Risk Assessment of Climate-Induced Environmental Degradation Using Remote Sensing
Received Date: Dec 02, 2024 / Published Date: Dec 31, 2024
Abstract
Climate change is one of the most significant global challenges of the 21st century, with widespread impacts on ecosystems, human societies, and natural resources. The degradation of environmental systems, including deforestation, desertification, and loss of biodiversity, is exacerbated by climate-induced stresses such as temperature increases, altered precipitation patterns, and extreme weather events. Remote sensing technologies offer an effective tool for monitoring and assessing these changes over large spatial scales, providing critical data for understanding the extent and dynamics of environmental degradation. This study explores the use of remote sensing techniques to assess climate-induced environmental degradation, focusing on key indicators such as land cover changes, vegetation health, and soil erosion. Using satellite data and advanced image processing methods, the study analyzes temporal and spatial patterns of environmental degradation across diverse ecosystems. Results indicate that remote sensing provides an invaluable means of tracking the impacts of climate change on the environment, offering key insights into areas of high risk and vulnerability. These findings highlight the potential for remote sensing-based risk assessments to inform policy and decision-making aimed at mitigating the effects of climate-induced degradation.
Citation: Rajesh K (2024) Risk Assessment of Climate-Induced Environmental Degradation Using Remote Sensing. J Earth Sci Clim Change, 15: 870. Doi: 10.4172/2157-7617.1000870
Copyright: 漏 2024 Rajesh K. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Share This Article
Recommended Journals
黑料网 Journals
Article Tools
Article Usage
- Total views: 99
- [From(publication date): 0-0 - Mar 09, 2025]
- Breakdown by view type
- HTML page views: 73
- PDF downloads: 26