Improved mapping of highland bamboo forests using Sentinel-2 time series and machine learning in Google Earth Engine
IF 3.3
4区 地球科学
Q2 ENVIRONMENTAL SCIENCES
引用次数: 0
Abstract
Recent advances in the application of spectral bands from satellite observations and machine learning algorithms (MLA) in the Google Earth Engine (GEE) cloud-computing platform have been demonstrat...利用哨兵-2 时间序列和谷歌地球引擎中的机器学习改进高原竹林制图
在谷歌地球引擎（GEE）云计算平台上应用卫星观测光谱波段和机器学习算法（MLA）的最新进展已经得到了证实。
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来源期刊
Geocarto International
ENVIRONMENTAL SCIENCES-GEOSCIENCES, MULTIDISCIPLINARY
CiteScore
6.30
自引率
13.20%
发文量
407
审稿时长
>12 weeks
期刊介绍：
Geocarto International is a professional academic journal serving the world-wide scientific and user community in the fields of remote sensing, GIS, geoscience and environmental sciences. The journal is designed: to promote multidisciplinary research in and application of remote sensing and GIS in geosciences and environmental sciences; to enhance international exchange of information on new developments and applications in the field of remote sensing and GIS and related disciplines; to foster interest in and understanding of science and applications on remote sensing and GIS technologies; and to encourage the publication of timely papers and research results on remote sensing and GIS applications in geosciences and environmental sciences from the world-wide science community.
The journal welcomes contributions on the following: precise, illustrated papers on new developments, technologies and applications of remote sensing; research results in remote sensing, GISciences and related disciplines;
Reports on new and innovative applications and projects in these areas; and assessment and evaluation of new remote sensing and GIS equipment, software and hardware.
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