ResilientPulse
An analytical platform for understanding where India is most climate-vulnerable — and where targeted intervention can deliver the highest impact. District-level screening. Evidence-based prioritisation. Open data.
Every district receives a structured diagnostic — dimension-level scores and targeted intervention recommendations. Five of seven dimensions are currently published.
Live district data — 5 dimensions published
Top recommendation: Strengthen cyclone early warning dissemination and expand NCRMP shelter coverage in coastal blocks
A snapshot of district-level performance from across the country — showing the geographic breadth of India's resilience landscape.
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Showing highest/lowest-scoring district from each state. Scores are modelled estimates — not official government rankings. Adjacent scores are not statistically distinguishable; ordering within a band is indicative, not definitive.
The same data, interpreted through the lens that matters to your work.
Monsoon variability, drought frequency, rainfed area dependency, crop insurance gaps, and irrigation deficits — the indicators that determine whether 120 million farming households can sustain their livelihoods.
Groundwater depletion, rainfall deviation, tap water coverage, wetland loss, and watershed management — critical for the 600 million Indians facing water stress.
Flood drainage, housing quality, urbanisation rate, road connectivity, and smart city climate action — where 500 million urban Indians face compounding heat, flood, and air quality risks.
Healthcare access, heat stress exposure, child malnutrition, drinking water safety, and disease surveillance — the infrastructure that determines whether climate shocks become health crises.
Forest cover trends, groundwater health, soil quality, and ecosystem services — the natural capital that either amplifies or absorbs climate impacts.
Renewable energy access, road connectivity, telecom penetration, healthcare infrastructure, and housing quality — the backbone that must withstand increasing climate stress.
Climate resilience disaggregated into seven measurable dimensions — enabling precise identification of systemic weaknesses and intervention opportunities at district level.
Quantifying the frequency and severity of climate shocks — temperature trends, rainfall deviation, extreme rain days, drought, cyclones, floods, heatwaves, and sea-level rise.
11 indicators (8 scored) | Weight: 20% | Sources: NASA POWER, CHIRPS, IBTrACS, Copernicus DEM, IPCC AR6Identifying which populations bear disproportionate climate risk — population density, poverty, agricultural dependence, demographic vulnerability, and urbanisation.
8 indicators | Weight: 15% | All [S] Census 2011 state referenceMeasuring environmental susceptibility — literacy, infant mortality, housing quality, groundwater depletion, crop concentration, sanitation, and malnutrition.
10 indicators | Weight: 12% | Mix of [S] Census/NFHS, [R] reanalysis, [D] CGWBAssessing structural resilience — housing quality, road connectivity, power infrastructure, health facility gaps, and digital access that determine recovery capacity.
Not yet scored — district data ingestion in V2.1 | Weight: 13%Evaluating systemic enablers of resilience — literacy, tap water, road connectivity, banking, crop insurance, sanitation, and internet access. Most values are Census 2011 or state-level proxies pending district data collection.
10 indicators | Weight: 15% | A2,A3,A7,A8,A10: [D] dashboards; rest: [S]Scoring institutional preparedness — disaster management plans, early warning systems, climate budgets, SAPCC implementation, NRLM SHGs, and institutional readiness.
8 indicators | Weight: 13% | G1,G7: [D] dashboards; G2-G4,G6,G8: [M] modelledMeasuring economic shock-absorption — livelihood diversification, credit access, insurance penetration, savings rates, and post-disaster recovery capacity.
Not yet scored — district data ingestion in V2.1 | Weight: 12%Real-time events from USGS, GDACS, NASA EONET and ReliefWeb. Select a district for nearby event details.
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Data class: live intelligence. Does not influence resilience scores. Follow official authorities for emergency action.
Indicators draw from open satellite products, Census 2011 district tables, and government programme data where available. Many socio-economic and governance values remain state-level proxies or modelled estimates pending district-level data collection.
Resilience scores are modelled estimates. This tool supports but does not replace official government risk assessments (NDMA, State DDMPs).
Climate data has limited value without a clear pathway to intervention. This platform bridges the gap between risk identification and strategic response.
