A library for off-line inverse geocoding that supports location up to district level

Related tags

GUI jetgeo
Overview

jetgeo Logo

GitHub Workflow Status GitHub release (latest SemVer) GitHub Repo stars GitHub

jetgeo 是一个用于离线逆地理编码的库,支持转换位置到县/地区级别, 通过它你可以消耗一定的内存以换取一个内存级别的转换。主要适用于精度要求不高的一些服务端场景。 如果你需要一个精确定位的场景,那么它可能并不合适,此时你可能需要适用地理位置信息提供商的一些服务, 但他们往往有次数限制或者需要支付更多的费用。

目录

快速开始

  1. 导入依赖

    <dependency>
        <groupId>com.ling5821</groupId>
        <artifactId>jetgeo</artifactId>
        <version>${jetgeo.version}</version>
    </dependency>
  2. 下载项目目录地理位置资源包 geodata.7z

  3. 解压数据到你的目录 例如 /data/geodata

注意: 解压后目录结构

geodata

├── province

├── city

├── district

  1. 一个例子

    public class JetGeoExample {
        public static final JetGeo jetGeo;
        static {
            JetGeoProperties properties = new JetGeoProperties();
            //填写你的geodata的目录
            properties.setGeoDataParentPath("/data/geodata");
            //设置逆地理编码的级别
            //properties.setLevel(LevelEnum.province);
            //properties.setLevel(LevelEnum.city);
            properties.setLevel(LevelEnum.district);
            jetGeo = new JetGeo(properties);
        }
    
        public static void main(String[] args) {
            //这里的经纬度坐标需要使用 wgs84 坐标系
            GeoInfo geoInfo = jetGeo.getGeoInfo(32.053197915979325,118.85999259252777);
            System.out.println(geoInfo);
        }
    }
    GeoInfo(formatAddress=江苏省南京市玄武区, province=江苏省, city=南京市, district=玄武区, street=, adcode=320102, level=null)

核心依赖

贡献者

请阅读CONTRIBUTING.md 查阅为该项目做出贡献的开发者。

如何参与开源项目

贡献使开源社区成为一个学习、激励和创造的绝佳场所。你所作的任何贡献都是非常感谢的。

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

作者


linG5821
@linG5821

您也可以在贡献者名单中参看所有参与该项目的开发者.

版权说明

Apache License 2.0, see LICENSE.

鸣谢


Tangchaoyue
@Tangchaoyue

感谢 @Tangchaoyue(lfr) 的陪伴, 支持以及给项目起的名字,给我极大的信心与鼓励,并且在我编码的时候耐心的照顾我的生活


halfrost
@halfrost

感谢 @halfrost 大佬的文章

高效的多维空间点索引算法 — Geohash 和 Google S2 Google S2 是如何解决空间覆盖最优解问题的

跳舞D猴子
@跳舞D猴子

感谢 @跳舞D猴子 的文章

Google的S2算法原理以及使用Java版本

lss
@lssaidong

感谢 @lssaidong 贡献的项目 Logo


renyiwei-xinyi
@renyiwei-xinyi

感谢 @renyiwei-xinyi 的捐赠以及支持

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