Each topic below explains the evidence, the business problem it creates, how GLOBEIR solves it, the benefits to your organisation, and how your data stays private and secure.
1. GIS-Based Decision Support for Departments
India's national planning platforms are now built around maps. The PM GatiShakti National Master Plan has onboarded 57 Central Ministries and Departments (8 infrastructure, 22 social and 27 economic and other) and 36 States and UTs, with about 1,700 data layers integrated, 969 of them contributed by States and UTs [4]. Every State and UT has a State Master Plan portal aligned to the national platform, and over 533 projects had been mapped by States on it by October 2024 [5]. A District Master Plan portal is being developed with BISAG-N for planning by State and district authorities, and District Master Plans have been launched for 28 aspirational districts [5][4].
The national platform also changes how projects are approved. Through the Network Planning Group, 293 infrastructure projects worth Rs 13.59 lakh crore had been evaluated by August 2025 for integrated planning, multimodality and last-mile connectivity [4]. At the base-map level, NIC's Bharat Maps brings together Survey of India topographic data, ISRO satellite imagery and village data into tiled map services at scales up to 1:4,000, delivered through OGC-standard services (such as WMS and WFS) so that e-governance applications can embed them instead of building their own base maps [6].
Business problem
Departments are expected to plan with each other on shared platforms, but much of their own data is still in spreadsheets, scanned registers or scheme portals that do not carry clean coordinates or standard boundary codes. That makes it hard to contribute layers to the State Master Plan, hard to answer simple questions such as which villages are more than a set distance from a health centre or school, and hard to see when two departments are about to dig up the same road.
Our solution
- An inventory of the department's datasets, with each record matched to standard State, district, block, gram panchayat and ward boundaries and a common ID.
- A WebGIS portal with base maps, thematic layers and analysis tools such as buffers, overlays, coverage gaps and travel-time catchments.
- Layers published as OGC services so they can be consumed by other departments and by State planning portals, in line with how Bharat Maps serves e-governance applications [6].
- Village and ward-level reference layers built through digital micro mapping, so planning works below the district level.
- Training for planning staff and simple update rules, so the layers stay current after handover.
Benefits
- Planning on one shared map, the approach PM GatiShakti has institutionalised for 57 ministries and 36 States and UTs (industry example) [4].
- Departmental layers that can be contributed to State Master Plan and District Master Plan portals [5].
- Faster answers to coverage and gap questions that take days with spreadsheets.
- Fewer clashes between departmental works through visible, shared project locations.
Privacy & data security
- Infrastructure and facility layers are mostly non-personal, but some, such as critical installations, may fall under the sensitive attributes that DST guidelines allow to be regulated, so each layer's sharing level is agreed with the department [20].
- High-accuracy geospatial data finer than the DST threshold is stored and processed in India, on government or India-hosted infrastructure [20][21].
- Published services carry role-based access, and layers meant for public portals are reviewed before release.
2. Scheme Asset Geotagging and Monitoring
Geotagging has become the standard evidence for rural schemes. Geotagging of rural employment assets began in September 2016 under an MoU between the Ministry of Rural Development and ISRO's NRSC; about 30 lakh assets were being created every year, and one crore were geotagged and placed in the public domain within seven months [3]. By end-2025 the GeoMGNREGA app had geotagged 6.44 crore assets at the "before", "during" and "after" stages, worker attendance was being captured with geotagged, time-stamped photographs twice a day through the NMMS app, and officials had recorded geotagged inspections of 16,67,847 worksites in 2025-26 up to November through the Area Officer app [1].
The framework is being strengthened. The VB-G RAM G Act, 2025, which replaced MGNREGA from 1 July 2026, provides for geo-tagging of assets, real-time dashboards, mobile-based monitoring and geo-referencing, along with biometric authentication and social audits [22]. Its backgrounder describes GPS and mobile-based monitoring of works in real time and Viksit Gram Panchayat Plans that are spatially integrated with PM GatiShakti [2]. In rural housing, the Awaas+ 2024 app captures time-stamped, geotagged photos of the existing house and the proposed site, and works offline [10], while AwaasSoft tracks registrations, sanctions, completions and instalments [1].
