USING GPS, BATHYMETRY, AND LIDAR DATA TO QUANTIFY THE IMPACT OF GLACIAL ISOSTATIC REBOUND ON THE POSITION OF THE LAKE ONTARIO SHORELINE, MONROE COUNTY, NY

2019 ◽  
Author(s):  
Seamus Kearny ◽  
◽  
Carolien Mossel ◽  
Scott Giorgis
Keyword(s):  
Lake Ontario ◽  
Lidar Data ◽  
Monroe County ◽  
Isostatic Rebound ◽  
The Impact

scholarly journals Sprawy polskie w Kanadzie w czasie I wojny światoweJ

2020 ◽  
Vol 46 (2 (176)) ◽  
pp. 227-245
Author(s):  
Anna Reczyńska
Keyword(s):  
North America ◽  
World War I ◽  
Ethnic Group ◽  
Lake Ontario ◽  
World War ◽  
Training Camp ◽  
The Us ◽  
The Impact

Polish Issues in Canada During World War I The article presents the impact of World War I on Polish immigrants in Canada, the position of the Polish ethnic group in this country and the efforts of persons of Polish descent in regard to recruitment for the Polish Army in North America. Poles, who were subjects of Germany or the Austro-Hungarian Empire were treated as enemy aliens. Those people were forced to register and report to the police on a regular basis and some of them were interned in labour camps during the war. Some were released from the camps after an intervention of Polish organizations and priests. Soldiers of Polish descent, volunteers and recruits also fought in the Canadian Expeditionary Forces in Europe. Over 20,000 Polish volunteers from the US (including over 200 from Canada) enrolled in a training camp formed in Niagara-on-the-Lake, Ontario on the border with the US. The problems with the organization and functioning of the camp, and opinions on Polish volunteers shaped the attitude of many Canadians towards the Polish diaspora and the newly established Polish state. Keywords: World War I, Polish Diaspora in Canada, Niagara-on-the-Lake camp, Haller’s Army, Colonel Arthur D’Orr LePan Streszczenie Artykuł przedstawia kilka przykładów obrazujących oddziaływanie wydarzeń I wojny światowej na żyjących w Kanadzie polskich imigrantów, pozycję polskiej grupy etnicznej w tym kraju oraz na aktywność osób polskiego pochodzenia na rzecz rekrutacji do wojska polskiego w Ameryce Północnej. Polaków, którzy byli poddanymi Niemiec lub monarchii austro-wegierskiej traktowano jak przedstawicieli państw wrogich. Mieli obowiązek rejestracji i regularnego zgłaszania się na policję a niektórzy zostali internowani w stworzonych w czasie wojny obozach pracy. Część z nich była z tych obozów zwolniona po interwencji polskich organizacji i polskich duchownych. Żołnierze polskiego pochodzenia, zarówno ochotnicy jak i poborowi, znaleźli się także w oddziałach Kanadyjskich Sił Ekspedycyjnych walczących w Europie. Ponad 20 tys. polskich ochotników z USA (w tym ponad 200 z Kanady) zgłosiło się też do obozu szkoleniowego utworzonego w Niagara-on-the-Lake, Ontario, przy granicy z USA. Problemy z organizacją i funkcjonowaniem tego obozu oraz opinie o polskich ochotnikach, kształtowały nastawienie wielu Kanadyjczyków do polskiej grupy etnicznej i nowotworzonego Państwa Polskiego.

scholarly journals ASSESSING LIDAR TRAINING DATA QUANTITIES FOR CLASSIFICATION MODELS

2021 ◽  
Vol XLVI-4/W4-2021 ◽  
pp. 101-106
Author(s):  
O. Majgaonkar ◽  
K. Panchal ◽  
D. Laefer ◽  
M. Stanley ◽  
Y. Zaki
Keyword(s):  
Point Cloud ◽  
Classification Performance ◽  
Training Data ◽  
Lidar Data ◽  
Data Sets ◽  
Classification Models ◽  
Fundamental Properties ◽  
Point Cloud Classification ◽  
The Impact ◽  
Insight Into

