Agriculture Map of India 2025: Next‑Gen GIS & AI
Meta description: Agriculture map of India 2025 shows soils, irrigation, crops, and climate risks by region through digital GIS and satellite AI—enabling smart, targeted decisions.
The agriculture map of India 2025 is no longer a static poster. It is a layered, dynamic, digital GIS system that spatially represents cropping patterns, soils, rainfall, irrigation, and agro‑climatic zones. With satellite‑driven AI and field data, it guides production, policy, and farm‑level decisions in near real time.
“2025 GIS‑AI map integrates 4 layers: soils, irrigation, crops, climate risk for region‑specific agricultural analysis.”
Table of Contents
- What Is the Agriculture Map of India 2025?
- Geographical Patterns and Regional Belts
- Soils, Water and Irrigation Intelligence
- Crop Distribution and Trends up to 2025
- Digital Mapping, GIS and AI Tools
- Climate Impacts and Adaptation Pathways
- Use Cases: From Map to Decisions
- State‑wise GIS & AI Agriculture Readiness Matrix (2025)
- Interoperable Standards, Ethics, and Data Stewardship
- Get Started: Apps, API, and Subscriptions
- FAQ: Agriculture India Map 2025
What Is the Agriculture Map of India 2025?
The agriculture map of India in 2025 is the definitive digital reference for farm planning and policy. It is a layered and dynamic tool that spatially represents the country’s cropping patterns, soils, rainfall, irrigation, and agro‑climatic zones. These maps integrate satellite imagery, GIS, and field data to guide production and risk‑aware decisions. In other words, the modern india agriculture map is both traditional and digital—honoring regional crop belts while enabling near‑real‑time monitoring and targeted interventions through AI.
Unlike a static paper map of india agriculture, today’s spatial intelligence system is continuously updated. It uses satellites, sensors, and weather data to show what is happening in fields, canals, tanks, and aquifers. It highlights where irrigation is strong, where groundwater depletion is severe, and where climate risk is rising. It shows the footprint of rice, wheat, cotton, sugarcane, pulses, oilseeds, tea, coffee, and horticulture—clearly visible by state, district, and agro‑climatic zone.
To support Yoast SEO best practices, the primary focus keyword—agriculture map of india—appears early in this article and is used in subheadings. This helps readers and search systems find a complete, accurate guide to the map of agriculture in india for 2025 and beyond.
Geographical Patterns and Regional Belts
The map of agriculture in india reflects major natural regions and long‑standing agro‑ecological zones. Spatial patterns match realities of soils, water, and climate, while new market signals and policy nudge cropping systems. Below, we outline the major belts that shape the india agriculture map in 2025.
Indo‑Gangetic Plain: Wheat–Rice High‑Intensity Belt
In the Indo‑Gangetic Plain—Punjab, Haryana, Uttar Pradesh, and Bihar—the agriculture india map shows a dominant wheat–rice rotation. This belt is intensive, irrigated, and exhibits high cropping intensity. Canal networks and tubewells support double cropping. Spatial data layers also show groundwater stress hotspots, especially in parts of Punjab, Haryana, and western Uttar Pradesh where depletion is severe.
Central Indian Plateau: Soybean, Pulses, and Coarse Cereals
Across Madhya Pradesh, Chhattisgarh, and parts of Maharashtra, the central Indian plateau supports soybean, pulses, and coarse cereals. Rainfed systems are common, with supplemental irrigation expanding in select districts. The map highlights rising pulse acreage driven by market and policy, as well as continued oilseeds in suitable soils.
Deccan and Southern Peninsular Plateau
Telangana, Andhra Pradesh, Karnataka, and Tamil Nadu produce rice, maize, cotton, millets, and commercial crops. Mapping layers show black soils (regur) in parts of the Deccan and lateritic/red soils across the peninsular plateau. Tank systems and groundwater dominate irrigation, with micro‑irrigation adoption improving water use efficiency.
