A field survey system for land consolidation based on 3S and speech recognition technology

Original papersA field survey system for land consolidation based on 3S and speech recognitiontechnologyXiaochuang Yao a ,b ,Dehai Zhu a ,b ,Sijing Ye a ,b ,Wenju Yun b ,c ,Nan Zhang a ,b ,Lin Li a ,b ,⇑aCollege of Information and Electrical Engineering,China Agricultural University,Beijing 100083,ChinabKey Laboratory of Agricultural Land Quality,Monitoring and Control,Ministry of Land and Resources,Beijing 100083,China cLand Consolidation and Rehabilitation Center,Ministry of Land and Resources,Beijing 100035,Chinaa r t i c l e i n f o Article history:Received 23October 2015Received in revised form 1July 2016Accepted 16July 2016Keywords:3SSpeech recognition Land consolidation Field survey systema b s t r a c tThe main objective of this study is to develop a field survey system for land consolidation based on 3S (geographic information system,GIS;Global Positioning System,GPS;and remote sensing,RS)and speech recognition technology.Field survey in land consolidation is a complex and high-tech process.Traditional survey methods are difficult to use in locating,measuring,recording,and other related tasks.Through 3S and speech recognition technology,Android smart phones could address the aforementioned problems by providing a new method of land information collection.In this study,we present a land con-solidation field survey system (LCFSS),which is developed on an Android mobile platform and integrates 3S and speech recognition technology to support the field survey of land consolidation.The proposed sys-tem is made advantageous by its low cost,high efficiency,portability,and user-friendliness.To improve the usability and feasibility of the LCFSS for decision making,we develop a data-adaptive development model,data compression model,three-parameter model for coordinate registration,and speech process-ing model.With the Unified Modeling Language,5functional modules and more than 16application cases are described.On the basis of these models,the functions of system management,data import,pro-ject survey,coordinate registration,and data output are implemented by adopting the system architec-ture with four layers.The key achievement is tested and applied to a land consolidation survey in the provinces of Ningxia,Anhui,Shandong,and others.Results show that the efficiency of land information collection and other functions is improved with the use of the proposed system.Therefore,the approaches and methodology presented in this work could serve as a reference for those who are inter-ested in developing mobile system applications based on 3S and speech recognition technology.Ó2016Elsevier B.V.All rights reserved.1.IntroductionField survey for land consolidation is significantly difficult because of its complex process and high-tech requirements (Jia et al.,2009;Xi et al.,2013).Traditional survey methods necessitate a considerable amount of time and effort and are also difficult to use in locating,measuring,and recording tasks (Jia et al.,2009;Wang et al.,2015a ).For example,with a paper map of one land consolidation project,workers tend to get lost because of the large area of the land consolidation project.In such a case,they would need to write down detailed information,such as location,length,and agricultural land type,to collect data about land features.For-tunately,3S technology,as the core of information engineering technology,provides a new method for collecting land information and thereby overcomes the aforementioned issues.For instance,geographic information systems provide technical support for data analysis and expression (Zhang et al.,2014),positioning through the Global Positioning System (GPS)can be used in field investiga-tion systems to improve the accuracy of data acquisition (Doner and Yomralioglu,2008;Mesas-Carrascosa et al.,2012),and remote sensing (RS)provides large-scale multi-source data and support for macro decision making.With the development of smartphones or personal digital assistants (PDAs)and the improvement of hard-ware performance in mobile terminals in recent years,integrated 3S technologies that are useful in spot investigations for land recla-mation project evaluation have been fully realized.In addition,data input methods are crucial in providing working efficiency in outdoor environments.However,using the Chinese input method usually requires several letters for one word as input,and in some cases,the variety of answers available makes choosing the right/10.1016/pag.2016.07.0130168-1699/Ó2016Elsevier B.V.All rights reserved.