Abstract. Classifying objects within aerial Light Detection and Ranging (LiDAR) data is an essential task to which machine learning (ML) is applied increasingly. ML has been shown to be more effective on LiDAR than imagery for classification, but most efforts have focused on imagery because of the challenges presented by LiDAR data. LiDAR datasets are of higher dimensionality, discontinuous, heterogenous, spatially incomplete, and often scarce. As such, there has been little examination into the fundamental properties of the training data required for acceptable performance of classification models tailored for LiDAR data. The quantity of training data is one such crucial property, because training on different sizes of data provides insight into a model’s performance with differing data sets. This paper assesses the impact of training data size on the accuracy of PointNet, a widely used ML approach for point cloud classification. Subsets of ModelNet ranging from 40 to 9,843 objects were validated on a test set of 400 objects. Accuracy improved logarithmically; decelerating from 45 objects onwards, it slowed significantly at a training size of 2,000 objects, corresponding to 20,000,000 points. This work contributes to the theoretical foundation for development of LiDAR-focused models by establishing a learning curve, suggesting the minimum quantity of manually labelled data necessary for satisfactory classification performance and providing a path for further analysis of the effects of modifying training data characteristics.

scholarly journals Integration of Lidar Data into a Coupled Mesoscale–Land Surface Model: A Theoretical Assessment of Sensitivity of Urban–Coastal Mesoscale Circulations to Urban Canopy Parameters

2012 ◽  
Vol 29 (3) ◽  
pp. 328-346 ◽  
Author(s):  
Michael Carter ◽  
J. Marshall Shepherd ◽  
Steve Burian ◽  
Indu Jeyachandran
Keyword(s):  
Urban Environment ◽  
Land Surface ◽  
Urban Canopy ◽  
Vertical Motion ◽  
Sea Breeze ◽  
Surface Model ◽  
Lidar Data ◽  
Mesoscale Circulations ◽  
The Impact ◽  
Urban Weather

Abstract Urban–coastal circulations affect urban weather, dispersion and transport of pollutants and contaminants, and climate. Proper characterization and prediction of thermodynamic and dynamic processes in such environments are warranted. A new generation of observation and modeling systems is enabling unprecedented characterization of the three-dimensionality of the urban environment, including morphological parameters. Urban areas of Houston, Texas, are classified according to lidar-measured building heights and assigned typical urban land surface parameters appropriate to each classification. The lidar data were degraded from 1 m to the model resolution (1 km) with the goal of evaluating the impact of degraded resolution urban canopy parameters (UCPs) and three-dimensionality on the coastal–urban mesoscale circulations in comparison to typical two-dimensional urban slab approaches. The study revealed complex interactions between the sea breeze and urban heat island and offers a novel diagnostic tool, the bulk Richardson shear number, for identifying shallow mesoscale circulation. Using the Advanced Research Weather Research and Forecasting model (ARW-WRF) coupled to an atmosphere–land surface–urban canopy model, the authors simulated a theoretical sea-breeze day and confirmed that while coastal morphology can itself lead to complex sea-breeze front structures, including preferred areas of vertical motion, the urban environment can have an impact on the evolution of the sea-breeze mesoscale boundary. The inclusion of lidar-derived UCPs, even at degraded resolution, in the model’s land surface representation can lead to significant differences in patterns of skin surface temperature, convergence, and vertical motion, which have implications for many aspects of urban weather.

