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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Fine Monitoring of Wetlands at Provincial Large-Scale Using Object-Based Technique and Medium-Resolution Image
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Fine Monitoring of Wetlands at Provincial Large-Scale Using Object-Based Technique and Medium-Resolution Image

机译：基于对象的技术和中等分辨率图像对省级湿地的精细监测

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Due to extreme similarity of wetland spectra, a significant uncertainty lies in the accuracy of the traditional pixel-based classification, which is a bottleneck in the extraction of wetland information. Object-based image analysis (OBIA) has brought opportunity for fine monitoring of wetland information. However, previous studies on monitoring wetlands have focused mainly on exploratory experiments involving high-resolution images for small areas. The application of OBIA in various medium-resolution images for large areas needs further verification. Here, Landsat and China's HJ-CCD images, a new OBIA mixed binary decision tree, tasseled cap transformation, and field samples were used to refine monitoring of changes in wetlands in Hubei Province. The results showed that while the overall accuracy and Kappa coefficient of the extracted wetland information for 2000 were, respectively, 88.98% and 0.87, the overall accuracy and Kappa coefficient of the detected change were 94.75% and 89.41. This indicated that OBIA performed well with medium-resolution HJ-CCD and Landsat images in monitoring changes in wetlands at provincial scale. The area of wetlands in Hubei increased by 171.03 km(2) during 2000-2010. Lakes and reservoirs/ponds increased the most in the province, with respective contributions to the total wetland area of 40.21% (108.97 km(2)) and 59.17% (160.37 km(2)). At administrative unit scale, Shiyan Prefecture (157.53 km(2)) and Fangxian County (317.33 km(2)) contributed the most to the increase of wetland area. The main reason for the increase in wetland area in Hubei in 2000-2010 was the implementation of major ecological projects during that decade.
机译：由于湿地光谱的极端相似性，传统的基于像素的分类的准确性存在很大的不确定性，这是提取湿地信息的瓶颈。基于对象的图像分析（OBIA）为精细监测湿地信息带来了机会。但是，先前有关监测湿地的研究主要集中在涉及小区域高分辨率图像的探索性实验中。 OBIA在大面积各种中等分辨率图像中的应用需要进一步验证。在这里，Landsat和中国的HJ-CCD图像，新的OBIA混合二叉决策树，流苏帽转换和野外采样被用于完善对湖北省湿地变化的监测。结果表明，提取的2000年湿地信息的总准确度和Kappa系数分别为88.98％和0.87，而检测到的变化的总准确度和Kappa系数为94.75％和89.41。这表明OBIA在中等分辨率的HJ-CCD和Landsat图像上可以很好地监测省级湿地的变化。在2000-2010年期间，湖北湿地面积增加了171.03 km（2）。湖泊和水库/池塘增幅最大，分别占湿地总面积的40.21％（108.97 km（2））和59.17％（160.37 km（2））。在行政单位规模上，十堰地区（157.53 km（2））和房县（317.33 km（2））对湿地面积的增加贡献最大。 2000-2010年湖北省湿地面积增加的主要原因是该十年期间实施的主要生态项目。

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