For each district, the platform generates a ranked set of interventions — with cost brackets, implementing agencies, and expected resilience uplift — enabling resource allocation where it matters most.
Connects identified vulnerabilities directly to 30+ central and state government programmes (loading... combined budget) — surfacing funding pathways that are often invisible to district-level planners.
Explore how district-level risk profiles shift under different emissions trajectories (SSP1-2.6 through SSP5-8.5) across 2030, 2050, and 2100 time horizons.
A continuously updated feed of climate developments relevant to Indian policy — drawn from IMD, CWC, NOAA, and institutional sources.
Seven dimensions defined, five currently published. Infrastructure Vulnerability and Economic Resilience are not yet scored. Provenance tagging declares whether each value is reanalysis-derived, state-referenced [S], or modelled [M].
Bilingual interface (English and Hindi), aligned with Indian administrative boundaries, government scheme architecture, and policy frameworks including NAPCC, SAPCCs, and India's Updated NDC (2022).
Adaptation actions tagged with India's Updated NDC goals (net-zero by 2070, 500 GW RE by 2030) and Mission LiFE pillars where applicable.
Identifies compound climate risks (heat+drought, extreme wet seasons, fire weather) using the H_COMPOUND indicator derived from NASA POWER and CHIRPS data, with per-district frequency counts.
Auto-generated phased implementation roadmaps (Phase 0: governance → Phase 1: water/agriculture → Phase 2: infrastructure) with budget reconciliation and scheme mapping.
Select a district to discover which central and state programmes can fund climate adaptation in your area.
Based on your district's vulnerability profile, we identify applicable government programmes.
Illustrative scenarios showing how district-level data translates into tangible adaptation outcomes.
Districts scoring below 35 on Climatic Hazard with high flood frequency can use the Adaptation Action Plan to prioritise MGNREGA-NRM convergence spending, early warning system deployment, and PMAY housing upgrades — reducing expected flood damage by targeting the three weakest indicators first.
The Scheme-to-Risk Mapper identifies Atal Bhujal Yojana, PMKSY watershed, and PM-KUSUM solar pumps as the highest-impact interventions for districts with groundwater depletion exceeding 100% of recharge — linking climate risk directly to available government funding.
Odisha's investment in cyclone shelters, IFLOWS early warning, and mangrove restoration illustrates how targeted governance action can strengthen coastal resilience. The platform identifies which indicators are weakest and which government schemes can address them.
*Estimated uplift figures are illustrative scenario models, not observed outcomes. Actual impact depends on implementation quality and local conditions.
Make district resilience data accessible to your community — embed on your website or share on WhatsApp.
For official disaster warnings and weather alerts, follow authoritative government services:
ResilientPulse is informational. Follow official authorities for emergency instructions. Email and WhatsApp alert channels are under development.
Free for all .edu/.ac.in researchers and registered NGOs. We welcome research collaborations and joint publications.
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Everything you need to know about ResilientPulse — India's climate resilience intelligence platform.
ResilientPulse is India's district-level climate resilience screening platform. It covers 676 districts across 36 states and union territories. Five of seven defined dimensions are currently published: Climatic Hazard, Socio-Economic Exposure, Ecological Sensitivity, Adaptive Capacity, and Governance Readiness. Infrastructure Vulnerability and Economic Resilience are defined but not yet scored. 47 indicators are scored from 17 open data sources. The methodology draws on IPCC AR6 WGII, INFORM Risk Index, and ND-GAIN frameworks. Scores are modelled estimates, not official government rankings. The map and dimension scores are free for all users — no login required. See /api/v2/stats for current coverage numbers.
Each district receives dimension-level scores via a 4-step process: (1) indicators are normalised to 0–100 using min-max scaling with national min/max bounds; (2) indicators are aggregated within each published dimension using weighted arithmetic mean; (3) scores are presented on a continuous 0–100 scale with colour-coded map visualisation and per-indicator provenance tags ([D] district-measured, [S] state-referenced, [M] modelled, [R] reanalysis-derived); (4) future projections under SSP scenarios use delta-method projections from IPCC AR6 WGI Atlas regional values for South Asia. Five of seven dimensions are published. Infrastructure Vulnerability and Economic Resilience are defined but not yet scored. No composite score is published — dimension scores are presented individually. Uncertainty quantification is not yet implemented. See /api/v2/stats for current indicator and dimension counts.
