Publication:
Google Earth Engine Algorithm for Evaluating the Performance of Landsat OLI-8 and Sentinel-2 in Mangrove Monitoring

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Issued Date

2023

Resource Type

Book Chapter

File Type

application/pdf

DOI

10.1007/978-3-031-16217-6_15

Rights Holder(s)

Scopus

Bibliographic Citation

Springer Geography. Vol , No. (2023), p.195-205

Suggested Citation

Sitthi A. Google Earth Engine Algorithm for Evaluating the Performance of Landsat OLI-8 and Sentinel-2 in Mangrove Monitoring. Springer Geography. Vol , No. (2023), p.195-205. doi:10.1007/978-3-031-16217-6_15 Retrieved from: https://hdl.handle.net/20.500.14740/10752

Title

Google Earth Engine Algorithm for Evaluating the Performance of Landsat OLI-8 and Sentinel-2 in Mangrove Monitoring

Author(s)

Sitthi A.

Other Contributor(s)

Srinakharinwirot University

Abstract

Mapping mangrove forest extents is important to assess the general health of coastal ecosystems. However, as mangrove forests are dense by nature and tend to grow in mudflats, this chapter introduces physical challenges that often hinder remote scientists from easily accessing the mangrove forestry in field surveys. The publicly available imagery produced by the commonly used Landsat OLI-8 satellite imagery and the newly released Sentinel-2 satellites may be used to map mangrove forest extents remotely. This chapter uses the Google Earth Engine (GEE) tool to conduct a comparative evaluation of the performance of Landsat OLI-8 and Sentinel-2 satellite imagery to map mangrove forest extents on the coast of the Trat province of Thailand. The results indicated that Sentinel-2 is visually and quantitatively preferable compared to Landsat OLI-8 when mapping mangrove forest extents with 88 percentage of accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Subject(s)

Artificial intelligence
 Machine learning
 Mangrove
 Remote sensing

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URI

https://hdl.handle.net/20.500.14740/10752

Collections

Scopus: Year 2023

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