⇑Corresponding author at:College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China.E-mail address:lilincau@ (L.Li).one difficult.The development of speech technology has improved the efficiency offield work(Huang and Chi,2012).With this tech-nology for land consolidation survey,users simply need to provide their voice input through the Chinese input method in their mobile phones;their voice data are then translated into text data auto-matically and quickly(Huyan et al.,2014).With the development of3S technologies,several types of field survey systems have emerged in many industries,some of which adopt more than one technology.The inability of informa-tion systems based on desktop computers or the web to meet the requirements of real-time and portable data collection in thefield(Che et al.,2010;Yan et al.,2015)has prompted the development of manyfield survey systems.With the maturity of mobile technologies,such as cellular phones and PDAs,work-ers are now able to collect data and obtain decision support wherever and whenever they want.Through GPS technology, information collection systems are increasingly being used in precision agriculture(Montoya et al.,2013),agricultural land leveling surveys(Li et al.,2005),field area measurement,and so on.With GPS and GIS technologies,the application offield survey technologies for land consolidation(Wang et al.,2015b) and variable rate irrigation control systems(Bartlett et al., 2015)has undergone obvious development.Moreover,3S tech-nologies have been successfully applied to insects(Han et al.,its large size(Ye et al.,2014).In the proposed land consolidation field survey system(LCFSS),a data compression method is used to store RS data on mobile devices,thus ensuring the availability of global project data on site.Moreover,speech recognition tech-nology is adopted,and a Chinese word segmentation model is developed to improve the efficiency of speech recognition through a local land consolidation word database.The proposedfield system for land consolidation based on3S and speech recognition technology is aimed at data acquisition for project-scale land consolidation with high efficiency.The pro-posed system benefits not only the government through the provi-sion of progress information but also the participating personnel through the monitoring of their location and improvement of their work efficiency in thefield.To ensure that the techniques and models are user-friendly infield surveys,we develop the LCFSS with a data-adaptive development model,which equips the system with improved expansibility and portability.2.Design of LCFSS2.1.System architectureThe main purpose of the LCFSS is to providefield survey equip-660X.Yao et al./Computers and Electronics in Agriculture127(2016)659–668(2)Data layerThe second layer is the data layer.The data layer stores and manages different types of data,including vector,raster,and the-matic data.For one land consolidation project,we use a planning map,a status map,remote sensing data,and inconsistent features.A SQLite database is utilized as the medium between offline vec-tors or XML data and data collection work;it holds local land speech words.Raster data are stored in a secure digital(SD)card in a pyramid format.(3)Inter-medium layerThe third layer is the inter-medium layer.The inter-mediate layer,which consists of a database interface and a mobile GIS developer kit,bridges data application and data storage.In this way,the interaction details between components and operating systems are concealed,and development efficiency is thus improved.(4)Function layerThe fourth layer is the function layer.Through the support of the aforementioned layers,the LCFSS provides functions of map control,data collection,trace tracking measurement diagram, and others.The application layer is constructed on the basis of the inter-mediate layer.As the executor of functions for data queries,editing,and analysis,the function layer supports concrete operations and provides a user interface(UI)for collecting index data.2.2.Data processingField survey in land consolidation is a complex and high-tech process.Thefirst step in this process is data processing.During dif-ferent periods,the different types of generated data(.JPG n.TIF n. DWG)result in the lack of unity for data types.Such drawback leads to inconvenient data storage and transmission.The work content of investigation is also changing with different stages of one land consolidation project.In the current paper,we transform all data into two data types,namely,.TPK and.SHP,and use XIAN 80(geographic coordinate system,GCS)as the coordinate system (see Table1).These relevant tasks are mainly performed in ArcMap 10.1.2.3.Requirement modelAccording to the requirements of the system function,5models with16use cases are diagrammed in the Unified Modeling Lan-guage,which is helpful in understanding operationflow(Li et al., 2010)and later development.Fig.2shows the case diagram of the LCFSS for users,along with the followingfive models:(1)data import,which involves loading vector and raster data into the sys-tem from a SD card;(2)project survey,in which users can edit and add map features(points denote farm wells,lines denote channels, polygons denote cultivated lands,etc.)through the GPS and GIS technology;(3)coordinate registration,which provides the transfer mathematical model from GPS WGS84coordinates