GIS based Web Enabling of Nationwide Biomass Digital Atlas with Data Compression
D. R. Anantha Deshpande
In the current trend, dynamic data access is considered essential, with synchronized updates, with ease of operation and support for secured multi-user access keeping different user categories in view. In the work presented here, a projection of power potential biomass residues like Sugarcane trash, Paddy Husk, Paddy Stalks, Groundnut stalk, Bamboo wastes and the likes are considered that are useful in meeting some of the requirements in the renewable energy sector and has been a challenging problem. In a synergetic approach in this effort, an electronic atlas of biomass resource for India that has already been developed as a stand-alone application is attempted to be made available on the Internet. The work reported here involves development of the essential GIS tools in addressing specific problems related to handling of the large sized data, successfully without significant loss of information.
In this context, a method for compression of the data, involving grouping of polygons of same crop and other attributes is used to generate the spatial layer having crop based biomass attributes. This leads to reduction of the datasets in the GIS graphic primitives resulting in “compression” of tuples of data. The polygons generated after such compressions are embedded to the crop map. Maps enabled with such GIS objects are used for the linked to GIS Web server. The method has shown a significant enhancement in the response for the Internet client and is identified as a significant enhancement since the data transfer sizes in the Internet media becomes a major point of concern response-wise as well as cost-wise.
In the overall approach, apart from compressing the data as described, the query made by a client will be processed at the server and the response specific graphic output representing the region of interest is formed and made available to the client along with the biomass data. One of the advantages of the Web design is taken to its best advantage with the data updates taken up at the server end that gets reflected soon enough on the client-side. This paper presents the effective way of using the network resources for disseminating GIS based Biomass Resource Atlas on a remote access on the Internet.
The work has been successfully completed in developing a code for converting the Biomass Resource Atlas for India. The tools developed and the methods used are adoptable to many other sets of interpretation and analysis of Remote Sensing Data and is considered useful to the development of such applications.
Biomass is a natural resource available that stores solar energy by the process of photo synthesis in the presence of sunlight. Biomass energy is used to produce either electrical or thermal through gasification. The residues which are available from the grown crops such as paddy Husk, paddy stalks, sugarcane trash or bagasse and many more are used in generation of power. In this scenario assessment of biomass geographically is increasing for budgetary purposes or feasibility study for energy production centre.
GIS [Geographic Information System] is the tool having the features for managing, analyzing and decision making by seamlessly combining both spatial and non-spatial geographical data. The GIS development platform used for this purpose is GeoConcept with its Web server called GCIS. GIS map contains different layers of information – Demography, Administrative Boundaries and Identified Crop Layers. By using the built in functions of GeoConcept a software tool has been developed to obtain the power estimation for the particular crop in a agricultural area a on stand alone system. With the advancement in Web and networks it is possible to extend these features available in stand-alone systems to remote clients for online biomass assessment. Further, the GIS software provides redistributable ActiveX with necessary API [Application Programming Interface].
It is necessary to reduce the server response time to enable faster service to the clients. It is therefore required to reduce the size of the map with an attempt to limited tampering or modifying of the information. The technique described is carried out by grouping several vectors in the map that have same properties to a compounded single vector graphic entity. In the context of biomass assessment Grouping of vectors is based on crop name. The grouping of polygons results in lesser number of rows of data representing each polygon resulting in overall reduction of file size and there by the query response time. Such a map is hosted on the Web site in a server. The client queries are allowed to be handled by a GIS engine at the server. When client puts a query to know the power estimation for particular place or region, the server would process for the queried parameters and delivers the results, actively generated as a raster in JPEG format with GIS tags.
The input Data for the analysis is received from various sources. The RSD [Remote Sense Data] Image after it is processed to generate the agriculture vector Polygons are available in suitable formats as map layers. The ground resolution used in this satellite imaging is 188 mts per pixel.
The statistical data which is available out of the surveys done at both taluka and districts levels are compared with the data available from Ministry of Agriculture and other sources. Using the parameters like CRR [crop residue ratio], Factor for power, Residue generation and the biomass utilization power assessment can be made to the required level of accuracies.
Such sets of data generated is analysed and refined to form a central repository of the crop information. These data sets in the maps along with statistical crop data are inputs for web enabling.