Business problem
Schemes now generate crores of geotagged photos, but storing photos is not the same as verifying work. Block and district officers still need to know which captures are far from the sanctioned site, which photos are reused, which stages are missing, and which assets have not changed on the ground. With staff stretched across many villages, inspections are often spread evenly rather than sent where the evidence is weakest, and instalments or closures wait.
Our solution
- Scheme-specific, stage-wise forms in the My GLOBEIR app with GPS and time-stamped photo capture, offline sync and checklists that match the department's guidelines.
- Automatic checks of each capture against the sanctioned location, earlier stages and nearby assets, flagging distant captures, duplicates and missing stages.
- A review map for block and district officers that turns exceptions into a targeted inspection list, with live tracking of inspection teams where the department chooses to use it.
- Satellite and drone change checks for works such as ponds, plantations and roads, using remote sensing.
- Verified status pushed back to the department's MIS or administration monitoring dashboard.
Benefits
- Remote verification at scale, as GeoMGNREGA has shown with 6.44 crore geotagged assets (industry example) [1].
- Inspections focused on flagged exceptions, so field staff spend less time on works that are already well evidenced.
- Faster stage verification for instalment release in housing schemes that depend on geotagged photos [10].
- A ready base for the geo-tagging, real-time dashboard and mobile monitoring provisions of the new rural employment framework [22].
Privacy & data security
- Photos of individual houses and worksites, worker attendance and beneficiary details are personal data under the DPDP Act when linked to an identifiable person [16].
- Beneficiary identifiers are masked or pseudonymised in analysis and dashboards, and only authorised roles see named records.
- Location capture in the My GLOBEIR app is limited to work purposes; background tracking of staff is optional and opt-in with a persistent notification.
3. Land Records Modernisation (DILRMP, Bhu-Aadhaar, SVAMITVA)
Land administration is moving from digitised text records to integrated, parcel-level GIS. By October 2024, around 95 per cent of rural land records covering over 6.26 lakh villages had been computerised, cadastral map digitisation stood at 68.02 per cent, and 168 districts in 16 States had reached "Platinum Grading" for completing over 99 per cent of core components [7]. The Unique Land Parcel Identification Number, or Bhu-Aadhaar, is a 14-digit code for each parcel based on its geo-coordinates, implemented in 29 States and UTs [7]. In September 2026 the Ministry of Rural Development launched DILRMP 3.0 (2026-2031, Rs 565.50 crore), reporting that 99.90 per cent of Records of Rights and 97 per cent of cadastral maps had been digitised; the new phase will build a GIS-enabled Land Stack integrating georeferenced cadastral maps, Records of Rights, registrations and court matters through APIs, give every parcel a Bhu-Aadhaar, and accelerate the NAKSHA pilot for GIS-based urban land records [8].
For inhabited rural areas, SVAMITVA uses drone surveys by Survey of India, supported by a network of Continuously Operating Reference Stations for accurate georeferencing. By April 2025, drone surveys were complete in 3.20 lakh villages covering 68,122 sq km, and over 2.42 crore property cards had been created for 1.61 lakh villages [9]. The scheme's stated objectives include reducing disputes, enabling bank credit against property, determining property tax for gram panchayats, and creating GIS maps that any department can use for planning, including Gram Panchayat Development Plans [9].
Business problem
Revenue departments must now link text records, maps and registration data that were digitised separately and often disagree on area, boundary or ownership. Old cadastral sheets need georeferencing before they can sit on a common map, parcel IDs must be assigned without duplicates, and other departments want to use land data for acquisition, planning and relief without being given unrestricted access to ownership records.
Our solution
- Georeferencing of scanned cadastral and village maps using ground control points and high-resolution imagery, through GIS mapping and cartography.
- Linking of parcels to Records of Rights, with automated flags for area and boundary mismatches for revenue staff to resolve.