Numerical models of the exchange flows between Hamilton Harbour and Lake Ontario

2003 ◽  
Vol 30 (1) ◽  
pp. 168-180 ◽  
Author(s):  
P F Hamblin ◽  
C He
Keyword(s):  
Water Quality ◽  
Transport Model ◽  
Numerical Models ◽  
Lake Ontario ◽  
Salt Transport ◽  
Water Level Fluctuations ◽  
Winter Period ◽  
Exchange Flows ◽  
Hamilton Harbour ◽  
The Impact

Accurate simulations of the flow and the transport of water quality constituents in such coastal zones of large lakes as the western end of Lake Ontario and Hamilton Harbour are needed to assess the impact on pollutant levels of cleanup operations and sewage diversions. Coastal models in temperate zone lakes are classified in terms of density stratification, uniform in winter and stratified during summer. During the winter period a 1-D model of the flow between a lake and adjacent harbour is shown to agree favourably with advanced acoustic measurements of the flow in the connecting passage, but does not account for the observed winter buildup of salinity in the harbour. A calibrated 2-D hydrodynamic and salt transport model is used to show that significant exchange does not take place unless the excursion of the inflow is several times greater than the length of the connecting channel, an infrequent occurrence. The exchange is also shown to depend on the flow field at the entrances of the channel. In summer a 1-D vertical model illustrates the dramatic effect of the inflow from Lake Ontario on hypolimnetic temperatures of the harbour. Three-dimensional hydrodynamic and temperature–salt transport models are validated by extensive field observations taken in 1996. The stratified exchange is much stronger than its winter counterpart and more steady. Winter exchange is forced by short-term water level fluctuations, whereas summer or stratified exchange by slowly fluctuating density contrasts between the two water bodies.Key words: exchange flows, hydrodynamic and transport modelling, lakes, harbours, water quality.

scholarly journals EXTRACTING DIMENSIONS AND LOCATIONS OF DOORS, WINDOWS, AND DOOR THRESHOLDS OUT OF MOBILE LIDAR DATA USING OBJECT DETECTION TO ESTIMATE THE IMPACT OF FLOODS

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 429-436 ◽  
Author(s):  
S. Van Ackere ◽  
J. Verbeurgt ◽  
L. De Sloover ◽  
A. De Wulf ◽  
N. Van de Weghe ◽  
...  
Keyword(s):  
Object Detection ◽  
Economic Impact ◽  
Flood Disaster ◽  
Lidar Data ◽  
Building Structures ◽  
Flood Events ◽  
Urban Flood ◽  
Impervious Area ◽  
Socio Economic Impact ◽  
The Impact

<p><strong>Abstract.</strong> Increasing urbanisation, changes in land use (e.g., more impervious area) and climate change have all led to an increasing frequency and severity of flood events and increased socio-economic impact. In order to deploy an urban flood disaster and risk management system, it is necessary to know what the consequences of a specific urban flood event are to adapt to a potential event and prepare for its impact. Therefore, an accurate socio-economic impact assessment must be conducted. Unfortunately, until now, there has been a lack of data regarding the design and construction of flood-prone building structures (e.g., locations and dimensions of doors and door thresholds and presence and dimensions of basement ventilation holes) to consider when calculating the flood impact on buildings. We propose a pipeline to detect the dimension and location of doors and windows based on mobile LiDAR data and 360° images. This paper reports on the current state of research in the domain of object detection and instance segmentation of images to detect doors and windows in mobile LiDAR data. The use and improvement of this algorithm can greatly enhance the accuracy of socio-economic impact of urban flood events and, therefore, can be of great importance for flood disaster management.</p>

Burlington Bay, Lake Ontario: Its Paleolimnology Based on Fossil Ostracodes

1996 ◽  
Vol 31 (3) ◽  
pp. 643-671 ◽  
Author(s):  
L. Denis Delorme
Keyword(s):  
Bottom Water ◽  
Agricultural Practices ◽  
Lake Ontario ◽  
Mean Annual Temperature ◽  
Water Oxygen ◽  
Oxygen Conditions ◽  
History Of ◽  
The Impact ◽  
Change In Mean

