Soil Salinity and Soil Water Content Estimation Using Digital Images in Coastal Field:A Case Study in Yancheng City of Jiangsu Province,China  

作　　者：XU Lu MA Hongyuan WANG Zhichun 

机构地区：[1]School of Geography,Geomatics and Planning,Jiangsu Normal University,Xuzhou 221116,China [2]Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences,Changchun 130012,China

出　　处：《Chinese Geographical Science》2022年第4期676-685,共10页中国地理科学（英文版）

基　　金：Under the auspices of the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA28110301,XDA2306040303);National Natural Science Foundation of China(No.41807001,41977424);Natural Science Foundation of Jilin Province(No.20200201026JC)。

摘　　要：Soil is the essential part for agricultural and environmental sciences,and soil salinity and soil water content are both the important influence factors for sustainable development of agriculture and ecological environment.Digital camera,as one of the most popular and convenient proximal sensing instruments,has its irreplaceable position for soil properties assessment.In this study,we collected 52 soil samples and photographs at the same time along the coast in Yancheng City of Jiangsu Province.We carefully analyzed the relationship between soil properties and image brightness,and found that soil salt content had higher correlation with average image brightness value than soil water content.From the brightness levels,the high correlation coefficients between soil salt content and brightness levels concentrated on the high brightness values,and the high correlation coefficients between soil water content and brightness levels focused on the low brightness values.Different significance levels(P)determined different brightness levels related to soil properties,hence P value setting can be an optional way to select brightness levels as the input variables for modeling soil properties.Given these information,random forest algorithm was applied to develop soil salt content and soil water content inversion models using randomly 70%of the dataset,and the rest data for testing models.The results showed that soil salt content model had high accuracy(R_(v)^(2)=0.79,RMSE_(v)=12 g/kg,and RPD_(v)=2.18),and soil water content inversion model was barely satisfied(R_(v)^(2)=0.47,RMSE_(v)=3.04%,and RPD_(v)=1.38).This study proposes a method of modeling soil properties with a digital camera.Combining unmanned aerial vehicle(UAV),it has potential popularization and application value for precise agriculture and land management.

关 键 词：soil salinity soil water content coastal soil digital image 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] S156.41[自动化与计算机技术—计算机科学与技术]