Urban nighttime leisure space mapping with nighttime light images and POI data

Urban nighttime leisure spaces (UNLSs), important urban sites of nighttime economic activity, have created enormous economic and social benefits. Both the physical features (e.g., location, shape, and area) and the social functions (e.g., commercial streets, office buildings, and entertainment venues) of UNLSs are important in UNLS mapping. However, most studies rely solely on census data or nighttime light (NTL) images to map the physical features of UNLSs, which limits UNLS mapping, and few studies perform UNLS mapping from a social function perspective. Point-of-interest (POI) data, which can reflect social activity functions, are needed. As a result, a novel methodological UNLS mapping framework, that integrates NTL images and POI data is required. Consequently, we first extracted high-NTL intensity and high-POI density areas from composite data as areas with high nightlife activity levels. Then, the POI data were analyzed to identify the social functions of leisure spaces revealing that nighttime leisure activities are not abundant in Beijing overall, the total UNLS area in Beijing is 31.08 km(2), which accounts for only 0.2% of the total area of Beijing. In addition, the nightlife activities in the central urban area are more abundant than those in the suburbs. The main urban area has the largest UNLS area. Compared with the nightlife landmarks in Beijing established by the government, our results provide more details on the spatial pattern of nighttime leisure activities throughout the city. Our study aims to provide new insights into how multisource data can be leveraged for UNLS mapping to enable researchers to broaden their study scope. This investigation can also help government departments better understand the local nightlife situation to rationally formulate planning and adjustment measures

Safer_RAIN: A DEM-based hierarchical filling-&-spilling algorithm for pluvial flood hazard assessment and mapping across large urban areas

The increase in frequency and intensity of extreme precipitation events caused by the changing climate (e.g., cloudbursts, rainstorms, heavy rainfall, hail, heavy snow), combined with the high population density and concentration of assets, makes urban areas particularly vulnerable to pluvial flooding. Hence, assessing their vulnerability under current and future climate scenarios is of paramount importance. Detailed hydrologic-hydraulic numerical modeling is resource intensive and therefore scarcely suitable for performing consistent hazard assessments across large urban settlements. Given the steadily increasing availability of LiDAR (Light Detection And Ranging) high-resolution DEMs (Digital Elevation Models), several studies highlighted the potential of fast-processing DEM-based methods, such as the Hierarchical Filling-&-Spilling or Puddle-to-Puddle Dynamic Filling-&-Spilling Algorithms (abbreviated herein as HFSAs). We develop a fast-processing HFSA, named Safer_RAIN, that enables mapping of pluvial flooding in large urban areas by accounting for spatially distributed rainfall input and infiltration processes through a pixel-based Green-Ampt model. We present the first applications of the algorithm to two case studies in Northern Italy. Safer_RAIN output is compared against ground evidence and detailed output from a two-dimensional (2D) hydrologic and hydraulic numerical model (overall index of agreement between Safer_RAIN and 2D benchmark model: sensitivity and specificity up to 71% and 99%, respectively), highlighting potential and limitations of the proposed algorithm for identifying pluvial flood-hazard hotspots across large urban environments

LakeCC: a tool for efficiently identifying lake basins with application to palaeogeographic reconstructions of North America

Along the margins of continental ice sheets, lakes formed in isostatically depressed basins duringglacial retreat. Their shorelines and extent are sensitive to the ice margin and the glacial history of the region.Proglacial lakes, in turn, also impact the glacial isostatic adjustment due to loading, and ice dynamics by posing amarine‐like boundary condition at the ice margin. In this study we present a tool that efficiently identifies lake basinsand the corresponding maximum water level for a given ice sheet and topography reconstruction. This algorithm,called the LakeCC model, iteratively checks the whole map for a set of increasing water levels and fills isolated basinsuntil they overflow into the ocean. We apply it to the present‐day Great Lakes and the results show good agreement(∼1−4%) with measured lake volume and depth. We then apply it to two topography reconstructions of NorthAmerica between the Last Glacial Maximum and the present. The model successfully reconstructs glacial lakes suchas Lake Agassiz, Lake McConnell and the predecessors of the Great Lakes. LakeCC can be used to judge the quality ofice sheet reconstructions

Investigating impacts of natural and human-induced environmental changes on hydrological processes and flood hazards using a GIS-based hydrological/hydraulic model and remote sensing data

