scholarly journals A global scale geospatially located landslide dam dataset

2020 ◽  
Author(s):  
Hang Wu ◽  
Mark Trigg ◽  
William Murphy
Keyword(s):  
Spatial Distribution ◽  
Spatial Information ◽  
Hot Spot ◽  
Landslide Dam ◽  
Volcanic Eruptions ◽  
Data Access ◽  
Global Scale ◽  
Mountainous Areas ◽  
Characteristic Analysis ◽  
Landslide Dams

<p>Landslide dams are a common hazard reported in mountainous areas around the world, where the dams block the normal flow of the river and can cause catastrophic flooding downstream when the temporary dam subsequently fails. Most of the research that couples landslide dams and fluvial systems have been concentrated on a site-specific scale and thus little is known about where these hazards are clustered and how they connect to climate and geology. A detailed and comprehensive dataset of landslide dams is not currently available at the global scale, since most global landslide dam datasets contain very little precise spatial information, which makes it harder to explore and to analyze the impacts on floods by modelling over larger scales. </p><p>To narrow this data gap, we are developing a new global landslide dam dataset, recording: spatial coordinates, time information, dam materials, geomorphic characteristics of catchments, landslides, landslide dams and impounded lakes, and hydrographic characteristics of subsequent flood events and their consequent damage. This has been collated from bibliographic works in a number of languages. In the process of building the database we have encountered several obstacles including language barriers, indistinct naming standards, vague and patchy spatial information, and the diversity of data access in different countries. So far, we have data from over 700 individual events that have been synthesized into the same data format with consistent units and spatial references.</p><p>The spatial distribution of landslide dam shows hazard hot spot areas concentrated around mountainous areas. The number of landslide dams reported increases exponentially during the past 1000 years, with the highest peak in the last 20 years. This increase is most likely due to better records in more recent years. Some extreme large-scale events, including earthquakes, floods, typhoons and volcanic eruptions have contributed to other peaks in the record. Initial analysis of the data will be used to explore distribution differences of dimension data, such as height, length and volume, of landslide dams that are induced by different triggers, to explore the triggers effect on landslide dam formation.</p><p>The summary information of the dataset and the characteristic analysis result will be presented with a comparison to existing landslide dam datasets. A spatial distribution map of landslide dams and hazard hot spot areas will also be presented. This extensive global landslide dam dataset will allow researchers to understand the spatial distribution, geomorphic characteristics of landslide dams, and the connections among the dimensions of landslide sources, landslide dams, impounded lakes and upstream catchments. We will continue to develop this current landslide dam dataset and welcome feedback and additional datasets to supplement the database. Upon completion, the dataset will be made open access for wider research purposes and collaborations.</p>

scholarly journals A new global landslide dam database (RAGLAD) and analysis utilizing auxiliary global fluvial datasets

Landslides ◽  
2022 ◽  
Author(s):  
Hang Wu ◽  
Mark A. Trigg ◽  
William Murphy ◽  
Raul Fuentes
Keyword(s):  
Landslide Dam ◽  
Global Scale ◽  
Current Data ◽  
Landslide Dams ◽  
Multiple Data ◽  
Landslide Volume ◽  
Catchment Areas ◽  
Geomorphological Parameters ◽  
Data Source ◽  
Relationship Of

AbstractTo address the current data and understanding knowledge gap in landslide dam inventories related to geomorphological parameters, a new global-scale landslide dam dataset named River Augmented Global Landslide Dams (RAGLAD) was created. RAGLAD is a collection of landslide dam records from multiple data sources published in various languages and many of these records we have been able to precisely geolocate. In total, 779 landslide dam records were compiled from 34 countries/regions. The spatial distribution, time trend, triggers, and geomorphological characteristic of the landslides and catchments where landslide dams formed are summarized. The relationships between geomorphological characteristics for landslides that form river dams are discussed and compared with those of landslides more generally. Additionally, a potential threshold for landslide dam formation is proposed, based on the relationship of landslide volume to river width. Our findings from our analysis of the value of the use of additional fluvial datasets to augment the database parameters indicate that they can be applied as a reliable supplemental data source, when the landslide dam records were accurately and precisely geolocated, although location precision in smaller river catchment areas can result in some uncertainty at this scale. This newly collected and supplemented dataset will allow the analysis and development of new relationships between landslides located near rivers and their actual propensity to block those particular rivers based on their geomorphology.

