Mapping Plastic-Mulched Farmland with Multi-Temporal Landsat-8 Data
Mapping Plastic-Mulched Farmland with Multi-Temporal Landsat-8 Data
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DOI：
10.3390/rs9060557
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发表时间：
2017-06
期刊：
影响因子：
--
通讯作者：
Hasituya;Zhongxin Chen
中科院分区：
文献类型：
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作者：
Hasituya;Zhongxin Chen
在农田中使用塑料覆盖物正在世界各地蓬勃发展。尽管地膜技术有利于保护农作物免受不利条件的影响并提高农作物产量，但大量使用地膜技术会造成许多环境问题。因此，及时有效地绘制塑料覆盖农田（PMF）地图对于政策制定者来说非常重要，以平衡经济利润和不利环境影响之间的关系。然而，由于其光谱特征随着农作物的生长季节和地理区域的变化而变化，基于遥感的PMF测绘仍然具有挑战性。在本研究中，我们研究了多时相 Landsat-8 图像用于绘制 PMF 的潜力。为此，我们将光谱、纹理、指数和热特征信息收集到随机森林（RF）和支持向量机（SVM）算法中，以选择区分 PMF 与其他土地覆盖类型的共同特征。试验在河北省冀州市进行。结果表明，NDVI（归一化植被指数）、GI（绿度指数）和均值纹理特征等光谱特征和指数特征对于蓟州PMF制图来说比其他特征更重要。因此，绘制 PMF 的最佳时期是 4 月，其次是 5 月。这两个时间（四月和五月）的组合比季节后期更好。蓟州的总体准确率、生产者准确率和用户准确率最高，分别为 97.01%、92.48% 和 96.40%。
Using plastic mulching for farmland is booming around the world. Despite its benefit of protecting crops from unfavorable conditions and increasing crop yield, the massive use of the plastic-mulching technique causes many environmental problems. Therefore, timely and effective mapping of plastic-mulched farmland (PMF) is of great interest to policy-makers to leverage the trade-off between economic profit and adverse environmental impacts. However, it is still challenging to implement remote-sensing-based PMF mapping due to its changing spectral characteristics with the growing seasons of crops and geographic regions. In this study, we examined the potential of multi-temporal Landsat-8 imagery for mapping PMF. To this end, we gathered the information of spectra, textures, indices, and thermal features into random forest (RF) and support vector machine (SVM) algorithms in order to select the common characteristics for distinguishing PMF from other land cover types. The experiment was conducted in Jizhou, Hebei Province. The results demonstrated that the spectral features and indices features of NDVI (normalized difference vegetation index), GI (greenness index), and textural features of mean are more important than the other features for mapping PMF in Jizhou. With that, the optimal period for mapping PMF is in April, followed by May. A combination of these two times (April and May) is better than later in the season. The highest overall, producer’s, and user’s accuracies achieved were 97.01%, 92.48%, and 96.40% in Jizhou, respectively.