Land cover classification and change detection analysis of multispectral satellite images using machine learning

Nyein Soe Thwal, Takaaki Ishikawa, Hiroshi Watanabe

研究成果

2 被引用数 (Scopus)

抄録

Land cover classification and change detection analysis based on remote sensing images using machine learning algorithm has become one of the important factors for environmental management and urban planning. We select Yangon as the study area because the government faces many problems in urban planning sectors due to the population growth and urban sprawl. Therefore, the proposed method aims to perform the land cover classification in Yangon using Random Forest (RF) classifier in Google Earth Engine (GEE) and post-classification change detection between 1987 and 2017 with 5 years interval periods are evaluated. Despite land cover classifications using satellite imagery have been executed in the past decades, the classification of remotely sensed data integrating with multiple spectral, temporal and textural features and processing time for classification using time series data still have limitations. To overcome these limitations, features extracted from Sentinel-2, Landsat-8, Landsat-7, Landsat-5 and Open Street Map (OSM) are executed for classification and cloud-based GEE platform is used to reduce the processing time. Some spectral indexes such as NDVI, NDBI and slope from SRTM are calculated to achieve better classification. Land cover classification is performed by using the RF classifier with the different bands' combination. Land cover classification map with 7 classes (Shrub Land, Bare Land, Forest, Vegetation, Urban Area, Lake and River) is obtained with the overall accuracy of 96.73% and kappa statistic of 0.95 for 2017. Finally, change detection analysis over 30 years is performed and the significant changes in build-up, bare land, and agriculture have been resulted.

本文言語English
ホスト出版物のタイトルImage and Signal Processing for Remote Sensing XXV
編集者Lorenzo Bruzzone, Francesca Bovolo, Jon Atli Benediktsson
出版社SPIE
ISBN(電子版)9781510630130
DOI
出版ステータスPublished - 2019
イベントImage and Signal Processing for Remote Sensing XXV 2019 - Strasbourg, France
継続期間: 2019 9 92019 9 11

出版物シリーズ

名前Proceedings of SPIE - The International Society for Optical Engineering
11155
ISSN(印刷版)0277-786X
ISSN(電子版)1996-756X

Conference

ConferenceImage and Signal Processing for Remote Sensing XXV 2019
国/地域France
CityStrasbourg
Period19/9/919/9/11

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • コンピュータ サイエンスの応用
  • 応用数学
  • 電子工学および電気工学

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