WebGIS-based Farmland Ecosystem Spatial Decision Support System

Chen Yaheng; Zhang Junmei; Men Mingxin

（College of Land and Resources; Agricultural University of Hebei; Baoding 071001;China）

Abstract: A quantitative dynamic knowledge model for evaluating the stability and analyzing the fluctuations of crop production was established in this study based on the results of farmland ecosystem stability and fluctuation of crop output. This dynamic model was combined with the technology of B/S distributive network structure and information management platform based on WebGIS to establish a Farmland Ecosystems Space Management System, which can perform the networking, digital and intelligent functions. This system is able to perform the functions of map manipulation, query and analysis of spatial information, the stability evaluation of regional farmland ecosystems, crop production volatility analysis, visualization output, and experts in intelligent decision-making and system maintenance. The test results of the system show that the structure and functions of Farmland Ecosystem Space Management System can meet the needs of the farmland ecosystem management and decision support with good stability and strong practicability. The implementation of this system provides technical foundation for the networked and digitalized farmland ecosystem spatial decision.

Keywords: WebGIS; Spatial decision support system; Farmland ecosystem; Stability evaluation; Volatility analysis

0 Introduction

With increases of the population, cities expanding and lands occupation, and the input in the process of crop production, the agricultural resources and environment have been going through an ever-worsening situation, resulting in serious problems on food issues. It is urgently necessary for policy makers, researchers, and the majority of farmers to obtain an effective management tool to provide services for the sustainable development of farmland ecosystems and crop production. In recent decades, the mathematical/statistical models and computer simulation technology as effective means have been applied to cropland management to provide beneficial information decision for production. Recently, Internet technologies have been widely used around the world due to its independent platform, low maintenance costs, the simple application and data sharing [1-4]. Therefore, these new tools can be integrated with the spatial information technology to build Web-based Farmland Ecosystem Space Management Information System.

Recently, network technology has been more and more widely used in natural resource management and

environmental planning such as HYDRA system (the Spatial Decision Support System for urban river water quality management)[5], Pl@nteInfo (the Information Decision Support System based on web technology applied in crop management)[6], and WEDSS providing services for environmental planning and watershed management [7] and WGAT (Web-based GIS and Analytic Tools) achieving geographic information services on three levels in respectively data storage, information display and spatial analysis [8]. The above systems play an important role in their respective fields. However, studies on the Farmland Ecosystem Space Management Information System based on WebGIS technology, spatial database technology, network technology, and comprehensive knowledge of the model have not been reported yet.

This paper aims at establishing a Farmland Ecosystem Space Management Information System based on WebGIS technology to provide data query and mapping services for the farmland ecosystem managers and decision makers and technical support for the network and informatization of farmland ecosystem space. This system establishes an interactive Web Geographical Information System based on WebGIS technology,

spatial database technology and computer network technology, which is combined with the fluctuation analysis model and stability evaluation model on the basis of environmental and farmland resources data in Hebei Province. The research selects open and interactive Internet as a development platform, allowing public access to data and making analysis [9-10].

1 The organizational structure and content of the system

The Farmland Ecosystem Spatial Management Information System is based on the characteristics of the WebGIS [11, 12] applying a more stable and popular B/S (Browser/Server) network structure. The system structure is divided into three levels: the client browser, including the WWW client, the Microsoft Internet Explorer (IE); network service layer, including the WWW the server, the Microsoft Internet Information Server (IIS); and the WebGIS server layer, including WWWbased GIS server (of ArcIMS) [13].

Information transfer process between the client and the server is divided into five stages (Figure 1): When the user operate on the client browser, corresponding request will be made and subsequently be sent to the network server (Webserver); network server (Web Server) will pass the request to the matching ArcIMS Application connector upon receipt; ArcIMS applications connector translates the request and sends it to the ArcIMS Application Server in ArcIMS data format; then ArcIMS application server handles the load distribution and tracks the ArcIMS.

When the space server running, and the received the request is sent to the running space server. There are 7 types of space servers: Image, Feature, Query, Geocode, Extract, Metadata, and ArcMap, where four types of services (Image, ArcMap Image, Feature and Metadata) are able to access the space server. But those four services have no direct access to the space servers, while they have to be through managing virtual server tools of multiple space servers. Incoming requests will be assigned to an instance of the virtual server group which runs the service; finally, the space server gets the request and makes corresponding response and sent back the results in turn reversely to the ArcIMS Application Server, ArcIMS connectors and the

network server (Web Server). Network server (Web Server) displays the query results on the HTML page, and the results return to the client browser, then users get the response results of the operation. The whole process forms a request/response cycle.

