Remote Sensing Based Building Extraction II

ISBN 10: 3036570640 / ISBN 13: 9783036570648

Published by MDPI AG, 2023

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Building extraction from remote sensing data plays an important role in geospatial applications such as urban planning, disaster management, navigation, and updating geographic databases. The rapid development of image processing techniques and the accessibility of very-high-resolution multispectral, hyperspectral, LiDAR, and SAR remote sensing images have further boosted research on building-extraction-related topics. In particular, to meet the recent demand for advanced artificial intelligence models, many research institutes and associations have provided open source datasets and annotated training data, presenting new opportunities to develop advanced approaches for building extraction and monitoring. Hence, there are higher expectations of the efficiency, accuracy, and robustness of building extraction approaches. Additionally, they should meet the demand for processing large city-, national-, and global-scale datasets. Moreover, learning and dealing with imperfect training data remains a challenge, as does unexpected objects in urban scenes such as trees, clouds, and shadows. In addition to building masks, more research has arisen on the automatic generation of LoD2/3 building models from remote sensing data. This follow-up Special Issue of 'Remote Sensing-based Building Extraction', has collected more research on cutting-edge approaches to essential urban processes such as 3D reconstruction, automatic building segmentation, and 3D roof modelling.

Seller Inventory # 9783036570648

Bibliographic Details

• Title: Remote Sensing Based Building Extraction II
• Publisher: MDPI AG
• Publication Date: 2023
• Language: English
• ISBN 10: 3036570640
• ISBN 13: 9783036570648
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 22D millimeters 250 millimeters width by 175 millimeters height by 22 millimeters depth
• Weight: 890 grams

About this title

Synopsis

Building extraction from remote sensing data plays an important role in geospatial applications such as urban planning, disaster management, navigation, and updating geographic databases. The rapid development of image processing techniques and the accessibility of very-high-resolution multispectral, hyperspectral, LiDAR, and SAR remote sensing images have further boosted research on building-extraction-related topics. In particular, to meet the recent demand for advanced artificial intelligence models, many research institutes and associations have provided open source datasets and annotated training data, presenting new opportunities to develop advanced approaches for building extraction and monitoring. Hence, there are higher expectations of the efficiency, accuracy, and robustness of building extraction approaches. Additionally, they should meet the demand for processing large city-, national-, and global-scale datasets. Moreover, learning and dealing with imperfect training data remains a challenge, as does unexpected objects in urban scenes such as trees, clouds, and shadows. In addition to building masks, more research has arisen on the automatic generation of LoD2/3 building models from remote sensing data. This follow-up Special Issue of "Remote Sensing-based Building Extraction", has collected more research on cutting-edge approaches to essential urban processes such as 3D reconstruction, automatic building segmentation, and 3D roof modelling.