The invention discloses a land
space planning and fine management method based on
big data, and relates to the technical field of land planning. A
random forest model is adopted to dynamically adjust a
weight factor, and factors such as land availability, ecological sensitivity and infrastructure
bearing capacity are combined, so that the land
space planning and fine management can be realized. The resource
bearing capacity is comprehensively quantified, high, medium and low
bearing capacity areas are divided, then ecological protection, industrial
layout and public
service coverage references are combined, an
analytic hierarchy process (AHP) is adopted to calculate suitability scores of
ecology, production and life, and accurate space division is realized through a rasterization method. Finally, the performability and adaptability of planning are enhanced through guided linear planning and a dynamic feedback mechanism, space conflicts are optimized through scene
simulation,
model parameters are continuously adjusted through
remote sensing and IoT
monitoring data, dynamic synchronization of planning and reality is achieved, and the problems that in traditional planning,
static performance is high, and adjustment lags are effectively solved.