Staff View: Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia

Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia

Agricultural drought is crucial in understanding the relationship to crop production functions which can be monitored using satellite remote sensors. The aim of this research is to combine temperature vegetation dryness index (TVDI) and normalized difference water index (NDWI) classifications for id...

Full description

Saved in:

Bibliographic Details
Main Authors:	Shashikant, Veena, Mohamed Shariff, Abdul Rashid, Wayayok, Aimrun, Kamal, Md Rowshon, Lee, Yang Ping, Takeuchi, Wataru
Format:	Article
Published:	MDPI 2021
Online Access:	http://psasir.upm.edu.my/id/eprint/93523/ https://www.mdpi.com/2073-4395/11/6/1243
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my.upm.eprints.93523
record_format	eprints
spelling	my.upm.eprints.935232023-01-13T03:43:36Z http://psasir.upm.edu.my/id/eprint/93523/ Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia Shashikant, Veena Mohamed Shariff, Abdul Rashid Wayayok, Aimrun Kamal, Md Rowshon Lee, Yang Ping Takeuchi, Wataru Agricultural drought is crucial in understanding the relationship to crop production functions which can be monitored using satellite remote sensors. The aim of this research is to combine temperature vegetation dryness index (TVDI) and normalized difference water index (NDWI) classifications for identifying drought areas in Chuping, Malaysia which has regularly recorded high temperatures. TVDI and NDWI are assessed using three images of the dry spell period in March for the years 2015, 2016 and 2017. NDWI value representing water content in vegetation decreases numerically to −0.39, −0.37 and −0.36 for the year 2015, 2016 and 2017. Normalized difference vegetation indices (NDVI) values representing vegetation health status in the given area for images of years 2015 to 2017 decreases significantly (p ≤ 0.05) from 0.50 to 0.35 respectively. Overall, TVDI in the Chuping area showed agricultural drought with an average value of 0.46. However, Kilang Gula Chuping area in Chuping showed a significant increase in dryness for all of the three years assessed with an average value of 0.70. When both TVDI and NDWI were assessed, significant clustering of spots in Chuping, Perlis for all the 3 years was identified where geographical local regressions of 0.84, 0.70 and 0.70 for the years 2015, 2016 and 2017 was determined. Furthermore, Moran’s I values revealed that the research area had a high I value of 0.63, 0.30 and 0.23 with respective Z scores of 17.80, 8.63 and 6.77 for the years 2015, 2016 and 2017, indicating that the cluster relationship is significant in the 95–99 percent confidence interval. Using both indices alone was sufficient to understand the drier spots of Chuping over 3 years. The findings of this research will be of interest to local agriculture authorities, like plantation and meteorology departments to understand drier MDPI 2021-06-19 Article PeerReviewed Shashikant, Veena and Mohamed Shariff, Abdul Rashid and Wayayok, Aimrun and Kamal, Md Rowshon and Lee, Yang Ping and Takeuchi, Wataru (2021) Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia. Agronomy, 11 (6). art. no. 1243. pp. 1-18. ISSN 2073-4395 https://www.mdpi.com/2073-4395/11/6/1243 10.3390/agronomy11061243
institution	Universiti Putra Malaysia
building	UPM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Putra Malaysia
content_source	UPM Institutional Repository
url_provider	http://psasir.upm.edu.my/
description	Agricultural drought is crucial in understanding the relationship to crop production functions which can be monitored using satellite remote sensors. The aim of this research is to combine temperature vegetation dryness index (TVDI) and normalized difference water index (NDWI) classifications for identifying drought areas in Chuping, Malaysia which has regularly recorded high temperatures. TVDI and NDWI are assessed using three images of the dry spell period in March for the years 2015, 2016 and 2017. NDWI value representing water content in vegetation decreases numerically to −0.39, −0.37 and −0.36 for the year 2015, 2016 and 2017. Normalized difference vegetation indices (NDVI) values representing vegetation health status in the given area for images of years 2015 to 2017 decreases significantly (p ≤ 0.05) from 0.50 to 0.35 respectively. Overall, TVDI in the Chuping area showed agricultural drought with an average value of 0.46. However, Kilang Gula Chuping area in Chuping showed a significant increase in dryness for all of the three years assessed with an average value of 0.70. When both TVDI and NDWI were assessed, significant clustering of spots in Chuping, Perlis for all the 3 years was identified where geographical local regressions of 0.84, 0.70 and 0.70 for the years 2015, 2016 and 2017 was determined. Furthermore, Moran’s I values revealed that the research area had a high I value of 0.63, 0.30 and 0.23 with respective Z scores of 17.80, 8.63 and 6.77 for the years 2015, 2016 and 2017, indicating that the cluster relationship is significant in the 95–99 percent confidence interval. Using both indices alone was sufficient to understand the drier spots of Chuping over 3 years. The findings of this research will be of interest to local agriculture authorities, like plantation and meteorology departments to understand drier
format	Article
author	Shashikant, Veena Mohamed Shariff, Abdul Rashid Wayayok, Aimrun Kamal, Md Rowshon Lee, Yang Ping Takeuchi, Wataru
spellingShingle	Shashikant, Veena Mohamed Shariff, Abdul Rashid Wayayok, Aimrun Kamal, Md Rowshon Lee, Yang Ping Takeuchi, Wataru Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia
author_facet	Shashikant, Veena Mohamed Shariff, Abdul Rashid Wayayok, Aimrun Kamal, Md Rowshon Lee, Yang Ping Takeuchi, Wataru
author_sort	Shashikant, Veena
title	Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia
title_short	Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia
title_full	Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia
title_fullStr	Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia
title_full_unstemmed	Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia
title_sort	utilizing tvdi and ndwi to classify severity of agricultural drought in chuping, malaysia
publisher	MDPI
publishDate	2021
url	http://psasir.upm.edu.my/id/eprint/93523/ https://www.mdpi.com/2073-4395/11/6/1243
_version_	1755873903225339904
score	13.211869

Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping, Malaysia

Similar Items