Natural and human-induced environmental changes have been altering the earth's surface and hydrological processes, and thus directly contribute to the severity of flood hazards. To understand these changes and their impacts, this research developed a GISbased hydrological and hydraulic modeling system, which incorporates state-of-the-art remote sensing data to simulate flood under various scenarios. The conceptual framework and technical issues of incorporating multi-scale remote sensing data have been addressed. This research develops an object-oriented hydrological modeling framework. Compared with traditional lumped or cell-based distributed hydrological modeling frameworks, the object-oriented framework allows basic spatial hydrologic units to have various size and irregular shape. This framework is capable of assimilating various GIS and remotely-sensed data with different spatial resolutions. It ensures the computational efficiency, while preserving sufficient spatial details of input data and model outputs. Sensitivity analysis and comparison of high resolution LIDAR DEM with traditional USGS 30m resolution DEM suggests that the use of LIDAR DEMs can greatly reduce uncertainty in calibration of flow parameters in the hydrologic model and hence increase the reliability of modeling results. In addition, subtle topographic features and hydrologic objects like surface depressions and detention basins can be extracted from the high resolution LiDAR DEMs. An innovative algorithm has been developed to efficiently delineate surface depressions and detention basins from LiDAR DEMs. Using a time series of Landsat images, a retrospective analysis of surface imperviousness has been conducted to assess the hydrologic impact of urbanization. The analysis reveals that with rapid urbanization the impervious surface has been increased from 10.1% to 38.4% for the case study area during 1974 - 2002. As a result, the peak flow for a 100-year flood event has increased by 20% and the floodplain extent has expanded by about 21.6%. The quantitative analysis suggests that the large regional detentions basins have effectively offset the adverse effect of increased impervious surface during the urbanization process. Based on the simulation and scenario analyses of land subsidence and potential climate changes, some planning measures and policy implications have been derived for guiding smart urban growth and sustainable resource development and management to minimize flood hazards

Identification of the emplacements with the greatest potential for the establishment of a sustainable wetland on Moncloa Campus (University City of Madrid)

García de Jalón, Diego (tutor académico)Los humedales son los ecosistemas que aportan más servicios ecosistémicos por unidad de superficie para la flora, la fauna y la especie humana. A pesar de los servicios de regulación que aportan los humedales, como el control de las inundaciones, la regulación local del clima y la purificación de aguas, entre otros, la degradación y destrucción de estos ecosistemas se ha incrementado en los últimos años, impulsado en muchos lugares por el aumento de la urbanización y la agricultura. El previsto crecimiento urbano que se espera en los próximos años supone una oportunidad para la planificación de grandes ciudades que incluya infraestructura verde y azul. El presente trabajo pretende realizar una prospección del Campus de Moncloa de la Ciudad Universitaria de Madrid para buscar zonas idóneas para el establecimiento de un humedal. Mediante el uso de sistemas de información geográfica se han localizado las depresiones existentes en la red de drenaje dentro del Campus, que puedan ser aprovechadas para recrear un humedal. Estas depresiones son las zonas con mayor acumulación de escorrentía, lo que permitirá aprovechar al máximo las lluvias. Se ha realizado un balance hídrico de la zona de estudio, para obtener información sobre el déficit hídrico, la cantidad aproximada de agua excedente en el sistema y los meses del año con mayor estrés hídrico, así como para tener una idea del tipo de humedal que podría albergar el área de estudio según su hidroperiodo. Proponemos una herramienta de planificación espacial para ayudar en la toma de decisiones.Wetlands are classified among the ecosystems which provide the most quantity of ecosystem services per unit of surface, benefiting flora, fauna and the human species. Despite the regulatory services that wetlands provide, such as flood control, local climate regulation and water purification, the degradation and destruction of these ecosystems has increased in recent years, driven by rapid urbanization and agriculture expansion and intensification. The urban growth expected for the following years can serve as a pivotal moment to include green and blue infrastructure into the spatial planification of large cities. This work pretends to carry out a prospection of the Campus de Moncloa of Ciudad Universitaria de Madrid with the objective of finding suitable areas for the establishment of a wetland. Through geographical information systems (GIS) the topographical depressions of the drainage network have been located, which can be used to recreate a wetland. These topographic depressions are located in zones with the largest accumulation of runoff, a fact that will allow to take the maximum advantage of the rain. A hydric balance of the study area has also been performed in order to obtain information about the water deficit, the approximate amount of surplus water in the system and the months with the highest water deficit. These hydric balance will also serve to have an approximate idea of the typology of wetland that the study area can harbor according to its hydroperiod. We propose here a tool of spatial planification to help with decision making.Máster Universitario en Restauración de Ecosistema

