Case Study: How to Evaluate Property Tax using Drone Photogrammetric Images?
Objective: Land and Revenue department of Bihar Government responsible for Tax and Revenue collection in the state of Bihar, India, was struggling with efficient property tax collection; considering the poor evaluation techniques and weaker effect of the existing system.
OVERVIEW
Property Tax is the principal source of revenue in urban local bodies in virtually every part of the world. In Bihar, India, the system of property tax evaluation has no regular update or proper monitoring regarding the removal or addition in new units of revenue (storeys in a building) which results in revenue staying unacknowledged to its potential. Due to such complications, major districts of Bihar were facing delays and a shortage in revenue collected. Also, there was no close monitoring to know whether property tax owners are regularly filing taxes on the addition of floor, the addition of house or in case of change of ownership.
Problems Faced by Government
- For effective property tax evaluation District Magistrate needs to know the following factors:
A. Commercial hoardings on buildings in the area
B. Telecom towers on the residential land if any
C. Basement/Godowns if any
D. Number of Commercial/ Residential /Agricultural land
E. Number of houses with the exact number of floors
2. There is no robust structure or guidelines to standardize the tax collection model, every district/local has its own procedure with respect to the geographical context.
Drone Photogrammetry and Property Tax Evaluation
Indshine took the project as a Proof Of Concept (POC) that aimed to evaluate UAV photogrammetric image used in property valuation in terms of property tax assessment, which is achieved by the production of orthophoto and finding out the elevation through the Digital Surface Model(DSM). The elevation helped in tax assessment of the houses (by counting the number of storeys). Starting with the determination of crucial criteria such as the parameter in rate on tax assessment of the area and storeys in a house and methods used to calculate, this POC can speed up the property valuation for the housing area, especially for tax assessment.
In Phase 1, The focus on the assessment of the area (to calculate estimated tax collection and comparison with actual tax collection.)
Phase 2, is about data acquisition which was followed by determining the area (taken into consideration) taken from Google Earth and the flight plan was designed using the Litchi software.
Phase 3, The raw data was collected from the field and then processed in the Agisoft software to create the orthomosaic and the DSM for the required output.
Phase 4, We ensured similar and correlate digitising of storey in a house by creating a control layer in terrace form before separately digitising each house.
After all the digitizing processes were done the area of each house was calculated by its geometry (polygon) and the storey through the elevation (DSM) from the ground.
The unit should be the same as the unit used to calculate the rate of tax assessment. The standard rate was calculated using the actual dimension/area of the building. After the digitizing processes on actual dimension of each storey of the house were completed, the areas of each storey of the house were calculated automatically.
Tax Calculation
The Challenge we faced:
It was a challenge to convince state authority that drones can be used in property valuation. This POC can help the local authority to manage and update their database, especially on tax assessment.
Solutions Provided
Indshine provided solutions for the existing problem as following:
- Detecting Building Footprint from orthomosaic aerial image.
- Vectorized output of building’s boundary Building Foot Prints.
- Area and the number of floors*.
- Estimated tax collection from the area.
(*FSI: Floor Space Index is used for taking the permission from the local municipal bodies in case of tax collection, generally FSI is 1.)
The data was provided on Indshine’s cloud platform (Indshine.com) which also has multiple organization’s user base where people often collaborate and do digitization, geospatial analysis, extract design information. All the vector data were superimposed over high-resolution orthomosaic map.
What Impact did the Solution Make?
- Quick: The first key metric to understand the increased efficiency is reduced man-hours (time); In the manual digitizing process it took 2 man-days to give qualified output for 5 sq. km, now the same is performed in 2 minutes employing 0.5 man days.
- Digitalized data: The raster drone images were digitalized to provide attributes for calculating revenue on the basis of the area and the number of storeys in the building. Digitalizing data is also synonymous to preserving it for future scope.
- Better: As the property tax and revenue collection was increased by 2.5x.
Methods Used
We used our drone (mounted with GPS) to fly over the area and captured a large number of high-resolution images. Then we used photogrammetry techniques to stitch those images and generate orthomosaics.
Let us look at some of the essential details about the methods used:
Area covered: 20 sq. km.
Images acquired: 3000 images — per sq. km. (We processed images in sq. km.)
3000*25 = 75000 images
Time taken in stitching those images to create a 2D map: 12 hrs per sq. km. We used 4 high config. computers for processing 25sq. km.
We used raster mover to align and make a seamless Orthomosaic
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