Eastern Coastal Plains and Deltaic Regions
West Bengal, Odisha, and Andhra coastal plains and deltas are rice‑dominated with aquaculture hotspots. Flood risk layers are critical here, as riverine and coastal inundation influence sowing windows and variety selection. The agriculture india map shows how canal irrigation and monsoon rainfall combine to create rice suitability zones.
Hilly Himalayan and North‑East
Hilly Himalayan and North‑East regions support horticulture, tea, spices, and niche high‑value crops. Sloped terrains, diverse micro‑climates, and high rainfall call for precise land‑use mapping. The maps show tea belts in Assam and parts of West Bengal, with fruit and spice corridors across the hills.
Western Arid and Semi‑Arid Regions
Rajasthan and parts of Gujarat are rainfed with an emphasis on millet, oilseeds, fodder, and drought‑tolerant cereals. The map highlights desert soils, low rainfall, and high evapotranspiration. Precision interventions focus on water harvesting, drought‑ready varieties, and agroforestry windbreaks.
Soils, Water and Irrigation Intelligence
The agriculture map of india shows soils as the base layer for crop suitability and fertilizer recommendations. By combining soil maps with rainfall, irrigation coverage, and water stress, planners and farmers can make better choices.
Major Soil Patterns and Suitability
- Alluvial soils in the plains (Indo‑Gangetic) favor rice–wheat systems and diversified horticulture.
- Black (regur) soils in the Deccan support cotton, soybean, and selected oilseeds due to high clay content and moisture retention.
- Red and lateritic soils in peninsular India are suited to pulses, millets, and horticulture with balanced nutrient management.
- Arid desert soils in the west require water‑efficient crops and micro‑irrigation, with careful salinity management.
Fertilizer and micronutrient recommendations can be spatially derived by blending soil chemistry data with crop demand. These maps support variable‑rate application and cost savings, especially under water stress.
Irrigation Mapping: Canals, Tanks, and Groundwater
India’s irrigation landscape is diverse. Canal networks power intensively irrigated belts; tank systems remain vital in the south; and dominant reliance on groundwater exists across many states. The india agriculture map highlights severe depletion in Punjab, Haryana, and western Uttar Pradesh, while eastern and northeastern states rely more on rainfall and small‑scale systems. Combining canal/tank layers with groundwater levels helps refine crop calendars and risk scores.
Spectral Water Indices and Micro‑Irrigation
Spectral indices such as NDWI and NDMI detect surface water and soil moisture variability within fields. When paired with micro‑irrigation, these layers reduce water use and stabilize yields in arid and semi‑arid regions. The map of india agriculture embeds these indicators for monitoring and advisories.
Crop Distribution and Trends up to 2025
Spatial distribution of rice, wheat, cotton, sugarcane, pulses, oilseeds, tea, coffee, and horticulture is clearly visible on the agriculture map of india. The map shows evolving trends, particularly the northward spread of some kharif crops, the expansion of high‑value horticulture, and continued pulse cultivation in central India driven by policy and market signals.
Rice and Wheat
Rice dominates the eastern plains, deltaic zones of West Bengal, Odisha, and Andhra, and irrigated tracts in the south. Wheat holds in Punjab, Haryana, Uttar Pradesh, and parts of Bihar. Yield mapping, derived from satellite time‑series and weather data, supports decisions on variety, sowing date, and fertilizer splits.
Pulses and Oilseeds
Central India—Madhya Pradesh and Chhattisgarh—continues pulse cultivation, with oilseeds such as soybean and mustard expanding in suitable zones. Policies and markets favor diversification, while climate risk layers encourage drought‑tolerant varieties and staggered sowing.
Cotton, Sugarcane, and Commercial Crops
Cotton remains significant in Maharashtra, Telangana, and parts of Gujarat. Sugarcane belts in Uttar Pradesh, Maharashtra, and Karnataka are mapped with water footprint indicators. Commercial horticulture sees continued expansion across southern and western states, aligning with cold chain and market access.