to WGS XIAN80coordinates,to improve the accuracy of the collected spatial data;(4)data output,which involves the export of the collected data from the LCFSS to the PC display;(5)systemTable1Data requirements.Data name Data type(before)Data type(after)Coordinate system(before)Coordinate system(after)LC-planning map.JPG n.TIF n.DWG.TPK None XIAN80(GCS) LC-status map.JPG n.TIF n.DWG.TPK None XIAN80(GCS) LC-completed map.JPG n.TIF n.DWG.TPK None XIAN80(GCS) LC-image map.TIF.TPK None XIAN80(GCS) LC-inconsistent features.SHP.SHP XIAN80(GCS)XIAN80(GCS)X.Yao et al./Computers and Electronics in Agriculture127(2016)659–668661management,which includes system update,contact information and help document,data clearance,and GPS network set.3.Implementation of LCFSSWith the development platform Eclipse,we develop the imple-mentation of the LCFSS,which is based on the following hardware and software specifications:Pentium IV2500MHz processor PC with Windows7and Ether-net card.Intel X Scale312MHz processor PDA with Android Mobile4.0, GPRS,Wi-Fi,and SD interface.Eclipse4.4.development model is designed for the proposed system to solve this problem.As shown in Fig.3,all spatial data of one land consol-idation project are divided into three main classes of data,namely, (1)raster,(2)shapefile,and(3)GPS.As a result of the differences in data classes,different data tables are generated automatically. According to the data analysis,methods for organizing and index-ing data can be automatically executed to reduce the influence of data type,range,and size.With the data-adaptive development model,the system could implement dynamic spatial data analysis to ensure that different types of spatial data with different spatial ranges could be identi-fied,organized,and displayed automatically forfield data collec-tion.Data processing(Section2.2)isfirst performed prior to the input of data into the system.662X.Yao et al./Computers and Electronics in Agriculture127(2016)659–668LCFSS because the system works best with maps that do not change frequently,such as planning maps or the completed maps of land consolidation projects.Although creating a cache tile pack-age is time consuming,the cost is only a one-time expense.3.3.Coordinate registration modelThe coordinate system of the location information from the GPS is WGS-84(Gaikwad and Pawar,2014;Lantzos et al.,2013), whereas that from the LCFSS is XIAN80(GCS).Hence,to ensure the accuracy of location data,GPS data must be subjected to coor-dinate system transformation from WGS-84to XIAN80(GCS).The most common transformation methods include seven-,four-,and three-parameter models.Given that the area of the land consolida-tion project is approximately10km,the results of the models at this scale vary only slightly.In this system,the three-parameter model is adopted,and the process is shown in the following steps:(1)Select one or more pairs of known coordinate points:WGS-84and XIAN80(GSC).(2)Select the model formula:the three-parameter model givenbyX2 637D X2637x2637registration model of the LCFSS,we can ensure that the accuracyof the GPS data is based on the mobile devices and consistent withthe impact of different coordinate systems.3.4.Speech processing modelThe speech processing model in the LCFSS aids workers in col-lecting basic information on land consolidation projects,such asland and road types.Fig.4shows that the speech processing modelincludesfive steps,which starts with the voice input of the speakerand ends with the data storage in the SQLite tables.In this work,we adopt offline speech processing,and thus,before the systemis run,the land key word database is trained with the speech pro-cessing model.Then,the dataset is matched with speech partici-ples in thefield survey process.We adopt the hidden Markov model toolkit to achieve offlinespeech recognition from the voice input of speakers.As shown inFig.4,a Chinese word segmentation model is implemented withthe maximum matching method to split the speech recognitionresults into many single words or new string arrays.Thereafter,adata processing model translates the new string arrays into Hash-Map data,in which the key is the data collectionfield(such as landtype and road type)and the value is the collection result(such ascultivatedfield andfield road).Finally,the system stores the Hash-X.Yao et al./Computers and Electronics in Agriculture127(2016)659–668663(2)Data managementThe LCFSS is used in the project-scale land consolidation.The dataset in the system mainly includes a planning map,a status map,a completed map,an image map,and inconsistent features (Table1).Users can easily interact with the contents of the database and run spatial analysis models by clicking buttons to manage data.As shown in Fig.5,the steps for data management using the LCFSS are as follows:(c)Edit the information on the subject or renew the geographicelements.