scholarly journals Comparison of different methods to assess the distribution of alien plants along the road network and use of Google Street View panoramas interpretation in Sicily (Italy) as a case study

2021 ◽  
Vol 9 ◽  
Author(s):  
Giulio Barone ◽  
Gianniantonio Domina ◽  
Emilio Di Gristina
Keyword(s):  
Road Network ◽  
Google Earth ◽  
Alien Plants ◽  
Aerial Images ◽  
Photo Interpretation ◽  
Aerial Photos ◽  
Google Street View ◽  
The Road ◽  
Street View ◽  
Complete Survey

The survey by foot in the field is compared to the survey from a car, the photo-interpretation of Google Street View (GSV) panoramas continuously and at intervals of 1.5 km and the photo-interpretation of Google Earth aerial images on a 10 km stretch of road in Sicily. The survey by foot was used as reference for the other methods. The interpretation of continuous GSV panoramas gave similar results as the assessment by car in terms of the number of species identified and their location, but with lower cost. The interpretation online of aerial photos allowed the identification of a limited number of taxa, but gave a good localisation for them. Interpretation of GSV panoramas, each of 1.5 km, allowed the recognition of twice as many taxa as the interpretation of aerial photos and taking half the time, but did not allow a complete localisation. None of these methods alone seems sufficient to carry out a complete survey. A mixture of different techniques, which may vary according to the available resources and the goal to be achieved, seems to be the best compromise. To further test the capabilities of the survey using the interpretation of GSV panoramas every 1.5 km along the roads, we proceeded to study the alien plants along 3500 km of the road network on the island of Sicily. This survey identified only 10% of the known species for the region, but allowed us to trace the distribution of invasive species whose distribution is currently poorly recorded.

scholarly journals ACCURACY ASSESSMENT OF 3D MODELS GENERATED FROM GOOGLE STREET VIEW IMAGERY

2019 ◽  
Vol XLII-2/W9 ◽  
pp. 181-188 ◽  
Author(s):  
N. Bruno ◽  
R. Roncella
Keyword(s):  
Accuracy Assessment ◽  
Average Distance ◽  
3D Models ◽  
Google Earth ◽  
Google Street View ◽  
3D City Model ◽  
Software Packages ◽  
Street View ◽  
Panoramic Images ◽  
City Model

<p><strong>Abstract.</strong> Google Street View is a technology implemented in several Google services/applications (e.g. Google Maps, Google Earth) which provides the user, interested in viewing a particular location on the map, with panoramic images (represented in equi-rectangular projection) at street level. Generally, consecutive panoramas are acquired with an average distance of 5&amp;ndash;10<span class="thinspace"></span>m and can be compared to a traditional photogrammetric strip and, thus, processed to reconstruct portion of city at nearly zero cost. Most of the photogrammetric software packages available today implement spherical camera models and can directly process images in equi-rectangular projection. Although many authors provided in the past relevant works that involved the use of Google Street View imagery, mainly for 3D city model reconstruction, very few references can be found about the actual accuracy that can be obtained with such data. The goal of the present work is to present preliminary tests (at time of writing just three case studies has been analysed) about the accuracy and reliability of the 3D models obtained from Google Street View panoramas.</p>

Using Google Earth and Google Street View To Rate Rock Slope Hazards

2018 ◽  
Vol 24 (2) ◽  
pp. 237-250
Author(s):  
William Swanger ◽  
Yonathan Admassu
Keyword(s):  
Google Earth ◽  
Orientation Data ◽  
Google Street View ◽  
Rockfall Hazard ◽  
Street View ◽  
Discontinuity Orientation ◽  
Measuring Tape ◽  
Study Sites ◽  
Weak Rock Masses ◽  
Geologic Information

Abstract Rockfall hazard from cut slopes along highways are caused primarily by unfavorable orientations of discontinuities, presence of unconsolidated cobble/boulder deposits, undercutting of strong rocks by weaker rocks, or degradation of weak rock masses. The rockfall hazard rating system (RHRS) was introduced in Oregon to evaluate the hazard and associated risk to an adjacent transportation facility for a cut slope's potential for releasing rockfalls. RHRS is a numerical score–based rating of parameters that characterize rockfalls. The parameters include slope geometry (height, angle, roughness, orientation), geologic information (discontinuity characterization, undercutting susceptibility), driver's line of sight, and climate. Geologic information, such as discontinuity orientation data, is traditionally collected using a transit compass and measuring tape at the site. The method is time consuming and expensive and can be dangerous. This study tests the use of Google Earth and Google Street View tools to remotely collect data for selected parameters that characterize rockfall hazard. The selected parameters are categorized under slope profile, geologic characteristics, and impact factor parameters, which are quantitatively and qualitatively measurable using Google Street View and Google Earth. A section of U.S. 33 with a high density of road cuts and two more sites along Interstate 64, all located in Virginia, were selected for the study. Sites were evaluated by using a combination of measurement tools available in Google Earth and a visual inspection of the rock units in Google Street View. The results of seven of the sites were re-evaluated using field-derived data.

