Soil Erosion Assessment and Early Warning Model Based on Big Data and Artificial Intelligence

Yunfeng Li, Ruixiang Song
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Abstract

Soil erosion can lead to the pollution of water bodies, further deterioration of the ecological environment, and pose a serious threat to humans and the biodiversity of the earth. In order to cope with this global challenge, it is particularly important to develop soil erosion assessment and early warning systems. With the support of soil erosion model and geographic information system, a new soil erosion assessment and early warning system based on the soil and water environment of Jilin Province was developed in this paper. The system can analyze rainfall data, satellite data and geographic information data more accurately, and then find out the key factors causing soil erosion. The study found that the slope had the greatest correlation with soil erosion, with a correlation of 1.12. The second is the soil type and vegetation type, and in the steep slope of > 25°, soil erosion is severe, and the land ecological condition is very poor. These research results not only have important reference value for the land spatial planning of Jilin Province, but also provide valuable experience and reference for the soil erosion control work in other areas. Through scientific planning and early warning system, it is expected to protect valuable land resources, maintain the ecological balance of the earth, and contribute to the sustainable development of mankind.
基于大数据和人工智能的土壤侵蚀评估与预警模型
水土流失会导致水体污染、生态环境进一步恶化,并对人类和地球的生物多样性构成严重威胁。为了应对这一全球性挑战,开发水土流失评估和预警系统尤为重要。在水土流失模型和地理信息系统的支持下,本文开发了基于吉林省水土环境的新型水土流失评估和预警系统。该系统能更准确地分析降雨数据、卫星数据和地理信息数据,进而找出造成水土流失的关键因素。研究发现,坡度与水土流失的相关性最大,达到 1.12。其次是土壤类型和植被类型,在大于 25°的陡坡上,水土流失严重,土地生态条件很差。这些研究成果不仅对吉林省国土空间规划具有重要的参考价值,也为其他地区的水土流失治理工作提供了宝贵的经验和借鉴。通过科学规划和预警系统,有望保护宝贵的土地资源,维护地球生态平衡,为人类的可持续发展做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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