Applications of Imaging Spectrometry in Inland Water Quality Monitoring-a Review of Recent Developments

被引:19
|
作者
Pu, Hongbin [1 ,2 ,3 ]
Liu, Dan [1 ,2 ,3 ]
Qu, Jia-Huan [1 ,2 ,3 ]
Sun, Da-Wen [1 ,2 ,3 ,4 ]
机构
[1] South China Univ Technol, Sch Food Sci & Engn, Guangzhou 510641, Guangdong, Peoples R China
[2] South China Univ Technol, Acad Contemporary Food Engn, Guangzhou Higher Educ Mega Ctr, Guangzhou 510006, Guangdong, Peoples R China
[3] Guangzhou Higher Educ Mega Ctr, Engn & Technol Res Ctr Guangdong Prov Intelligent, Guangzhou, Guangdong, Peoples R China
[4] Natl Univ Ireland, Univ Coll Dublin, Agr & Food Sci Ctr, Food Refrigerat & Computerized Food Technol, Dublin 4, Ireland
关键词
Imaging spectrometry; Hyperspectral; Inland water quality; Water constituents; TURBID PRODUCTIVE WATERS; ESTIMATING CHLOROPHYLL-A; SUSPENDED SEDIMENT CONCENTRATIONS; INHERENT OPTICAL-PROPERTIES; MECKLENBURG LAKE DISTRICT; LEAST-SQUARES REGRESSION; REMOTELY-SENSED DATA; LANDSAT ETM PLUS; COASTAL WATERS; SATELLITE DATA;
D O I
10.1007/s11270-017-3294-8
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Inland waters represent complex and highly variable ecosystems, which are also of immense recreational and economic values to humans. The maintenance of high quality of inland water status necessitates development of means for rapid quality monitoring. Imaging spectrometry techniques are proven technology that can provide useful information for the estimation of inland water quality attributes due to fast speed, noninvasiveness, ease of use, and in situ operation. Although there have been many studies conducted on the use of imaging spectrometry for marine water quality monitoring and assessment, relatively few studies have considered inland water bodies. The aim of this review is to present an overview of imaging spectrometry technologies for the monitoring of inland waters including spaceborne and airborne and field or ground-based hyperspectral systems. Some viewpoints on the current situation and suggestions for future research directions are also proposed.
引用
收藏
页数:17
相关论文
共 31 条
  • [21] Applications of emerging imaging techniques for meat quality and safety detection and evaluation: A review
    Xiong, Zhenjie
    Sun, Da-Wen
    Pu, Hongbin
    Gao, Wenhong
    Dai, Qiong
    CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION, 2017, 57 (04) : 755 - 768
  • [22] Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons
    Kallio, K
    Kutser, T
    Hannonen, T
    Koponen, S
    Pulliainen, J
    Vepsäläinen, J
    Pyhälahti, T
    SCIENCE OF THE TOTAL ENVIRONMENT, 2001, 268 (1-3) : 59 - 77
  • [23] Integrating Remote Sensing Methods for Monitoring Lake Water Quality: A Comprehensive Review
    Batina, Anja
    Krtalic, Andrija
    HYDROLOGY, 2024, 11 (07)
  • [24] Evaluating Landsat-8 and Sentinel-2 Data Consistency for High Spatiotemporal Inland and Coastal Water Quality Monitoring
    Hafeez, Sidrah
    Wong, Man Sing
    Abbas, Sawaid
    Asim, Muhammad
    REMOTE SENSING, 2022, 14 (13)
  • [25] Optimization of a Semi-Analytical Algorithm for Multi-Temporal Water Quality Monitoring in Inland Waters with Wide Natural Variability
    Bramante, James F.
    Sin, Tsai Min
    REMOTE SENSING, 2015, 7 (12) : 16623 - 16646
  • [26] Validation of Water Quality Monitoring Algorithms for Sentinel-2 and Sentinel-3 in Mediterranean Inland Waters with In Situ Reflectance Data
    Soria-Perpinya, Xavier
    Vicente, Eduardo
    Urrego, Patricia
    Pereira-Sandoval, Marcela
    Tenjo, Carolina
    Ruiz-Verdu, Antonio
    Delegido, Jesus
    Soria, Juan Miguel
    Pena, Ramon
    Moreno, Jose
    WATER, 2021, 13 (05)
  • [27] Principles and Applications of Hyperspectral Imaging in Quality Evaluation of Agro-Food Products: A Review
    Elmasry, Gamal
    Kamruzzaman, Mohammed
    Sun, Da-Wen
    Allen, Paul
    CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION, 2012, 52 (11) : 999 - 1023
  • [28] Review of Recent Advances in Remote Sensing and Machine Learning Methods for Lake Water Quality Management
    Deng, Ying
    Zhang, Yue
    Pan, Daiwei
    Yang, Simon X.
    Gharabaghi, Bahram
    REMOTE SENSING, 2024, 16 (22)
  • [29] A comprehensive review of catchment water quality monitoring using a tiered framework of integrated sensing technologies
    O'Grady, Joyce
    Zhang, Dian
    O'Connor, Noel
    Regan, Fiona
    SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 765