Figure1.The process of information transfer between client and

server

1.1 Server-side The server-side provides major service functions.

Its functional modules include Database Management Systems (DBMS), Model Base Management System (MMS), ArcIMS (ArcGIS Internet Information Server), IIS (Microsoft Internet Information Server), J2SDK and ServletExec.

1.1.1 Database Management System (DBMS) Database Management System supports the Model

Base Management System by managing spatial and attribute data. The underlying database builds the object-oriented spatial database using the Geodatabase data model [14]. The background forms a basic platform using the Commercial Relational Database Management System Oracle9i and the database engine ArcSDE. ArcSDE interface can achieve the storage of spatial data in the commercial database [15] and fulfill the extension of the relational database, making spatial database a true spatial geodatabase. The user can transparently access the geospatial data without considering the format, data storage location, methods and data structures, etc. [16] (See figure 2).

Browser (Microsoft Internet Explorer)

Network server (IIS)

Spatial data Attribute data Model base

Application connector (Servlet, ActiveX, Java)

ArcIMS Application Server

ArcIMS Spatial Server

DBMS MMS

Figure2. Sketch map of DBMS framework

System data includes spatial data and attribute data. Spatial data are mainly vector maps which are classified into the underlying spatial database and intermediate outcomes library. Data in the underlying spatial database includes the basis maps such as the administrative maps, soil type maps, organic matter maps, rainfall maps and topographic maps (Table 1). Results library stores the intermediate outcomes and evaluation results map. Attribute data includes the data of natural conditions and socio-economic data. Associated fields associate the databases [17].

Table1. The data of FESDSS

Data type Name of data

Spatial data

Administrative map of Hebei Province

Soil type map of Hebei Province

Organic matter map of Hebei Province

Rainfall map of Hebei Province

Topographic map of Hebei Province

Stability score map of Farmland

Ecosystem of Hebei Province

Crop Production Volatility score map of

Hebei Province

Stability grade map of Farmland

Ecosystem of Hebei Province

Attribute

data

Meteorological data

Soil character data

Social economy data

1.1.2 Model Base Management System (MMS) The model-based library of the system is the premise of qualitative analysis and quantitative calculation. The model library contains a model set, model description and management subsystem. In the FESDSS Model Library, the model set is composed of the stability

evaluation model of the farmland ecosystem, crop fluctuation analysis model and statistical models. The development of the model relies on machine language combining land resource science, soil science, agronomy, geography knowledge and expertise. The model library combining farm management information and knowledge is a set of model components (dll) which was developed with Visual Basic 6.0 language. In the actual evaluation process, the model extracts data from the database for calculation and returns the results to the database to achieve the resource sharing between the model library and database. The model explanation is mainly the explanatory annotations that tell users how to use the model. It’s in form of text files. The Model Base Management System is able to query, retrieve, add or delete, call and modify the parameter of the model. It organizes the model set into an organic related system that support decision-making and coordinate the control of the decision-making statement. The model functions are integrated to the client user interface through ArcIMS.

1.2 Client-side The client interface is implemented through the

design Java, JavaScript, HTML, and Active Server Pages (ASP). JavaScript interprets users’ input to the HTML page into URL address information and convey it to the IIS service at the server-side. Through the application GUI technology, a friendly HTML interface is built. Microsoft's ASP technology is a simple tool that allows you to create dynamic pages to collect user input information. Map display and publishing tools are created by ArcIMS.

Web

Database

ArcGIS Server

ArcSDE

ArcIMS Server

ArcSDE

Client ClientClient

Client

Figure3. Functions of FESDSS

2 The main functions of the systems

The system achieves the standardization management of spatial information of regional farmland ecosystem and decision-making for different scales of farmland production, including functions such as the operation of the basic map, query and analysis of spatial information of farmland ecosystem, stability evaluation of regional farmland ecosystems, crop production volatility analysis, visualization output and system maintenance (Figure 3).

2.1 Operation of the basic map The basic map operating functions of the system

includes the basic operations such as zoom in and out, pan, area measurement and download. 2.2 Query and analysis of spatial information

The system provides time series attribute data query and spatial map query services that allows users to query temporal data in different ways and conditions. Users need to select the condition query and point query to query the time series data. Spatial data query is

made by selecting different spatial data. Users can also make analysis of the data through

this system. The analysis of spatial data is done by selecting a different range of values and display. Time series attribute data can be analyzed using statistical analysis tools, it can also be made into histograms, pie charts and line charts using the chart tool for secondary analysis.

