Journal of Geo-information Science >
Accuracy Evaluation of Land Use Mapping Using Remote Sensing Techniques in Coastal Zone of China
Received date: 2018-04-12
Request revised date: 2018-06-22
Online published: 2018-10-17
Supported by
The Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA19060205, XDA11020305
National Natural Science Foundation of China, No.31461143032, 40801016.
Copyright
Land use mapping using remote sensing techniques supplies essential datasets for scientific researches including global climate change, regional sustainable development and so on. The evaluation information on the accuracy of the land use mapping determines the integrity, reliability, usability, controllability and shareability of the land use maps obtained by the applications of remote sensing techniques. In this paper, the methods, processes and results of multiple temporal land use mapping for China's coastal zone using remote sensing techniques were overviewed, and the land use maps in 2010 and 2015 were selected for accuracy evaluation. The validation samples were collected based on Google Earth and the confusion matrices were established for the whole coastal zone and its sub-regions, respectively. Then, the overall accuracy and Kappa coefficient were calculated. Main findings are as follows: (1) Results of land use mapping in 2010 and 2015 using remote sensing techniques achieved high accuracy. For the entire coastal zone in China, the overall accuracy came to 95.15% and 93.98%, with the Kappa coefficients of 0.9357 and 0.9229 in 2010 and 2015, respectively. (2) The accuracy of land use mapping in China's coastal zone exhibited obvious regional differences. The best accuracy was found in the coastal area of Jiangsu province in 2010, and very high accuracy were found in the coastal area of Hebei-Tianjin, Shanghai city, Hainan province and Taiwan province in 2015, while the worst accuracy was found in the coastal area of Fujian province in both 2010 and 2015. (3) The accuracy of land use mapping in China's coastal zone exhibited obvious typological differences. The very high accuracy (both producer precision and user precision) were achieved for farmland, forest, grassland and saltwater wetlands, and the high accuracy for built-up, freshwater wetlands and human made saltwater wetland, while the worst accuracy for unused land. (4) The misclassification between cultivated land and forest land, construction land and grassland is quite significant. Inland water bodies were easily misclassified into cultivated land, forest land and construction land. Artificial salt water wetlands were easily misclassified into cultivated land and construction land, and unused land. It was easy to mistakenly classify the unused land as cultivated land. These are the issues that should be paid more attention during the continuous update of the land use maps in the future. This study provides supports for the dynamic monitoring and scientific researches on coastal land use changes.
Key words: land use; remote sensing mapping; accuracy evaluation; coastal zone; China
HOU Xiyong , DI Xianghong , HOU Wan , WU Li , LIU Jing , WANG Junhui , SU Hongfan , LU Xiao , YING Lanlan , YU Xinyang , WU Ting , ZHU Mingming , HAN Lei , LI Mingjie . Accuracy Evaluation of Land Use Mapping Using Remote Sensing Techniques in Coastal Zone of China[J]. Journal of Geo-information Science, 2018 , 20(10) : 1478 -1488 . DOI: 10.12082/dqxxkx.2018.180184
Tab. 1 Land use hierarchy for China's coastal zone based on remote sensing techniques表1 中国海岸带土地利用遥感分类系统 |
一级类型 (编码+名称) | 二级类型 (编码+名称) |
---|---|
1 耕地 | 11水田;12旱地 |
2 林地 | 21有林地;22疏林地;23灌木林地;24其他林地 |
3 草地 | 31高覆盖度草地;32中覆盖度草地;33低覆盖度草地 |
