Improving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series
Improving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series
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利用光学和雷达卫星图像时间序列提高云持续区域土地覆盖分类的准确性
DOI：
10.1111/2041-210x.13359
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发表时间：
2020
影响因子：
6.6
通讯作者：
Lopes M
中科院分区：
文献类型：
--
作者：
Lopes M
最近提供的高空间和时间分辨率光学和雷达卫星图像大大增加了以精细比例绘制土地覆盖图的机会。由于光学和雷达图像的互补性，它们的融合在受云层影响的热带地区很有用。然而，这些数据现在提供的多时间维度往往被忽视，因为这些领域的主要特点是相对较低的季节性，因为考虑多时间数据需要更多的处理时间。因此，这些区域的土地覆盖测绘往往是基于一个日期或多个日期的平均数获得的图像，这项工作的目的是评估光学和雷达时间序列的时间维度在热带环境土地覆盖测绘时带来的附加值。具体而言，我们比较了分类的准确性，分类的基础是（a）光学时间序列，（B）它们的时间平均值，（c）雷达时间序列，（d）它们的时间平均值，（e）光学和雷达时间序列的组合，（f）它们的时间平均值的组合，用于绘制印度尼西亚詹比省的土地覆盖图，使用Sentinel‐1和Sentinel‐2影像。使用时间序列中包含的全部信息比使用时间平均值的分类精度高得多（Sentinel-1为+14.7%，Sentinel-2为+2.5%，Sentinel-1和Sentinel-2为+2%）。总的来说，结合Sentinel-2和Sentinel-1时间序列提供了最高的准确度（Kappa = 88.5%）。我们的研究表明，保留卫星图像时间序列提供的时间信息可以显着改善热带生物多样性热点地区的土地覆盖分类，提高我们监测泥炭地等高度保护相关生态系统的能力。所提出的方法是可重复的，自动化的，并基于开源工具卫星图像。
The recent availability of high spatial and temporal resolution optical and radar satellite imagery has dramatically increased opportunities for mapping land cover at fine scales. Fusion of optical and radar images has been found useful in tropical areas affected by cloud cover because of their complementarity. However, the multitemporal dimension these data now offer is often neglected because these areas are primarily characterized by relatively low levels of seasonality and because the consideration of multitemporal data requires more processing time. Hence, land cover mapping in these regions is often based on imagery acquired for a single date or on an average of multiple dates.The aim of this work is to assess the added value brought by the temporal dimension of optical and radar time series when mapping land cover in tropical environments. Specifically, we compared the accuracies of classifications based on (a) optical time series, (b) their temporal average, (c) radar time series, (d) their temporal average, (e) a combination of optical and radar time series and (f) a combination of their temporal averages for mapping land cover in Jambi province, Indonesia, using Sentinel‐1 and Sentinel‐2 imagery.Using the full information contained in the time series resulted in significantly higher classification accuracies than using temporal averages (+14.7% for Sentinel‐1, +2.5% for Sentinel‐2 and +2% combining Sentinel‐1 and Sentinel‐2). Overall, combining Sentinel‐2 and Sentinel‐1 time series provided the highest accuracies (Kappa = 88.5%).Our study demonstrates that preserving the temporal information provided by satellite image time series can significantly improve land cover classifications in tropical biodiversity hotspots, improving our capacity to monitor ecosystems of high conservation relevance such as peatlands. The proposed method is reproducible, automated and based on open‐source tools satellite imagery.
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Takashi Norito 农业页面
DOI：
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影响因子：
3.9
作者：
M. Hirschmugl;Carina Sobe;Janik Deutscher;M. Schardt
通讯作者：
M. Hirschmugl;Carina Sobe;Janik Deutscher;M. Schardt
DOI：
10.3390/rs11080979
发表时间：
2019-04
期刊：
Remote. Sens.
影响因子：
--
作者：
Audrey Mercier;J. Betbeder;F. Rumiano;J. Baudry;V. Gond;L. Blanc;C. Bourgoin;Guillaume Cornu;C. Ciudad;M. Marchamalo;R. Poccard-Chapuis;L. Hubert‐Moy
通讯作者：
Audrey Mercier;J. Betbeder;F. Rumiano;J. Baudry;V. Gond;L. Blanc;C. Bourgoin;Guillaume Cornu;C. Ciudad;M. Marchamalo;R. Poccard-Chapuis;L. Hubert‐Moy
DOI：
10.2307/j.ctv177thv2.12
发表时间：
2020
期刊：
The Yoruba
影响因子：
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作者：
John
通讯作者：
John
影响因子：
10.3
作者：
Miettinen, Jukka;Shi, Chenghua;Liew, Soo Chin
通讯作者：
Liew, Soo Chin