GISdevelopment.net --> Application --> Urban Planning
Mr. Sanket Dinesh Shah
Executive - GIS Analyst
Lavasa Corporation Ltd (An HCC Group Company)
Mail id: sanket.shah@lavasa.com
Synopsis
The concept of New Urbanism has integrated various fields such as Environment, Engineering and Construction, Urban Planning and Architecture for planning, execution and sustainable development. These components constitute the process of urban development and planning and require timely assistance of GIS to ensure accuracy as well as ease of operation.
In such a demanding environment, catering to spatial needs accurately and promptly is a measure of the capability of GIS. Once the process is defined, human intervention is mostly monotonous up to the supervisory level. Most of these processes can be customized for faster execution enabling better resource utilization.
This paper presents the development of the architecture of a unified application, accommodating the various processes used frequently at Lavasa. It discusses in detail a tool developed to categorize, convert and automatically update surveyed data from a total positioning station (TPS). The primary intention of developing such an application was to introduce ease of converting volumes of raw survey data into GIS. The designed tool assists GIS professionals and non GIS users to ensure accuracy in converting voluminous data in a limited amount of time, thus enhancing managerial decisions.
1.Introduction
1.1 About Lavasa
Lavasa Corporation Limited was formed to undertake a large scale lifestyle development in India. Based on new urbanism principles, and located near city of Pune in the state of Maharashtra, India, a township is being developed over a sprawling area of approximately 10,000 acres.
The project area lies between the latitudes 18 º 26’ 33’’ and 18 º 21’ 16’’ North and longitudes 73 º 25’ 13’’ and 73 º 37’ 18’’ East. Lavasa is located on the backwaters of Warasgaon dam on the Western Ghats between Pune and Mumbai.
At such a large scale of development the individual aspects of planning, execution and decision making deploy various challenges. GIS holds the capacity of synchronizing these activities through its capability to handle huge amounts of spatial data, providing user friendly visualizations and facilitating faster analysis.
1.2 GIS at Lavasa
Spatial data for the entire project is managed using an spatial database engine (SDE) which incorporates enterprise GIS architecture. The spatial inputs are received from various sources ranging from AutoCAD designs to raw total station points.
Presently the GIS database acts as a central repository for all enterprise level data. Analysis and decision making are derived from the GIS database and hence accurate conversion, storing and frequent updating are very crucial steps which are followed.
Spatial Data from these sources carries discrepancies which do not allow accurate transformation into a GIS. Hence methodologies include constant topological checks before updating in the SDE.
1.3 Present Scenario
Survey data collection in a topographically challenging environment like Lavasa is a tedious process. In many cases it is not possible to collect data in a sequential form due to various factors such as visibility of station points, time constraints in completing surveys etc.
To maintain data standards and processes, the data collected, has to undergo a series of quality procedures which are as follows:
In the above process it is seen that the time taken to import CSV files to the different layers of ACAD file, involves ample amount of time. Further digitization process may result in for error which account to the data inaccuracy. Earlier trials of correcting these errors infer that the amount of time correcting these errors is almost equal to the time of regenerating the data manually.
To ease this monotonous process, automated tools were proposed to be developed with the help of ArcGIS desktop using VBA.
2. Survey Data Conversion Tool (SDCT)
Figure 1. SDCT view in ArcMap.
Process description
This tool converts the CSV file to a staging Geodatabase. It creates different Feature Classes and sorts according to the ‘Description’ field in CSV files.
As mentioned in the section 1.3, the various steps of converting data in an ACAD environment namely : Importing to CAD, organizing layers, Joining points, exporting to shape and converting to geodatabase are now done in an automated environment in the order : Organize data as per description, join points and export to geodatabase directly. Figure 2 Demonstrates the difference in the two methods.
The basic challenge while developing this tool was the method in which data is collected. Most of the times it is random point collection due to lesser visibility, lack of time, bad weather conditions etc. but the survey team ensures proper and complete collection of features. Due to such a crude method of data collection, it became difficult to join the points based on their FID (which is the sequence in which the data is collected). Hence the logical answer to sorting these points was to generate a unique ID for each feature as per their occurrence on ground. This was fulfilled using the distance between the two points as the source of ID generation.
It was expected that the program would encounter cases where this logic would not provide proper results, but out of the total conversions done, this logic still holds good.
Comparison of Existing methodology Vs Automated methodology
Figure2. Process flows for manual and automated survey data updation
Both the processes are similar to each other to a number of steps, but the time taken and the human involvement reduces manifold due to the automated work flow.
3. Conclusion
Timeline comparison for Existing process Vs Automated process
*Taking CSV file for the 200 point features
As we can see in the above chart, total time taken by the existing method is 10 minutes while time taken by the automated method is 35 seconds.
This tool has reduced the total time in conversion of the data by around 17 times also ensuring the accuracy of the data. The comparison sheet between these two processes is shown in the concluding section. Thus the automated method delivers more precise results within fractions of seconds.
4. Future Scope
Lavasa GIS caters to all departments who use data in a spatial context. Various processes are repetitive and time consuming in nature. The present tool is limited to line features. It will complete when there will be successful conversion of polygon features.
This tool is the part of a complex software system envisioned to encompass various such tools used daily. It is proposed to create a object oriented flexible toolset which will be used across the organization by everyone, thus decreasing the barriers between GIS and non GIS professionals in the organization.
New Urbanism - An Automated Approach
Mr. Sanket Dinesh Shah
Executive - GIS Analyst
Lavasa Corporation Ltd (An HCC Group Company)
Mail id: sanket.shah@lavasa.com
Synopsis
The concept of New Urbanism has integrated various fields such as Environment, Engineering and Construction, Urban Planning and Architecture for planning, execution and sustainable development. These components constitute the process of urban development and planning and require timely assistance of GIS to ensure accuracy as well as ease of operation.
