Semantic analysis of deforestation soil effect using multispectral reflectance

In several last decades' deforestation as act of denudation and devastation has growing to critical levels. Although the effects of deforestation are hugely impactive, many people do not fully well understand the effects due to deforestation acts. To present deep knowledge about deforestation, after gaining knowledge about deforestation rates, it is necessary to understanding the deforestation impact on factual conditions. In this paper, we proposed a new method to represent semantic analysis for the deforestation soil in human interpretation. We proposed idea to interpret reflected 'substances (material)' of deforestation area in spectrum domain into human language. To portray the deforestation soil condition into meaningful words, we construct three-dimensional semantic spaces to analyze the soil condition in deforestation area, which are: (1) Soil Moisture Measurement, (2) soil thermal, and (3) soil salinity were used to interpreting the soil condition after deforestation activity. Riau has been selected as the study area, where the data was acquired by using Landsat Satellite images between 2013 and 2014; where there is a big forest fire occurs. The experimental result produces new semantic analysis matrices to determining the soil condition after deforestation in different context.