- Quality checks to support Bhu-Aadhaar assignment, such as overlaps, gaps and duplicate parcels.
- Use of SVAMITVA drone maps and property records, where available, as the base for village-level planning layers and digital micro mapping.
- Access-controlled map services and APIs so other departments can query parcel layers within agreed limits, in line with the Land Stack approach [8].
Benefits
- A parcel layer that matches the text record, the foundation DILRMP 3.0 sets for State Land Stacks (industry example) [8].
- Faster mutation, registration and due diligence when map and record agree.
- Rural property records that support credit, dispute resolution and gram panchayat property tax, as SVAMITVA intends (industry example) [9].
- Shared land data for planning and relief without duplicating surveys.
Privacy & data security
- Ownership records linked to parcels identify individuals and are personal data under the DPDP Act; erasure and purpose rules apply unless law requires retention [16].
- Parcel geometry and ownership attributes are separated in services, so other departments can see parcels without seeing names unless authorised.
- High-accuracy cadastral and drone data is stored and processed in India, on government cloud, State data centre or on-premise infrastructure [20][21].
4. Property Tax and Municipal GIS
Property tax is the main own-source revenue for most cities, yet the World Bank reports that India collects about 0.2 per cent of GDP from it, roughly one-sixth of the OECD average of about 1.1 per cent [11]. Incomplete registers are a major cause: the Second Administrative Reforms Commission estimated that only about 60 to 70 per cent of urban properties were assessed, and a World Bank-commissioned study of three municipalities in Madhya Pradesh found that 25 to 30 per cent of properties were not registered [11]. The 15th Finance Commission made notification of property tax floor rates and improvement in collection an entry condition for local body grants [12].
GIS has a record of closing this gap. Visakhapatnam mapped 352,000 properties using GIS, a property survey and unique property IDs, added 50,000 new properties and 47,000 vacant plots to its register, and roughly doubled property tax from Rs 77 crore in 2010-11 to Rs 169 crore in 2013-14 [11]. Bengaluru mapped 1.6 million properties and added 100,000 to its roll [11]. The World Bank also notes the main weakness: after one-time GIS mapping under JnNURM, many cities did not keep data current, and it recommends linking GIS registers to cadastral maps and building permits [11].
Business problem
Municipal tax teams know their registers are incomplete but cannot easily see which buildings are missing, which have added floors or changed use, and which vacant plots are untaxed. One-time surveys go out of date within a few years, data sits in separate tax, water and building permission systems, and the grant conditions on collection growth make the gap more pressing.
Our solution
- Building footprint extraction from satellite or drone imagery, using AI and machine learning, with a unique property ID for each structure.
- Door-to-door verification of use, floors and built-up area through the My GLOBEIR app, with geotagged photos.
- Matching of survey records with the tax register to flag unassessed and under-assessed properties for the tax department to review.
- Periodic change detection and linkage with building permissions to keep the register current, addressing the update gap the World Bank identifies [11].
- A municipal WebGIS base that also serves water, sanitation, ward planning and heatmap analysis of collection by ward.
Benefits
- A more complete tax base; Visakhapatnam roughly doubled collections after GIS mapping (industry example) [11].
- Evidence to support the collection growth expected for Finance Commission grants [12].
- A register that stays current through change detection rather than another full survey.
- One property base shared across municipal departments.
Privacy & data security
- Owner names, contact details and tax dues are personal data and stay within the municipality's systems, with role-based access and audit logs [16].
- Imagery-based building analysis works on structures, not people; street-level and drone surveys follow DST guidelines and avoid restricted premises [20].
- Survey photos are captured for assessment only and are not used for any other purpose.