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

Geometric data understanding : deriving case specific features

There exists a tradition using precise geometric modeling, where uncertainties in data can be considered noise. Another tradition relies on statistical nature of vast quantity of data, where geometric regularity is intrinsic to data and statistical models usually grasp this level only indirectly. This work focuses on point cloud data of natural resources and the silhouette recognition from video input as two real world examples of problems having geometric content which is intangible at the raw data presentation. This content could be discovered and modeled to some degree by such machine learning (ML) approaches like deep learning, but either a direct coverage of geometry in samples or addition of special geometry invariant layer is necessary. Geometric content is central when there is a need for direct observations of spatial variables, or one needs to gain a mapping to a geometrically consistent data representation, where e.g. outliers or noise can be easily discerned. In this thesis we consider transformation of original input data to a geometric feature space in two example problems. The first example is curvature of surfaces, which has met renewed interest since the introduction of ubiquitous point cloud data and the maturation of the discrete differential geometry. Curvature spectra can characterize a spatial sample rather well, and provide useful features for ML purposes. The second example involves projective methods used to video stereo-signal analysis in swimming analytics. The aim is to find meaningful local geometric representations for feature generation, which also facilitate additional analysis based on geometric understanding of the model. The features are associated directly to some geometric quantity, and this makes it easier to express the geometric constraints in a natural way, as shown in the thesis. Also, the visualization and further feature generation is much easier. Third, the approach provides sound baseline methods to more traditional ML approaches, e.g. neural network methods. Fourth, most of the ML methods can utilize the geometric features presented in this work as additional features.Geometriassa käytetään perinteisesti tarkkoja malleja, jolloin datassa esiintyvät epätarkkuudet edustavat melua. Toisessa perinteessä nojataan suuren datamäärän tilastolliseen luonteeseen, jolloin geometrinen säännönmukaisuus on datan sisäsyntyinen ominaisuus, joka hahmotetaan tilastollisilla malleilla ainoastaan epäsuorasti. Tämä työ keskittyy kahteen esimerkkiin: luonnonvaroja kuvaaviin pistepilviin ja videohahmontunnistukseen. Nämä ovat todellisia ongelmia, joissa geometrinen sisältö on tavoittamattomissa raakadatan tasolla. Tämä sisältö voitaisiin jossain määrin löytää ja mallintaa koneoppimisen keinoin, esim. syväoppimisen avulla, mutta joko geometria pitää kattaa suoraan näytteistämällä tai tarvitaan neuronien lisäkerros geometrisia invariansseja varten. Geometrinen sisältö on keskeinen, kun tarvitaan suoraa avaruudellisten suureiden havainnointia, tai kun tarvitaan kuvaus geometrisesti yhtenäiseen dataesitykseen, jossa poikkeavat näytteet tai melu voidaan helposti erottaa. Tässä työssä tarkastellaan datan muuntamista geometriseen piirreavaruuteen kahden esimerkkiohjelman suhteen. Ensimmäinen esimerkki on pintakaarevuus, joka on uudelleen virinneen kiinnostuksen kohde kaikkialle saatavissa olevan datan ja diskreetin geometrian kypsymisen takia. Kaarevuusspektrit voivat luonnehtia avaruudellista kohdetta melko hyvin ja tarjota koneoppimisessa hyödyllisiä piirteitä. Toinen esimerkki koskee projektiivisia menetelmiä käytettäessä stereovideosignaalia uinnin analytiikkaan. Tavoite on löytää merkityksellisiä paikallisen geometrian esityksiä, jotka samalla mahdollistavat muun geometrian ymmärrykseen perustuvan analyysin. Piirteet liittyvät suoraan johonkin geometriseen suureeseen, ja tämä helpottaa luonnollisella tavalla geometristen rajoitteiden käsittelyä, kuten väitöstyössä osoitetaan. Myös visualisointi ja lisäpiirteiden luonti muuttuu helpommaksi. Kolmanneksi, lähestymistapa suo selkeän vertailumenetelmän perinteisemmille koneoppimisen lähestymistavoille, esim. hermoverkkomenetelmille. Neljänneksi, useimmat koneoppimismenetelmät voivat hyödyntää tässä työssä esitettyjä geometrisia piirteitä lisäämällä ne muiden piirteiden joukkoon

