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Review of lake remote sensing research

  • role： First author第一作者
  • Affiliation：

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

    Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China

    College of Urban and Environment, Northwest University, Xi'an 710127, China

  • Email：htduan@niglas.ac.cn
  • Introduction：段洪涛，1979年生，男，研究员，研究方向为湖泊遥感和智慧流域。E-mail： htduan@niglas.ac.cn
DUAN Hongtao123,  
  • Affiliation：

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

CAO Zhigang1,  
  • Affiliation：

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

SHEN Ming1,  
  • Affiliation：

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

MA Jinge1,  
  • Affiliation：

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

QI Tianci1

Resümee

Lake remote sensing is an important branch of limnology and remote sensing science as a new interdisciplinary discipline. In general, lake remote sensing includes water color remote sensing, lake water environment remote sensing, and lake hydrology remote sensing. The key to lake remote sensing is to initially study the lake’s specific problems to address individual or a type of sensitive factors. To accomplish the monitoring of these lake factors through remote sensing, the scientific questions about the preprocessing of remote sensing data, atmospheric correction, algorithm development, and validation, as well as the reconstruction of a long time series data record, were introduced one by one.With the reviews in published studies, this research discussed the research object, content, and method of lake remote sensing science and summarized five development progresses of lake remote sensing by reviewing the research progress, as follows:(1) Concerns: from interest-oriented to problem-oriented. Lake remote sensing has gradually expanded from the water color remote sensing to water environment, water ecology, and hydrology remote sensing, with diverse research fields.(2) Observation equipment: from ground-based remote sensing and medium resolution satellite to high-resolution/hyperspectral/drone. Satellite instruments for remote sensing of lakes have developed from scratch and achieved a development stage from low to high spatial, radiometric, and spectral resolution.(3) Algorithm and computing force: from stand-alone experience/mechanism model to machine learning algorithms based on cloud computing. The machine learning models have been used to retrieve water constituents in the lakes with complicated optical properties, which were difficult for traditional empirical and semi-analytical algorithms.(4) Research dimension: from surface to vertical profile. The remote sensing reflectance was related to the vertical distribution of lake water quality parameters (e.g., algae biomass) in the water column; aquatic remote sensing has been gradually developed in a 3D scale.(5) Spatial coverage: from individual/regional lake to national/continental/global scale. A number of aquatic parameters in national and global lakes, such as lake boundary, algae blooms, and water clarity, have been monitored by remote sensing data through cloud computing platforms.Finally, the future development directions of lake remote sensing are identified, as follows: (1) Launch geostationary satellites or small satellite constellation to satisfy the requirements for lake observation; (2) Develop standard algorithms of lake remote sensing and establish the global lake satellite remote sensing monitoring network; (3) strengthen remote sensing of salinity, temperature, and carbon cycle in lakes under the background of global change; (4) conduct research with respect to satellites, aircraft, and ground remote sensing monitoring and simulation over lakes and the entire watershed.

Schlüsselwort

lake remote sensing;machine learning;network;satellite constellation;SDG;big data;water color remote sensing

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