Research Progress in the Application of SAR Data in Soil Salinity Monitoring
Soil salinization is a significant issue that not only leads to ecological problems like land desertification but also poses a threat to food security by reducing the quantity and quality of arable land. Therefore,it is crucial to rapidly and accurately obtain information about soil salinization for timely and effective soil management. In recent years,the development of microwave remote sensing has provided new methods for large-scale and rapid monitoring of soil salinization,with Synthetic Aperture Radar (SAR) data-based soil salinization monitoring becoming a hotspot in remote sensing research. Recent advancements in SAR remote sensing for soil salinization monitoring can be summarized in four main aspects:(1) Microwave scattering mechanism of saline soil:Research has clarified the correlation between soil salinity and radar backscattering coefficients,providing a basis for estimating soil salinity using SAR data. Understanding the microwave scattering mechanism of saline soil is essential for accurately interpreting SAR data and extracting meaningful information about soil salinization. (2) Construction and extraction of characteristic parameters of saline soil:The construction and extraction of characteristic parameters of saline soil have shown a trend towards diversification and integration. Various parameters,such as backscattering coefficients,polarization ratios,and texture features,are used to characterize the properties of saline soil. By utilizing a combination of these parameters,researchers can obtain a more comprehensive understanding of soil salinization. (3) Classification of saline soil:The classification methods for saline soil have shifted from traditional machine learning to deep learning methods. Deep learning algorithms,such as convolutional neural networks,have shown promising results in accurately classifying saline soil areas. These advanced techniques enable the identification and mapping of different levels of soil salinity,aiding in effective soil management strategies. (4) Inversion of soil salinity:The inversion of soil salinity has transitioned from regression analysis to inversion methods that combine scattering mechanisms. By considering the microwave scattering mechanisms and using multiple data sources,more accurate estimations of soil salinity can be obtained. This approach allows for a better understanding of the spatial distribution and variability of soil salinity,facilitating targeted interventions and management practices. Despite these advancements,there are still challenges and issues in the current research on soil salinization monitoring using SAR remote sensing. Some of these challenges include the influence of multiple factors on the relationship between soil salinity and backscattering coefficients,the need for further analysis of mechanisms,the construction of characteristic parameters,and the fusion of multi-source data for achieving high-precision soil salinization monitoring using SAR remote sensing.
NETL
NSTL
万方数据
