but introduce a new framework for comparing variability of spatial properties across scales. My thesis considers soil spatial variability from a number of geostatistical angles. We find the following: • Field scale variograms show differing variance across several magnitudes. Further work is required to ensure consistency between survey design, experimental methodology and statistical methodology if these results are to become useful for comparison. • Declustering is a useful tool to deal with the patchy design of legacy data. It is not a replacement for an evenly distributed dataset, but it does allow the use of legacy data which would otherwise have limited utility. • A framework which allows ‘roughness’ to be expressed as a continuous variable appears to fit the data better than the mono-fractal or multi-fractal framework generally associated with multi–scale modelling of soil spatial variability. • Soil appears to have a similar degree of stochasticity to short range topographic variability, and a higher degree of stochasticity at short ranges (less than 10km and 100km) than vegetation and Radiometrics respectively. • At longer ranges of variability (i.e. around 100km) only rainfall and height above sea level show distinctly different stochasticity. • Global variograms show strong isotropy, unlike the variograms for the Australian continent

Climatic and Topologic Controls on the Complexity of River Networks

The emergence and evolution of channel networks are controlled by the competition between the hillslopes and fluvial processes on the landscape. Investigating the geomorphic and topologic properties of these networks is important for developing predictive models describing the network dynamics under changing environment as well as for quantifying the roles of processes in creating distinct patterns of channel networks. In this dissertation, the response of landscapes to changing climatic forcing via numerical-modeling and field observations was investigated. A new framework was proposed to evaluate the complexity of catchments using two different representations of channel networks. The structural complexity was studied using the width function, which characterizes the spatial arrangement of channels. Whereas, the functional complexity was explored using the incremental area function, capturing the patterns of transport of fluxes. Our analysis reveals stronger controls of topological connectivity on the functional complexity than on structural complexity, indicating that the unchannelized surface (hillslope) contributes to the increase of heterogeneity in transport processes. Furthermore, the channel network structure was investigated using a physically-based numerical landscape evolution model for varying hillslope and fluvial processes. Different magnitudes of soil transport (D) and fluvial incision (K) coefficients represent different magnitudes of hillslope and fluvial processes. We show that different combinations of D and K result in distinct branching structure in landscapes. For example, for smaller D and K combinations (mimicking dry climate), a higher number of branching channels was observed. Whereas, for larger D and K combinations (mimicking humid climate), a higher number of side-branching channels is obtained. These results are consistent with the field observations suggesting that varying climatic conditions imprint distinct signatures on the branching structure of channel networks

