Ecological Dissimilarity Matters More Than Geographical Distance When Predicting Land Surface Indicators Using Machine Learning
Author:
Affiliation:
1. Department of Geography, University of California, Los Angeles, CA, USA
2. National Operations Center, Bureau of Land Management, Denver Federal Center, Denver, CO, USA
3. U.S. Geological Survey, Southwest Biological Science Center, Moab, UT, USA
Funder
National Aeronautics and Space Administration
National Institutes of Health
United States Department of Agriculture (USDA) Agricultural Research Service
DOI-Department of Interior Bureau of Land Management
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/36/10354519/10536906.pdf?arnumber=10536906
Reference45 articles.
1. A double-sampling approach to deriving training and validation data for remotely-sensed vegetation products
2. Strategies for monitoring terrestrial animals and habitats
3. Assimilating optical satellite remote sensing images and field data to predict surface indicators in the Western U.S.: Assessing error in satellite predictions based on large geographical datasets with the use of machine learning
4. Leveraging Google Earth Engine (GEE) and machine learning algorithms to incorporate in situ measurement from different times for rangelands monitoring
5. Spatially Balanced Sampling of Natural Resources
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3