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Remote Sensing based Building Extraction

Building extraction from remote sensing data plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Even though significant research has been carried out for more than two decades, the success of automatic...

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Bibliographic Details
Main Author: Yang, Bisheng
Other Authors: Awrangjeb, Mohammad, Hu, Xiangyun, Tian, Jiaojiao
Format: eBook
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
Subjects:
3-d
High-resolution Aerial Imagery
Imagery
U-net
Feature Fusion
Elevation Map
5g Signal Simulation
Mathematical Morphology
N/a
3d Urban Expansion
High-resolution Satellite Images
Accuracy Analysis
High Resolution Optical Images
Data Fusion
Inria Aerial Image Labeling Dataset
Developing City
Occlusion
Generative Adversarial Network
Deep Learning
Unmanned Aerial Vehicle (uav)
Multiscale Siamese Convolutional Networks (mscns)
Richer Convolution Features
Simple Linear Iterative Clustering (slic)
Urban Building Extraction
Building Edges Detection
Modelling
History Of Engineering & Technology / Bicssc
Indoor Modelling
Lidar Point Cloud
Digital Building Height
Land-use
Outline Extraction
Very High Resolution Imagery
Method Comparison
Feature Extraction
Binary Decision Network
Morphological Attribute Filter
Building Detection
Aerial Images
Attention Mechanism
Image Fusion
Straight-line Segment Matching
Boundary Extraction
Building Regularization Technique
High Spatial Resolution Remote Sensing Imagery
Deep Convolutional Neural Network
Object Recognition
Building Reconstruction
High Spatial Resolution Remotely Sensed Imagery
Open Data
Building Extraction
Gabor Filter
Web-net
Lidar
Remote Sensing
Point Clouds
Morphological Profile
High-resolution Aerial Images
Massachusetts Buildings Dataset
Building Boundary Extraction
Building
Semantic Segmentation
Ultra-hierarchical Sampling
Boundary Regulated Network
Gis Data
Roof Segmentation
Convolutional Neural Network
Vhr Remote Sensing Imagery
Very High Resolution
Dtm Extraction
Building Index
Point Cloud
Reconstruction
Fully Convolutional Network
Change Detection
Mobile Laser Scanning
Regularization
Active Contour Model
Feature-level-fusion
3d Reconstruction
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:Building extraction from remote sensing data plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Even though significant research has been carried out for more than two decades, the success of automatic building extraction and modeling is still largely impeded by scene complexity, incomplete cue extraction, and sensor dependency of data. Most recently, deep neural networks (DNN) have been widely applied for high classification accuracy in various areas including land-cover and land-use classification. Therefore, intelligent and innovative algorithms are needed for the success of automatic building extraction and modeling. This Special Issue focuses on newly developed methods for classification and feature extraction from remote sensing data for automatic building extraction and 3D
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by-nc-nd/4.0/
Physical Description:1 electronic resource (442 p.)
ISBN:9783039283835
books978-3-03928-383-5
9783039283828

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