...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Aquatic Sciences >Integrating catchment land cover data to remotely assess freshwater quality: a step forward in heterogeneity analysis of river networks
【24h】

Integrating catchment land cover data to remotely assess freshwater quality: a step forward in heterogeneity analysis of river networks

机译：整合集水区覆盖数据以远程评估淡水质量：河流网络异质性分析前进

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Attempts to obtain information from geospatial data in freshwater ecology is a highly challenging task requiring the development of new concepts and adequate tools. Conventionally, river networks are represented as collections of vectors, but they can also be thought of as a succession of raster cells corresponding to the digital elevation model of the landscape they traverse. Based on the principle that each cell in the river raster collects environmental influences from its upstream drainage basin, we defined a remote measure of the potential of pollution named RWQ (Remote Water Quality). We used the CORINE Land Cover categories found in the catchment area of each cell in the river network grouped by ecological relevance and weighted by their respective areas in the catchment. To refine the index to account for the proximity of potential pollution sources, we tested successive buffers of 1km up to the full catchment of each investigated point, concluding that the RWQ calculated for the full catchment is the most suitable index. For implementation, we developed RIVERenhancer, a free Python-based ArcGIS tool making possible the enhancement of raster river networks with data extracted from various files. The reliability of RWQ was tested with the aid of in situ measurements of chemical and biological water quality obtained from several sources in Danube basin (Romania and Hungary). The strong correlation with field data shows that this index can be considered a surrogate to depict the quality of freshwater habitats and to analyse network heterogeneity. The strength of this concept comes from taking advantage of the dendritic nature of river networks, opening new directions of operations for large scale approaches concerning important issues in global ecology, biogeography and conservation.
机译：尝试从淡水生态学中获取来自地理空间数据的信息是一个高度挑战的任务，需要开发新的概念和适当的工具。传统上，河网络被代表为载体的集合，但它们也可以被认为是对应于它们遍历的景观的数字高度模型的光栅细胞的连续。基于河流光栅中的每个细胞收集来自其上游排水盆地的环境影响，我们定义了污染潜力的远程测量名为RWQ（远程水质）。我们使用了通过生态相关性和集水区中的各自区域进行了生态相关性和加权的河网络中的康塞陆地面积。为了优化索引来解释潜在污染源的邻近，我们将1km的连续缓冲区1公里到每个调查点的全部集水区进行了1km，得出结论是为全集水区计算的RWQ是最合适的指标。为了实施，我们开发了Riverenhancer，这是一个免费的Python-CarmGIS工具，使得栅格河网络的增强能够通过各种文件提取的数据。借助于从多瑙河盆地（罗马尼亚和匈牙利）的几个来源获得的化学和生物水质的借助于化学和生物水质的原位测量来测试RWQ的可靠性。与现场数据的强烈相关性表明，该指数可以被认为是描绘淡水栖息地的质量并分析网络异质性的代理人。这一概念的实力来自于利用河流网络的树突性质，为全球生态，生物地理和保护中的重要问题开辟了大规模方法的新方向。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号