| The rapid and accurate acquisition of soil quality information is a prerequisite for achieving precision agriculture and increasing crop yields.With the development of the digital information industry,smart agriculture has become a new trend in agricultural development,placing higher demands on the timeliness and intelligence of soil quality information acquisition.Currently,scientists from around the world have constructed many quantitative remote sensing inversion models for soil,which can effectively obtain the Soil MoistureNutrients-Salinity(SMNS)content status of large regions.However,these models need to be systematized and intelligentized in order for farmers,agricultural managers,and agricultural researchers to benefit from quantitative remote sensing inversion.Therefore,the development of a soil quality analysis information system or platform based on quantitative remote sensing models has become the current trend.To meet the different needs of farmers,agricultural managers,and agricultural researchers for regional soil quality information,this paper designs and implements the SMNS intelligent analysis platform.The platform is based on the soil-water-fertilizer-saltalkali quantitative remote sensing model developed by the research team,using Geo Scene and Arc GIS software,and programming languages such as C#,Java,and Java Script.It adopts a three-layer structure of data layer,service layer,and user layer.For the above three types of users,the user layer is designed with three types of clients: PC,web,and mobile APP.The database adopts the Arc SDE+Geodatabase(geographical data model)+SQL Server mode.The research team developed and implemented functions such as m APPing,SMNS content intelligent inversion,data analysis and mining,soil knowledge base,platform management,and conducted system APPlications.The specific research content and results are as follows:(1)Design of SMNS Intelligent Analysis Platform.The SMNS intelligent analysis platform was designed to meet the different needs of farmers,agricultural managers,and agricultural researchers.The platform was divided into three layers: data layer,service layer,and user layer,with PC,Web,and mobile APP clients designed for the user layer.The PC client is intended for agricultural researchers and can be used for large-scale data processing and mining.The Web client is for agricultural managers,allowing them to obtain regional SMNS information online and conduct regional analysis.The mobile APP client is for farmers to view soil information and learn knowledge in the field.The platform functions include map display,SMNS intelligent inversion,data analysis and mining,soil knowledge base,and platform management.A database design was carried out to support the required data types,adopting the Arc SDE+Geodatabase+SQL Server database management model.(2)Implementation of SMNS Intelligent Analysis PlatformThe platform server and database were installed and deployed,and the required spatial and attribute data were obtained and preprocessed.The PC client was developed and implemented in the Microsoft Visual Studio 2010 development environment,using C#programming language and Arc GIS Engine to complete the development and implementation of functions.The web client was developed based on the Microsoft Visual Studio Code development environment,using front-end languages such as Java Script,Html,CSS and the Arc GIS API for Java Script third-party library,and calling GP(Geoprocessing)services using the Geo Processor class.The mobile APP client was developed using the object-oriented Java language and the Arc GIS API for Android in the Android Studio development environment.Geoscene Pro was used to design and encapsulate all functions as GP services and publish them.Accessing Arc GIS Server can complete the call.The backend management system was compiled using the Java Script language.(3)The platform APPlication of SMNS intelligent analysis platform.This article presents a case study of the platform APPlication using soil organic matter in southwestern Shandong and soil salinity in the Kenli area of the Yellow River Delta as examples.Taking organic matter inversion in southwestern Shandong as an example,the platform uses remote sensing inversion models to accurately obtain the organic matter content in the region.The regional analysis function can effectively provide feedback to users on the distribution of soil organic matter in the region,thus improving the efficiency of regional soil quality collection.Taking the temporal and spatial variation analysis of soil salinity in Kenli as an example,the platform compares soil salinity data at different time points through spatial analysis based on the inversion of soil salinity,providing important data support for soil salinization control.The case study shows that the platform can quickly obtain regional soil moisture and salinity indicators,with good APPlication effects.n summary,this paper comprehensively APPlied 3S technology,Internet technology,and mobile communication technology to develop the SMNS intelligent analysis platform,which achieved intelligent inversion and decision analysis of important soil quality information such as SMNS.Taking soil organic matter in the southwestern Shandong Province and soil salinity in the Kenli district of the Yellow River Delta as examples,the platform was APPlied with good results.The platform not only satisfies different user needs but also realizes intelligent and rapid inversion of important soil quality information.Moreover,it can customize model parameters based on regional characteristics to improve data acquisition accuracy and expand APPlication scope.This research will provide fast data analysis and technical support for regional agricultural production and help the last mile of agriculture. |
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