ResilientPulse draws from 17 open data sources: NASA POWER (daily temperature 2005–2024, representative-point reanalysis — not ground-station data), CHIRPS v2.0 (monthly precipitation 1991–2025), IBTrACS v04r01 (cyclone tracks), Copernicus DEM GLO-30 (30 m slope for landslide susceptibility), Census of India 2011 (demographics, housing, workforce — 15 years old, next census pending), NFHS-5 (health/nutrition), CGWB 2023 (groundwater), MoEFCC/FSI (forest cover), JJM Dashboard (tap water), SBM/PMAY dashboards, RBI (banking), TRAI (telecom), SECC 2011, NITI Aayog, and IPCC AR6 (SLR projections, SSP scenario deltas). Each indicator displays a provenance tag showing whether data is district-measured [D], state-referenced [S], modelled [M], or reanalysis-derived [R]. Climate projections use delta-method values from the IPCC AR6 WGI Atlas for South Asia — these are not processed CMIP6 model outputs.
The map, dimension scores, district comparisons, scheme eligibility finder, SSP projections, and open API (1,000 calls/day) are free — no login required. Free PDF summary reports (7 pages) are available for every district. Paid products include the District Climate Action Plan (DCAP, ~80+ pages, from ₹19,999 + GST), Developer API for high-volume access, institutional deployments, and advisory services.
A DCAP is a comprehensive climate action plan (~100 pages) generated for any Indian district. It includes: an executive summary with resilience score and radar chart, district climate profile, 9 sector chapters (water, agriculture, health, infrastructure, livelihoods, ecosystem, urban, economic, governance), 30+ prioritised intervention cards with costs and implementing agencies, government scheme convergence mapping for 30+ central schemes, a phased 5-year implementation roadmap, budget reconciliation, RACI matrix with actual department names, M&E framework with SMART KPIs, and India NDC alignment. DCAPs are generated in 30–120 seconds and priced from ₹19,999 + GST per district (volume discounts for 2/5/10 packs and state packages).
ResilientPulse maps 30+ central and state government schemes to each district's vulnerability profile. Key schemes include: Jal Jeevan Mission (JJM), MGNREGA-NRM, PM Krishi Sinchayee Yojana (PMKSY), National Cyclone Risk Mitigation Project (NCRMP), PM Awas Yojana (PMAY), Atal Bhujal Yojana, MISHTI (Mangrove Initiative for Shoreline Habitats & Tangible Incomes), PM Surya Ghar, Swachh Bharat Mission 2.0, Namami Gange, National Adaptation Fund for Climate Change (NAFCC), PMGSY, GOBAR-DHAN, National Mission for Sustaining the Himalayan Ecosystem (NMSHE), and the National Disaster Mitigation Fund (NDMF). The Scheme Eligibility Finder tool identifies which schemes apply to a specific district based on its risk profile.
Dimension scores are modelled estimates, not ground-truth measurements. Climate hazard data uses NASA POWER daily reanalysis (a coarse gridded product sampled at representative points, not ground-station data), CHIRPS satellite-rainfall estimates, and IBTrACS cyclone tracks. Socio-economic indicators are derived from Census 2011 (15 years old — the next census is pending) and use state-level proxies where district data is unavailable. Governance indicators require manual assessment. Uncertainty quantification (confidence intervals) is not yet implemented — scores do not carry P5/P50/P95 bounds. The platform displays per-indicator provenance tags: [D] district-measured, [S] state-referenced, [M] modelled, [R] reanalysis-derived. For formal policy decisions, on-ground verification is recommended. The platform supports — but does not replace — official NDMA/DDMP risk assessments.
