GF-6与Landsat-8影像在水质监测中的差异性分析

李弘哲; 王世杰; 李成名

doi:10.13205/j.hjgc.202204028

GF-6与Landsat-8影像在水质监测中的差异性分析

doi: 10.13205/j.hjgc.202204028

李弘哲^1,2,3,
王世杰^1,2,3, ,,
李成名⁴

1. 兰州交通大学测绘与地理信息学院, 兰州 730070;
2. 地理国情监测技术应用国家地方联合工程研究中心, 兰州 730070;
3. 甘肃省地理国情监测工程实验室, 兰州 730070;
4. 中国测绘科学研究院, 北京 100830

基金项目:

兰州交通大学天佑创新团队(TY202001)

国家自然科学基金项目(41861061)

详细信息

作者简介:
李弘哲(1997-),男,硕士研究生,主要研究方向为地理信息系统与遥感应用。727590441@qq.com

通讯作者:
王世杰(1971-),男,教授级高级工程师,主要研究方向为摄影测量与遥感。wangshijie@mail.lzjtu.cn

计量
- 文章访问数: 69
- HTML全文浏览量: 5
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- 被引次数: 0
出版历程
- 收稿日期: 2021-04-14
- 网络出版日期: 2022-07-06

ANALYSIS OF THE DIFFERENCE BETWEEN GF-6 AND LANDSAT-8 IN WATER QUALITY MONITORING

LI Hongzhe^1,2,3,
WANG Shijie^{1,2,3
, ,},
LI Chengming⁴

1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China;
2. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China;
3. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China;
4. Chinese Academy of Surveying&Mapping, Beijing 100830, China

摘要

摘要: 针对GF-6与Landsat-8影像在水质监测中的差异性问题,以巢湖水质富营养状态评价为研究内容,对水质参数进行反演,利用综合营养状态指数法构建水质评价模型。运用ENVI 5.3和ArcGIS 10.3软件,实现各项水质参数和综合营养状态指数TLI可视化。对比实测数据,运用Person相关性模型进行反演结果精度评定。结果表明:影像成像时刻巢湖水质营养状态为中营养;GF-6和Landsat-8反演得到的综合营养状态指数TLI分别为42.75和42.13,两者差别较小,但经过与实测数据的相关性分析可得,GF-6和Landsat-8的Person系数分别为0.988和0.965,表明GF-6反演的数据与实测值相关性更强,更加准确可靠。研究结论可为水质监测中如何选用遥感影像数据提供参考。
- GF-6 /
- Landsat-8 /
- 巢湖 /
- 水质监测 /
- 差异性
Abstract: In view of the difference between GF-6 and Landsat-8 images in water quality monitoring, the eutrophication assessment of water quality in Chao Lake was taken as the research content, the water quality parameters were inversed, and the water quality assessment model was constructed by using the method of integrated nutritional state index. Using ENVI 5.3 and ArcGIS 10.3 software, the visualization of water quality parameters and TLI was realized. Compared with the measured data, the accuracy of the inversion result was evaluated by using Pearson correlation model. The main conclusions were as follows: the nutrient status of the water quality in Chao Lake at the time of imaging was medium nutrient; the comprehensive nutrient status index TLI derived from GF-6 and Landsat-8 were 42.75 and 42.13 respectively, and there was no significant difference between them, however, the coefficients of GF-6 and Landsat-8 were 0.988 and 0.965, respectively, indicating that GF-6 was more accurate and reliable. The conclusion could provide reference for selecting remote sensing image data in water quality monitoring.
- GF-6 /
- Landsat-8 /
- Chaohu Lake /
- water quality monitoring /
- difference

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