Soil pH Mapping of Pineapple Crop: A Feasibility Study using Aerial Photo

Mapping and monitoring of soils properties are crucial as they directly affect natural resource management and agricultural activities. Mapping of soil properties at certain interval could ensure sufficient provision of macronutrients for optimum agricultural produce. The use of drone with different imaging capabilities is fairly wide, overcoming time constraints and laborious laboratory analysis. The primary objective of this paper is to demonstrate the application of a standard camera drone to predict peat soil pH of pineapple crop. For the first time, prediction of soil pH is based on the square of Visible Atmospherically Resistant Index (VARI), and is then compared with laboratory-analysed soil pH. Correlation between the two parameters is favourable with R-squared value of about 51%, which compares well with the literature. A considerably large soil sampling may be considered for future study to obtain improved prediction irrespective of soil variability.

I. Introduction

Mapping and monitoring of soils properties are important as they directly affect natural resource management and agricultural activities [1]. Mapping of soil properties at certain interval could ensure sufficient provision of macronutrients for optimum agricultural produce. Conventionally, scaled scale soil maps are produced by dividing the land of interest into reasonable mapping units using aerial photo. Often, these maps do not provide sufficient detail for localized soil properties because extensive analysis of soil properties is prohibitively expensive and laboriously time consuming. For this reason, soil variability is generally not accounted for in soil maps.