Hosting of GIS based maps or information through a media servers several advantages such as
Enabling of GIS maps on web is carried out through GCIS internet server to create fully functional Web-based mapping applications for GIS. Geo Concept Internet Server (GCIS) has open architecture, which allows the data to be embedded within a page rapidly, and a selection of map browsing tools to be provided for the user's convenience. Web enabling demands care to optimize client time, server Time & Network resources. The architectural block diagram for the client-server operation to remotely assess the biomass is as under in Fig1.
- Global access of huge data & hosted information of the GIS maps provided with platform independence.
- Ease in modifying or updating of maps in a centrally located repository.
Fig.1 Architecture requirement on the server side Working Principle
Fig. 2 Flow chart for Web Enabling
Following steps are pipelined to deploy the maps, the server, activeX server pages and the necessary html pages to enable remote assessment of biomass. Fig.2 shows the flow of query and information during web access. The HTML Pages containing references to the GCIS server are created by embedding GCIS tags. These tags acts as the query interface for running maps on the web server. The Geo Concept Internet Server tags (GCIS Tags) are categorized into different types depending on usage as listed below.
Tags used in Geo Concept Internet Server headers.
Tags used to view a GCIS HTML page.
Tags used to obtain a map image.
Tags used to handle display scales.
Tags used to move a map.
Tags used to display information about map objects.
Tags used to manipulate the Go to function.
The GCIS tags serve two functions – They enable default parameters to be set for the first user request addressed to GCIS and also enable certain "user context" variables to be embedded within the HTML document which will be returned to the user. On the web server side, a CGI (Common Gateway Interface) or ISAPI (Microsoft Internet Server API) program handles communication between the web server & GCIS add-on. This means that the main workload falls to the server, which will construct the responses. This type of architecture is referred to as being "client-light". Loading a plug-in on the client side in this context is quite unnecessary a standard browser such as Internet Explorer or Netscape Navigator is all that is needed.
The way GCIS operates is to use a CGI (gcis.exe) or ISAPI (gcis.dll) script to communicate with the client's browser via the URLs, or Uniform Resource Locators. The script program will open one or several hosted HTML pages. These pages are different in the way they incorporate special headers and tags called ‘GCIS tags’. It is these tags and headers that GCIS will analyze before sending a reply to the client's request.
All the GIS based crops map are uploaded onto the web server & link to the each map is done through a browsing interface using HTML. The GCIS server is configured to specify the required HTML pages to access the concerned maps. The simultaneous number of users is also configurable. When ever the remote user activates or clicks on the URL, the navigator interprets data as though it had direct access to the file. The GCIS scripts interact with the client’s browser & incorporate tags onto HTML files. The client side tag directs the GCIS to respond to the required data by opening the right map on the server side. The map running on the GCIS server is then returned onto the client end in the form of HTML having all the information of the map embedded in it. The data or the biomass assessed information of the map is displayed in the form of table as shown below.
The design aspects are discussed for the following modules:
- "Grouping technique is carried out by grouping a several vectors of the GIS map which have same properties to a single vector entity.
- Web response Improvement, an interface that would enable user to select the spatial features and query the associated non-spatial attributes with a quick response.
- Statistical Data Query, a flexible user interface where the users would interact to get on non-spatial attributes and display the associated spatial features.
- Simple Map Browsing on the web: A user interface where the users would be able to browse the map by zooming in/out, querying etc.
Grouping Technique is achieved by grouping same polygon vectors of the Crop layers which have same crop at taluk level resulting in a ‘compression’. These grouped different polygons are then represented by a single vector polygon [spatial separation of polygons are maintained] thus by reducing the number of rows representing each polygon.
Steps followed in Grouping
- The crop map is subjected to analysis & processing to make a list of unique crop names distributed in the map.
- The land use layer polygons are then classified based on the different type of land use pattern which is represented by a particular land use code.
- Based on type of crop & the land use polygons are selected & grouped in to a list. This is done by API available in GIS.
The Table.1 Shows a sample excerpt from the pre grouping list to grouped list. It can be seen that for the crop ‘Coconut’ there are 10 spatially separated polygons before grouping in the Sringeri taluk, Chikmagalur district, India. After the grouping this is reduced one by aggregating the spatial area other attributes remaining the same. This type of grouping resulting in compression is also similar to data normalization.
