Monitoring Plant Health Using Multispectral Satellite Imagery Based on Various Spectral Indices

Abstract

Multispectral satellite images acquired through remote sensing can identify, estimate, monitor, and manage the ecological environment, agricultural health, drought, and yield. This paper compares the effectiveness of the Temperature Vegetation Dryness Index (TVDI) and Vegetation Health Index (VHI) in plant growth monitoring. An oil palm plantation owned by New Britain Palm Oil Limited (NBPOL) near Erap station, within the Markham River basin, was selected for this study. Multispectral bands, like red, near-infrared, shortwave infrared, and thermal bands of a Landsat 8 Satellite, were utilized to produce land surface temperature (LST) and normalized difference vegetation index (NDVI) databases, which are key parameters for calculating the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). These VCI and TCI indices were then used in the VHI and TVDI models. The VHI ranged from 11.83 to 87.78, while the TVDI ranged from 0.142 to 0.969. Low VHI values and high TVDI values indicate extreme drought conditions. A strong coefficient of determination was found between LST and VHI (R² = 0.89) and between NDVI and VHI (R² = 0.88), indicating that NDVI and LST are equally crucial for assessing vegetation health. Conversely, a near-perfect correlation was observed between LST and TVDI (R² = 0.98), compared to NDVI and TVDI (R² = 0.48). The results showed that VHI offers more efficient and spatially detailed results than TVDI. The study revealed that VHI helps monitor agricultural drought by better combining vegetation condition and temperature information than other models. Furthermore, the normalized difference moisture index (NDMI) and NDVI were derived using Sentinel-2 data over 2 years. The correlation shows that the vegetation index decreases as moisture levels decline.