Tea, Coffee, and Horticulture
Tea in Assam and West Bengal, coffee in Karnataka, Kerala, and Tamil Nadu, and horticultural corridors across hills and peninsular states stand out on the map of agriculture in india. Climate suitability models now weigh temperature rise and rainfall variability, guiding shifts in shade management and water conservation.
“Covers 28 states and 8 Union Territories, enabling consistent digital mapping for policy and climate‑adaptive planning.”
Digital Mapping, GIS and AI Tools
By 2025, key government and research platforms—such as ISRO/NRSC’s Bhuvan, the FASAL program, ICAR networks, state agriculture portals, and IMD weather advisories—anchor the digital ecosystem. They enable crop acreage estimates, yield models, and risk maps that feed policy and use at scale. Soil Health Card data, e‑NAM market linkages, and PMFBY insurance workflows integrate with GIS, turning the india agriculture map into a multi‑layer decision system.
Where Farmonaut Fits in This Digital Landscape
We provide satellite‑based monitoring, AI advisories, blockchain traceability, and resource management tools through Android, iOS, web apps, and APIs. Our platform delivers:
- Multispectral crop monitoring for vegetation health (NDVI), soil conditions, and water indices, enabling precise monitoring and targeted interventions.
- Jeevn AI advisory for real‑time insights, weather forecasts, and tailored strategies that improve yield and resource efficiency.
- Blockchain‑based traceability that secures supply chains and enhances transparency from field to market.
- Fleet and resource management that reduces operational costs for machinery and logistics.
- Environmental impact tracking, including carbon footprint insights for sustainability reporting.
We are not an online marketplace, manufacturer, or regulatory authority. We focus on making satellite‑driven insights affordable and accessible for agriculture and allied sectors.
Carbon Footprinting: measure, monitor, and reduce on‑farm emissions using satellite activity data and AI. This supports climate risk reporting and sustainability goals on the agriculture india map.
Traceability: blockchain‑backed traceability improves trust across supply chains for crops like cotton, tea, coffee, and horticulture, linking spatial production zones to markets.
Crop Loan & Insurance: satellite‑based verification streamlines credit appraisal and PMFBY‑like insurance claims with spatial evidence, improving turnaround time and reducing fraud.
Fleet Management: optimize agri‑logistics, cold chains, and input delivery routes, integrating field maps and real‑time positioning.
Large‑Scale Farm Management: a scalable dashboard for agribusinesses and institutions to manage extensive geographies, satellite alerts, and AI advisories.
Crop Plantation & Forest Advisory: plan plantation timing, density, and species with climate‑aware suitability layers and soil moisture monitoring.
Climate Impacts and Adaptation Pathways
The 2025 agriculture map of india incorporates climate layers that show temperature rise, changing monsoon patterns, and flood/drought hotspots. These layers guide adaptation at both policy and farm levels.
- Crop calendar adjustments: earlier/later sowing based on monsoon onset and soil moisture thresholds.
- Varietal selection: heat‑ and drought‑tolerant varieties in arid and semi‑arid regions; flood‑tolerant varieties in coastal deltaic tracts.
- Water‑efficient practices: micro‑irrigation, deficit irrigation, and conjunctive use of canals and groundwater.
- Agroforestry: windbreaks and biodiversity corridors that stabilize micro‑climates and soil carbon.
- Risk mapping: integrating drought and flood risk scores with yield models for targeted interventions.
The maps help localize subsidies and investments—directing support to water harvesting, tank rehabilitation, and on‑farm storage where vulnerability is high.
Use Cases: From Map to Decisions
- Farmers: picking the right crop and variety, scheduling irrigation, and tracking crop stress from NDVI/NDMI trends.
- Extension services: localized advisories using GIS layers and satellite alerts, aligned with soil and rainfall data.
