Loading…

Exploiting Sentinel-1 data and machine learning–based random forest for collectively mapping rice fields in Taiwan

Rice is the most important crop in Taiwan. Monitoring rice-growing areas is thus essential for crop management and food decision-making processes. This research aims to develop an approach for seasonally mapping rice areas from time-series Sentinel-1 data in Taiwan. The data were processed for 2019...

Full description

Saved in:
Bibliographic Details
Published in:Applied geomatics 2022-06, Vol.14 (2), p.405-419, Article 405
Main Authors: Son, Nguyen-Thanh, Chen, Chi-Farn, Chen, Cheng-Ru, Cheng, Youg-Sin, Toscano, Piero, Syu, Chein-Hui, Guo, Horng-Yuh, Chen, Shu-Ling, Liu, Tsang-Sen, Zhang, Yi-Ting, Lin, Huan-Sheng, Chen, Shih-Hsiang, Valdez, Miguel
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Rice is the most important crop in Taiwan. Monitoring rice-growing areas is thus essential for crop management and food decision-making processes. This research aims to develop an approach for seasonally mapping rice areas from time-series Sentinel-1 data in Taiwan. The data were processed for 2019 and 2020 rice cropping seasons, following three main steps: (1) data pre-processing to construct smooth time-series satellite data, (2) rice area estimation using random forests (RF), and (3) accuracy assessment. The mapping results compared with the government’s reference data showed overall accuracy and kappa coefficient higher than 87.7% and 0.76, respectively. The rice area estimates at the county level well agreed with the official statistics, with the root mean square error (RMSE) in percentage smaller than 19.7%. An examination of changes in cropping areas between 2019 and 2020 showed a noticeable reduction of rice areas in 2020, mainly attributed to severe drought conditions.
ISSN:1866-9298
0034-4257
1866-928X
1879-0704
DOI:10.1007/s12518-022-00440-4