The Digital Crop Survey is India’s season-by-season record of which crop is sown on each farm plot, captured from the field through a mobile interface. Geographic Information System (GIS) technology makes this possible by linking every crop record to a plot on a geo-referenced village map, so that crop area can be counted plot by plot across the country.
Introduction: Why India Is Recording Crops Plot by Plot
Knowing what is growing where is basic to almost every farm decision a government makes. Crop area shapes production estimates, procurement planning, crop insurance, and the timing of support to farmers. For a long time, much of this information came from manual records and estimates that took time to compile. The Digital Crop Survey changes the starting point. According to a Lok Sabha reply, the survey collects crop-sown details through a mobile interface, so data is captured directly from the field and gives crop area information for every agricultural plot. In Rabi 2025-26 alone, it covered 648 districts and more than 31.3 crore plots.
What Is the Digital Crop Survey?
The Digital Crop Survey (DCS) is a mobile-based ground survey that records the crop sown on each farm plot every season. Surveyors capture crop-sown details through a mobile interface, so the record comes straight from the field. The result is a plot-level database of crop area that supports more accurate production estimates. The survey builds the Crop Sown Registry, one of the three registries under AgriStack. A pilot was conducted in 11 states in 2023-24, with targets of 400 districts in FY 2024-25 and all districts in FY 2025-26. The survey is designed around data protection as well as accuracy. According to the Ministry of Agriculture and Farmers Welfare, AgriStack has been developed in line with the Digital Personal Data Protection Act, 2023, and other IT laws.
AgriStack and the Digital Agriculture Mission: Three Registries and One Farmer ID
On 2 September 2024, the Union Cabinet approved the Digital Agriculture Mission with an outlay of ₹2,817 crore, including a central share of ₹1,940 crore. The mission builds digital public infrastructure for agriculture, with AgriStack at its center. AgriStack consists of three foundational registries, all created and maintained by State Governments and Union Territories:
- Farmers’ Registry: A record of farmers, each given a digital identity called a Farmer ID.
- Geo-referenced village maps: Village land maps tied to real-world coordinates, so each plot has a known location.
- Crop Sown Registry: The season-wise record of crops sown on each plot, built through the Digital Crop Survey.
The Farmer ID is described as a digital identity similar to Aadhaar, a trusted “Kisan ki Pehchaan.” According to a PIB factsheet, more than 10.31 crore Farmer IDs had been created across the country as of 3 August 2026. The mission also includes the Krishi Decision Support System (Krishi DSS). A Lok Sabha reply describes it as a geospatial platform that integrates satellite imagery, weather, soil, and crop data using GIS to support agricultural planning and decision-making.
How the Digital Crop Survey Uses GIS: From Geo-Referenced Village Maps to the Crop Sown Registry
The survey works only because each crop record has a place on a map. GIS connects the village map, the plot, and the crop into one record.
The Village Map as the Base Layer
A plot can carry a crop record only once its village map is geo-referenced, meaning the map is tied to real coordinates on the ground. Many village maps were first drawn on paper and do not line up with satellite imagery or GPS readings. Geo-referencing fixes each plot boundary to its true position, so a surveyor standing in a field can find the right plot on the map. This makes the geo-referenced village map the foundation of the whole registry.
Linking the Plot to the Crop
During each season, the crop sown on a plot is recorded against that plot on the map. Because every record has a location, crop area can be added up for a village, a district, or a state without re-entering data. The same records can also be filtered by crop, so officials can see, for example, how much area is under paddy in one block. This removes the delay of collecting village totals and adding them up by hand.
Building the Registry Season by Season
Each Kharif and Rabi season adds a new layer of plot-level records. Over time, this shows how cropping patterns change on the same land, such as a shift from one crop to another or land left fallow. These patterns help planners see where demand for water, seeds, and procurement may rise or fall.
Scale Over Four Seasons
The survey has grown quickly. The Lok Sabha reply of 21 July 2026 gives the season-wise coverage below.
| Season | Districts | Plots Surveyed |
| Kharif 2024-25 | 434 | 18,02,55,171 |
| Rabi 2024-25 | 492 | 25,23,06,949 |
| Kharif 2025-26 | 604 | 28,53,88,878 |
| Rabi 2025-26 | 648 | 31,40,04,270 |
In under two years, coverage grew from 434 districts to 648, and the number of plots surveyed in a season rose from about 18 crore to more than 31 crore. Each of these plots is a point that can be mapped, counted, and compared with the next season.
From Crop Records to Decisions: Crop Estimation, Insurance, and Krishi DSS
A plot-level crop record becomes far more useful when it is combined with other data.
Area Times Yield
Crop production is crop area multiplied by yield. While the Digital Crop Survey provides crop sown area in near real time, DGCES provides crop yield data for production estimates, and digitized crop cutting experiments were conducted in 43,105 villages during 2025-26. Both datasets work best when they share the same plot geography. If area and yield are measured for different units, production estimates can be off even when each number is correct on its own.