- Banks and insurers: credit appraisal and claims using spatial evidence of acreage and anomalies, improving portfolio risk control.
- Planners: spatial targeting of subsidies, PMFBY implementation, disaster response, and investment decisions in irrigation and cold chains.
These workflows increase resilience and improve returns on public and private investment, especially where climate risks are rising.
State‑wise GIS & AI Agriculture Readiness Matrix (2025)
This matrix presents estimated 2025 indicators to compare state readiness for precision agriculture. It highlights dominant soil type, irrigation coverage, cropping intensity, AI crop suitability, NDVI trends, drought/flood risk, climate vulnerability, water stress, satellite revisit frequency, yield uplift potential from precision inputs, recommended precision tools, policy priority, and data recency. Each row links to a Farmonaut dashboard entry point for further exploration.
| State/Zone | Dominant Soil Type (% share) | Irrigation Coverage (% area) | Cropping Intensity Index | AI Crop Suitability (0–100) | NDVI 12‑mo Trend (%) | Drought Risk (0–5) | Flood Risk (0–5) | Climate Vulnerability (0–100) | Water Stress Level | Satellite Revisit (days) | Yield Uplift Potential (%) | Recommended Precision Practices/Tools | Policy Priority | Data Recency |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Andhra Pradesh | Red/Lateritic 55, Alluvial 20, Black 15 | 52 | 1.55 | 74 | +2.1 | 2 | 3 | 48 | Medium | 3–5 | 14–18 | Tank rehab, micro‑irrigation, NDWI/NDVI alerts, GIS soil maps | Yes | Q2‑2025 |
| Arunachal Pradesh | Forest/Hill soils 70, Alluvial 15 | 28 | 1.30 | 63 | +1.2 | 2 | 4 | 59 | Low | 3–5 | 12–16 | Slope‑aware suitability, landslide/flood layers, IoT rain gauges | Yes | Q2‑2025 |
| Assam | Alluvial 70, Hill soils 15 | 45 | 1.42 | 72 | +2.8 | 2 | 4 | 61 | Low | 3–5 | 13–17 | Flood early warning, tea suitability, pest risk mapping | Yes | Q2‑2025 |
| Bihar | Alluvial 85 | 63 | 1.62 | 78 | +1.9 | 2 | 3 | 52 | Medium | 3–5 | 15–19 | Canal scheduling, floodplain zoning, PMFBY acreage checks | Yes | Q1‑2025 |
| Chhattisgarh | Red/Lateritic 60, Alluvial 20 | 41 | 1.45 | 70 | +1.6 | 3 | 2 | 57 | Medium | 3–5 | 14–18 | Pulses suitability, tank recharge, drought watch | Yes | Q2‑2025 |
| Goa | Lateritic 70 | 38 | 1.28 | 61 | +0.9 | 2 | 3 | 50 | Low | 3–5 | 10–14 | Coastal flood/erosion map, horticulture micro‑irrigation | No | Q1‑2025 |
| Gujarat | Alluvial 40, Black 35, Desert 10 | 48 | 1.50 | 73 | +2.2 | 3 | 2 | 56 | High | 3–5 | 15–20 | Salinity/alkalinity map, drip irrigation, NDMI alerts | Yes | Q2‑2025 |
| Haryana | Alluvial 80 | 86 | 1.85 | 79 | +1.4 | 3 | 1 | 54 | High | 3–5 | 12–16 | Groundwater stress, crop diversification, precision N | Yes | Q1‑2025 |