4 建设用地 | 41城镇用地;42农村居民点;43独立工矿及交通用地 |
5 内陆水体 | 51河渠;52湖泊;53水库坑塘;54滩地 |
6 滨海湿地 | 61滩涂;62河口水域;63河口三角洲湿地;64沿海瀉湖;65浅海水域 |
7 人工咸水湿地 | 71盐田;72养殖 |
8 未利用地 | 81未利用地 |
Fig. 1 Land use maps in multiple years in China's coastal zone based on remote sensing techniques图1 中国海岸带多时相土地利用遥感制图结果 |
Fig. 2 Technical approaches of land use mapping and accuracy evaluation for China's coastal zone图2 中国海岸带土地利用遥感制图及精度评价的技术流程 |
Tab. 2 Spacing and amounts of sampling points in each administrative region表2 不同行政区域的采样间距及样点数量 |
行政区域 | 辽宁 | 河北 | 天津 | 山东 | 江苏 | 上海 | 浙江 | 福建 | 广东 | 广西 | 海南 | 港澳 | 台湾 | 合计 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
采样间距/km | 7 | 7 | 5 | 7 | 7 | 4.5 | 8 | 7 | 7 | 6 | 6 | 2 | 10 | |
2010年采样点数量/个 | 1358 | 730 | 500 | 1410 | 1098 | 500 | 1163 | 1117 | 1772 | 1000 | 1311 | 500 | 554 | 13013 |
2015年采样点数量/个 | 1780 | 1019 | 474 | 2445 | 1318 | 578 | 1463 | 1304 | 2397 | 1123 | 1311 | 652 | 554 | 16418 |
Tab. 3 Accuracy of land use mapping in each administrative region in China's coastal zone表3 分区层面中国海岸带土地利用遥感制图的精度 |
分区编号 | 所属的 行政区 | 2010年 | 2015年 | |||
---|---|---|---|---|---|---|
总体精度/% | Kappa系数 | 总体精度/% | Kappa系数 | |||
1 | 辽宁 | 95.06 | 0.9318 | 94.83 | 0.9332 | |
2 | 津冀 | 94.39 | 0.9110 | 95.71 | 0.9348 | |
3 | 山东 | 93.90 | 0.8991 | 95.17 | 0.9288 | |
4 | 江苏 | 97.45 | 0.9641 | 94.69 | 0.9280 | |
5 | 上海 | 95.20 | 0.9331 | 95.33 | 0.9374 | |
6 | 浙江 | 95.96 | 0.9430 | 94.81 | 0.9317 | |
7 | 福建 | 92.57 | 0.8839 | 90.95 | 0.8714 | |
8 | 广东 | 93.12 | 0.8996 | 90.99 | 0.8809 | |
9 | 广西 | 96.90 | 0.9523 | 92.43 | 0.8917 | |
10 | 海南 | 97.40 | 0.9606 | 95.65 | 0.9342 | |
11 | 港澳 | 96.20 | 0.9408 | 94.02 | 0.9180 | |
12 | 台湾 | 96.39 | 0.9500 | 95.30 | 0.9349 |
Tab. 4 Confusion matrix of land use mapping in China's coastal zone in 2010表4 2010年中国海岸带土地利用遥感制图混淆矩阵 |
分类数据 | 标准数据 | 行总数 | 用户精度/% | |||||||
---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |||
1 | 4103 | 102 | 33 | 83 | 26 | 4 | 19 | 3 | 4373 | 93.83 |
2 | 88 | 4170 | 7 | 15 | 8 | 1 | 0 | 2 | 4291 | 97.18 |
3 | 32 | 10 | 671 | 4 | 5 | 0 | 3 | 3 | 728 | 92.17 |
4 | 39 | 17 | 2 | 1484 | 7 | 4 | 10 | 1 | 1564 | 94.88 |
5 | 11 | 5 | 5 | 6 | 664 | 3 | 7 | 2 | 703 | 94.45 |
6 | 2 | 5 | 1 | 2 | 0 | 901 | 3 | 0 | 914 | 98.58 |
7 | 7 | 1 | 1 | 5 | 3 | 0 | 335 | 2 | 354 | 94.63 |
8 | 12 | 9 | 0 | 3 | 0 | 6 | 1 | 55 | 86 | 63.95 |
列总数 | 4294 | 4319 | 720 | 1602 | 713 | 919 | 378 | 68 | ||
生产者精度/% | 95.55 | 96.55 | 93.19 | 92.63 | 93.13 | 98.04 | 88.62 | 80.88 | ||
总体精度/% | 95.16 | Kappa系数 | 0.9357 |
注:土地利用类型编码请参表1 |
Tab. 5 Confusion matrix of land use mapping in China's coastal zone in 2015表5 2015年中国海岸带土地利用遥感制图混淆矩阵 |
分类数据 | 标准数据 | 行总数 | 用户精度/% | |||||||
---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |||
1 | 4424 | 231 | 5 | 173 | 26 | 2 | 6 | 1 | 4868 | 90.88 |
2 | 107 | 4117 | 5 | 48 | 11 | 10 | 6 | 2 | 4306 | 95.61 |
3 | 31 | 4 | 723 | 23 | 4 | 7 | 4 | 4 | 800 | 90.38 |
4 | 58 | 42 | 9 | 1587 | 17 | 10 | 4 | 2 | 1729 | 91.79 |
5 | 29 | 14 | 8 | 18 | 625 | 3 | 6 | 2 | 705 | 88.65 |
6 | 3 | 8 | 2 | 3 | 0 | 3559 | 1 | 0 | 3576 | 99.52 |
7 | 2 | 0 | 0 | 5 | 2 | 2 | 350 | 0 | 361 | 96.95 |
8 | 16 | 4 | 1 | 2 | 0 | 5 | 0 | 45 | 73 | 61.64 |
列总数 | 4670 | 4420 | 753 | 1859 | 685 | 3598 | 377 | 56 | ||
生产者精度/% | 94.73 | 93.14 | 96.02 | 85.37 | 91.24 | 98.92 | 92.84 | 80.36 | ||
总体精度/% | 93.98 | Kappa系数 | 0.9229 |
注:土地利用类型编码请参表1 |
Fig. 3 Confusions between remote sensing based land use map and Google Earth based samples in 2010 and 2015图3 土地利用遥感制图与Google Earth验证样本混淆特征 |
Fig. 4 Statistical characters of misclassified samples of land use mapping in 2010 and 2015图4 土地利用遥感制图错误样点统计特征 |
The authors have declared that no competing interests exist.
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