scholarly journals ASSESSMENT OF SNOW AVALANCHE SUSCEPTIBILITY OF ROAD NETWORK - A CASE STUDY OF ALAKNANDA BASIN

2018 ◽  
Vol XLII-5 ◽  
pp. 461-468
Author(s):  
V. Singh ◽  
P. K. Thakur ◽  
V. Garg ◽  
S. P. Aggarwal
Keyword(s):  
Road Network ◽  
Thermal Emission ◽  
Armed Forces ◽  
Western Himalaya ◽  
Google Earth ◽  
Snow Avalanche ◽  
Slope Aspect ◽  
Static Parameter ◽  
The Road ◽  
Avalanche Formation

<p><strong>Abstract.</strong> Snow avalanche occurring in a micro-climatic condition causing hydro-geo (Hydrological and geological) hazard to the deployed armed forces and nearby inhabitant to the North Western Himalaya about 3000 MSL. In recent years, frequencies of snow avalanche have increase and consequently the death toll have also surged to many folds. These unavoidable occurrences not only cause road blocks which disrupts transportation connectivity in the rugged terrain of Himalaya as well as loss of infrastructure and life. Here, in this study an attempt has been made to assess the susceptibility of road network of Alaknanda Basin from snow avalanche. Potential avalanche formation zones have been generated using Analytical Hierarchical Process (AHP) of Multi-Criteria Decision Making (MCDM. Advance Thermal Emission Reflection Radiometer (ASTER) Global Digital Elevation (GDEM) 30 meter has been used to generate static parameters like slope, aspect, curvature etc. using GIS platform. ISRO-Geosphere Biosphere Program Land Use Land Cover (LULC) used as another static parameter. Weights are generated using comparison matrix and ratings to different static parameter layers assigned on the basis of field visit and literature review while the road network are digitized from Google earth. A methodology has been prepared to categorize the road stretches on the basis of potential snow avalanche formation zone including hydrological processing. Buffer zone are assigned with weights according to potential snow avalanche formation zones. Later roads are intersected with sub basin with assigned values that resulted very high avalanche potential zonation, considered as most susceptible to snow avalanche hazard.</p>

scholarly journals With Geospatial in Path of Smart City

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1381-1387 ◽  
Author(s):  
A. S. Homainejad
Keyword(s):  
Information And Communication Technologies ◽  
Smart City ◽  
Traffic Management ◽  
Road Network ◽  
Aerial Images ◽  
Transport Systems ◽  
City Management ◽  
Traffic Jam ◽  
The Road ◽  
On The Road

With growth of urbanisation, there is a requirement for using the leverage of smart city in city management. The core of smart city is Information and Communication Technologies (ICT), and one of its elements is smart transport which includes sustainable transport and Intelligent Transport Systems (ITS). Cities and especially megacities are facing urgent transport challenge in traffic management. Geospatial can provide reliable tools for monitoring and coordinating traffic. In this paper a method for monitoring and managing the ongoing traffic in roads using aerial images and CCTV will be addressed. In this method, the road network was initially extracted and geo-referenced and captured in a 3D model. The aim is to detect and geo-referenced any vehicles on the road from images in order to assess the density and the volume of vehicles on the roads. If a traffic jam was recognised from the images, an alternative route would be suggested for easing the traffic jam. In a separate test, a road network was replicated in the computer and a simulated traffic was implemented in order to assess the traffic management during a pick time using this method.

scholarly journals Mutações Urbanas na Região Metropolitana de Campinas

2020 ◽  
Vol 6 (2) ◽  
pp. e00100
Author(s):  
Daniel Teixeira Turczyn ◽  
Evandro Ziggiatti Monteiro
Keyword(s):  
Sao Paulo ◽  
Google Earth ◽  
São Paulo ◽  
Google Street View ◽  
Street View