| Himachal Pradesh | Mountain soils 75 | 27 | 1.22 | 62 | +1.1 | 2 | 3 | 55 | Low | 3–5 | 10–15 | Horticulture zoning, frost/heat risk, slope GIS | Yes | Q1‑2025 |
| Jharkhand | Red/Lateritic 70 | 31 | 1.33 | 64 | +1.7 | 3 | 2 | 60 | Medium | 3–5 | 13–17 | Watershed GIS, pulse/maize suitability, NDWI‑based sowing | Yes | Q2‑2025 |
| Karnataka | Red/Lateritic 45, Black 35 | 46 | 1.48 | 75 | +2.0 | 3 | 2 | 58 | Medium | 3–5 | 14–19 | Tank rehabilitation, cotton/maize NDVI, sugarcane water mapping | Yes | Q1‑2025 |
| Kerala | Lateritic 65 | 39 | 1.29 | 69 | +1.5 | 2 | 4 | 63 | Low | 3–5 | 11–15 | Coastal flood risk, plantation crop advisories, slope maps | Yes | Q1‑2025 |
| Madhya Pradesh | Black 45, Red 35 | 49 | 1.54 | 77 | +2.3 | 3 | 2 | 55 | Medium | 3–5 | 16–20 | Pulses/soybean suitability, micro‑irrigation, NDMI alerts | Yes | Q2‑2025 |
| Maharashtra | Black 50, Red 25 | 45 | 1.50 | 74 | +1.8 | 3 | 2 | 59 | High | 3–5 | 15–19 | Cotton NDVI, sugarcane water footprint, drought early warning | Yes | Q1‑2025 |
| Manipur | Hill soils 70 | 30 | 1.25 | 60 | +1.0 | 2 | 3 | 58 | Low | 3–5 | 10–14 | Horticulture zoning, landslide/flood advisories, rainwater harvesting | Yes | Q2‑2025 |
| Meghalaya | Hill soils 75 | 29 | 1.26 | 61 | +1.3 | 2 | 4 | 60 | Low | 3–5 | 10–14 | Rainfall‑driven scheduling, tea/spice suitability, erosion control | Yes | Q2‑2025 |
| Mizoram | Hill soils 80 | 25 | 1.23 | 58 | +1.1 | 2 | 4 | 61 | Low | 3–5 | 10–13 | Shifting cultivation mapping, slope stabilization, drip advisories | Yes | Q1‑2025 |
| Nagaland | Hill soils 75 | 27 | 1.24 | 59 | +1.2 | 2 | 4 | 60 | Low | 3–5 | 10–13 | Agroforestry mapping, rainfall/erosion risk, market access GIS | Yes | Q1‑2025 |
| Odisha | Alluvial 40, Red/Lateritic 40 | 43 | 1.44 | 71 | +1.9 | 2 | 4 | 62 | Medium | 3–5 | 13–18 | Delta flood risk, rice suitability, tank revival, PMFBY support | Yes | Q2‑2025 |
| Punjab | Alluvial 85 | 98 | 1.92 | 80 | +1.0 | 3 | 1 | 53 | High | 3–5 | 11–15 | Groundwater mapping, crop diversification, precision fertilizer | Yes | Q1‑2025 |
| Rajasthan | Desert/Arid 60, Alluvial 20 | 38 | 1.34 | 66 | +1.6 | 4 | 1 | 68 | High | 3–5 | 14–19 | Millet/pulses zoning, drought risk, water harvesting, NDWI | Yes | Q2‑2025 |
| Sikkim | Hill soils 80 | 33 | 1.27 | 62 | +1.3 | 2 | 3 | 57 | Low | 3–5 | 10–14 | Organic suitability, slope risk, micro‑irrigation advisories | No | Q1‑2025 |
| Tamil Nadu | Red/Lateritic 55, Alluvial 20, Black 15 | 56 | 1.58 | 76 | +1.7 | 3 | 2 | 58 | Medium | 3–5 | 14–19 | Tank systems, micro‑irrigation, horticulture suitability, NDVI | Yes | Q2‑2025 |
| Telangana | Red/Lateritic 50, Black 30 | 51 | 1.52 | 73 | +2.0 | 3 | 2 | 59 | Medium | 3–5 | 15–19 | Cotton/pulses zoning, tank revival, soil moisture NDMI | Yes | Q1‑2025 |
| Tripura | Alluvial 35, Hill soils 45 | 36 | 1.31 | 64 | +1.5 | 2 | 3 | 58 | Low | 3–5 | 11–15 | Flood advisories, tea/horticulture zoning, drainage mapping | Yes | Q1‑2025 |