Modeling soil erosion and reservoir sedimentation at hillslope and catchment scale in semi-arid Burkina Faso

Soil erosion is a major factor of land degradation in Sub-Saharan Africa. The loss of nutrient-rich topsoil from hillslopes causes severe agricultural problems for an extremely vulnerable agricultural society that depends on soil quality as a fundamental base for its livelihood. The removal of soil in source areas leads to sediment accumulation in sink areas such as dammed reservoirs. Especially the siltation of small reservoirs is seen as a serious environmental threat in Burkina Faso, where more than a thousand dams have been built to store unevenly distributed rainwater for the dry season. These dams are in danger of losing their function as essential water reservoirs for domestic use, irrigation and stock watering in the near future. This study presents an integrative, scale-dependent approach to assess on-site and off-site impacts of soil erosion by quantifying the magnitude and intensity of soil loss/deposition at hillslope and catchment scales and by considering the spatial dimension of these processes in a complex landscape system in southwestern Burkina Faso. At the hillslope scale, the spatial variability of soils is analyzed by soil profile investigations along a catena and subsequently considered in soil erosion simulations by the physically-based WEPP model. WEPP model predictions indicate that although average soil loss rates simulated for the entire hillslope are comparatively low, they can be forty times higher at particular hillslope positions. These spatial differences, even in the relatively flat terrain of Burkina Faso, are also confirmed by Cs-137 measurements with averaged soil loss rates of less than 5 t/ha/yr and maximum erosion rates of more than 50 t/ha/yr in erosion hotspots. The identification of such hazard zones can be used to target site-specific land management options. WEPP model simulations show that the application of stone lines, minimum tillage, contour farming and residue management could reduce soil loss by up to 95 %, 70 %, 55 % and 45 % at these erosion-prone hillslope positions. At the catchment scale, sedimentation rates of three reservoirs are analyzed by bathymetric surveys, sediment core sampling and sediment yield calculations using the soil erosion and sediment delivery model WaTEM/SEDEM. For the model, a digital elevation models is generated and land-cover maps are derived from remote sensing images. A comparison between the initial and actual reservoir bed morphology shows that the reservoirs have lost approximately 10-15 % of their original storage capacity and more than 60 % of their inactive storage volume in the last 15 to 20 years. During that period, a sedimentation layer of 0.3 m to 0.5 m thickness has accumulated on the reservoir bed. This was verified by stratigraphical changes and downcore variations in sediment properties and Cs-137 concentrations. Predictions by WaTEM/SEDEM show similar magnitudes of siltation with specific sediment yield rates of 0.5 t/ha/yr to 3.4 t/ha/yr. These results indicate that the half-life of the dams might be reached in about 25 years assuming constant siltation rates under current conditions. In order to identify the sediment source areas and the potential soil-erosion risk zones leading to these high siltation rates, a spatially-explicit soil erosion and deposition hazard maps generated by WaTEM/SEDEM can be used. These hazard maps present a powerful tool to support policy makers in their decisions on which landscapes are primarily at risk and where action plans for sustainable soil and water conservation should be implemented.Modellierung von Bodenerosion und Sedimentation von Stauseen auf Hang- und Wassereinzugsgebietsebene im semi-ariden Burkina Faso Die Bodenerosion hat einen wesentlichen Einfluss auf die Landdegradierung semi-arider Gebiete in Afrika südlich der Sahara. Der Abtrag von humusreichem Oberboden am Hang verursacht schwerwiegende landwirtschaftliche Probleme, insbesondere für eine fragile Ackerbaugesellschaft, die