Land Use Simulation of Shanghai Based on Multi-source Data Integration

Abstract

With the continuous improvement of big data mining technology, massive and multi-source land use spatio-temporal big data began to emerge. Big data thinking plays an increasingly important role in ecological monitoring, smart city construction, public safety and support for major decisions. Taking Shanghai as an example, this paper integrates ESA CCI, GlobeLand 30 and MODIS data by voting method, and inputs MCE-CA-Markov model to obtain more accurate prediction results. This study provides a new simulation thinking, which can provide ideas for the prediction of Shanghai and other similar cities.