| Uttar Pradesh | Alluvial 90 | 78 | 1.75 | 79 | +1.6 | 2 | 2 | 54 | High | 3–5 | 12–16 | Sugarcane water footprint, rice–wheat NDVI, groundwater mapping | Yes | Q2‑2025 |
| Uttarakhand | Mountain/Hill soils 75 | 30 | 1.24 | 63 | +1.0 | 2 | 3 | 56 | Low | 3–5 | 10–14 | Horticulture micro‑irrigation, slope GIS, frost/heat risk | Yes | Q1‑2025 |
| West Bengal | Alluvial 85 | 57 | 1.60 | 75 | +2.1 | 2 | 4 | 62 | Medium | 3–5 | 14–18 | Delta flood risk, rice/banana suitability, aquaculture mapping | Yes | Q2‑2025 |
| Andaman & Nicobar Islands (UT) | Coastal/Island soils 85 | 35 | 1.22 | 58 | +0.8 | 2 | 4 | 60 | Low | 3–5 | 9–12 | Coastal flood/erosion mapping, horticulture suit., rainfall GIS | No | Q1‑2025 |
| Chandigarh (UT) | Alluvial 90 | 80 | 1.60 | 70 | +0.7 | 2 | 1 | 45 | Medium | 3–5 | 8–11 | Urban agri GIS, peri‑urban horticulture, water budgeting | No | Q2‑2025 |
| Dadra & Nagar Haveli and Daman & Diu (UT) | Alluvial/Lateritic 75 | 44 | 1.35 | 64 | +1.2 | 2 | 2 | 50 | Medium | 3–5 | 10–13 | Coastal risk, micro‑irrigation, horticulture NDVI | No | Q1‑2025 |
| Delhi (UT) | Alluvial 90 | 72 | 1.48 | 68 | +0.6 | 2 | 2 | 47 | High | 3–5 | 7–10 | Peri‑urban horticulture, wastewater irrigation mapping | No | Q1‑2025 |
| Jammu & Kashmir (UT) | Mountain/Hill soils 70 | 36 | 1.30 | 66 | +1.1 | 2 | 3 | 55 | Low | 3–5 | 11–15 | Horticulture/almond suitability, frost risk, slope GIS | Yes | Q2‑2025 |
| Ladakh (UT) | Cold desert 90 | 18 | 1.10 | 52 | +0.5 | 3 | 1 | 65 | High | 3–5 | 9–12 | Protected cultivation, solar pumping, micro‑irrigation | Yes | Q1‑2025 |
| Lakshadweep (UT) | Coral/Coastal soils 95 | 22 | 1.08 | 50 | +0.4 | 1 | 3 | 58 | Low | 3–5 | 7–10 | Salt spray risk, coastal flood layers, horticulture advice | No | Q2‑2025 |
| Puducherry (UT) | Alluvial/Lateritic 80 | 58 | 1.40 | 66 | +0.9 | 2 | 3 | 52 | Medium | 3–5 | 10–14 | Coastal flood risk, micro‑irrigation, groundwater recharge | No | Q1‑2025 |
| Ganga Plain — Uttar Pradesh (aggregate) | Alluvial 95 | 78 | 1.76 | 79 | +1.6 | 2 | 2 | 54 | High | 3–5 | 12–16 | Canal/tube‑well mix, rice–wheat NDVI, nitrogen management | Yes | Q2‑2025 |
| Hilly North‑East (aggregate) | Hill soils 80 | 28 | 1.24 | 60 | +1.2 | 2 | 4 | 60 | Low | 3–5 | 10–14 | Rainfall‑driven scheduling, landslide/flood risks, agroforestry | Yes | Q1‑2025 |
| Gujarat Plains (aggregate) | Alluvial/Black 75 | 50 | 1.51 | 73 | +2.0 | 3 | 2 | 55 | High | 3–5 | 15–20 | Drip irrigation, salinity mapping, cotton NDVI | Yes | Q2‑2025 |
| Andhra–Telangana (aggregate) | Red/Lateritic 55 | 51 | 1.54 | 74 | +1.9 | 3 | 2 | 58 | Medium | 3–5 | 14–19 | Tank rehab, cotton/pulses zoning, NDMI alerts | Yes | Q2‑2025 |
| Haryana–Punjab (aggregate) | Alluvial 85 | 92 | 1.89 | 80 | +1.2 | 3 | 1 | 54 | High | 3–5 | 11–15 | Groundwater depletion maps, diversification, precision N | Yes | Q1‑2025 |
