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ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Forage and Livestock Production Research » Research » Publications at this Location » Publication #351584

Research Project: Bridging Project: Integrated Forage Systems for Food and Energy Production in the Southern Great Plains

Location: Forage and Livestock Production Research

Title: Application of the water-related spectral reflectance indices: A review

Author
item Ma, Shengfang - CHINESE ACADEMY OF SCIENCES
item Zhou, Yuting - OKLAHOMA STATE UNIVERSITY
item Gowda, Prasanna
item Dong, Jinwei - CHINESE ACADEMY OF SCIENCES
item Zhang, Geli - CHINA AGRICULTURAL UNIVERSITY
item Kakani, Vijaya - OKLAHOMA STATE UNIVERSITY
item Wagle, Pradeep
item Chen, Liangfu - CHINESE ACADEMY OF SCIENCES
item Flynn, K. - OKLAHOMA STATE UNIVERSITY
item Jiang, Weiguo - BEIJING NORMAL UNIVERSITY

Submitted to: Ecological Indicators
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/22/2018
Publication Date: 10/30/2018
Citation: Ma, S., Zhou, Y., Gowda, P.H., Dong, J., Zhang, G., Kakani, V., Wagle, P., Chen, L., Flynn, K.C., Jiang, W. 2018. Application of the water-related spectral reflectance indices: a review. Ecological Indicators. 98: 68-79. https://doi.org/10.1016/j.ecolind.2018.10.049.
DOI: https://doi.org/10.1016/j.ecolind.2018.10.049

Interpretive Summary: Dynamics of liquid water on the land surface is of great importance to agricultural production, public water supply, recreation, and so on. Satellite remote sensing has been widely used in water-related applications because of its large spatial coverage. Its use in detecting surface water bodies, vegetation water content, soil water status, and wetlands has facilitated the development of various water-related spectral reflectance indices (WIs) using different bands and index configurations. However, the appropriate usage of different WIs in different applications is challenging as much confusion exists. This study presents a thorough summary of existing WIs in the literature and their appropriate applications; and identifies knowledge gaps to facilitate future studies in different study domains. We started with the principles of WIs and introduced the evolution of WIs for specific research areas. The terminologies for WIs were briefly summarized to facilitate the usage of appropriate terms in specific studies. In addition, a field experiment was used to examine the sensitivities of WIs to different mixing ratios of water with soil or vegetation.

Technical Abstract: Based on the spectral signatures of liquid water and other land surface features (soil and vegetation etc.), many water-related spectral reflectance indices (WIs) have been developed to characterize the existence of liquid water. These WIs are widely used in vegetation water detection, surface water body characterization, soil water content assessment, and wetland monitoring. However, choosing the right WIs for specific studies is confusing because of arbitrary selections of WIs in respective applications, and occasionally cross use of the same WIs names in different studies. To increase the clarity of appropriate usage of WIs in specific conditions, this study reviewed the principles, development, and applications of various WIs in order to identify the suitability of different WIs for different applications. We started with the discussion of the underlying principles and developments (e.g., from ratio to normalized difference of two bands) of different WIs, based on the spectrum features of water, vegetation, and soil from widely used spectral libraries. Applications from different studies in each category were then compared to show the performances of different WIs. Following that is a brief summary about the terminology of WIs in different studies to further reduce the confusion caused by the cross use of WIs terms. A field experiment was designed to investigate the dynamics of various WIs in response to different mixing ratios of water and soil or plant. The effectiveness of combining WIs and greenness indices for detecting surface water body and wetland was evaluated using the field experiment data. Finally, we identified the major gaps and pointed out the potential improvements in future.