A Fast Detection Algorithm for Change Detection in National Forestland “One Map” Based on NLNE Quad-Tree-Reference-Cited by-同舟云学术

A Fast Detection Algorithm for Change Detection in National Forestland “One Map” Based on NLNE Quad-Tree

Published:2024-04-02 Issue:4 Volume:15 Page:646
ISSN:1999-4907
Container-title:Forests
language:en
Short-container-title:Forests

Author:

Gao Fei¹²^ORCID,Su Xiaohui³^ORCID,Chen Yuling⁴,Wu Baoguo³,Tian Yingze²^ORCID,Zhang Wenjie³^ORCID,Li Tao¹

Affiliation:

1. School of Cyber Science and Engineering, Sichuan University, Chengdu 610065, China

2. Sichuan Forestry and Grassland Survey and Planning Institute, Chengdu 610084, China

3. School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China

4. Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China

Abstract

The National Forestland “One Map” applies the boundaries and attributes of sub-elements to mountain plots by means of spatial data to achieve digital management of forest resources. The change detection and analysis of forest space and property is the key to determining the change characteristics, evolution trend and management effectiveness of forest land. The existing spatial overlay method, rasterization method, object matching method, etc., cannot meet the requirements of high efficiency and high precision at the same time. In this paper, we investigate a fast algorithm for the detection of changes in “One Map”, taking Sichuan Province as an example. The key spatial characteristic extraction method is used to uniquely determine the sub-compartments. We construct an unbalanced quadtree based on the number of maximum leaf node elements (NLNE Quad-Tree) to narrow down the query range of the target sub-compartments and quickly locate the sub-compartments. Based on NLNE Quad-Tree, we establish a change detection model for “One Map” (NQT-FCDM). The results show that the spatial feature combination of barycentric coordinates and area can ensure the spatial uniqueness of 44.45 million sub-compartments in Sichuan Province with 1 m~0.000001 m precision. The NQT-FCDM constructed with 1000–6000 as the maximum number of leaf nodes has the best retrieval efficiency in the range of 100,000–500,000 sub-compartments. The NQT-FCDM shortens the time by about 75% compared with the traditional spatial union analysis method, shortens the time by about 50% compared with the normal quadtree and effectively solves the problem of generating a large amount of intermediate data in the spatial union analysis method. The NQT-FCDM proposed in this paper improves the efficiency of change detection in “One Map” and can be generalized to other industries applying geographic information systems to carry out change detection, providing a basis for the detection of changes in vector spatial data.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Sichuan Youth Science and Technology Innovation Team

Sichuan Science and Technology Program

Science and Technology on Communication Security Laboratory Foundation

Publisher

MDPI AG

Link

https://www.mdpi.com/1999-4907/15/4/646/pdf

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