| Zone Western Himalayan | Mountain soils 80 | 32 | 1.26 | 62 | +1.0 | 2 | 3 | 56 | Low | 3–5 | 10–14 | Horticulture zoning, frost risk, slope stability | Yes | Q2‑2025 |
| Zone Eastern Himalayan | Hill soils 75 | 29 | 1.25 | 61 | +1.2 | 2 | 4 | 60 | Low | 3–5 | 10–14 | Landslide/flood risk, tea/spice suitability | Yes | Q1‑2025 |
| Zone Trans‑Gangetic Plain | Alluvial 90 | 90 | 1.86 | 79 | +1.1 | 3 | 1 | 53 | High | 3–5 | 11–15 | Groundwater stress, rice–wheat precision | Yes | Q2‑2025 |
| Zone Upper/Middle Gangetic Plain | Alluvial 95 | 76 | 1.72 | 78 | +1.5 | 2 | 2 | 54 | Medium | 3–5 | 12–16 | Canal scheduling, floodplain zoning | Yes | Q1‑2025 |
| Zone Lower Gangetic Plain | Alluvial 90 | 58 | 1.60 | 75 | +2.0 | 2 | 4 | 62 | Medium | 3–5 | 14–18 | Delta flood risk, rice suitability | Yes | Q2‑2025 |
| Zone Eastern Plateau & Hills | Red/Lateritic 70 | 35 | 1.33 | 65 | +1.7 | 3 | 2 | 59 | Medium | 3–5 | 13–17 | Watershed GIS, pulses/maize zoning | Yes | Q1‑2025 |
| Zone Central Plateau & Hills | Black/Red 70 | 47 | 1.50 | 74 | +2.1 | 3 | 2 | 57 | Medium | 3–5 | 15–19 | Soybean/pulses, micro‑irrigation | Yes | Q2‑2025 |
| Zone Western Plateau & Hills (Deccan) | Black 50, Red 30 | 45 | 1.49 | 73 | +1.9 | 3 | 2 | 58 | High | 3–5 | 15–19 | Cotton NDVI, drought watch | Yes | Q1‑2025 |
| Zone Southern Plateau & Hills | Red/Lateritic 60 | 52 | 1.56 | 75 | +1.8 | 3 | 2 | 58 | Medium | 3–5 | 14–19 | Tank systems, horticulture suitability | Yes | Q2‑2025 |
| Zone East Coast Plains & Hills | Alluvial/Lateritic 75 | 49 | 1.50 | 72 | +1.9 | 2 | 4 | 61 | Medium | 3–5 | 13–18 | Coastal flood risk, rice/aquaculture zoning | Yes | Q1‑2025 |
| Zone West Coast Plains & Ghats | Lateritic 70 | 40 | 1.30 | 66 | +1.4 | 2 | 3 | 54 | Low | 3–5 | 11–15 | Plantation crop advisories, slope/erosion GIS | Yes | Q2‑2025 |
| Zone Gujarat Plains & Hills | Alluvial/Black 75 | 50 | 1.51 | 73 | +2.0 | 3 | 2 | 55 | High | 3–5 | 15–20 | Drip irrigation, salinity maps | Yes | Q2‑2025 |
| Zone Western Dry Region (Thar) | Desert 85 | 30 | 1.28 | 62 | +1.5 | 4 | 1 | 66 | High | 3–5 | 12–16 | Millets, water harvesting, NDWI drought watch | Yes | Q1‑2025 |
| Zone Island Zone | Coastal/Island soils 90 | 30 | 1.20 | 58 | +0.7 | 2 | 4 | 60 | Low | 3–5 | 9–12 | Coastal flood/erosion, salinity management | No | Q2‑2025 |
Interoperable Standards, Ethics, and Data Stewardship
Interoperable data standards help different systems talk to each other. GIS best practices, schema‑friendly metadata, and clear data recency tags make the india agriculture map more useful. Ethical use of remote‑sensing data requires privacy, security, and consent frameworks. Public dashboards should share aggregated insights while protecting individual farmers.
