APPLICATION OF KRIGING REGRESSION TO SOIL ORGANIC CARBON MAPPING: A CASE IN HUONG LAM COMMUNE, A LUOI DISTRICT, THUA THIEN HUE PROVINCE

Abstract

Soil organic carbon plays an essential role in the assessment of soil quality, especially for agricultural purposes. This research was conducted in Huong Lam commune, A Luoi district, to understand the influence of slope, elevation, and normalized difference vegetation index (NDVI) on soil organic carbon mapping using the kriging regression model. Soil organic carbon data were obtained from 48 randomly chosen locations at a depth from 0 to 30 cm. Three independent variables consisting of the slope, elevation, and NDVI were extracted from remote sensing data. The results show that the slope is the most influential on the soil organic carbon content with a correlation of 43% compared with 7% and 1% for NDVI and elevation, respectively. The slope could be used for soil organic carbon mapping using kriging regression. More independent variables should be considered to establish the best model for kriging regression