Yes. ResilientPulse data is free to use, cite, and include in reports for academic research, journalism, policy briefs, and internal analysis — provided you include the attribution: "Climate resilience data powered by ResilientPulse (RSustain)" with a link to pulse.rsustain.com. Commercial bulk redistribution of datasets requires a Developer API licence. Academic institutions (.edu / .ac.in) and registered NGOs receive free enhanced access. We welcome research collaborations — contact info@rsustain.com.
The platform provides forward-looking climate projections under three Shared Socioeconomic Pathways (SSPs): SSP1-2.6 (low emissions, Paris-aligned), SSP2-4.5 (middle-of-the-road), and SSP5-8.5 (high emissions, fossil-fuel intensive). Projections are available at three time horizons: 2030 (near-term), 2050 (mid-century), and 2100 (end-century). Each projection shows how climate indicators shift under different emissions trajectories, using delta-method downscaling with values transcribed from the IPCC AR6 WGI Atlas (South Asia regional assessment) and per-state regional factors. These are not processed CMIP6 model outputs — they apply published ensemble mean deltas to baseline indicator values.
ResilientPulse is built and operated by Resilient Sustainance Pvt. Ltd. (RSPL), an environmental engineering and sustainability advisory company registered in India. RSPL is part of the RSustain Group, which includes RSustain Ltd (UK) and GSustain (Qatar). The group operates a suite of climate, ESG, and sustainability tools including RSustain Academy, GreenCampus, Career Compass, GreenSetu, and the RECI Global Index. ResilientPulse is an independent product of RSPL — not endorsed by or affiliated with IPCC, INFORM, ND-GAIN, or any government agency.
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District-specific hazard assessment from satellite and climate reanalysis data
NASA POWER 20-year average (2005-2024)
Side-by-side climate resilience analysis
A structured approach to quantifying climate resilience at district level, drawing on internationally recognised frameworks
ResilientPulse employs a hybrid methodology drawing on three internationally recognised frameworks to assess climate resilience at the district level across India:
Each district receives dimension-level scores (0–100) across 5 published dimensions (of 7 defined), derived from 47 scored indicators using weighted arithmetic mean aggregation and min-max normalisation. Each indicator carries a provenance tag ([D] district-measured, [S] state-referenced, [M] modelled, [R] reanalysis-derived). Two additional dimensions (Infrastructure Vulnerability, Economic Resilience) are defined but not scored due to absent district-level data. No composite score is published. Current counts are served live from /api/v2/stats.
Data provenance (live-computed from database): Indicators are scored across published dimensions. Provenance is computed from the database at load time. Primary sources: NASA POWER (reanalysis, centroid sampling), CHIRPS (satellite rainfall), IBTrACS (cyclone tracks), Copernicus DEM GLO-30 (slope), Census 2011 (district tables). Many socio-economic and governance values are state-level proxies or modelled estimates. Each indicator value carries a provenance tag ([D] district-measured, [S] state proxy, [M] modelled, [R] reanalysis-derived). Uncertainty quantification is not yet implemented.