Table.1: Before and After Grouping Technique
The Fig. 3 below shows the compression done on Chikmagalur Taluk. Graphically the grouping may be explained as follows. The polygons in color- Cyan represent coconut. The image cannot explicitly display the effect of grouping. But if the map is opened containing vector polygons in GIS and any coconut polygon is selected, all the spatially separated polygons belonging to crop ‘coconut’ in that grouped region will also be selected. This is not possible if the ungrouped map is queried for coconut selection, instead only that polygon will be selected for viewing.
Fig.3, Compression done on Chickmagalur Taluk
Web response Improvement
During the remote client access the server responds to the queries applied on the complete map data. By reducing the data without compromising the information it is possible to improve the response and there by bring down the server time. The reduction in number of polygons is around 98% in this particular map. Reduction percentage in number of polygons varies depending on the no. of polygons and no. of types of crops in each Taluk. To secure the services of the web ASP.NET form authentication is adopted.
Statistical Data Query:
The analyzed data which is embedded along map is available for querying, which contains the information like total crop Area, cropproduction, Biomassgeneartion etc.User can feed the criteria in the Query Builder form give his own values for selection criteria. Finally, for the query presented by the user, only those features that match the criteria are displayed dynamically. A sample queried table for Sringeri taluk of Chickmagalur, district is shown below.
Table.2 Sample queried table for Taluk Data for Major Crops - Chikmagalur, Sringeri
Simple Map browsing on the web
The maps are presented in an JPEG form so that the user can perform the zooming operations (zoom in, zoom out, re center) on the map. These operations allow the user to see the map with a suitable view. The Maps in the website are generated dynamically based on the geographic selection made by the user. Once the user makes the geographic selection, then the map file is generated with the layers available for that geographic entity. This file is consulted for the layers available, order in which the layers are to be displayed and so on. Some of view settings available at client desktop:
Zooming & Paning Options
The zooming options include zoom in, zoom out and centering the map. These options allow the user to view the map under different magnification scales.
The Legend portion of the map displays all the layers of the map, its visibility status and the colour used to represent it. The user is provided with the option of turning a layer on/off. The user can at any time change the colour of a layer from the palette and this change will be reflected in the map once it is redrawn.
The other remote features such as query based on circle of interest, distance computation and latt-long navigation will be added in the next phase for further improvement in web access.
Results & Discussions:
The advantages of compression can be known practically by following example. From the above pictures obtained before & after grouping of crop maps we can conclude few points which is given below
- The response would be normal for the first query, where as it would be faster for subsequent queries, because the same map would have been loaded on the server for handling earlier queries on the same state or region.
- Considering each row of the map contains 100 bytes of data. The amount of size occupied by the polygons in the file before compression was found to be 100 x 10107 bytes, which equals to around 1Mb. But considering size after compression it returns to be 100 x 215 Bytes, which equals to around 21Kb. This shows the significance of compression. Thus the crop map size can be effectively reduced without any visual loss & information.
- The Fig.4 shows the results obtained by accessing the GIS crops map through web. There was as effective reducing in time response accessing the compressed maps in respect to the maps without compression. With the use of GCIS server the access to rich amount of GIS data were made easy in the form of HTML pages. Development time in building & updating web server was reduced to significant extent.
Fig.4 shows the results obtained by accessing the GIS Map over web
The approach has been able to provide a means of data dissemination of one of vital areas of renewable energy of the country related to Biomass Resource Assessment. The advantages of the Web design is taken to its best advantage with the data updates taken up at the server end that gets reflected on the client-side as and when such update occurs, one of the most important part of data presentation with specific reference to the production of Agro-Crop Residues that are changing periodically.
The work has been successfully completed in developing a code for converting the Biomass Resource Atlas for India, as a sponsored research project of MNES, GOI. The tools developed and the methods being adoptable to other sets of RSD interpretations could be considered significant for the development for such applications.
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- Professional ASP.NET 1.1,by Alex Homer, Dave Sussman, Rob Howard, Brian Francis, Karli Watson, Richard Anderson, April 2004
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Authors: "The Team from CGPL IISc,2003