Cover Image
Read Now

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...

Full description

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:
U-net
Feature Fusion
5g Signal Simulation
Mathematical Morphology
High Resolution Optical Images
Data Fusion
Developing City
Deep Learning
Multiscale Siamese Convolutional Networks (mscns)
Richer Convolution Features
Modelling
Indoor Modelling
Lidar Point Cloud
Digital Building Height
Land-use
Very High Resolution Imagery
Method Comparison
Morphological Attribute Filter
Building Detection
Aerial Images
Attention Mechanism
Image Fusion
Boundary Extraction
High Spatial Resolution Remote Sensing Imagery
Deep Convolutional Neural Network
Building Reconstruction
Building Extraction
Gabor Filter
Point Clouds
Morphological Profile
Gis Data
Vhr Remote Sensing Imagery
Point Cloud
Change Detection
Active Contour Model
3d Reconstruction
High-resolution Aerial Imagery
3-d
Imagery
Elevation Map
N/a
3d Urban Expansion
High-resolution Satellite Images
Accuracy Analysis
Inria Aerial Image Labeling Dataset
Generative Adversarial Network
Occlusion
Unmanned Aerial Vehicle (uav)
Urban Building Extraction
Simple Linear Iterative Clustering (slic)
Building Edges Detection
History Of Engineering And Technology / Bicssc
Outline Extraction
Feature Extraction
Binary Decision Network
Straight-line Segment Matching
Building Regularization Technique
Object Recognition
Open Data
High Spatial Resolution Remotely Sensed Imagery
Web-net
Lidar
Remote Sensing
High-resolution Aerial Images
Building Boundary Extraction
Massachusetts Buildings Dataset
Building
Ultra-hierarchical Sampling
Semantic Segmentation
Boundary Regulated Network
Roof Segmentation
Convolutional Neural Network
Very High Resolution
Dtm Extraction
Building Index
Reconstruction
Fully Convolutional Network
Mobile Laser Scanning
Feature-level-fusion
Regularization
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

Similar Items