scholarly journals Modeling Spatiotemporal Population Changes by Integrating DMSP-OLS and NPP-VIIRS Nighttime Light Data in Chongqing, China

2021 ◽  
Vol 13 (2) ◽  
pp. 284
Author(s):  
Dan Lu ◽  
Yahui Wang ◽  
Qingyuan Yang ◽  
Kangchuan Su ◽  
Haozhe Zhang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Relative Error ◽  
Urban Areas ◽  
Large Scale ◽  
Population Distribution ◽  
Spatial Optimization ◽  
Distribution Data ◽  
Mountainous Areas ◽  
Mean Relative Error ◽  
Nighttime Light

The sustained growth of non-farm wages has led to large-scale migration of rural population to cities in China, especially in mountainous areas. It is of great significance to study the spatial and temporal pattern of population migration mentioned above for guiding population spatial optimization and the effective supply of public services in the mountainous areas. Here, we determined the spatiotemporal evolution of population in the Chongqing municipality of China from 2000–2018 by employing multi-period spatial distribution data, including nighttime light (NTL) data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). There was a power function relationship between the two datasets at the pixel scale, with a mean relative error of NTL integration of 8.19%, 4.78% less than achieved by a previous study at the provincial scale. The spatial simulations of population distribution achieved a mean relative error of 26.98%, improved the simulation accuracy for mountainous population by nearly 20% and confirmed the feasibility of this method in Chongqing. During the study period, the spatial distribution of Chongqing’s population has increased in the west and decreased in the east, while also increased in low-altitude areas and decreased in medium-high altitude areas. Population agglomeration was common in all of districts and counties and the population density of central urban areas and its surrounding areas significantly increased, while that of non-urban areas such as northeast Chongqing significantly decreased.

scholarly journals The Role of Spatio-Temporal Information to Govern the COVID-19 Pandemic: A European Perspective

2021 ◽  
Vol 10 (3) ◽  
pp. 166
Author(s):  
Hartmut Müller ◽  
Marije Louwsma
Keyword(s):  
European Union ◽  
Spatial Distribution ◽  
Spatial Information ◽  
National Level ◽  
Temporal Information ◽  
The European Union ◽  
Member States ◽  
Heavy Burden ◽  
Spatio Temporal

The Covid-19 pandemic put a heavy burden on member states in the European Union. To govern the pandemic, having access to reliable geo-information is key for monitoring the spatial distribution of the outbreak over time. This study aims to analyze the role of spatio-temporal information in governing the pandemic in the European Union and its member states. The European Nomenclature of Territorial Units for Statistics (NUTS) system and selected national dashboards from member states were assessed to analyze which spatio-temporal information was used, how the information was visualized and whether this changed over the course of the pandemic. Initially, member states focused on their own jurisdiction by creating national dashboards to monitor the pandemic. Information between member states was not aligned. Producing reliable data and timeliness reporting was problematic, just like selecting indictors to monitor the spatial distribution and intensity of the outbreak. Over the course of the pandemic, with more knowledge about the virus and its characteristics, interventions of member states to govern the outbreak were better aligned at the European level. However, further integration and alignment of public health data, statistical data and spatio-temporal data could provide even better information for governments and actors involved in managing the outbreak, both at national and supra-national level. The Infrastructure for Spatial Information in Europe (INSPIRE) initiative and the NUTS system provide a framework to guide future integration and extension of existing systems.

scholarly journals Spatial Pattern and Hotspots of Urban Rail Public Transport to Public Access Using Geospatial Techniques in Selangor, Malaysia

