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

LI Hongzhe; WANG Shijie; LI Chengming

doi:10.13205/j.hjgc.202204028

Volume 40 Issue 4

Apr. 2022

Turn off MathJax

Article Contents

Article Navigation > ENVIRONMENTAL ENGINEERING > 2022 > 40(4): 196-201

LI Hongzhe, WANG Shijie, LI Chengming. ANALYSIS OF THE DIFFERENCE BETWEEN GF-6 AND LANDSAT-8 IN WATER QUALITY MONITORING[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(4): 196-201. doi: 10.13205/j.hjgc.202204028

Citation:

LI Hongzhe, WANG Shijie, LI Chengming. ANALYSIS OF THE DIFFERENCE BETWEEN GF-6 AND LANDSAT-8 IN WATER QUALITY MONITORING[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(4): 196-201. doi: 10.13205/j.hjgc.202204028

Citation:

PDF( 6525 KB)

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

doi: 10.13205/j.hjgc.202204028

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

Received Date: 2021-04-14
Available Online: 2022-07-06

Abstract

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

FullText(HTML)

References(15)

References

[1]	徐涵秋,唐菲.新一代Landsat系列卫星:Landsat 8遥感影像新增特征及其生态环境意义[J].生态学报,2013,33(11):3249-3257.
[2]	张丽华,武捷春,包玉海,等.基于MODIS数据的乌梁素海水体遥感监测[J].环境工程,2016,34(3):161-165.
[3]	朱利,姚延娟,吴传庆,等.基于环境一号卫星的内陆水体水质多光谱遥感监测[J].地理与地理信息科学,2010,26(2):81-84 ,113.
[4]	朱利,李云梅,赵少华,等.基于GF-1号卫星WFV数据的太湖水质遥感监测[J].国土资源遥感,2015,27(1):113-120.
[5]	汪雨豪,李家国,汪洁,等.基于GF-2影像的苏州市区水质遥感监测[J].科学技术与工程,2020,20(14):5875-5885.
[6]	白开源.基于3S技术的湖泊富营养化监测与评价系统[D].武汉:华中科技大学,2019.
[7]	LEI F, YU Y, ZHANG D, et al. Water remote sensing eutrophication inversion algorithm based on multilayer convolutional neural network[J]. Journal of Intelligent&Fuzzy Systems,2020, 39(4):5319-5327.
[8]	刘文雅,邓孺孺,梁业恒,等.基于辐射传输模型的巢湖叶绿素a浓度反演[J].国土资源遥感,2019,31(2):102-110.
[9]	王小平.遥感和三维荧光技术支持的艾比湖流域地表水水质监测研究[D].乌鲁木齐:新疆大学,2018.
[10]	雷添杰,张鹏鹏,胡连兴,等.无人船遥感系统及其应用[J].测绘通报,2021(2):82-86,92.
[11]	BAI S, GAO J, SUN D, et al. Monitoring water transparency in shallow and eutrophic lake waters based on goci observations[J]. Remote Sensing, 2020, 12(1):163.
[12]	NAZIROVA K, ALFERYEVA Y, LAVROVA O, et al. Comparison of in situ and remote-sensing methods to determine turbidity and concentration of suspended matter in the estuary zone of the Mzymta river, black sea[J]. Remote Sensing, 2021, 13(1):143-143.
[13]	但雨生,周忠发,李韶慧,等.基于Sentinel-2的平寨水库叶绿素a浓度反演[J].环境工程, 2020,38(3):180-185 ,127.
[14]	张东彦,尹勋,佘宝,等.多源卫星遥感数据监测巢湖蓝藻水华爆发研究[J].红外与激光工程,2019,48(7):303-314.
[15]	谭小琴,罗勇,赵铮,等.基于高分遥感的河流水质反演研究:以金马河温江段为例[J].环境生态学,2020,2(7):29-36.