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Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis

This study presents a novel approach to predicting paddy yields in Brunei's Wasan Rice Scheme using projected normalized difference vegetation index (NDVI) values derived from climate projections under three time periods: near future (2020–2046), mid-future (2047–2073), and far future (2074–...

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Main Authors: Hamizah, Rhymee, Shahriar, Shams, Uditha, Ratanyake, Ena Kartina, Abdul Rahman
Format: Article
Language:English
English
Published: INTI International University 2024
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
Online Access:http://eprints.intimal.edu.my/2071/1/ij2024_45.pdf
http://eprints.intimal.edu.my/2071/2/612
http://eprints.intimal.edu.my/2071/
https://intijournal.intimal.edu.my
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id my-inti-eprints.2071
record_format eprints
spelling my-inti-eprints.20712024-12-02T03:55:05Z http://eprints.intimal.edu.my/2071/ Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis Hamizah, Rhymee Shahriar, Shams Uditha, Ratanyake Ena Kartina, Abdul Rahman T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery This study presents a novel approach to predicting paddy yields in Brunei's Wasan Rice Scheme using projected normalized difference vegetation index (NDVI) values derived from climate projections under three time periods: near future (2020–2046), mid-future (2047–2073), and far future (2074–2100). Employing CMIP6 socioeconomic pathways (SSP245, SSP370, SSP585), random forest (RF) and multiple linear regression (MLR) models were utilised to link historical NDVI with meteorological factors such as rainfall and temperature. Results indicate that main-season yields are expected to decline or stabilize across scenarios, while off-season NDVI consistently increases, reflecting robust vegetation recovery. These findings emphasise the differential impacts of climate change across growing seasons, providing critical insights for agricultural planning and adaptation strategies. By integrating scenario-based NDVI projections and predictive modeling, this study offers a comprehensive framework for understanding future crop dynamics under changing climatic conditions. INTI International University 2024-12 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2071/1/ij2024_45.pdf text en cc_by_4 http://eprints.intimal.edu.my/2071/2/612 Hamizah, Rhymee and Shahriar, Shams and Uditha, Ratanyake and Ena Kartina, Abdul Rahman (2024) Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis. INTI JOURNAL, 2024 (45). pp. 1-12. ISSN e2600-7320 https://intijournal.intimal.edu.my
institution INTI International University
building INTI Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider INTI International University
content_source INTI Institutional Repository
url_provider http://eprints.intimal.edu.my
language English
English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
Hamizah, Rhymee
Shahriar, Shams
Uditha, Ratanyake
Ena Kartina, Abdul Rahman
Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis
description This study presents a novel approach to predicting paddy yields in Brunei's Wasan Rice Scheme using projected normalized difference vegetation index (NDVI) values derived from climate projections under three time periods: near future (2020–2046), mid-future (2047–2073), and far future (2074–2100). Employing CMIP6 socioeconomic pathways (SSP245, SSP370, SSP585), random forest (RF) and multiple linear regression (MLR) models were utilised to link historical NDVI with meteorological factors such as rainfall and temperature. Results indicate that main-season yields are expected to decline or stabilize across scenarios, while off-season NDVI consistently increases, reflecting robust vegetation recovery. These findings emphasise the differential impacts of climate change across growing seasons, providing critical insights for agricultural planning and adaptation strategies. By integrating scenario-based NDVI projections and predictive modeling, this study offers a comprehensive framework for understanding future crop dynamics under changing climatic conditions.
format Article
author Hamizah, Rhymee
Shahriar, Shams
Uditha, Ratanyake
Ena Kartina, Abdul Rahman
author_facet Hamizah, Rhymee
Shahriar, Shams
Uditha, Ratanyake
Ena Kartina, Abdul Rahman
author_sort Hamizah, Rhymee
title Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis
title_short Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis
title_full Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis
title_fullStr Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis
title_full_unstemmed Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis
title_sort exploring rice yield variability under climate change through ndvi analysis
publisher INTI International University
publishDate 2024
url http://eprints.intimal.edu.my/2071/1/ij2024_45.pdf
http://eprints.intimal.edu.my/2071/2/612
http://eprints.intimal.edu.my/2071/
https://intijournal.intimal.edu.my
_version_ 1817849529535299584
score 13.223943

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