von einer guten Bodenqualität zur Sicherung ihrer Existenzgrundlage abhängig ist. Der Abtrag von Bodensedimenten aus Quellgebieten hat gleichzeitig die Akkumulation von Sedimenten in Zielgebieten wie beispielsweise eingedämmten Rückhaltebecken zur Folge. Insbesondere die Verschlämmung von Kleinstauseen stellt für das Land Burkina Faso, in dem über tausend Staudämme gebaut worden sind, um das Regenwasser der uneinheitlich verteilten Niederschläge für die Trockenzeit stauen zu können, ein zunehmendes Umweltproblem dar. In naher Zukunft drohen diese Staudämme ihre Funktion als unverzichtbare Wasserspeicher für Haushalt, Bewässerungsfeldbau und Viehzucht zu verlieren. Um die Auswirkungen von Bodenerosion sowohl on-site als auch off-site zu bewerten, verfolgt die vorliegende Arbeit einen integrativen, skalenabhängigen Ansatz, bei dem einerseits das Ausmaß und die Intensität von Bodenerosion und deren Ablagerung auf Hang- und Einzugsgebietsebene quantifiziert werden und bei der andererseits die räumliche Dimension dieser Prozesse in einem komplexen Landschaftssystem im Südwesten Burkina Fasos berücksichtigt wird. Auf der Hangebene wird die räumliche Variabilität von Boden anhand von Bodenprofilen entlang einer Catena untersucht und in die Erosionsmodellierung mittels des physikalisch-basierten WEPP-Model miteinbezogen. Die Ergebnisse der Modellierung verdeutlichen, dass, obwohl die simulierten Abtragsraten für den Gesamthang als vergleichsweise gering einzuschätzen sind, diese bis zu vierzigfach erhöht an einzelnen Hangbereichen auftreten können. Auch Cs-137 Messungen bestätigen mit durchschnittlichen Abtragsraten von weniger als 5 t/ha/yr für den Gesamthang und maximalen Abtragsraten von mehr als 50 t/ha/yr in gefährdeten Zonen diese hohen, räumlichen und für die verhältnismäßig flache Landschaft Burkina Fasos auffälligen Differenzen. Die Identifikation dieser Gefährdungszonen kann jedoch einer standortspezifischen Anpassung von Landnutzungsmethoden dienen. Die Simulationsergebnisse des WEPP-Models zeigen, dass durch die Anlegung von Steinwällen, weniger intensiven Bodenbearbeitungsmethoden, Konturpflügen und Mulchsaat der Bodenabtrag an diesen besonders erosionsgefährdeten Hangbereichen um bis zu 95 %, 70 %, 55 % und 45 % reduziert werden könnte. Auf Wassereinzugsgebietsebene wird die Sedimentationsrate von drei Kleinstaudämmen durch bathymetrische Methoden, Sedimentbohrungen und die Berechnung der Sedimentfracht anhand des Bodenerosions- und Sedimentaustragsmodelles WaTEM/SEDEM ermittelt. Für die Modellierung wird ein digitales Höhenmodel erstellt, Landbedeckungskarten werden wiederum von Fernerkundungsbildern abgeleitet. Ein Vergleich zwischen der ursprünglichen und aktuellen Stauseemorphologie zeigt, dass die Staubecken in den letzten 15 bis 20 Jahren zwischen 10-15% ihrer gesamten Speicherkapazität und mehr als 60% ihres inaktiven Speichervolums eingebüßt haben. In diesem Zeitraum hat sich auch eine Sedimentschicht von 0.3 m bis 0.5 m Mächtigkeit auf dem Stauseeboden abgelagert, was mittels stratigraphischer Analysen und Veränderungen sedimentspezifischer Eigenschaften sowie Cs-137 Konzentrationen im Bohrkern belegt wird. Modellberechnungen mit WaTEM/SEDEM bestätigen einen ähnlich hohen Verschlämmungsgrad mit spezifischen Sedimentfrachtraten von 0.5 t/ha/yr bis 3.4 t/ha/yr. Die Ergebnisse verdeutlichen, dass - setzt man gleichbleibende Sedimentationsraten unter den heutigen Bedingungen voraus - die Halbzeit der prognostizierten Lebensdauer der Staudämme in etwa 25 Jahren erreicht sein wird. Um Sedimentbereitstellungsgebiete und potentielle Erosionsrisikobereiche, die zu diesem hohen Sedimenteintrag in Stauseen führen, zu identifizieren, dienen räumlich-detaillierte Bodenabtrags- und Akkumulationsgefahrenkarten, die mit WaTEM/SEDEM erstellt werden. Diese Gefahrenkarten können schließlich von Entscheidungsträgern als sinnvolle Planungsgrundlage genutzt werden, um festzulegen, welche Landschaftsbereiche vorrangig als Risikogebiete ausgewiesen werden sollten, um dort nachhaltige Boden- und Wasserschutzmaßnahmen zu implementieren