A Semantic Multi-Valued Logic for Deforestation Phenomena Interpretation

The detection of deforestation by remote sensing technologies has been one of the most important research issues in forest monitoring over the last decades. However, only identifying the area of change is usually not sufficient to understand how critical the effects are on the environment including increased CO2 emissions, loss of biodiversity, and soil degradation. To interpret the causes of the detected forest loss and the full impacts upon an ecosystem, additional expert knowledge is required. Traditionally the environmental standard classifies the measurement value, as called parameter value, from the environmental sensor into several condition categories to presenting meaningful quantitative measures of environmental results and establishing whether or not the problem of environmental exists. There are several traditional calculations to measure the interpretation of environmental phenomena such as numerical approach as represented, e.g., by pattern matching that is supported by classical Boolean logic rule. However, in the Boolean logic rule, the truth interpretation values of parameters may only be the truth values, true and false in a category. This paper demonstrates the type of logical approach that has huge potential to assign the interpretation of environmental phenomena in where the truth value may fall in the range between completely true and completely false.