A Harmonious Satellite-Unmanned Aerial Vehicle-Ground Measurement Inversion Method for Monitoring Salinity in Coastal Saline Soil

Abstract

Soil salinization adversely impacts crop growth and production, especially in coastal areas which experience serious soil salinization. Therefore, rapid and accurate monitoring of the salinity and distribution of coastal saline soil is crucial. Representative areas of the Yellow River Delta (YRD)—the Hekou District (the core test area with 140 sampling points) and the Kenli District (the verification area with 69 sampling points)—were investigated. Ground measurement data, unmanned aerial vehicle (UAV) multispectral imagery and Sentinel-2A multispectral imagery were used as the data sources and a satellite-UAV-ground integrated inversion of the coastal soil salinity was performed. Correlation analyses and multiple regression methods were used to construct an accurate model. Then, a UAV-based inversion model was applied to the satellite imagery with reflectance normalization. Finally, the spatial and temporal universality of the UAV-based inversion model was verified and the soil salinity inversion results were obtained. The results showed that the green, red, red-edge and near-infrared bands were significantly correlated with soil salinity and the spectral parameters significantly improved this correlation; hence, the model is more effective upon combining spectral parameters with sensitive bands, with modeling precision and verification precision of the best model being 0.743 and 0.809, respectively. The reflectance normalization yielded good results. These findings proved that applying the UAV-based model to reflectance normalized Sentinel-2A images produces results that are consistent with the actual situation. Moreover, the inversion results effectively reflect the distributions characteristic of the soil salinity in the core test area and the study area. This study integrated the advantages of satellite, UAV and ground methods and then proposed a method for the inversion of the salinity of coastal saline soils at different scales, which is of great value for real-time, rapid and accurate soil salinity monitoring applications.

Spectral Index Fusion for Salinized Soil Salinity Inversion Using Sentinel-2A and UAV Images in a Coastal Area

“…In this study, samples were collected in spring. The characteristics of low precipitation and vegetation coverage in this season cause the soil spectrum to show a good response to SSC, which is consistent with the study by Zhang et al [36], in which spring was the sampling time associated with the inversion of SSC and good inversion results were obtained. The model obtained in this study has good SSC prediction results in this season, but whether the same result can be obtained in other seasons remains to be studied.…”

Soil Salinity Inversion of Winter Wheat Areas Based on Satellite-Unmanned Aerial Vehicle-Ground Collaborative System in Coastal of the Yellow River Delta

“…In order to ensure the representativeness of modeling samples, the samples are sorted and sampled at equal intervals at the ratio of 2:1 between the calibration set and the validation set. Compared with the traditional method of random partition modeling set and validation set [ 5 , 49 ], the data is more uniform and effective, thus ensuring the strong universality and high stability of the model.…”

“…Compared with the salt value measured on the ground, the “true salt value” is a more comprehensive representation of the true salt status in the Sentinel-2A pixel. Most of the previous studies have realized the up-scaling inversion method of UAV model by establishing the relationship of spectral information between UAV image and satellite image [ 5 , 50 ]. The method in this paper is a collaborative inversion model based on satellite images which is constructed by taking the UAV “salt truth value” as the bridge of “Satellite-UAV-Ground” collaborative inversion.…”

The Linear Hygroscopic Expansion Coefficient of Cement-Based Materials and Its Determination

“…Moreover, it may take a long time to determine the deformation of a certain size of materials after the materials are completely balanced with different environments during testing, especially when the relative humidity of the environment is low. Therefore, the inversion analysis method can be considered for the determination of the LCHE of cement-based materials [38,39].…”