- Use consistent spatial reference systems and clean attribute naming for layers like soils, irrigation, cropping, and risk.
- Document data lineage and update cycles so users know how fresh the maps are.
- Adopt “minimum necessary” principles in field data collection to safeguard privacy.
- Maintain transparent quality flags for climatic anomalies and sensor gaps.
Get Started: Apps, API, and Subscriptions
Ready to use the agriculture map of india in your operations? Explore mobile and web tools built for 2025 and beyond.
API Access: integrate satellite layers, crop health indices, and weather into your systems. See the Developer Docs for endpoints and examples.
FAQ: Agriculture India Map 2025
What is meant by a layered, dynamic agriculture map?
It is a spatial system that stacks soils, rainfall, irrigation, crops, and climate risk layers, updated regularly using satellites and field data. The goal is to guide production and policy decisions in near real time.
How does GIS improve farm decisions?
GIS ties location to data. Farmers and planners can see where soils and water are suitable, where drought or flood risk is high, and how cropping patterns change over time. This helps optimize inputs and reduce risk.
Which regions show groundwater depletion?
Depletion is severe in Punjab, Haryana, and western Uttar Pradesh. Eastern and northeastern states rely more on rainfall and small‑scale irrigation systems.
How are crop yield estimates produced?
Yield models use satellite vegetation indices, weather, and crop calendars. Platforms like Bhuvan and FASAL support official estimates, while private tools add farm‑level insights.
What climate risks are mapped in 2025?
Temperature rise, changing monsoon patterns, and flood/drought hotspots. These layers inform crop calendars, tolerance traits, and water‑efficient practices.
Can smallholders use these maps without complex hardware?
Yes. Mobile‑friendly apps and web dashboards provide ready‑to‑use insights. Remote sensing reduces the need for on‑field devices, keeping costs low.
Does the agriculture map support insurance and credit?
Yes. Spatial evidence of acreage, crop condition, and anomalies improves loan appraisal and claim verification, enabling faster, more transparent processes.
What makes the 2025 map “definitive”?
It combines traditional regional knowledge with digital GIS, satellite AI, and field data—enabling near‑real‑time monitoring and targeted interventions at scale.
What is the role of drones and field sensors?
They enhance the resolution of farm observations and calibrate satellite models, especially for high‑value horticulture and specialty crops.
Which crops are expanding in 2025?
Some kharif crops show northward spread. High‑value horticulture continues to expand. Pulse cultivation in central India remains strong due to policy and market signals.
Closing Note
The agriculture map of India 2025 is a living spatial intelligence platform. It reflects natural patterns and modern digital mapping. Continued investment in high‑resolution satellites, interoperable standards, farmer‑friendly interfaces, and local capacity building will translate this intelligence into income, sustainability, and food security for India’s smallholders through the decade ahead.