In such a demanding environment, catering to spatial needs accurately and promptly is a measure of the capability of GIS. Once the process is defined, human intervention is mostly monotonous up to the supervisory level. Most of these processes can be customized for faster execution enabling better resource utilization.
This paper presents the development of the architecture of a unified application, accommodating the various processes used frequently at Lavasa. It discusses in detail a tool developed to categorize, convert and automatically update surveyed data from a total positioning station (TPS). The primary intention of developing such an application was to introduce ease of converting volumes of raw survey data into GIS. The designed tool assists GIS professionals and non GIS users to ensure accuracy in converting voluminous data in a limited amount of time, thus enhancing managerial decisions.
1.Introduction
1.1 About Lavasa
Lavasa Corporation Limited was formed to undertake a large scale lifestyle development in India. Based on new urbanism principles, and located near city of Pune in the state of Maharashtra, India, a township is being developed over a sprawling area of approximately 10,000 acres.
The project area lies between the latitudes 18 º 26’ 33’’ and 18 º 21’ 16’’ North and longitudes 73 º 25’ 13’’ and 73 º 37’ 18’’ East. Lavasa is located on the backwaters of Warasgaon dam on the Western Ghats between Pune and Mumbai.
At such a large scale of development the individual aspects of planning, execution and decision making deploy various challenges. GIS holds the capacity of synchronizing these activities through its capability to handle huge amounts of spatial data, providing user friendly visualizations and facilitating faster analysis.
1.2 GIS at Lavasa
Spatial data for the entire project is managed using an spatial database engine (SDE) which incorporates enterprise GIS architecture. The spatial inputs are received from various sources ranging from AutoCAD designs to raw total station points.
Presently the GIS database acts as a central repository for all enterprise level data. Analysis and decision making are derived from the GIS database and hence accurate conversion, storing and frequent updating are very crucial steps which are followed.
Spatial Data from these sources carries discrepancies which do not allow accurate transformation into a GIS. Hence methodologies include constant topological checks before updating in the SDE.
1.3 Present Scenario
Survey data collection in a topographically challenging environment like Lavasa is a tedious process. In many cases it is not possible to collect data in a sequential form due to various factors such as visibility of station points, time constraints in completing surveys etc.
To maintain data standards and processes, the data collected, has to undergo a series of quality procedures which are as follows:
- Total station survey generated points in a CSV (Comma Separated Value)
format which has following fields:
X, Y and Z - Precision of these values is up to 5 decimal places.
Description -It indicates the abbreviation used to denote the attribute information. For ex. Road center is denoted as RC, Road Edge as RE etc
Date – Date on which survey has taken place (mmddyy) - CSV file imported into different layers in a consolidated ACAD drawing file based upon the description field.
- Line features are created using these point features.
- The surveyor then exports these features into a shape file where all the required fields are verified.
- This data becomes a part of an external geodatabase whose schema is a replica of the enterprise GIS data used at Lavasa.
- A series of topology checks are carried out to ensure data integrity and its compliance to standards.
- After successful topology check and editing, the data is uploaded to the SDE.
In the above process it is seen that the time taken to import CSV files to the different layers of ACAD file, involves ample amount of time. Further digitization process may result in for error which account to the data inaccuracy. Earlier trials of correcting these errors infer that the amount of time correcting these errors is almost equal to the time of regenerating the data manually.
To ease this monotonous process, automated tools were proposed to be developed with the help of ArcGIS desktop using VBA.
2. Survey Data Conversion Tool (SDCT)
Figure 1. SDCT view in ArcMap.
Process description
This tool converts the CSV file to a staging Geodatabase. It creates different Feature Classes and sorts according to the ‘Description’ field in CSV files.
As mentioned in the section 1.3, the various steps of converting data in an ACAD environment namely : Importing to CAD, organizing layers, Joining points, exporting to shape and converting to geodatabase are now done in an automated environment in the order : Organize data as per description, join points and export to geodatabase directly. Figure 2 Demonstrates the difference in the two methods.
The basic challenge while developing this tool was the method in which data is collected. Most of the times it is random point collection due to lesser visibility, lack of time, bad weather conditions etc. but the survey team ensures proper and complete collection of features. Due to such a crude method of data collection, it became difficult to join the points based on their FID (which is the sequence in which the data is collected). Hence the logical answer to sorting these points was to generate a unique ID for each feature as per their occurrence on ground. This was fulfilled using the distance between the two points as the source of ID generation.
It was expected that the program would encounter cases where this logic would not provide proper results, but out of the total conversions done, this logic still holds good.
Comparison of Existing methodology Vs Automated methodology
Figure2. Process flows for manual and automated survey data updation
Both the processes are similar to each other to a number of steps, but the time taken and the human involvement reduces manifold due to the automated work flow.
3. Conclusion
Timeline comparison for Existing process Vs Automated process
*Taking CSV file for the 200 point features
As we can see in the above chart, total time taken by the existing method is 10 minutes while time taken by the automated method is 35 seconds.
This tool has reduced the total time in conversion of the data by around 17 times also ensuring the accuracy of the data. The comparison sheet between these two processes is shown in the concluding section. Thus the automated method delivers more precise results within fractions of seconds.
4. Future Scope
Lavasa GIS caters to all departments who use data in a spatial context. Various processes are repetitive and time consuming in nature. The present tool is limited to line features. It will complete when there will be successful conversion of polygon features.
This tool is the part of a complex software system envisioned to encompass various such tools used daily. It is proposed to create a object oriented flexible toolset which will be used across the organization by everyone, thus decreasing the barriers between GIS and non GIS professionals in the organization.