2.3 Evaluation of stability

Stability evaluation mainly targets at exploring the best management model for farmland ecosystem, it forms the stability evaluation knowledge model by parsing and analyzing the quantitative relationship between the natural, social and economic impact resulting from farmland ecosystem productivity and productivity fluctuations. The model can achieve the stability evaluation of the different scales of farmland ecosystems. It uses the AHP to determine the weight of indexes, and eliminate the impact of the data dimension with the commonly used Z-Score method, and synthesize various indicators with the linear weighted sum method.

2.4 Crop production volatility analysis The function includes fluctuation analysis of the yield and the total production. And it analyses the law of the volatility in conjunction with the time and space of crop production. Tendency outlier method is employed to calculate the crop volatility index based on the calculated coefficient of variation. In the end, the volatility index reflects fluctuations in time-series trends, and the coefficient of variation reflects the law of Spatial Variation of the fluctuations. 2.5 Experts’ intelligent decision of regional farmland ecosystem Regional Farmland Ecosystem Expert Knowledge Base reserves the problem needs to be solved, generally including knowledge of experts’ judgmental knowledge and various descriptive facts. In fact, the knowledge stored in the Expert Knowledge Base of Regional Farmland Ecosystem is a rule which is established upon plenty of analysis and judgment on the stability of the regional farmland ecosystem and the extract and

Query and analysis of spatial data

Basic map operation

Evaluation of stability

Crop production volatility analysis

Experts’ intelligent decision

Basic information query

Temporal analysis

Stability constraints analysis

Evaluation of stability

Time series analysis

Spatial variation comparison

Problem diagnosis

Experts’ intelligent decision

Fluctuation classification

FESDSS

System Maintenance

Data update

Maintenance of system component

Visual Output Thematic map

Tables of statistics

summary of expert s’ knowledge. The diagnosed through the farmland ecosystems Expert Knowledge Base can recommend the targeted recommendations and countermeasures. 2.6 Visual output

On the basis of system-generated data, the application of ArcIMS software realizes the thematic map display of the farmland ecosystem management decision-making results and output function of the statistical reports.

3 Design and implementation of the system

3.1 Development environment The system was developed in the Chinese Windows 2000 operating platform of Intel Pentium4 2.8, 1 G-memory computer, ArcIMS9.0 as WebGIS

development platform. Oracle9i and ArcSDE9 are selected to build the basic spatial database of integrated properties, models are developed through Visual Basic 6.0 and ASP language is employed as the language for the development of the system integration, Html language is employed in the interface design. 3.2 User’s interface and its application

The system creates a simple html page for the needs of different user groups on the basis of the initial customization of Author and Designer module of ArcIMS software. Then by modifying ArcIMSparam.js files and combining with Html, ASP, JavaScript and other languages, simple and fast customized HTML browser is achieved, thus the site layout and secondary development of the client interface is fulfilled. The main function interface of Farmland Ecological Spatial Decision Support System is shown in Figure 4.

Figure4. The main function interface of FESDSS

3.3 Application of the System Hebei Province is chosen as the research base,

query, analysis and stability evaluation on spatio-temporal data of the established system and crop output volatility analysis have been made; decision support and other functions have been put into use. Results in Hebei show that the structure and function of the system design meets the needs of farmland eco-management and spatial decision-making, and good stability and strong

practicability are obtained. （1）Generate the basic unit of farmland

ecosystem stability evaluation Farmland ecosystem stability evaluation unit

refers to a region where the stability index of the regional farmland ecosystem is relatively uniform. The system is able to build the farmland ecosystem stability evaluation unit automatically by the space discretization technique according to the spatial difference of the farmland ecosystem components.

Firstly, the system positions accurately the sample input by the users at the client-side according to the spatial coordinates and makes supplementary data survey: standardized processing is carried out for light stable index during crop growth period, the accumulated temperature stability index, precipitation stability index, the disaster-resistant rate of farmland, the stability index of soil nutrient content and agricultural irrigation water quality; the weights are determined based on fuzzy clustering method of the rough set theory; and the weighted linear sum method is applied to calculate the factors of the yield formation. And then call the kriging interpolation algorithm on the server side implemented by the middleware technology for space discretization of the regional yield formation factors, to obtain the figure of regional differences of yield formation factors. And then it superimposes soil maps and land use maps with the merging of small polygons, and theregional farmland ecosystem stability evaluation unit is generated.

