Details

Autor(en) / Beteiligte

• Jiang, Ce
• Miao, Yahui
• Xi, Zenglei

Titel

A new method of extracting built-up area based on multi-source remote sensing data: a case study of Baoding central city, China

Ist Teil von

• Geocarto international, 2022-10, Vol.37 (20), p.6072-6086

Ort / Verlag

Taylor & Francis

Erscheinungsjahr

2022

Link zum Volltext

Quelle

Taylor & Francis Journals Complete

Beschreibungen/Notizen

• The accurate extraction of Built-Up Areas (BUAs) is of great significance for analysing urban spatial evolution patterns. In this study, we proposed a new method for high-precision extraction of BUA based on multi-source remote sensing data. Firstly, Built-Up Area Extraction Index (BAEI) was used to preliminarily identify the BUA based on Landsat 8 imagery. Secondly, the Support Vector Machine (SVM) algorithm was used for improving the extraction precision of BUA, whose selected training sample was established on the Nighttime Light (NTL) data. Then, images fusion and continuity correction were carried out. Finally, the Neighbourhood Statistics Analysis (NSA) was used to adjust and remove the part of the non-urban centre which was misjudged as the BUA. Our results show that this method has better performance on both overall accuracy and Kappa coefficient compared with other classic methods, which provides empirical reference for understanding law of land expansion and rational land planning.