Congiungere la modellazione dei movimenti di massa alla realtà

I flussi di massa sono pericoli naturali di tipo gravitativo tipici delle zone montane che causano ogni anno perdite economiche e vittime. I modelli numerici sono strumenti per prevedere la propagazione di potenziali eventi di flussi di massa su una determinata topografia, ma questi richiedono diversi input. Gli input e i processi che sostanzialmente influenzano i risultati dei modelli sono rappresentati dalla dal volume, dalle condizioni di innesco e dalle interazioni topografia – flusso di massa. Pertanto, l'obiettivo principale della tesi è quello di migliorare la quantificazione del volume coinvolto in un evento di flusso di massa e di aumentare la rappresentazione dell’interazione tra il flusso e la topografia. Quindi, sono stati studiati due tipi di flussi di massa: debris flow e valanghe di neve. Per quanto riguarda i debris flow, la tesi vuole migliorare l'affidabilità dei modelli analizzando l'aumento del volume del flusso attraverso l'erosione del letto del canale e il collasso di strutture di mitigazione. Per le valanghe di neve, lo studio ha come obbiettivo quello di migliorare l'identificazione delle possibili aree di distacco. La tesi è strutturata come una raccolta di articoli dei quali tre sono stati pubblicati e uno è in fase di revisione. Il primo articolo ha migliorato la rappresentazione dei fenomeni erosivi nei modelli numerici grazie ai dati di un evento di debris flow avvenuto nel bacino del rio Gere (Veneto, IT). Una funzione basata sui valori di pendenza è stata definita per calcolare il coefficiente di erosione, successivamente utilizzato per riprodurre l’erosione osservata nel canale. I risultati sono utili per migliorare l'accuratezza di futuri scenari da debris flow per i quali l'erosione è un importante processo nella dinamica del flusso. Il secondo studio ha definito una procedura per simulare l'effetto del collasso delle briglie di consolidamento in un evento di debris flow. La metodologia è stata sviluppata nel rio Rotian (Trentino, IT), dove un evento di pioggia estrema ha innescato un debris flow che ha provocato il collasso di una serie di 15 briglie. La metodologia sviluppata può essere direttamente applicata per mappare il rischio residuo dei canali da debris flow in cui siano presenti opere o dove la mancanza di manutenzione delle misure di mitigazione può diminuire la loro stabilità. Il terzo progetto riguarda lo studio della rugosità del terreno. Sette algoritmi di calcolo della rugosità sono stati testati in due aree studio al fine di identificare quale algoritmo possa rappresentare nel modo più appropriato le tipologie del terreno che interagiscono con i fenomeni di massa. I risultati hanno mostrato che il miglior algoritmo è risultato il vector ruggedness e che l’utilizzo di una risoluzione maggiore non ha migliorato le performance. Il quarto progetto ha analizzato la capacità di protezione delle foreste colpite da tempeste di vento. Due nuovi algoritmi per valutare le caratteristiche degli alberi abbattuti sono stati sviluppati. I risultati hanno evidenziato che il momento di protezione minimo delle foreste contro le valanghe di neve è dopo 10 anni l'evento di tempesta. Inoltre, gli algoritmi possono essere applicati direttamente su scala regionale per la gestione e il monitoraggio delle aree forestali colpite da tempeste. I diversi studi hanno analizzato i processi di erosione, l'effetto del collasso di briglie e l'identificazione di potenziali aree di innesco. I risultati dei quattro progetti hanno risposto ai corrispondenti obbiettivi, migliorando la comprensione dei flussi di massa e quindi la previsione di eventi futuri. Inoltre, i progetti forniscono importanti risultati metodologici e nuovi metodi sono stati sviluppati e testati al fine di migliorare la stima del volume dei flussi di massa. Tali metodi sono inoltre applicabili al di fuori delle aree di studio prese in esame, dando supporto a diversi stakeholder nella gestione dei rischi naturali.Mass flows are gravitational natural hazards typical of mountain areas causing economic losses and fatalities every year. Numerical models are a way to predict the propagation of potential mass flow events over a certain topography. To appropriately reproduce future events, models required different inputs. Inputs and processes consistently affecting the outcomes of mass flow models regard the released volume, the triggering conditions and the interaction with the topography and the features on the ground once the flow is in motion. Therefore, the main objective of the thesis is to improve the quantification of the input volume and to improve the implementation of processes of interaction with the basal topography. In this context, the focus has been placed on two types of mass flows: debris flows and snow avalanches. Regarding debris flows, the study aims to improve the reliability of models to capture the increase in flow volume through channel bed erosion and mitigation structure collapse. For snow avalanches, the study wants to improve the identification of possible avalanche release areas taking into account the role of different types of vegetation structures. The thesis was structured as a collection of articles of which three have been published and one is currently under review. The first paper investigated the improvement of debris flow erosion in computational models thanks to data of a severe event occurred in the Gere catchment (Veneto, IT). A function based on a smoothed terrain slope map was calibrated to derive the erosion coefficient, successively used to reproduce the observed erosion process occurred in the channel. Results can improve the reliability of future scenarios related to debris flows for which bed erosion plays an important role in volume increase. The second study defined a procedure to simulate the effect of check dam collapse in a debris flow event. The methodology was developed in the rio Rotian (Trentino, IT) where an extreme rainfall event triggered a debris flow that collapsed a series of 15 check dams. The adopted methodology can be straight applied to map the residual risk of mountain channels or where the lack of maintenance may decrease torrent countermeasure stability. The third project involves the study of terrain roughness. We tested seven algorithms computing terrain roughness in two study areas with the aim to identify which roughness algorithm can represent in the most appropriate way the features on the ground interacting with natural hazards. Outcomes showed that the best algorithm resulted the vector ruggedness and that the increase in data resolution did not improve the classification performance. Results can improve the reliability of mass flow propagation models over natural areas. The fourth project analysed the protection capacity of forests affected by windstorms. We developed and tested two algorithms to assess the characteristics of abated trees. Results assessed that the time of minimum level of forest protection against snow avalanches in 10 years after the storm event. The developed algorithms can be straight applied at regional scale to monitor and improve the management of windthrow areas. The projects investigated entrainment processes, effect of mitigation structure failures and the identification of potential triggering areas. Outcomes of the four projects filled the respective gaps of knowledge, improving the understanding of mass flows and then the prediction of future events. Furthermore, the projects have strong methodological outcomes and new methods to improve the volume estimation of mass flows have been developed and tested. Such methods are further applicable outside of the study areas, supporting different stakeholders in the management of natural hazards of mountain areas