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Chi-Farn Chen
Researcher at National Central University
Publications - 35
Citations - 1022
Chi-Farn Chen is an academic researcher from National Central University. The author has contributed to research in topics: Computer science & Normalized Difference Vegetation Index. The author has an hindex of 14, co-authored 30 publications receiving 780 citations.
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Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data
TL;DR: In this paper, the applicability of monthly MODIS normalized difference vegetation index (NDVI) and land surface temperature (LST) data for agricultural drought monitoring in the Lower Mekong Basin (LMB) in the dry season from November 2001 to April 2010 was explored.
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A comparative analysis of multitemporal MODIS EVI and NDVI data for large-scale rice yield estimation
TL;DR: In this article, a comparative analysis of multitemporal Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) and normalized difference index (NDVI) data for estimating rice crop yields in the Mekong River Delta (MRD), Vietnam was performed.
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Multi-decadal mangrove forest change detection and prediction in honduras, central america, with landsat imagery and a markov chain model
Chi-Farn Chen,Nguyen Thanh Son,Ni-Bin Chang,Cheng Ru Chen,L. Y. Chang,Miguel Valdez,Gustavo Centeno,Carlos Alberto Thompson,Jorge Luis Aceituno +8 more
TL;DR: Investigating spatiotemporal changes in Honduran mangrove forests using Landsat imagery during the periods 1985–1996, 1996–2002, and 2002–2013 found that the area of mangroves could be continuously reduced by 1,200 ha from 2013 to 2020, indicating that institutional interventions should be taken for sustainable management ofMangrove ecosystems in this coastal region.
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Mangrove Mapping and Change Detection in Ca Mau Peninsula, Vietnam, Using Landsat Data and Object-Based Image Analysis
TL;DR: The objective of this study is to investigate the multidecadal change in mangrove forests in Ca Mau peninsula, South Vietnam, based on Landsat data from 1979 to 2013, and show satisfactory agreement with the overall accuracy higher than 82%.
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Prediction of rice crop yield using MODIS EVI−LAI data in the Mekong Delta, Vietnam
TL;DR: In this paper, the authors developed an approach for rice crop yield prediction in the Vietnamese Mekong Delta using the Moderate Resolution Imaging Spectroradiometer MODIS enhanced vegetation index EVI and leaf area index LAI.