Abstract
Abstract. Based on an improved generative adversarial networks algorithm (CGAN), this paper explores a technical way to realize map transformation through autonomous learning and training of remote sensing images. Just skip the trial process vector data update and cumbersome process of mapping the basic map elements can be automatically transform, the image on the main streets and typical rules of construction material, can achieve automatic identification and transformation, greatly shorten the tile map production and update cycle, improve the efficiency of the network map service quality. The results of the test platform have proved that it can be applied to a certain extent and can basically meet the requirements of network map production.
Highlights
1.1 General InstructionsProviding map service based on network has become a mainstream way of geospatial data application
The intelligent transformation tile map model of remote sensing image based on generative adversarial network will directly skip the vector data extraction and tedious mapping process, greatly shorten the tile map production and update cycle, improve the timeliness and service quality of network map service, and meet the timeliness requirements of network map service application. this paper explores a technical way to realize map transformation through autonomous learning and training of remote sensing images
Based on samples of network map service platform on-line automatic remote sensing image building technology and the network map samples to libraries, to train the map of remote sensing image intelligent switching network model based on Generative adversarial networks (GAN), used to build the model of remote sensing image to Internet map service fast intelligent transformation, combined with the actual demand, the special elements such as text notes, point symbol generation technique, in order to form for users to use the elements of a complete network map, at the same time in order to satisfy different users demand for different levels of the network map, network at different levels to map processing, consistency and network map fidelity of the remote sensing
Summary
Providing map service based on network has become a mainstream way of geospatial data application. At present , tiled map production and update methods is mainly based on remote sensing image In this way, image recognition and extraction are used to update vector data to complete mapping, and tile maps are generated to provide services. The intelligent transformation tile map model of remote sensing image based on generative adversarial network will directly skip the vector data extraction and tedious mapping process, greatly shorten the tile map production and update cycle, improve the timeliness and service quality of network map service, and meet the timeliness requirements of network map service application. Just skip the trial process vector data update and cumbersome process of mapping the basic map elements can be automatically transform, the image on the main streets and typical rules of construction material, can achieve automatic identification and transformation, greatly shorten the tile map production and update cycle, improve the efficiency of the network map service quality, The results of the test platform
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