O objetivo da pesquisa foi identificar e analisar áreas que podem ser classificadas como mutações urbanas na Região Metropolitana de Campinas, estado de São Paulo/Brasil, e evidenciar os padrões de paisagens mais recorrentes na sua formação. A Região Metropolitana de Campinas é constituída por vinte municípios e sete deles apresentam áreas que podem ser identificadas como mutações urbanas. Mutação urbana é um conceito forjado por Solà-Morales (2002) que auxilia o entendimento das dinâmicas de formação da cidade contemporânea. O método baseia-se em uma abordagem que utiliza o conceito de mutação como chave para uma sintaxe de leitura espacial, permitindo enfatizar e delimitar as aglomerações urbanas que compartilham o mesmo conjunto de características morfológicas. O método inclui procedimentos de análise de imagens aéreas e de fotografias urbanas disponibilizadas pelas ferramentas Google Earth e Google Street View. Os resultados apontam a formação de um eixo metropolitano que concentra vinte e uma mutações urbanas e extensas áreas de vazios urbanos. A paisagem urbana que está sendo formada é genérica e carente de elementos típicos da cidade tradicional pública e democrática, sendo estruturada por um conjunto de vinte e cinco padrões de paisagens, que retratam o ambiente construído na escala do pedestre.

scholarly journals COBERTURA DA TERRA E QUALIDADE AMBIENTAL DA BACIA HIDROGRÁFICA DO CÓRREGO VILA PINHEIROS, CURITIBA, PARANÁ.

2021 ◽  
Vol 22 (80) ◽  
pp. 153-168
Author(s):  
Gabriela Muller Gouvea ◽  
João Carlos Nucci ◽  
Eduardo Liberti
Keyword(s):  
Google Earth ◽  
Google Street View ◽  
Street View

A fragmentação e supressão das áreas com vegetação e o aumento das superfícies impermeabilizadas nas cidades colaboram para uma diminuição da qualidade ambiental. O objetivo do estudo foi avaliar a qualidade ambiental da bacia do Córrego Vila Pinheiros, localizada em Curitiba/Paraná (Brasil), com base na cobertura da terra. Foram utilizadas imagens orbitais disponibilizadas pelo Google Earth Pro e Google Street View, ano 2018, nas escalas 1:3.000 e 1:5.000, utilizando-se a quadra como área mínima. O mapeamento foi feito de maneira não automática no software ArcGis, e, posteriormente, foram analisadas as dinâmicas ambientais da bacia, gerando o mapa de qualidade ambiental. Constatou-se que 66,19% (0,98 km²) da bacia são constituídos por espaços edificados, sendo que as edificações de até 4 pavimentos com vegetação nas áreas adjacentes ocupam 46,62% (0,69 km²) da bacia. Os melhores níveis de qualidade ambiental representam 4,04% (0,06 km²) do total da área estudada e são constituídos por espaços não edificados e com vegetação nos estratos arbustivos e/ou herbáceo e solo exposto. Os piores índices de qualidade ambiental da bacia concentram-se nas regiões sudeste, leste e nordeste e representam cerca de 4,05% (0,06 km²) da área total. Esses dados apontam para uma baixa qualidade ambiental na bacia estudada.

scholarly journals Desenvolvimento de Metodologia Para Mapeamento da Estimativa de Geração Distribuída com Sistemas Fotovoltaicos em Áreas Urbanas

2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Giuliano Arns Rampinelli ◽  
Caio Scardueli
Keyword(s):  
Google Earth ◽  
Santa Catarina ◽  
Google Street View ◽  
Street View

O presente trabalho tem como objetivo desenvolver uma metodologia para o cálculo do potencial de geração distribuída com sistemas fotovoltaicos utilizando a área das coberturas de edificações já existentes. A metodologia desenvolvida também foi aplicada em duas regiões distintas da cidade de Araranguá, Santa Catarina. Para tanto, primeiramente foram realizadas estimativas das áreas em potencial através do uso dos programas Google Earth e Google Street View. Em um segundo momento, foi realizada a classificação das coberturas quanto ao seu ângulo de inclinação e orientação. Por fim, foi utilizado porcentagens da área total como área real disponível, de acordo com a classificação da cobertura, e após realizou-se simulações utilizando esta área. A partir dos resultados obtidos, pode-se concluir que a geração fotovoltaica das regiões estudas apresentam um potencial muito maior que suas demandas.

scholarly journals Mapas fotográficos do Google:

ALCEU ◽  
2020 ◽  
Vol 20 (40) ◽  
pp. 104-122
Author(s):  
Grécia Desirée Falcão de Araujo
Keyword(s):  
Google Earth ◽  
Google Maps ◽  
Google Street View ◽  
Street View

