A quality check and modification on the individual toposheet vector data was completed after digitisation of various features and finally all the toposheets have been edge-matched to get one digital map for the project area. Village maps for all the 18 villages under the project area obtained from the DILR Office / PCMC were already in the GIS-compatible format. The details available in these maps were
- Village boundary
- Cadastral plot boundary
- Survey number / cadastral number
- Roads.
Regional Plan maps obtained from PCMC was integrated with the village maps of the newly merged area. This RP map served as a guideline for framing proposals for the DP of newly merged area.
Creation of Initial Base Map
Map of SOI toposheets, cadastral maps, and RP maps were all integrated to form a base map of the study area.
Remote Sensing Data
Browsing and procurement of Satellite Image from NRSA
IRS satellite PAN digital image has been identified and procured from NRSA, Hyderabad for the minimum cloud period. For land use classification, IRS LISS-III images were procured from NRSA.
Collection of Ground Control Points (GCPs) and Registration of Satellite Image into Project Database
Ground control points were collected with the help of Satellite Image and a digital base maps was prepared. Well-distributed GCPs (e.g. road, railway intersection, intersection, of roads, bridges and river confluence's etc.) were selected over the area. GCP was verified and extended by using Global Positioning System (GPS). IRS 1C LISS-III and PAN were registered using a number of GCPs over the SOI toposheets. All the images were merged to get a single one. Various image enhancement techniques were applied to increase the visibility for visual interpretation.
Visual interpretation was carried out to study the digitally enhanced satellite image. This was carried out based on the various image characteristics such as shape, size, texture, pattern, tone, association, etc. Depending on these keys, various land use / cover classes were identified.
Ground truth verification was conducted for verifying the land uses classes and accordingly incorporated into the map. GPS was used for ground truth verification. The output of this work helped in developing an interpretation key.
False colour composite (FCC) was prepared using IRS LISS-III multi-spectral image to identify the land use classes. For better identification of the land use classes, IRS PAN data was merged into the IRS LISS-III data. The minimum level of accuracy was 85 to 90 percent. A database was created to store the satellite image data and the vector data of the base maps. All the vector layers were then imported into the vector segments of the database created and imported into separate layers. The IRS 1C PAN and LISS-III digital images were imported to the plan database.
The Base map of the planning area was updated for the features, obtainable from the satellite image. All the roads and linear features were updated using satellite image in the base map. Prominent buildings identified from the satellite image were transferred to the base map.