（2）Crop production volatility analysis

The purpose of the management of farmland ecosystems is to achieve stable farmland productivity, while the regional farmland crop production volatility is an important indicator of the farmland ecosystem stability. Therefore, the volatility research of regional farmland crop production is an important part of regional farmland ecological system stability research. The system abstracts the fluctuations in crop production systems using empirical mode decomposition (EMD) and calculates the coefficient of fluctuation of crop output by the residual method, and the volatility of crop production is analyzed from both the aspects of time series and geographical differences. Based on the quantitative relationship model between the factors of productivity formation of established farmland ecosystem and fluctuations of farm productivity, the volatility score of crop production of regional farmland is calculated, and the different volatility levels and

distribution of farmland crop production are shown in different colors.

The system can perform statistical analysis for field plots of different levels of volatility by using charting tools such as histograms, bar charts and line charts to help the users make decision. Users can visually view the plots range where the fluctuation of crop output coefficient of the region exceeds the threshold set by the system via the fluctuation parameters set by the server side. The system can make reports regarding factors affecting the volatility of the crop yield of the field plots to help the users make decision.

Users can call the multivariate regression analysis model in the system model library and make the dominant factor analysis using cluster analysis model such as the mining model to identify the main factors that affect the volatility of the region, and take corresponding measures according to the system Expert Decision-making Knowledge Base. The contrast of the total crop output and yield fluctuation of Hebei Province is shown in Figure 5, and the fluctuation grade area proportion of farmland ecosystem is shown in Figure 6. （3）Stability evaluation of Farmland Ecosystem

The system builds a farmland ecosystem stability evaluation knowledge model by parsing the quantitative relationship between the formation factors of the farmland ecosystem productivity and productivity fluctuations. The innovative of this model not only involves the evaluation of farmland ecosystem in terms of structure, function, energy and the nature, society and economy but also focus on the evaluation from the perspective of the important processes of the ecosystem. User can input the supplementary survey data at the client-side and call evaluation model at the server-side to evaluate the stability of the region's farmland ecosystem and query the stability level of the farmland ecosystem and analyze the stability differences and distribution law of different regional farmland ecosystems. Users can also keep and abreast of the spatial extent of the farmland with unstable ecosystem that exceeds the threshold

of the system. For unstable farmland, the system will conduct cluster analysis, multivariate regression analysis on the dominant factors affecting the stability of the farmland ecosystem, to control or improve the methods or measures against the main influencing factors according to the knowledge recommended by the expert knowledge base. Apart from that, the system will recommend favorable farmland ecosystem management models for different emphases, such as crop yield formation process, soil ecological process or input-output process or the ecological environment.

For each farmland ecological system evaluation unit, users have an easy access to print report concerning location of the plots, ownership, and other natural, socio-economic attributes as well as the instability of control measures and best management mode, as it is, the management of farmland ecosystems is very user-friendly. Farmland Ecosystem Stability Evaluation of Hebei is shown in Figure 7. （ 4 ） Prediction on the stability of farmland ecosystem

The system is able to analyze the trend of the stability of the farmland ecosystem and predict the future stability of the farmland ecosystem. Through the analysis and prediction of the factors affecting the stability of the farmland ecosystem based on the farmland ecosystem stability evaluation knowledge model, the system can predict the future stability of regional farmland ecosystem and early detect the potential regional instability of farmland ecosystem for measures to be taken to prevent these instabilities. At the same time, users can choose

appropriate farmland ecosystem management models based on the development and trend of farmland ecosystem stability to ensure the sustainable development of the farmland ecosystem. Prediction of the farmland ecosystem stability is shown in Figure 8.

Figure5. Compared of crop production fluctuation of

Hebei

Figure6. Fluctuation grade area proportion of farmland

ecosystem

Figure7. Farmland Ecosystem Stability Value Map of Hebei

Figure8. Develop trend of farmland ecosystem stability

4 Conclusion

1）On the basis of the stability of farmland ecosystem and fluctuation of crop output combined with the system modeling approach, a quantitative dynamic knowledge model of stability evaluation and the fluctuation analysis of crop output is established.

2）The system realizes the functions of query and analysis of spatial information of the farmland ecosystem, stability evaluation of regional farmland ecosystems, crop production fluctuation analysis, data visualization output and intelligent decision-making.

3 ） WebGIS technology, spatial database

technology, computer network technology are applied integrally to build the networked, digitalized and intelligent Farmland Ecological Spatial Decision Support System. The system has good compatibility, high stability and high efficiency in operation and high practicality in function.

4）The development of the system provide the

key technologies and constructs the basic framework for the further application of modeling techniques and the 3S integration technology when building farmland ecosystem resources and environment information systems.

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