Surface water body product generation method and system based on Google Earth Engine cloud platform

Abstract

The invention discloses a surface water body product generation method and system based on a Google Earth Engine cloud platform. According to the invention, the method comprises the steps: acquiring afull-time-sequence Landsat8 satellite remote sensing image by using a Google Earth Engine remote sensing big data cloud platform; manually selecting high-precision training samples to form differenttypes of water body and non-water body typical sample libraries; constructing a characteristic wave band by adopting a plurality of indexes such as a normalized vegetation index, a normalized water body index and a topographic slope and an image original wave band; in combination with high-precision training samples and characteristic wave bands, realizing the full-time-sequence surface water bodyintelligent extraction by adopting a random forest classifier, constructing a surface water body occurrence frequency model, and realizing automatic generation of surface water body products. According to the invention, the water body product generated by the method has higher spatial-temporal resolution, can reflect the seasonal dynamic change rule of the surface water body, and can be applied to automatic production of national or global scale long-time sequence surface water body products.

Description

technical field [0001] The invention relates to the technical field of intelligent recognition of remote sensing images, in particular to a method and system for generating surface water body products based on the Google EarthEngine cloud platform. Background technique [0002] Water is the foundation that supports the survival and development of all kinds of life in nature, and it also profoundly affects the natural and human landscape on the earth's surface. Generally speaking, surface water bodies refer to surface types such as lakes, rivers, reservoirs, and breeding areas in inland areas. Affected by factors such as natural rainfall and human production and life, surface water bodies have significant seasonal dynamic changes. Satellite remote sensing itself has the advantages of large scale, low cost, and fast revisiting, and can quickly and accurately grasp the temporal and spatial dynamic distribution information of surface water bodies. [0003] The fast-returning s...

AI Technical Summary

Problems solved by technology

The surface water body has obvious seasonal dynamic change characteristics, and the current surface water body products are mostly single-phase products, which are difficult to reflect the seasonal dynamics of the water body

Some surface water products are developed using multi-temporal images, but there are still few products developed using full-time series Landsat remote sensing data

Images