Utilizing TVDI and NDWI to Classify Severity of Agricultural Drought in Chuping, Malaysia
| Autor: | Aimrun Wayayok, Wataru Takeuchi, Rowshon Kamal, Abdul Rashid Mohamed Shariff, Yang Ping Lee, Veena Shashikant |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
010504 meteorology & atmospheric sciences
Cloud seeding 010501 environmental sciences Standard score Disease cluster 01 natural sciences Normalized Difference Vegetation Index remote sensing medicine Water content 0105 earth and related environmental sciences LST business.industry NDWI Agriculture TVDI Vegetation agricultural drought Dryness Environmental science Physical geography medicine.symptom business Agronomy and Crop Science |
| Zdroj: | Agronomy Volume 11 Issue 6 Agronomy, Vol 11, Iss 1243, p 1243 (2021) |
| ISSN: | 2073-4395 |
| DOI: | 10.3390/agronomy11061243 |
| Popis: | 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 areas in the state to evaluate water deficits severity and cloud seeding points during drought. |
| Databáze: | OpenAIRE |
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