학술논문

Landscape Patterns in Mining Cities Influenced by Extraction and Terrain Features
Document Type
Conference
Source
2023 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI) Data Science, Agents & Artificial Intelligence (ICDSAAI), 2023 International Conference on. :1-8 Dec, 2023
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Atmospheric modeling
Urban areas
Predictive models
Feature extraction
Data mining
Stakeholders
Artificial intelligence
Landscape Patterns
Mining Cities
Mining Activity
Terrain Gradient
Urban Planning
Environmental Conservation
Language
Abstract
The combined influence of mining activities and the underlying terrain gradient has caused significant transformations in the landscape patterns of mining cities. The natural topography being altered by mining operations can result in a distinct evolution in the spatial arrangement and ecological dynamics of these cities. Spatial heterogeneities are influenced by factors such as extraction techniques, waste disposal methods, and infrastructure development. The inherent terrain gradient heavily influences the distribution of mining sites and urban expansion patterns. This research underscores the intricate interplay between human-induced activities and natural topographical features in shaping the landscape of mining cities. The development of resilient communities in areas that are evolving due to mining requires a clear understanding of these dynamics for sustainable urban planning, environmental conservation, and community development.