Abstract The history of Burlington Bay for the last 8,400 years has recorded two significant changes in its environment. The first occurred about 2,540 years ago, resulting from a change in mean annual temperature. This, in turn, changed the chemistry of the bay water. The second change occurred about 125 years ago (ca. 1865 A.D.). This time, it was the impact of agricultural practices and industrialization. Agricultural practices caused the lake to become eutrophic. This rapidly (within 40 years) changed the bottom water oxygen conditions to anaerobic. Industrialization had an impact on the fauna and the flora. Some fauna became locally extinct while some phytoplankton became deformed.

scholarly journals Effective resolution concepts for lidar observations

2015 ◽  
Vol 8 (5) ◽  
pp. 5363-5424
Author(s):  
M. Iarlori ◽  
F. Madonna ◽  
V. Rizi ◽  
T. Trickl ◽  
A. Amodeo
Keyword(s):  
Digital Signal ◽  
High Spectral Resolution ◽  
Lidar Data ◽  
Vertical Profiles ◽  
Range Resolution ◽  
True Profile ◽  
Low Pass ◽  
Low Pass Filters ◽  
The Impact ◽  
Aerosol Properties

Abstract. Since its first establishment in 2000, EARLINET (European Aerosol Research Lidar NETwork) has been devoted to providing, through its database, exclusively quantitative aerosol properties, such as aerosol backscatter and aerosol extinction coefficients, the latter only for stations able to retrieve it independently (from Raman or High Spectral Resolution Lidars). As these coefficients are provided in terms of vertical profiles, EARLINET database must also include the details on the range resolution of the submitted data. In fact, the algorithms used in the lidar data analysis often alter the spectral content of the data, mainly working as low pass filters with the purpose of noise damping. Low pass filters are mathematically described by the Digital Signal Processing (DSP) theory as a convolution sum. As a consequence, this implies that each filter's output, at a given range (or time) in our case, will be the result of a linear combination of several lidar input data relative to different ranges (times) before and after the given range (time): a first hint of loss of resolution of the output signal. The application of filtering processes will also always distort the underlying true profile whose relevant features, like aerosol layers, will then be affected both in magnitude and in spatial extension. Thus, both the removal of noise and the spatial distortion of the true profile produce a reduction of the range resolution. This paper provides the determination of the effective resolution (ERes) of the vertical profiles of aerosol properties retrieved starting from lidar data. Large attention has been addressed to provide an assessment of the impact of low-pass filtering on the effective range resolution in the retrieval procedure.

scholarly journals Impact of Lidar Data Assimilation on Low-Level Wind Shear Simulation at Lanzhou Zhongchuan International Airport, China: A Case Study

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1342
Author(s):  
Lanqian Li ◽  
Ningjing Xie ◽  
Longyan Fu ◽  
Kaijun Zhang ◽  
Aimei Shao ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Wind Shear ◽  
Three Dimensional ◽  
Wrf Model ◽  
Lidar Data ◽  
Positive Role ◽  
Low Level ◽  
Wind Lidar ◽  
The Impact ◽  
Doppler Wind Lidar

Doppler wind lidar has played an important role in alerting low-level wind shear (LLW). However, these high-resolution observations are underused in the model-based analysis and forecasting of LLW. In this regard, we employed the Weather Research and Forecasting (WRF) model and its three-dimensional variational (3D-VAR) system to investigate the impact of lidar data assimilation (DA) on LLW simulations. Eight experiments (including six assimilation experiments) were designed for an LLW process as reported by pilots, in which different assimilation intervals, assimilation timespans, and model vertical resolutions were examined. Verified against observations from Doppler wind lidar and an automated weather observing system (AWOS), the introduction of lidar data is helpful for describing the LLW event, which can represent the temporal and spatial features of LLW, whereas experiments without lidar DA have no ability to capture LLW. While lidar DA has an obviously positive role in simulating LLW in the 10–20 min after the assimilation time, this advantage cannot be maintained over a longer time. Therefore, a smaller assimilation interval is favorable for improving the simulated effect of LLW. In addition, increasing the vertical resolution does not evidently improve the experimental results, either with or without assimilation.

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