Identification of Agricultural Drought through Vegetation Health Analysis at Erap Station under the Markham Valley of Papua New Guinea

Abstract

Drought is a phenomenon caused by insufficient soil moisture resulting from prolonged periods of low rainfall and the absence of proper irrigation systems. Its impact on crops, agricultural productivity, and the overall environment is significant. The use of multispectral satellite remote sensing data greatly facilitates the identification of agricultural drought. This study outlines a practical approach for assessing drought using multispectral satellite data. The main objective of this research is to estimate drought indicators and their relationship with ground conditions by analyzing remote sensing datasets through vegetation health index (VHI) analysis. The study is conducted at Erap, which is situated on the northern bank of the Markam River. Spectral bands, like near-infrared, red, and thermal bands of the Landsat 8 satellite are used to produce the VHI database. Multispectral data from the Landsat 8 satellite is the key dataset used to calculate the normalized differential vegetation index (NDVI) and land surface temperature (LST). The vegetation condition index (VCI) and temperature condition index (TCI) are derived from NDVI and LST, respectively. Ultimately, the VHI is calculated by combining VCI and TCI. The resulting VHI varies from 8 to 87, where the lower VHI values refer to extreme drought conditions and higher values denote normal conditions. Mild to moderate drought conditions were observed in the central and some areas in the western part of the research area. The R² between NDVI and VHI is calculated higher (0.72) compared to LST and VHI (0.40). The research indicates that multispectral satellite data is highly beneficial in predicting agricultural drought in any region based on temperature and vegetation conditions. VHI has the potential to be utilized in scientific contexts across different fields, particularly in agriculture and land use planning.