首页|Assessing the quality of chlorophyll-a concentration products under multiple spatial and temporal scales

Assessing the quality of chlorophyll-a concentration products under multiple spatial and temporal scales

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The chlorophyll-a concentration data obtained through remote sensing are important for a wide range of scientific concerns.However,cloud cover and limitations of inversion algorithms of chlorophyll-a concentration lead to data loss,which critically limits studying the mechanism of spatial-temporal patterns of chlorophyll-a concentration in response to marine environment changes.If the commonly used operational chlorophyll-a concentration products can offer the best data coverage frequency,highest accuracy,best applicability,and greatest robustness at different scales remains debatable to date.Therefore,in the present study,four commonly used operational multi-sensor multi-algorithm fusion products were compared and subjected to validation based on statistical analysis using the available data measured at multiple spatial and temporal scales.The experimental results revealed that in terms of spatial distribution,the chlorophyll-a concentra-tion products generated by averaging method(Chl1-AV/AVW)and GSM model(Chl 1-GSM)presented a relatively high data coverage frequency in Case Ⅰ water regions and extremely low or no data coverage frequency in the estuarine coastal zone regions and inland water regions,the chlorophyll-a concentration products gener-ated by the Neural Network algorithm(Ch12)presented high data coverage frequency in the estuarine coastal zone Case 2 water regions.The chlorophyll-a concentration products generated by the OC5 algorithm(ChlOC5)presented high data coverage frequency in Case Ⅰ water regions and the turbid Case Ⅱ water regions.In terms of absolute precision,the Chl1-AV/AVW and Chl 1-GSM chlorophyll-a concentration products performed better in Class Ⅰ water regions,and the Chl2 product performed well only in Case Ⅱ estuarine coastal zones,while presenting large errors in absolute precision in the Case Ⅰ water regions.The ChlOC5 product presented a higher precision in Case Ⅰ and Case Ⅱ water regions,with a better and more stable performance in both regions compared to the other products.

remote sensingchlorophyll-a concentrationdata coverage frequencyaccuracyvalidationmultiple spatial and temporal scales

Zheng WANG、Qun ZENG、Shike QIU、Chao WANG、Tingting SUN、Jun DU

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Institute of Geographical Science,Henan Academy of Sciences,Zhengzhou 450052,China

State Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography(Ministry of Natural Resources),Hangzhou 310012,China

Editorial Department of Journal of Central China Normal University,Wuhan 430079,China

Project for Fostering Outstanding Young talents of Henan Academy of SciencesSpecial Project for Team Building of Henan Academy of SciencesScience and Technology Research Project of Henan ProvinceScience and Technology Research Project of Henan ProvinceScience and Technology Research Project of Henan ProvinceMajor Scientific Research Focus Project of Henan Academy of Sciences

210401001200501007212102310424222102320467212102310024210101007

2024

10.1007/s11707-022-1022-1

地球科学前沿
高等教育出版社

地球科学前沿

CSTPCD
影响因子：0.585
ISSN：2095-0195
年,卷(期)：2024.18(3)
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