优化空间预测和采样策略的污染现场基于蒂森的多边形合插曲的采样策略
Xingwang Liu1, Lanting Zheng1, Zhuang Li2
1College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China.
概括
调查偏斜污染场所需要先进的方法. 这项研究优化了使用蒂森多边形,地理统计学和确定性插值的空间预测和采样策略,提高了准确度20-70%.
科学领域:
- 环境科学 环境科学
- 地理空间分析的研究.
- 环境化学环境化学
背景情况:
- 污染的场所带来了重大的生态和人类健康风险.
- 污染数据通常表现出多个峰值,空间异质性和倾斜分布,从而降低了插值预测的准确性.
- 现有的方法难以应对高度歪曲的受污染现场数据的复杂性.
研究的目的:
- 提出和验证一种用于调查高度偏的污染场所的新方法.
- 优化污染场所的空间预测和采样策略.
- 提高污染预测和范围识别的准确性,同时降低成本.
主要方法:
- 将蒂森多边形与地球统计学和确定性插值技术集成.
- 使用普通 kriging (OK) 进行插值预测的准确性.
- 使用辐射基函数-反向距离加权 (RBF_IMQ) 来预测污染范围.
- 验证使用 Luohe 的一个工业场所,采用最低 40x40 m 的初始采样单位.
主要成果:
- 一个40x40米的最低初始采样单位提供了代表性的区域污染数据.
- 普通 kriging (OK) 和 RBF_IMQ 方法显著提高了空间预测的准确性和污染范围的识别.
- 在补充了可疑地区的采样点后,准确性指标提高了20-70%.
- 污染范围识别的准确性接近95%.
结论:
- 拟议的方法有效地解决了调查高度倾斜的污染场所所面临的挑战.
- 这种方法优化了空间预测准确性和采样策略,导致更可靠的环境评估.
- 该方法为管理受污染的地点和减轻环境风险提供了具有成本效益的解决方案.
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