2021 ◽  
Vol 6 (1) ◽  
pp. 234-244
Author(s):  
Mohd Sahrul Syukri BIN Yahya ◽  
Edie Ezwan Mohd Safian ◽  
Burhaida Burhan
Keyword(s):  
Open Access ◽  
Spatial Pattern ◽  
Public Transport ◽  
Public Transportation ◽  
Spatial Information ◽  
Hot Spot ◽  
Developed Countries ◽  
Transportation Systems ◽  
Gis Mapping ◽  
Urban Public Transport

Currently, the trends in urban public transport have been changing over the years in developing countries for mobilization and accessibility development. Urban public transportation systems are the most popular in Selangor State, including big cities such as the Klang Valley Region. Objective measures of spatial pattern and hotspots have been used to understand how urban public transport development relate to open access. This method relies on specific spatial information and available web-based tool that shows the pattern primarily based on given vicinity and statistics connectivity. To date, several studies have finished tested in developed countries. In this study, we use Geographic Information Systems to analyse and consider hotspots identification precisely and efficaciously. Therefore, in this paper, we focus on two types of point sample evaluations – Gi* hot spot and point density analysis evaluation as statistical operations. Public rail transport was evaluated as a validation to describe the percentage of distribution of open access. The final result, GIS mapping capabilities to show that GIS's technology offers to the variation of urban public transport relate to public services, is to create maps and spatial interpretations.

scholarly journals ZOOPLANKTON SPATIAL DISTRIBUTION AND COMMUNITY STRUCTURE IN BANGGAI SEA

2012 ◽  
Vol 4 (2) ◽  
Author(s):  
Arief Rachman ◽  
Elly Asniariati
Keyword(s):  
Spatial Distribution ◽  
Community Structure ◽  
Hot Spot ◽  
Zooplankton Community ◽  
Anthropogenic Activity ◽  
Zooplankton Abundance ◽  
Total Density ◽  
Importance Value ◽  
Zooplankton Community Structure ◽  
Specific Distribution

<p>Banggai Sea is an interesting ecosystem due to mixing influences from Banda Sea in the west and Maluccas Sea in the east. Therefore, a unique zooplankton community structure and specific distribution pattern should be found in this area. This research was carried on using Baruna Jaya VIII research vessel and samples were collected in 14 sampling stations. Vertical towing using NORPAC plankton net (300 μm) was conducted to collect zooplankton samples. Result showed that inner Mesamat Bay had the lowest abundance of zooplankton, probably due to low water quality resulted from anthropogenic activity. Meanwhile the strait between Liang and Labobo Island had the highest zooplankton abundance in Banggai Sea. Calanoids was the dominant zooplankton taxa in the ecosystem and contributing 55.7% of total density of zooplankton community. The highest importance value made this taxa to be very important factor that regulates the lower trophic level organisms. Results also showed that zooplankton was distributed nearly uniform in eastern but aggregated to several stations in western Banggai Sea. Zooplankton abundance was higher in the central of Banggai Sea, compared to western and eastern area. According to Bray-Curtis clustering analysis the strait between Liang and Labobo Island has unique zooplankton community structure. This might happened due to mixing of water from two highly productive seas that influenced the Banggai Sea ecosystem. From this research we conclude that this strait probably was the zooplankton hot spot area which might also indicate that this area also a hot spot of fishes in the Banggai Sea.</p><p>Keywords: spatial distribution, zooplankton, community structure, hot spot, Banggai</p>

scholarly journals Spatial odor discrimination in hawkmoth, Manduca sexta (L.)

