Credit line processing method and device, user resource processing method and device

Abstract

The embodiment of this specification provides a credit line processing method and device, and a user resource processing method and device, wherein, a credit line processing method includes: obtaining the identity information entered by the target user and the plot information of the crop plot; The target user displays the map page; if the labeling action input on the map page is detected, the plot boundary information corresponding to the labeling action is determined; the labeling area of ​​the crop plot is calculated based on the plot boundary information; according to the Determine the credit line of the target user based on the marked area, the land plot information, and the user data obtained based on the identity information.

Description

technical field [0001] This document relates to the technical field of data processing, and in particular to a credit line processing method and device, and a user resource processing method and device. Background technique [0002] With the promotion and application of communication technology and big data in traditional industries, services for digital production management based on big data have emerged in agriculture, forestry, aquaculture and other fields. It mainly depends on the production and planting activities, depending on the crop planting area and crop types. These users are limited by the thin data dimension when performing asset evaluation, contract signing, credit analysis and other activities, and are often in a relatively disadvantaged position. Contents of the invention [0003] One or more embodiments of this specification provide a credit line processing method. The credit line processing method includes: obtaining the identity information entered by ...

AI Technical Summary

Problems solved by technology

[0002] With the promotion and application of communication technology and big data in traditional industries, services for digital production management based on big data have emerged in agriculture, forestry, aquaculture and other fields. It mainly depends on the production and planting activities, depending on the crop planting area and crop types. These users are limited by the thin data dimension when performing asset evaluation, contract signing, credit analysis and other activities, and are often in a relatively disadvantaged position.

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