| Dimension | Weight | Indicators | Key Measures | Provenance |
|---|---|---|---|---|
| Climatic Hazard | 20% | 11 (8 scored) | Rainfall deviation (H2), drought (H4), flood (H5), cyclone (H6), heat-wave events (H7), SLR (H8), compound events (H_COMPOUND), landslide susceptibility (CH11). Also: temperature trend (H1), extreme rain (H3), monsoon delay (H_MONSOON) — in database but not in composite. | [R] NASA POWER reanalysis, CHIRPS, IBTrACS, Copernicus DEM, IPCC AR6 |
| Socio-Economic Exposure | 15% | 8 | Population density (E1), urban population % (E2), agricultural land % (E3), forest cover % (E4), rainfed agriculture % (E5), coastal/flood-plain % (E6), groundwater depletion (E7), built-up growth (E8) | All [S] Census 2011 state reference |
| Ecological Sensitivity | 12% | 10 | MPI proxy (S1), workforce in agriculture (S2), child stunting (S3), dependency ratio (S4), female literacy (S5), SC/ST share (S6), kutcha housing (S7), net migration (S8), agricultural drought (H_AGDRGHT), water quality exceedance (H_WATERQ) | [S] Census/NFHS state ref; H_AGDRGHT [R] reanalysis; H_WATERQ [D] CGWB |
| Infrastructure Vulnerability | 13% | — | Not yet scored — district-level data ingestion scheduled for V2.1 | |
| Adaptive Capacity | 15% | 10 | Irrigated area (A1), tap water FHTC (A2), road connectivity (A3), internet penetration (A4), hospital beds (A5), banking access (A6), crop insurance (A7), ODF Plus (A8), renewable energy (A9), early warning (A10) | A2,A3,A7,A8,A10: [D] govt dashboards; rest: [S] state ref |
| Governance Readiness | 13% | 8 | DDMP currency (G1), SAPCC (G2), GPDP climate (G3), convergence spending (G4), disaster response (G5), CSA adoption (G6), NRLM SHGs (G7), institutional readiness (G8) | G1,G7: [D] dashboards; G2-G4,G6,G8: [M] modelled; G5: mostly [M] |
| Economic Resilience | 12% | — | Not yet scored — district-level data ingestion scheduled for V2.1 | |
Step 1 — Normalisation: Each indicator is normalised to 0-100 using min-max scaling with national min/max bounds from the indicator catalogue. Values below min are clamped to min; above max to max. After normalisation, 100 = best (least hazardous or highest capacity) regardless of original direction.
Step 2 — Dimension Aggregation: Indicators within each dimension are combined using weighted arithmetic mean. Each dimension produces a score on 0-100.
Step 3 — Display: Dimension scores are presented individually on a 0–100 scale with colour-coded map visualisation and per-indicator provenance tags. No composite score is published. Five of seven dimensions are published. Climatic Hazard uses NASA POWER daily reanalysis (2005–2024) sampled at district representative points, CHIRPS v2.0 monthly precipitation (1991–2025), IBTrACS cyclone tracks, and Copernicus DEM GLO-30 slope analysis. NASA POWER is a coarse gridded reanalysis product, not ground-station data. No statistical uncertainty interval is currently published.
Step 4 — Uncertainty: Uncertainty quantification is not yet implemented. Scores do not carry confidence intervals. When implemented, uncertainty will use indicator-specific noise calibrated to provenance quality.
Step 5 — Climate Projections: Future projections under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios at 2030, 2050, and 2100 time horizons using delta-method downscaling with values transcribed from the IPCC AR6 WGI Atlas (South Asia), applied with per-state regional factors. These are not processed CMIP6 model outputs.
| Colour | Score Range |
|---|---|
| 80 - 100 | |
| 60 - 80 | |
| 40 - 60 | |
| 20 - 40 | |
| 0 - 20 |
Categorical band labels are suppressed while a scoring methodology review is in progress. Numeric scores and colour gradients remain available. See the methodology paper for details.
