Road Extraction and Road Width Estimation Via Fusion of Aerial Optical Imagery, Geospatial Data, and Street-Level Images

2021 ◽  
Author(s):  
Andrea Grillo ◽  
Vladimir A. Krylov ◽  
Gabriele Moser ◽  
Sebastiano B. Serpico
Keyword(s):  
Geospatial Data ◽  
Road Extraction ◽  
Street Level ◽  
Road Width ◽  
Optical Imagery

scholarly journals Road Information Extraction from High-Resolution Remote Sensing Images Based on Road Reconstruction

2019 ◽  
Vol 11 (1) ◽  
pp. 79 ◽  
Author(s):  
Tingting Zhou ◽  
Chenglin Sun ◽  
Haoyang Fu
Keyword(s):  
Fast Marching Method ◽  
Road Extraction ◽  
Fast Marching ◽  
Distance Field ◽  
Distance Fields ◽  
Source Distance ◽  
Road Surfaces ◽  
Road Width ◽  
Marching Method ◽  
Boundary Distance

Traditional road extraction algorithms, which focus on improving the accuracy of road surfaces, cannot overcome the interference of shelter caused by vegetation, buildings, and shadows. In this paper, we extract the roads via road centerline extraction, road width extraction, broken centerline connection, and road reconstruction. We use a multiscale segmentation algorithm to segment the images, and feature extraction to get the initial road. The fast marching method (FMM) algorithm is employed to obtain the boundary distance field and the source distance field, and the branch backing-tracking method is used to acquire the initial centerline. Road width of each initial centerline is calculated by combining the boundary distance fields, before a tensor field is applied for connecting the broken centerline to gain the final centerline. The final centerline is matched with its road width when the final road is reconstructed. Three experimental results show that the proposed method improves the accuracy of the centerline and solves the problem of broken centerline, and that the method reconstructing the roads is excellent for maintain their integrity.

scholarly journals Semi-Automatic Extraction of Rural Roads under the Constraint of Combined Geometric and Texture Features

2021 ◽  
Vol 10 (11) ◽  
pp. 754
Author(s):  
Hai Tan ◽  
Zimo Shen ◽  
Jiguang Dai
Keyword(s):  
Image Data ◽  
Texture Features ◽  
Remotely Sensed ◽  
Extraction Methods ◽  
Continuous Change ◽  
Road Extraction ◽  
Rural Roads ◽  
The Road ◽  
Road Width ◽  
Remotely Sensed Image

The extraction of road information from high-resolution remotely-sensed images has important application value in many fields. Rural roads have the characteristics of relatively narrow widths and diversified pavement materials; these characteristics can easily lead to problems involving the similarity of the road texture with the texture of surrounding objects and make it difficult to improve the automation of traditional high-precision road extraction methods. Based on this background, a semi-automatic rural road extraction method constrained by a combination of geometric and texture features is proposed in this paper. First, an adaptive road width extraction model is proposed to improve the accuracy of the initial road centre point. Then, aiming at the continuous change of curvature of rural roads, a tracking direction prediction model is proposed. Finally, a matching model under geometric texture constraints is proposed, which solves the problem of similarity between road and neighbourhood texture to a certain extent. The experimental results show that by selecting different types of experimental scenes or remotely sensed image data, compared with other methods, the proposed method can not only guarantee the road extraction accuracy but also improve the degree of automation to a certain extent.

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.

Web Based GIS Application using Open Source Software for Sharing Geospatial Data

2015 ◽  
Vol 4 (1) ◽  
pp. 1224-1228 ◽  
Author(s):  
Debasish Chakraborty ◽  
◽  
Debanjan Sarkar ◽  
Shubham Agarwal ◽  
Dibyendu Dutta ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Geospatial Data ◽  
Web Based ◽  
Gis Application

Using the potential of peripheral green areas of cities for educational and recreational purposes on the example of Stary Sącz, Nowy Targ and Kraków

2020 ◽  
Vol 65 (1) ◽  
pp. 53-63
Author(s):  
Mateusz Kulig ◽  
Anna Przeniczny ◽  
Piotr Ogórek
Keyword(s):  
Land Cover ◽  
Environmental Protection ◽  
Public Spaces ◽  
Geospatial Data ◽  
Valuable Resource ◽  
Green Areas

AbstractGreen areas located on the peripheries of cities have the potential to become green public spaces not only of recreational but also educational character, promoting at the same time the knowledge about environmental protection. The cities included in the research belong to the małopolskie voivodeship (Lesser Poland voivodeship). With the use of geospatial data of land cover, as well as territorial forms of environmental protection, it was pointed that 48.4% of forest, wooded and shrub green areas located within city borders are covered by a form of environmental protection, thus being a valuable resource of significant nature potential. Making such spaces available in a conscious and attractive way is presented on the example of projects implemented in the cities of: Stary Sącz, Nowy Targ and Kraków. The presented projects were used to make recommendations for city authorities to create green public spaces.

Forest canopy disturbance geospatial data for Lake Superior basin, USA, 1985-2008

2014 ◽  
Author(s):  
Ian W. Housman ◽  
Mark D. Nelson ◽  
Charles H. Perry ◽  
Kirk M. Stueve ◽  
Chengquan Huang
Keyword(s):  
Forest Canopy ◽  
Lake Superior ◽  
Geospatial Data ◽  
Canopy Disturbance

Forest canopy disturbance geospatial data for Lake Michigan basin, USA, 1985-2008

2014 ◽  
Author(s):  
Ian W. Housman ◽  
Mark D. Nelson ◽  
Charles H. Perry ◽  
Kirk M. Stueve ◽  
Chengquan Huang
Keyword(s):  
Forest Canopy ◽  
Lake Michigan ◽  
Geospatial Data ◽  
Michigan Basin ◽  
Canopy Disturbance

Robust Watermarking Scheme for GIS Vector Maps

2018 ◽  
Vol 31 (1) ◽  
pp. 277 ◽  
Author(s):  
Methaq Talib Gaata
Keyword(s):  
Main Idea ◽  
Geospatial Data ◽  
Robust Watermarking ◽  
Digital Map ◽  
Statistical Measures ◽  
Data Authentication ◽  
Two Factors ◽  
Illegal Copying ◽  
Value Decomposition ◽  
Watermarking Scheme

  With the fast progress of information technology and the computer networks, it becomes very easy to reproduce and share the geospatial data due to its digital styles. Therefore, the usage of geospatial data suffers from various problems such as data authentication, ownership proffering, and illegal copying ,etc. These problems can represent the big challenge to future uses of the geospatial data. This paper introduces a new watermarking scheme to ensure the copyright protection of the digital vector map. The main idea of proposed scheme is based on transforming  the digital map to frequently domain using the Singular Value Decomposition (SVD) in order to determine suitable areas to insert the watermark data. The digital map is separated into the isolated parts.Watermark data are embedded within the nominated magnitudes in each part when satisfied the definite criteria. The efficiency of proposed watermarking scheme is assessed within statistical measures based on two factors which are fidelity and robustness. Experimental results demonstrate the proposed watermarking scheme representing ideal trade off for disagreement issue between distortion amount and robustness. Also, the proposed scheme shows  robust resistance for many kinds of attacks.

Sign in / Sign up

Export Citation Format

Share Document