5. Citizen Services and Grievance Mapping
Grievance redress has become a large digital workload. CPGRAMS connects all Central Ministries, Departments, States and UTs; grievances handled each year rose from about 3.01 lakh in 2014 to around 27 lakh in 2024, and the number of grievance officers rose to more than 1.11 lakh by 2025 [13]. Citizens can file through the portal, the mobile app, UMANG or over 5 lakh Common Service Centres, and the system maps the last-mile grievance officer to auto-route complaints [13]. Guidelines issued in August 2024 cut the resolution timeline from 30 to 21 days and require dedicated grievance cells and root cause analysis; average disposal time fell from 157 days in 2014 to 15 days in 2025 [13].
Location is central to many grievances, about roads, water, drainage, power or local offices. For matters relating to States and districts, CPGRAMS marks grievances to State nodal officers and maintains pendency State-wise [14]. Mapping complaints by ward, village or asset turns a list into a picture of where problems recur.
Business problem
Departments are measured on disposal time, but closing individual complaints does not stop the next one from the same broken pipeline or road. Without location, repeat complaints are not recognised as a cluster, field teams are dispatched without context, and root cause analysis, now expected under the 2024 guidelines [13], is hard to do.
Our solution
- Geocoding of grievance and service request records to ward, village, landmark or asset, using address cleaning and the department's own asset layers.
- Heatmaps and cluster views by category, age and status, with drill-down to individual cases for authorised staff.
- Links from clusters to the responsible asset, department or contractor, and field tasks issued through the My GLOBEIR app.
- Access analysis that maps offices, camps and service centres against population to show where citizens travel far for services.
- Monthly reports of recurring locations and root causes for review meetings, built with geospatial data science.
Benefits
- Recurring problem locations become visible, supporting the root cause analysis the 2024 guidelines require (industry example) [13].
- Field teams arrive with context about nearby complaints and assets.
- Better placement of camps and service points where access is weakest.
- Clear evidence for review meetings on where action has, and has not, reduced complaints.
Privacy & data security
- Complainants' names, contacts and addresses are personal data; public and management views show aggregated clusters, never individual complainants [16].
- Free-text complaints are screened, and personal details are masked before analysis where possible.
- Breach and incident handling follows CERT-In reporting timelines and DPDP breach obligations [18][17].
6. District Dashboards and Administration Monitoring
District administrations are increasingly reviewed on data. The Aspirational Districts Programme, launched by NITI Aayog in 2018 for 112 districts, tracks progress through a real-time, public Champions of Change dashboard that scores districts on 49 indicators across health and nutrition, education, agriculture and water resources, financial inclusion and skill development, and infrastructure, using "delta ranking" to reward improvement [15]. DISHA committees chaired by Members of Parliament operate in 776 districts, supported by a dashboard of 100 schemes from 35 ministries with progress down to village level [1].
These systems show which districts are improving. District collectors and programme units still need views below the district, by block, gram panchayat and ward, that combine scheme progress with field inspection and follow-up.
Business problem
A district team may review dozens of schemes each month from separate portals, each with its own format and lag. Lagging villages are lost inside block totals, review decisions are noted in minutes rather than tracked, and there is no single view that shows where indicators, inspections and grievances all point to the same problem.
Our solution
- Administration monitoring dashboards with indicators chosen by the district, mapped by block, gram panchayat and ward.
- Integration of MIS exports, field app data and departmental sheets, with data quality flags where sources disagree.
- Village and ward reference layers from digital micro mapping, so indicators can be seen at the level where action happens.
- Logging of review decisions and assigned actions, with status tracked on the same map.
- Optional field inspection workflows through the My GLOBEIR app and live tracking of inspection teams.
Benefits
- Lagging areas visible below the district, complementing the district-level ranking of the Champions of Change dashboard (industry example) [15].
- One view across schemes for DISHA and district review meetings [1].
- Follow-up on review decisions that can be tracked rather than re-discussed.
- Less time spent compiling reports before each review.
Privacy & data security
- Dashboards show aggregated indicators by area; individual beneficiary data stays in scheme systems and is accessed only by authorised roles.
- Indicators relating to health or nutrition are shown only as area-level aggregates.
- Access is role-based by district, block and department, with audit logs of who viewed and exported data.