Insurance and Benefits
Plot-level crop records and Farmer IDs give a clearer basis for confirming what was sown and by whom. When a farmer applies for crop insurance or support, the claim can be checked against the crop recorded on that plot that season. This can help schemes reach the right person for the right plot and reduce disputes over what was grown.
Krishi DSS and Other Layers
Krishi DSS brings satellite imagery, weather, soil, and crop data together using GIS. Plot records from the survey can sit alongside these layers, so a dry spell or a pest outbreak can be linked to the crops actually growing in the affected area. Soil data is growing too, with the Soil and Land Use Survey of India mapping soils at village level on a 1:10,000 scale. As of June 2026, a soil survey of 52.38 million hectares had been carried out.
Ground Truth for Satellites
Satellite imagery can classify crops over large areas, but it needs field records to train and check its results. Plot-level survey data can act as that ground truth. ArcGIS Image Server can manage and analyze satellite imagery over time, so field records and imagery can be compared on the same map. Where the two disagree, the difference points to plots worth checking on the ground.
How State Agencies Use GIS for Crop Management
State agencies already use GIS to manage crop data at scale. In Haryana, the Haryana Space Applications Centre (HARSAC) built a Crop Management Solution using Esri’s geospatial technology. A mobile app lets surveyors measure farmland areas, add attributes, and take pictures of crops using integrated GIS and GPS, with real-time data upload. Field surveys are carried out by students using the mobile app, which also builds their geospatial and GIS skills.
The GFasal Dashboard shows district-wise crop details, including crops surveyed, crop types, and village-level data. About 1.2 million farmers are registered on the common portal, and according to the case study, the state has saved approximately 300-400 crores.
The Crop Management Solution developed using Esri’s Geospatial Technology is enabling HARSAC to effectively govern the full lifecycle of agricultural production in the State of Haryana. By removing demand-supply gaps and minimizing errors in yield estimations and procurement predictions, it fosters a culture of sustainable agriculture, bringing about 300-400 crores worth of savings to the State.
Dr. Sultan Singh, Director, HARSAC
Other state teams can build similar workflows with ArcGIS tools. ArcGIS Survey123 can support structured field surveys with photos and locations. ArcGIS Dashboards can then show progress by district and village.
For analysis, ArcGIS Pro can compare crop records with soil, water, and imagery layers. Indo ArcGIS Living Atlas adds ready-to-use India layers such as village and district boundaries.
Agriculture departments can explore Agriculture solutions from Esri India, and central ministries can look at National Government solutions for digital agriculture planning.
Challenges and the Road Ahead
Small and Fragmented Holdings
Many Indian farms are small and split into several separate plots, sometimes in different parts of the village. Recording each plot every season multiplies the surveyor’s work, and small plots are harder to locate precisely on a map. A small error in position can place a crop record on a neighbor’s plot. Accurate base maps and tools that show the surveyor’s location on the map help reduce these mistakes.
Mixed Cropping on One Plot
Farmers often grow more than one crop on the same plot, such as pulses intercropped with cereals. Recording the share of each crop is harder than recording a single crop, and different surveyors may judge it differently. These differences can affect area estimates when they are added up across districts. Clear rules for recording mixed crops, applied the same way everywhere, keep the numbers comparable.
Outdated Village Maps
The survey depends on geo-referenced village maps, but some maps are old or no longer match the ground. Plots get divided among heirs, sold, or merged, and the map may not show these changes. If the map is wrong, the crop record sits on the wrong plot, and that error flows into every system that uses it. Updating maps is slow, but it is the step that makes every later record reliable.
Surveyor Workload and Connectivity
The survey must be completed within a short window after sowing, when crops can be clearly seen in the field. With crores of plots to cover each season, every surveyor has a large number of plots to visit in a few weeks. Weak mobile networks in some villages can also delay uploads and slow the work. Offline data capture and well-planned survey routes can help teams finish on time.
The Digital Crop Survey gives India something it has long needed: a plot-level record of what farmers grow, season after season. When that record sits on a geo-referenced map and links to Farmer IDs, yield data, and satellite layers, decisions on support, insurance, and procurement can rest on what is actually in the field. For farmers, that can mean faster and fairer help when it matters most.
FAQs
1.What is the Digital Crop Survey in India?
The Digital Crop Survey is a mobile-based survey that records the crop sown on each farm plot every season. It builds the Crop Sown Registry under AgriStack.
2.How is the Digital Crop Survey conducted?
Crop-sown details are collected through a mobile interface, so data is captured directly from the field. Each record is linked to a plot on a geo-referenced village map.
3.What is AgriStack and what are its three registries?
AgriStack is the digital public infrastructure for agriculture under the Digital Agriculture Mission. Its three registries are the Farmers’ Registry, geo-referenced village maps, and the Crop Sown Registry.
4.What is the difference between the Digital Crop Survey and DGCES?
The Digital Crop Survey records how much area is sown with each crop. DGCES provides crop yield data, and the two together support production estimates.
5.How does GIS help with crop surveys and crop area estimation?
GIS links each crop record to a mapped plot, so crop area can be added up for any village, district, or state. It also lets plot records be compared with satellite imagery, soil, and weather data.
Written by
Esri India Marketing