Os sistemas de mapeamento geográfico do Google (Google Maps) e demais softwares acopladosao serviço (Google Earth e Google Street View) utilizam o registro fotográfico como principal121ALCEU – v. 20 – n. 40 – jan-jul/2020ferramenta de documentação e de mapeamento da geografia terrestre. Para a ciência cartográfica,a fotografia aérea é uma importante ferramenta de análise e de gerenciamento de informaçõesgeográficas, sendo a técnica ideal para a criação de uma narrativa visual, que preza pelaverossimilhança, ou seja: pela “melhor” e “mais fiel” representação possível do espaço. Por outrolado, neste paper, gostaria de problematizar o sentido comunicacional dos registros fotográficosfornecidos pelos mapas Google a partir da análise de duas séries fotográficas criadas por MishkaHenner: artista belga conhecido por utilizar, como fonte de pesquisa para suas obras, arquivosfotográficos disponíveis online. Ao que parece, as estratégias de apropriação, produção e montagemexpositiva operacionalizadas pelo artista são capazes de multiplicar as formas de comunicação dasimagens fotográficas, e de “fazer variar” o sentido deste conjunto de “fotografias-mapa” geradas pelaempresa Google.

scholarly journals Knud Rasmussen Glacier Status Analysis Based on Historical Data and Moving Detection Using RPAS

2021 ◽  
Vol 11 (2) ◽  
pp. 754
Author(s):  
Karel Pavelka ◽  
Jaroslav Šedina ◽  
Karel Pavelka
Keyword(s):  
Three Dimensional ◽  
Image Data ◽  
Point Clouds ◽  
Multiscale Model ◽  
Satellite System ◽  
Flow Speed ◽  
Middle Part ◽  
Google Earth ◽  
Aerial Images ◽  
Aerial Photos

This article discusses partial results of an international scientific expedition to Greenland that researched the geography, geodesy, botany, and glaciology of the area. The results here focus on the photogrammetrical results obtained with the eBee drone in the eastern part of Greenland at the front of the Knud Rasmussen Glacier and the use of archive image data for monitoring the condition of this glacier. In these short-term visits to the site, the possibility of using a drone is discussed and the results show not only the flow speed of the glacier but also the shape and structure from a height of up to 200 m. From two overflights near the glacier front at different times, it was possible to obtain the speed of the glacier flow and the distribution of velocities in the glacier stream. The technology uses a comparison of two point clouds derived from a set of aerial photos taken with the eBee drone, and calculating the M3C2 (Multiscale Model-to-Model Cloud Comparison) distances with CloudCompare software. The results correlate with other measurement methods like accurate and long-term measurement with Global Navigation Satellite System (GNSS), satellite radar, or ground geodetical technology. The resulting speed from the drone data reached in the middle part of the glacier, was approximately 12–15m per day. The second part of the paper focuses on the analysis of modern satellite images of the Knud Rasmussen Glacier from Google Earth (Landsat series 1984–2016) and Sentinel 2a, and a comparison with historical aerial images from 1932 to 1933. Historical images were processed photogrammetrically into a three-dimensional (3D) model. Finally, orthogonalized image data from three systems (drone photos, historical aerial photos, and satellite data) were compared in the ArcGIS software. This allows us to analyze glacier changes over time in the time span from 1932 to 2020, with the caveat that from 1933 to 1983 we did not have data at our disposal. The result shows that more significant changes in the area of this glacier occurred after 2011. The main aim of this article is to research the use of photogrammetric methods for monitoring the condition and parameters of glaciers based on non-traditional technology, such as drones or new processing of historical photos.

scholarly journals AUTOMATIC EXTRACTION OF ROAD CENTERLINES AND EDGE LINES FROM AERIAL IMAGES VIA CNN-BASED REGRESSION

2020 ◽  
Vol V-2-2020 ◽  
pp. 925-932
Author(s):  
Y. Wei ◽  
X. Hu ◽  
M. Zhang ◽  
Y. Xu
Keyword(s):  
Road Network ◽  
Aerial Images ◽  
Automatic Extraction ◽  
Tensor Voting ◽  
Road Extraction ◽  
The Road ◽  
Road Width ◽  
Road Intersections ◽  
On The Road ◽  
Segmentation Problem

Abstract. Extracting roads from aerial images is a challenging task in the field of remote sensing. Most approaches formulate road extraction as a segmentation problem and use thinning and edge detection to obtain road centerlines and edge lines, which could produce spurs around the extracted centerlines/edge lines. In this study, a novel regression-based method is proposed to extract road centerlines and edge lines directly from aerial images. The method consists of three major steps. First, an end-to-end regression network based on CNN is trained to predict confidence maps for road centerlines and estimate road width. Then, after the CNN predicts the confidence map, non-maximum suppression and road tracking are applied to extract accurate road centerlines and construct road topology. Meanwhile, Road edge lines are generated based on the road width estimated by the CNN. Finally, in order to improve the connectivity of extracted road network, tensor voting is applied to detect road intersections and the detected intersections are used as guidance for the overcome of discontinuities. The experiments conducted on the SpaceNet and DeepGlobe datasets show that our approach achieves better performance than other methods.

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