2020 ◽  
Author(s):  
P. Kalyanasundaram ◽  
M. A. Willis
Keyword(s):  
Spatial Distribution ◽  
Manduca Sexta ◽  
Flight Control ◽  
Spatial Information ◽  
Egg Laying ◽  
Proboscis Extension Reflex ◽  
Flying Insects ◽  
Odor Learning ◽  
Odor Plumes ◽  
Proboscis Extension

AbstractFlying insects track turbulent odor plumes to find mates, food and egg-laying sites. To maintain contact with the plume, insects are thought to adapt their flight control according to the distribution of odor in the plume using the timing of odor onsets and intervals between odor encounters. Although timing cues are important, few studies have addressed whether insects are capable of deriving spatial information about odor distribution from bilateral comparisons between their antennae in flight. The proboscis extension reflex (PER) associative learning protocol, originally developed to study odor learning in honeybees, was modified to show hawkmoths, Manduca sexta, can discriminate between odor stimuli arriving on either antenna. We show moths discriminated the odor arrival side with an accuracy of >70%. The information about spatial distribution of odor stimuli is thus available to moths searching for odor sources, opening the possibility that they use both spatial and temporal odor information.

scholarly journals Study on the effect of rainfall spatial variability on runoff modelling

2018 ◽  
Vol 20 (3) ◽  
pp. 577-587 ◽  
Author(s):  
Jun Zhang ◽  
Dawei Han ◽  
Yang Song ◽  
Qiang Dai
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Spatial Information ◽  
Model Performance ◽  
Moran’S I ◽  
Image Size ◽  
Moran's I ◽  
Rainfall Events ◽  
Lumped Model ◽  
Distributed Models

Abstract Rainfall spatial variability was assessed to explore its influence on runoff modelling. Image size, coefficient of variation (Cv) and Moran's I were chosen to assess for rainfall spatial variability. The smaller the image size after compression, the less complex is the rainfall spatial variability. The results showed that due to the drawing procedure and varied compression methods, a large uncertainty exists for using image size to describe rainfall spatial variability. Cv quantifies the variability between different rainfall values without considering rainfall spatial distribution and Moran's I describes the spatial autocorrelation between gauges rather than the values. As both rainfall values and spatial distribution have an influence on runoff modelling, the combination of Cv and Moran's I was further explored. The results showed that the combination of Cv and Moran's I is reliable to describe rainfall spatial variability. Furthermore, with the increase of rainfall spatial variability, the hydrological model performance decreases. Moreover, it is difficult for a lumped model to cope with rainfall events assigned with complex rainfall spatial variability since spatial information is not taken into consideration (i.e. the VIC model used in this study). Therefore, it is recommended to apply distributed models that can deal with more spatial input information.

Spatial distribution of levoglucosan and alternative biomass burning tracers in atmospheric aerosols, in an urban and industrial hot-spot of Central Italy

2020 ◽  
Vol 239 ◽  
pp. 104904 ◽  
Author(s):  
Lorenzo Massimi ◽  
Giulia Simonetti ◽  
Francesca Buiarelli ◽  
Patrizia Di Filippo ◽  
Donatella Pomata ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Biomass Burning ◽  
Atmospheric Aerosols ◽  
Hot Spot ◽  
Central Italy

scholarly journals An Evolutionary Approach to Technology Innovation of Cadastre for Smart Land Management Policy

Land ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 50
Author(s):  
Hae Ok Choi
Keyword(s):  
Land Management ◽  
Semantic Analysis ◽  
Technology Innovation ◽  
Spatial Information ◽  
Global Scale ◽  
Management Policy ◽  
Geospatial Information ◽  
Interest In Research ◽  
Spatial Information Technology ◽  
Land Management Policy

In this study, we attempted to quantitatively determine the characteristics of keyword networks in the cadastre field using major contents of research drawn from international academic papers. Furthermore, we investigated the macroscopic evolution of cadastral research and examined its keyword network in detail (at a global scale) using semantic analysis. The analysis was carried out based on cadastral-research-related publications extracted from “Scopus” for 1987 to 2019. It was found that cadastre research has closely followed the recent trend of a growing interest in research on geospatial information and standardization. The results showed the advancement of technology innovation within the field of cadastres, as highlighted in the combination of relevant keywords (mostly from those related to spatial information technology and participation of civilians). These new issues are expected to drive the evolution of the academic scope in the future through synthesis with other fields for smart land management policy.

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