(d)Save the data and move on to the next one.As illustrated in Fig.7,many miscellaneous functions are devel-oped to improve the operation of the system.These functions include map measurement,spatial orientation,trace tracking, coordinate registration,and so on.(a)Map measurementmanagement interfaces of the LCFSS:(1)main interface withfive function models,(2)data import interface,(3)system map data control 664X.Yao et al./Computers and Electronics in Agriculture127(2016)659–668(d)Coordinate registrationAs detailed in Section3.2,coordinate registration is aimed at promoting the precision of GPS data.(e)System managementThis function involves the system update,net set,data clear-ance,and user assistance.4.System evaluationFor the system evaluation of the LCFSS,three different types of mobile terminals are tested:PDA,smartphone,and professional GPS devices.This system evaluation test mainly includes three aspects of content,namely,(1)function of the data integration dis-play with the cache tile package of the raster data,(2)location accuracy of the GPS data with the coordinate registration model in this system,and(3)data collection with the speech recognition technology.Every mobile device maintains a basic storage space of8–16GB or more.All of the data of one land consolidation project require a storage space of not less than7GB and may thus slow down devices.Through the data compression model proposed in this work,the data size is compressed by aboutfive times,and the dis-play speed becomes nine times faster than before(see Table2).To ensure the accuracy of the GPS data,using a professional GPS with a coverage of less than1m in4s is preferable.However,with cost taken into account,PDAs and smartphones are more widely data via a professional GPS is direct,the data accuracy achieved with PDAs is about7.35m,and the data accuracy achieved with smartphones is approximately13.32m.In the same test environ-ment involving the coordinate registration model presented in this paper,the PDA achieves a data accuracy of about4.12m,whereas the smartphone achieves a data accuracy of approximately6.03m. After modification,the GPS data can meet the data accuracy requirement of the given land consolidation project.The users can then choose different Android-based platforms according to their work requirements.With regard to speech recognition,the main performance parameters include error rate(ER),accuracy rate(AR),and recogni-tion speed.ER¼IþDþSNAR¼NÀDÀSNRS¼R timeS timeð2Þwhere N includes all the words in the land key word database,I includes the inserted words,D denotes the deleted words,and S represents the replaced words.The recognition time is the speech time as a unit.For example,if speech time is2h and recognition time is6h,then the recognition speed is3ST.The number of test samples is100,which includes5people with20speeches each.The real dataset comprises4land consoli-dation tables,including14classes and52Chinese words.It includes ditches,roads,farmland,agricultural wells,and other land features.Before the test,all of the real datasets are stored in the SQLite tables and trained with the speech processing model.As the contrast test results show(see Table3),the speech processing model in the LCFSS meets the required application accuracy;that is,an error rate of not more than6%and a recognition speed ofdata collection interfaces of the LCFSS:(1)main function model interface,(2)spatial data query interface,(3)spatial editing interface,(4)editing editing interface,(6)polygon collection interface,(7)attribute collection interface,and(8)pictures of collection interface.In addition to the above system tests,all system functions are tested during use in the provinces of Ningxia,Anhui,Shandong,etc.A case study on the LCFSS is presented in the next section.5.Case study:land consolidation survey in Ningxia,China In this section,a case study on the LCFSS is described on the basis of the factual dataset in Table 4.We take one major land con-solidation project in Ningxia province as an example.The total area is 3363.5ha.The three basic maps are shown in Table 4.On the basis of the data processing in Section 2.2,we obtain inconsistent features,such as field roads,ditches,and newly added cultivated lands.This application case study is aimed at surveying the real progress and verifying the inconsistent features of the land consol-During the course of this investigation,we tested all the func-tions of the LCFSS,as shown in Section 3.5.In the project scale,the LCFSS could meet the requirements well.To finish this project survey,we established a survey schedule with the LC-image map and then ensured that all inconsistent objects were within our ing the GPS orientation function,we arrived at the survey features one by one and edited or renewed the features with spa-tial or attribution properties using the GIS functions.We used the speech input function to enter or select lists containing the data collection information.We took pictures as well.The results for one project are shown in Fig.8.For the survey results in this application case,146inconsistent features were