TRANSITION - Multi-Level ABM

Welcome to TRANSITION!

Disclaimer:

All results are computational estimates derived from models and available data, which may involve uncertainties or limitations. They do not constitute professional, financial, or policy advice and should be used for informational purposes only.

Multi-Level Agent Types (Farmers, Cooperatives, Markets, Policymakers)

👤 Individual (Farmers/Parcels):

Decide crop type or solar PV based on profitability, climate suitability, and social influence

🤝 Community (Cooperatives):

Aggregate individual decisions, share knowledge, broadcast market signals, and establish social norms

📊 Market (Commodity Markets):

Set crop prices via supply/demand dynamics, aggregate production, and apply policy regulations

🏛️ Policy (Policymakers):

Set subsidies and regulations, evaluate effectiveness, and adjust based on market outcomes

Interactions: Policies influence markets → markets influence cooperatives → cooperatives influence farmers. Results reflect these cross-scale dynamics.

Get started:

  • • Use the left sidebar to draw polygons for spatial filtering
  • • Browse example queries from the right sidebar
  • • Or type your own query in the input box below

Example Queries

📊Data Sources Reference

Info only

CCA & MLU

• Satellite terrain data (Copernicus DEM)
• Historical & projected climate (ERA5-Land, CORDEX)
• Crop yield estimations (Aquacrop)
• Soil information (SoilGrids)

GCP

• Satellite terrain data (Copernicus DEM)
• Soil information (SoilGrids)
• Climate projections (CORDEX)
• Socioeconomic indicators (EUROSTAT, FADN, ECB)
• Renewable energy potential (ENSPRESO)

Click any example below to copy it to the input box, or use them as templates for your own queries.

Climate Change Adaptation (CCA)

CCA-03
1.

"Simulate wheat yield under moderate scenario for 10 years with 20 farmers"

Click to use
2.

"Simulate wheat yield with 50 farmers, 3 cooperatives, 2 markets, and 2 policymakers under optimistic scenario"

Click to use
3.

"Simulate maize yield under pessimistic scenario for 10 years at (40.65, 22.75), (40.6, 22.58)"

Click to use
4.

"Simulate wheat yield under moderate scenario for 7 years with 30 farmers using AquaCrop"

Click to use
CCA-04
1.

"Evaluate PV suitability under optimistic scenario with 2 energy companies"

Click to use
2.

"Evaluate PV suitability at (40.65, 22.75), (40.6, 22.58) under moderate scenario with 5 energy companies"

Click to use
3.

"Show PV installation potential under pessimistic scenario with 3 energy companies"

Click to use
4.

"Evaluate PV suitability under optimistic scenario with 4 energy companies using AquaCrop"

Click to use
CCA-10
1.

"Show cross-scale interactions under moderate scenario for 10 years with 20 farmers"

Click to use
2.

"Run cross-scale interactions with 20 farmers, 4 collectives, 2 markets, and 1 policymaker under pessimistic scenario"

Click to use
3.

"Analyze policy impacts under pessimistic scenario for 10 years with 30 farmers"

Click to use
4.

"Show cross-scale interactions under moderate scenario for 8 years with 25 farmers using AquaCrop"

Click to use

Multi-Land Use (MLU)

MLU-04
1.

"Categorize 15 land parcels under moderate scenario"

Click to use
2.

"Categorize 20 land parcels under optimistic scenario"

Click to use
3.

"Categorize at (40.65, 22.75), (40.6, 22.6) parcels under moderate scenario"

Click to use
MLU-05
1.

"Simulate land use under moderate scenario for 10 years with 15 parcels"

Click to use
2.

"Simulate wheat at (40.65, 22.75), maize at (40.70, 22.80) under moderate scenario for 10 years"

Click to use
3.

"Simulate 10 years: wheat at (40.65, 22.7), maize at (40.7, 22.8), wheat at (40.75, 22.85) with 5 collectives, 2 markets, and 1 policymaker under moderate scenario"

Click to use
4.

"Simulate land use under moderate scenario for 7 years with 25 parcels using AquaCrop"

Click to use
MLU-07
1.

"Compare historical vs future suitability for wheat under moderate scenario"

Click to use
2.

"Show wheat suitability changes under optimistic scenario"

Click to use
3.

"Benchmark historical vs future land suitability for maize under pessimistic scenario"

Click to use
MLU-08
1.

"Show future climate scenarios for wheat under pessimistic scenario with ensemble size 3"

Click to use
2.

"Compare climate scenarios for maize under moderate scenario with ensemble size 5"

Click to use
3.

"Analyze future projections under optimistic scenario with ensemble size 3"

Click to use
4.

"Show future climate scenarios for wheat under pessimistic scenario with ensemble size 3 using AquaCrop"

Click to use

Green Credit Policy (GCP)

GCP-03
1.

"Simulate PV adoption under moderate support with optimistic scenario and 20 landowners"

Click to use
2.

"Simulate PV at (40.65, 22.75) and (40.6, 22.59) under high support with moderate scenario for 10 years"

Click to use
3.

"Analyze solar installation under low support with pessimistic scenario for 15 years"

Click to use
GCP-07
1.

"Map PV adoption under low support policy with pessimistic scenario for 10 years with 20 landowners"

Click to use
2.

"Show geographic distribution of PV at (40.65, 22.75), (40.70, 22.80) under moderate support with optimistic scenario"

Click to use
3.

"Display solar adoption map under high support with moderate scenario for 25 landowners"

Click to use
GCP-16
1.

"Monitor feedback loops under moderate scenario for 10 years with 30 landowners"

Click to use
2.

"Analyze policy feedback under optimistic scenario for 10 years with 25 landowners"

Click to use
3.

"Track subsidy effectiveness under pessimistic scenario for 20 years"

Click to use

Irrigation

IRR-US-01
1.

"Analyze temporal phenology patterns from April to September 2025"

Click to use
2.

"Classify bare soil parcels from May 1 to August 31, 2023"

Click to use
3.

"Identify fallow parcels from June to August 2022 with 30 parcels"

Click to use
4.

"Analyze seasonal phenology at coordinates (40.6, 22.8) from April to September 2021"

Click to use
5.

"Show me time-series analysis to distinguish harvested from fallow field from April to August 2024"

Click to use
IRR-US-02
1.

"Simulate irrigation ABM with 20 farmers from January to February 2022 with 2 cooperatives"

Click to use
2.

"Simulate irrigation ABM with 50 farmers and 3 water cooperatives from January 1 to February 20 2025"

Click to use
IRR-US-03
1.

"Detect rice flooding from May to June 2022"

Click to use
2.

"Show rice flood detection from May to June 2024 with 30 parcels"

Click to use
3.

"Analyze rice paddy flooding with NDWI from May to September 2025"

Click to use
IRR-US-04
1.

"Run AquaCrop simulation for 3 years with 20 farmers under moderate scenario"

Click to use
2.

"Simulate irrigation demand with AquaCrop for 3 years with 30 farmers under optimistic scenario"

Click to use
3.

"Analyze crop water requirements for 2 years with 50 farmers under pessimistic scenario"

Click to use
IRR-US-05
1.

"Compare static crop map vs dynamic EO-based forecasting for 2 years"

Click to use
2.

"Compare static vs dynamic for 1 years starting from 2022 under moderate scenario"

Click to use
3.

"Compare static baseline vs dynamic forecasting for 3 years starting from 2022 with 25 farmers"

Click to use

💡Use the left sidebar to draw polygons for spatial filtering!