| Source | Data Type | Used In |
|---|---|---|
| NASA POWER (2005–2024) | Daily Tmax reanalysis, representative-point sampling | H2, H7, H_COMPOUND |
| CHIRPS v2.0 (1991–2025) | Monthly precipitation, SPI drought index | H4, H5 |
| IBTrACS v04r01 | Global tropical cyclone tracks | H6 |
| Copernicus DEM GLO-30 | 30 m elevation, slope analysis (392 tiles) | CH11 |
| IPCC AR6 | Sea-level rise projections, SSP scenario deltas | H8, projections |
| Census of India 2011 | Demographics, literacy, housing, workforce, migration | E1–E8, S1–S8 |
| NFHS-5 (2019–21) | Child stunting, malnutrition, health indicators | S3, S7 |
| SECC 2011 | Deprivation indicators | S1 |
| CGWB 2023 | Groundwater extraction, recharge, water quality | E7, H_WATERQ |
| MoEFCC / FSI | Forest cover | E4 |
| Jal Jeevan Mission | Tap water coverage (FHTC) | A2 |
| SBM Dashboard | ODF Plus status | A8 |
| PMAY Dashboard | Housing programme coverage | S7 |
| RBI | District banking statistics | A6 |
| TRAI | Telecom and internet penetration | A4 |
| NITI Aayog | SDG India Index, Aspirational Districts | G indicators |
| ISRO | SLR coastal exposure | H8 |
Dimension weights are derived from the relative importance of each component in the IPCC AR6 WGII risk framework, calibrated against INFORM Risk Index v8.0 and ND-GAIN Country Index methodologies:
| Dimension | Weight | Justification |
|---|---|---|
| Climatic Hazard | 20% | Primary exogenous forcing (IPCC AR6 WGII Ch.16) — the physical driver that all other dimensions respond to |
| Socio-Economic Exposure | 15% | Population characteristics amplifying impact (IPCC AR6 WGII Ch.8; INFORM exposure component) |
| Adaptive Capacity | 15% | Capacity to absorb, adjust and transform (ND-GAIN readiness; IPCC AR6 WGII glossary) |
| Governance Readiness | 13% | Institutional systems enabling collective response (Sendai Framework Priority 2; INFORM LoCC) |
| Infrastructure Vulnerability | 13% | Physical systems mediating hazard impact (IPCC AR6 WGII Ch.6) |
| Ecological Sensitivity | 12% | Environmental degradation amplifying vulnerability (IPCC AR6 WGII Ch.2) |
| Economic Resilience | 12% | Financial buffers enabling recovery (ND-GAIN economic readiness; World Bank CCKP) |
Score distribution note: The compressed score distribution (national range ~15 points on a 100-point scale across 666 scored districts) means adjacent scores are not statistically distinguishable. Dimension scores are presented as continuous values; no categorical band classification is applied. Sensitivity analysis results are not currently published.
Each indicator value carries a provenance tag indicating measurement quality:
| Tag | Meaning | Uncertainty (MC) | Count |
|---|---|---|---|
| [D] | District-measured (satellite, government dashboard, census) | ±2-5% | --% of values |
| [S] | State-referenced (state average applied to districts within) | ±20% | --% of values |
| [M] | Modelled / estimated (governance proxies requiring field verification) | ±25% | --% of values |
State-proxied indicators assume intra-state homogeneity, which is clearly incorrect for large heterogeneous states (UP, Maharashtra, Rajasthan). When uncertainty quantification is implemented, state-proxied and modelled indicators will carry wider uncertainty bands reflecting this data quality limitation.
This platform uses the following open-source libraries:
ResilientPulse is an independent product of Resilient Sustainance Pvt. Ltd. It is not endorsed by, affiliated with, or officially connected to the IPCC, INFORM (IASC/JRC/OCHA), the University of Notre Dame (ND-GAIN), NITI Aayog, or any government agency. Framework references are for methodological alignment purposes only.
This platform uses real climate data from NASA POWER combined with Census 2011 and government statistics for socio-economic indicators. Scores are indicative and based on the best available public data. For formal policy decisions, on-ground verification is recommended.
The methodology is aligned with the IPCC AR6 WGII (2022) risk framework and draws on INFORM and ND-GAIN peer-reviewed methodologies. For questions or collaboration, contact info@rsustain.com.
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District Climate Action Plans (DCAPs) with phased interventions, budgets, and institutional frameworks — conceptually aligned with the IPCC AR6 risk framing.
Beta: Scores include modelled estimates and state-level proxies. Methodology v2.1 is under review.
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Our Advisory service starts with the automated DCAP, then adds local data validation, field work, stakeholder consultations, block-level detailing, and DPR preparation support.
Request advisory scoping callAbout this product: The District Climate Resilience Action Plan is a screening and planning-support document generated from validated public datasets. It uses four currently validated resilience dimensions. The Climatic Hazard dimension is excluded while its independent data-quality review is completed. All cost estimates are indicative planning assumptions. The report does not replace statutory studies, engineering design, DPR preparation, stakeholder consultation or field verification. It is not government-approved, statutory, investment-grade, engineering-ready or independently assured.
Effective: 1 May 2026 | Last Updated: 23 May 2026
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