verified,24new features were collected,and more than 250pictures were obtained from the investigated scene.In Fig.8,0means ‘‘true,”which indicates that the feature really exists,and 1means ‘‘false.”The additional information about the features,such as the attributes and pictures,was assigned with a unique ID Table 2Contrast test between cache tile package and raster data of one land project.Data typeData size Display speed Raster data8.4GB 3.78s Cache tile package1.61GB0.4sTable 3Contrast test between lab and field results of the speech processing model.Location Error rate (RR),%Recognition speed (RS)Lab 3.7 1.83Field5.61.89Table 4Real dataset for major land consolidation project in Ningxia,China.Data nameData type Size Size (compressed at five levels)LC-planning map .TIF 1.26GB 0.47GB LC-status map .TIF 1.35GB 0.53GB LC-image map .TIF 0.94GB 0.38GB Field road .SHP 64KB /Field ditch.SHP 56KB /Newly added cultivated land.SHP48KB/miscellaneous function interfaces of the LCFSS:(1)measurement type selection interface,(2)polygon measurement result interface,(3)spatial spatial navigation,(5)trace tracking interface,(6)and (7)coordinate registration interface,and (8)system management interface.system and exported in one folder.Applying the LCFSS could improve the efficiency offield work and ensure the scientific accu-racy of data collection.In addition,the LCFSS allows for an easy integration with other systems because of the standardization of the data results.6.DiscussionThe proposed smartphone system is beneficial for land consol-idationfield survey at a project scale as it provides accurate loca-tion information and formidable GIS functions.The accurate location information generated with the GPS model provides a spa-tial orientation feature,which enables users to determine their current location and target destination.RS data as the main data serve as the basic map.By comparing the different periods of RS image data,we can master land consolidation projects and their corresponding changes.The different features from the RS data serve as the main investigation objects.GIS technology facilitates land consolidation.Speech recognition technology,as an auxiliary function,makes the data acquisition system convenient and quick.The system test shows that3S technology and speech recogni-tion significantly improve the quality and efficiency of thefield investigation work for land consolidation projects.The system could address a series of practical problems and make complex scene investigation work highly efficient.For example,during pro-ject inspection,investigators can easily determine their position and direction,identify project area boundaries,and locate project construction sites and scope changes.Moreover,users can deter-mine whether the work routine layout is in line with the planning and design and whether the completed construction task should be approved.7.ConclusionIn this study,an integrated system for thefield survey of land consolidation projects using Android-based smartphones or PDAs is successfully designed by using ArcGIS API for Android,Eclipse, SQLite,and JAVA programming language.This system provides sys-coordinate registration,data export,and system management.The system graphical UI offers single or double click functionality.The above combination of software indicates that the system functions are efficient enough to bring the following remarkable advantages for the LCFSS.First,the proposed system realizes data integration in mobile phones or PDAs.Data format exchange,data interoper-ability,and direct data access provide a data basis for thefield sur-vey of land consolidation and facilitate the sharing of data between PDA and workstations based on unified standards.Second,the pro-posed system provides afield survey system for land consolidation and realizes the integration of multi-source data,spatial query, spatial orientation,and map measurement.Thus,the system allows users to obtain scientific information technology support for land consolidation survey work.Third,the technology devel-oped in this study,which is based on3S and speech recognition technology,can be considered as infrastructure for data providers for other related applications.According to the progress of our project,the system is set to be upgraded with further improvements in online data access,data wireless transmission,and so on.AcknowledgmentThis work was conducted as part of the‘‘Land Management Major Project Dynamic Monitoring Method and Technology Research”,which was sponsored by Ministry of Land and Resources under grant201305410810073.ReferencesBartlett,A.C.,Andales,A.A.,Arabi,M.,Bauder,T.A.,2015.A smartphone app to extend use of a cloud-based irrigation scheduling put.Electron.Agric.111,127–130.Ben-Harush,O.,Carroll,J.A.,Marsh,B.,ing mobile social media and GIS in health and place research.Continuum J.Media Cult.26,715–730.Che,Y.,Li,M.,Zheng,L.,Deng,X.,2010.Development of a movable 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