lilgw402 / an-adaptive-size-vector-tile-pyramid-considering-spatial-data-distribution-density-characteristics

An-Adaptive-Size-Vector-Tile-Pyramid-Construction-Method-Considering-Spatial-Data-Distribution-Density-Characteristics

Introduction

This project proposes a novel three-step method for dynamically adjusting tile sizes based on spatial data distribution density during construction. It addresses the issues commonly encountered in traditional vector tile construction methods, such as excessive tile quantity and data volume imbalance between tiles.

Development Platform

ArcEngine 10.7.1

Installation

To run this project, you'll need the following:

1. Visual Studio 2015 or above: Ensure you have Visual Studio 2015 or a more recent version installed.

2. Project Dependencies: This project relies on the following GIS-related libraries and tools:

• [ESRI ArcObjects]: ESRI's ArcObjects library is used for handling and analyzing geospatial data and integrating with ArcGIS software.

• [OSGeo GDAL]: OSGeo GDAL (Geospatial Data Abstraction Library) is used for reading, writing, and transforming various geospatial data formats.

Please ensure that these libraries are correctly installed before setting up and running the project. Refer to the respective documentation for further instructions and guidance.

Method Overview

Our approach consists of three main steps:

1. Data Generalization: In this step, we transform raw data into a multi-resolution vector dataset, encompassing varying levels of detail.

2. Quadtree-based Construction: For each level within the dataset, we employ a quadtree-based approach to construct adaptive-size vector tiles that align with specific spatial distribution density characteristics.

3. Geohash Encoding: Finally, we encode these differently-sized vector tiles using Geohash technology to facilitate spatial indexing and internet transmission.

Example

Results

The data that support the findings of this study are openly available at http://doi.org/10.6084/m9.figshare.24407779, reference number 24407779.