An Application into Using Artificial Intelligence for Estimating Organic Carbon

Soil is an important resource that is vital for the sustainability of plants, animals and humans. Organic Carbon is an important soil property that describes the amount of carbon broken down from plants or life forms to the soil below. Traditionally to quantify soils organic carbon content, a soil sample is collected and analysed in a laboratory. The collection of the soil sample is a time consuming and expensive process. A promising alternative is to estimate organic carbon based solely upon remotely sensed data. The advantage of using remotely sensed data is that organic carbon can be estimated without going out into the field. Researchers have investigated the association between organic carbon and climatic factors as well as soil site attributes. Factors such as precipitation, temperature, clay content and soil texture have been found to relate to organic carbon content. Artificial Intelligence (AI) and statistical techniques have been successfully used in variou