Multidecadal evaluation of changes in coffee-growing areas using Landsat data in Central Highlands, Vietnam

Nguyen Thanh Son, Chi Farn Chen, Cheng Ru Chen, Youg Sin Cheng, Shih Hsiang Chen

Research output: Contribution to journalArticlepeer-review

Abstract

Vietnam is the world’s second-largest coffee exporter. Information on coffee-growing areas is thus important for production estimation. This research developed an approach for coffee mapping and change detection using Landsat and DEM data in Central Highlands, Vietnam. The data were processed for 1995, 2005, and 2020 using random forests (RF). The mapping results, verified with reference data, showed overall accuracy and Kappa coefficient higher than 86.9% and 0.74, respectively. These findings were reaffirmed by a close relationship between the satellite-based coffee area and official statistics, with the root mean squared percentage error (RMSPE) and mean absolute percentage error (MAPE) greater than 9.9% and 7.6%, respectively. From 1995 to 2020, the newly planted coffee area increased by 135,520 ha, due to the conversion of forests to coffee plantations. Such distributions of coffee areas and decadal changes in farming activities are critically useful for policymakers to formulate successful crop planning strategies.

Original languageEnglish
Article number2204099
JournalGeocarto International
Volume38
Issue number1
DOIs
StatePublished - 2023

Keywords

  • Landsat data
  • Vietnam
  • change detection
  • coffee
  • random forests

Fingerprint

Dive into the research topics of 'Multidecadal evaluation of changes in coffee-growing areas using Landsat data in Central Highlands, Vietnam'. Together they form a unique fingerprint.

Cite this