KartaCam如何为GrabMaps提供动力

The foundation for making any map is in imagery, but due to the complexity and dynamism of the real world, it is difficult for companies to collect high-quality, fresh images in an efficient yet low-cost manner. This is the case for Grab’s Geo team as well.

制作任何地图的基础在于图像,但由于现实世界的复杂性和动态性,公司很难以高效而低成本的方式收集高质量、新鲜的图像。Grab 的地理团队也是如此。

Traditional map-making methods rely on professional-grade cameras that provide high resolution images to collect mapping imagery. These images are rich in content and detail, providing a good snapshot of the real world. However, we see two major challenges with this approach.

传统的地图制作方法依靠专业级相机提供高分辨率的图像来收集测绘图像。这些图像具有丰富的内容和细节,为现实世界提供了一个良好的快照。然而,我们看到这种方法有两个主要挑战。

The first is high cost. Professional cameras are too expensive to use at scale, especially in an emerging region like Southeast Asia. Apart from high equipment cost, operational cost is also high as local operation teams need professional training before collecting imagery.

首先是高成本。专业相机的成本太高,无法大规模使用,尤其是在东南亚这样的新兴地区。除了高额的设备成本,操作成本也很高,因为当地的操作团队在收集图像之前需要专业培训。

The other major challenge, related to the first, is that imagery will not be refreshed in a timely manner because of the high cost and operational effort required. It typically takes months or years before imagery is refreshed, which means maps get outdated easily.

与第一个挑战相关的另一个主要挑战是,由于所需的高成本和操作努力,图像不会被及时刷新。通常需要几个月或几年的时间才能刷新图像,这意味着地图很容易过时。

Compared to traditional collection methods, there are more affordable alternatives that some emerging map providers are using, such as crowdsourced collection done with smartphones or other consumer-grade action cameras. This allows more timely imagery refresh at a much lower cost.

与传统的收集方法相比,一些新兴的地图供应商正在使用更实惠的替代方法,例如用智能手机或其他消费级的行动相机进行的众包收集。这可以以更低的成本实现更及时的图像更新。

That said, there are several challenges with crowdsourcing imagery, such as:

尽管如此,众包图像也有一些挑战,例如:。

  • Inconsistent quality in collected images.
  • 收集的图像质量不一致。
  • Low operational efficiency as cameras and smartphones are not optimised for mapping.
  • 操作效率低,因为相机和智能手机没有被优化用于测绘。
  • Unreliable location accuracy.
  • 不可靠的定位精...
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