文献类型：期刊文献

中文题名：基于大数据的森林生态系统服务功能评估进展

英文题名：Review on forest ecosystem services assessment based on big data

作者：宋庆丰[1] 牛香[1] 王兵[1]

第一作者：宋庆丰

机构：[1]中国林业科学研究院森林生态环境与保护研究所国家林业局森林生态环境重点实验室

年份：2015

卷号：34

期号：10

起止页码：2914-2921

中文期刊名：生态学杂志

外文期刊名：Chinese Journal of Ecology

收录：CSTPCD;;Scopus;北大核心:【北大核心2014】；CSCD:【CSCD2015_2016】；

基金：林业公益性行业科研专项(201204101;201404303)资助

语种：中文

中文关键词：大数据;森林生态站;森林生态系统服务功能评估

外文关键词：big data; forest ecological station; forest ecosystem services evaluation.

分类号：Q968.1

摘要：与传统的数据相比,大数据的感知、获取、处理和表示都面临着巨大的挑战。森林生态系统作为陆地生态系统的主体,其所产生的服务功能在全球生态系统中发挥着极为重要的作用。森林生态系统服务功能评估在经历了小数据和表象大数据的评估阶段后,已经进入了大数据评估阶段。基于森林生态站长期监测数据开展的森林生态系统服务功能评估,能够在大数据中获取所需要的详细信息,开展多尺度镶嵌评估工作。同时,还可以避免小数据样本选择所带来的随机性误差,使得评估结果更趋于可靠,进而为森林资源的保护与可持续发展提供数据支撑。
Compared with traditional data, perception, acquisition, processing and expression of big data hag been faced with enormous challenges. As forest ecosystem is the main body of terres- trial ecosystem, forest ecosystem services play an extremely important role in the global ecosys- tem. Forest ecosystem services assessment has entered the period of big data after the period of small data and surface big data. Forest ecosystem services assessment based on the long-term mo- nitoring data from forest ecological stations could obtain more detailed information from the big data, and thus the multi-scale evaluation could be carried out. At the same time, the random error brought by selection of small sample data could be avoided to make the evaluation results more reliable. So long-term monitoring data from forest ecological stations provide supports for for- est resources protection and sustainable development.