Global Warming Prediction Model of Fish Migration Based on ArcGIS

Abstract

Rising global ocean temperatures will disrupt the livelihoods of people who depend on fishing for marine crops. Therefore, we propose fishery migration prediction models to solve the problem. We considered the effects of seawater temperature and salinity, and constructed a fish school migration prediction model based on ArcGIS. On this basis, a thermodynamic map of fish school distribution were made using ArcGIS software and kriging interpolation and nuclear density analysis. Moreover, linear interpolation and fitting are used to obtain the relationship between the annual fish movement distance and the year to predict the fish migration routes in the next 50 years.

Keywords

• rising global ocean temperatures
• fish migration prediction model
• arcgis
• fitting