Spatial analysis of forest biomass in Mississippi state using GIS

performing spatial analysis is valuable in which it can aid humans in understanding any natural phenomena and to predict human interaction with the environment and any other natural earth processes. Geographic information system (GIS) is a powerful tool can be used in a real-world for solving issues concerning health-care, climate, water, land sacristy and other complex problems. The project aims to examine and analyze data layers of forest biomass in Mississippi State and to display how to map natural and environmental resources in a proper way. The methods provided in this analysis were beneficial in showing the biomass average, variance, as well as its Z score index values. Maps showing forest biomass average and variance were produced. From these maps, it can be determined that Southern Mississippi especially in the southeast has a much higher forest biomass due to large portions of forest being located in these counties. Additionally, covariance and correlation matrices were formed based on biomass average and distance to river. This confirmed that there was no relationship between forest biomass and distance to Mississippi river. According to the Spatial Autocorrelation report, Moran's index is (0.257) positive indicating clustering of forest biomass especially in the southeast. A Z score is -0.336, which is negative and supports randomization, according to the High/Low clustering report. Finally, clustering and hotspot maps show that counties in the southeast have higher forest biomass resource than other counties, which have a random distribution of biomass. Positive significant values show in southeast part of Mississippi State.