This paper retrieved categorical mainland coastline information in the Bohai Rim from 1980, 1990, 2000 and 2010 utilizing remote sensing and GIS technologies and analyzed the characteristics and causes of the spatial–temporal variation over the past 30 years. The results showed that during the research period, the length of the coastline of the Bohai Rim increased continuously for a total increase of 1071.3 km. The types of coastline changed significantly. The amount of artificial coastlines increased continuously and dramatically from 20.4 % in 1980 to 72.2 % in 2010, while the length of the natural coastlines decreased acutely. Areas that had coastlines that changed significantly were concentrated in Bohai Bay, the south and west bank of Laizhou Bay and the north bank of Liaodong Bay. Due to the comprehensive effects of natural and anthropogenic factors, the coastline mainly expanded seaward. Coastal engineering construction were the leading factor in coastal evolution. Furthermore, the reclamation of aquaculture pond, salt field and harbor construction were the top three construction activities. Additionally, the driving force caused coastline change showed significant temporal heterogeneity.

A long-term reliable satellite chlorophyll-a (chl-a) data record is essential in understanding the state of ocean biology and quantifying its changes. Creating a long-term data record requires a combination/merger of multiple satellite products into one data record, since the lifetime of any single ocean color sensor is finite. However, because of differences in sensor design, calibration, and retrieval models, apparent cross-mission biases are usually observed between different sensor products. To attain a coherent multisensor chl-a data record, the observed cross-mission biases should be accurately addressed in the data combination/merging schemes. In this study, a multivariable data interpolating empirical orthogonal functions (M-DINEOF) approach was used to create long-term chl-a records by applying the sea-viewing wide field-of-view sensor and moderate resolution imaging spectroradiometer products. Under the assumption that the single-sensor chl-a product is free from spurious temporal artifacts and can be reference time series representing the actual variability of chl-a, the discrepancies of trends derived from different chl-a series were quantitatively evaluated based on statistical t-test and Taylor diagram analyses. Compared with direct concatenation and linear regression methods, the M-DINEOF method more effectively reproduced the main trend patterns observed in reference data series during their overlapped periods. The results highlight the importance of a cross-mission bias correction when combining multisensor satellite data records and suggest that the M-DINEOF reconstruction provides a simple and effective path forward for creating reliable multisensor ocean color records suitable for long-term trend analysis.