Ecological bearing capacity estimation system and method based on multi-source remote sensing data

By using rasterization and comprehensive evaluation methods based on multi-source remote sensing data, the spatial heterogeneity and dynamic changes in traditional ecological carrying capacity estimation have been addressed, resulting in a more accurate assessment of ecological carrying capacity and supporting resource management and policy formulation.

CN122334702APending Publication Date: 2026-07-03SOUTHWEST FORESTRY UNIVERSITY
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Patent Information

Application Number
CN202610497139.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-15
Publication Date
2026-07-03

AI Technical Summary

Technical Problem

Traditional methods for estimating ecological carrying capacity rely on ground-based statistical data and simplified ecological footprint models, which are difficult to reflect spatial heterogeneity and dynamic changes, resulting in high uncertainty in the evaluation. Furthermore, existing methods are limited in scope and cannot provide a comprehensive assessment.

Method used

Multi-source remote sensing data is used to divide the data into grids to construct the basic ecological carrying capacity. The actual ecological carrying capacity is then constructed by combining the impact of landscape restoration, nighttime light intrusion, and supply-demand differences through an early warning mechanism.

Benefits of technology

It significantly improves the spatial resolution and data richness of the assessment, comprehensively reflects the true carrying capacity of regional ecosystems, and provides a scientific basis for resource management and sustainable development policies.

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Abstract

The invention relates to the technical field of ecological bearing capacity estimation, and discloses an ecological bearing capacity estimation system and method based on multi-source remote sensing data. According to the system, multi-source remote sensing data and actual ground collection data are integrated through the data collection module, grid division is carried out on an area, the basic ecological bearing capacity can be constructed grid by grid, the spatial resolution and data richness of evaluation are remarkably improved, the defects that a traditional statistical method is single in data and rough in spatial expression are overcome, and the method is suitable for large-scale popularization and application. Then the ecological bearing capacity evaluation module is used for integrating the basic ecological bearing capacity with three influence evaluation directions, namely landscape recovery influence, night illumination invasion and supply and demand difference, so that actual ecological bearing capacity is constructed, objectivity driven by remote sensing data is reserved, and multi-dimensional artificial and natural disturbance factors are fused; the real bearing state of the regional ecological system can be comprehensively reflected, and a scientific basis is provided for resource management, ecological compensation and sustainable development policy making.
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