The current widely used bathymetric inversion model based on multispectral satellite imagery mostly relies on in-situ depth data for establishing a liner/non-linear relationship between water depth and pixel reflectance. This paper evaluates the performance of a dual-band log-linear analysis model based on physics (P-DLA) for bathymetry without in-situ depth data. This is done using WorldView-2 images of blue and green bands. Further, the pixel sampling principles for solving the four key parameters of the model are summarized. Firstly, this paper elaborates on the physical mechanism of the P-DLA model. All unknown parameters of the P-DLA model are solved by different types of sampling pixels extracted from multispectral images for bathymetric measurements. Ganquan Island and Zhaoshu Island, where accuracy evaluation is performed for the bathymetric results of the P-DLA model with in-situ depth data, were selected to be processed using the method to evaluate its performance. The root mean square errors (RMSEs) of the Ganquan Island and Zhaoshu Island results are 1.69 m and 1.74 m with the mean relative error (MREs) of 14.8% and 18.3%, respectively. Meanwhile, the bathymetric inversion is performed with in-situ depth data using the traditional dual-band log-linear regression model (DLR). The results show that the accuracy of the P-DLA model bathymetry without in-situ depth data is roughly equal to that of the DLR model water depth inversion based on in-situ depth data. The results indicate that the P-DLA model can still obtain relatively ideal bathymetric results despite not having actual bathymetric data in the model training. It also demonstrates underwater microscopic features and changes in the islands and reefs.

The research on urban innovation links is of great significance for revealing the structural characteristics of innovation space. At the same time, it is of great significance for formulating regional innovation development strategies. Based on statistics from 2008, 2013 and 2018, the time and spatial characteristics of the urban innovation contact network evolution in Henan Province were investigated using the entropy weight and gravity-model method. The results show that the overall pattern of the regional innovation network in Henan Province is radial, with the characteristics of a “core edge”. It shows that it radiates to the surrounding cities with Zhengzhou as the core. From the perspective of time evolution, the radiation range and intensity of the innovation center city have changed to varying degrees and the overall radiation pattern has not significantly changed. From the perspective of spatial evolution, the evolution of Henan Province’s innovation network presents the following development trends. The central and southern regions developed rapidly, and the western, northern and eastern regions developed slowly.