ERC SCALAR

Agent-based modelling of post-disaster recovery with remote sensing data

In this recent study, we develop an agent-based model using machine learning-derived information from remote sensing data to simulate and explore the post-disaster recovery processes in urban areas of Tacloban, the Philippines, devastated by Typhoon Haiyan in 2013.

A review of agent-based flood risk models

In this paper, we systematically reviewed the ABMs that explore mid to long-term reactions of socio-economic systems to flood hazards...

Call for collaboration

For those of you who study the drivers of individual adaptation to floods, with primary survey data... let’s get in touch and explore the synergies of uniting fragmented knowledge!

Dealing with scale and scaling

We recently published a paper identifying and formulating 8 grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling...

Methodology to link ABM and CGE models

We present a novel methodology to scale up behavioral changes among heterogeneous individuals regarding energy choices while tracing their macroeconomic and cross-sectoral impacts...

Download our ABM model on risk perception and housing prices

Open Access agent-based model to simulate the aggregated impacts of households’ residential location choices and their changing risk perceptions in response to flooding.

Download our data and R scripts on flood surveys

Meta analysis of published flood surveys to reveal the role of culture in reported data on individual climate change adaptation taking floods as an example...

Repetitive floods intensify outmigration and climate gentrification in coastal cities

Our results suggest that pure market-driven processes can cause shifts in demographics in climate-sensitive hotspots placing low-income households further at risk...

Culture plays a role in climate change adaptation

To better encourage adaptation at a household level (and not just for the wealthy), it is critical that we better understand what motivates adaptation by looking at who adapts and why...

How do we build our Agent Based Models?

We first start from the theory to isolate the cause-effect relationships and to formulate hypotheses. We then collect a set of very different data, ranging from market transactions to GIS, Lab experiments and surveys to test alternative behavioral theories and compare to observed macro data.
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ERC SCALAR

Scaling up behavior and autonomous adaptation for macro models of climate change damage assessment
Damage associated with climate change is a core benchmark in science and policy. Macro Integrated Assessment Models estimating damages are criticized for neglecting risk distribution, adaptation dynamics and the possible collapse of regional economies. Micro-level social science studies contain substantial knowledge on individual behavior, decisions under risk and autonomous climate adaptation, and go beyond monetary losses by focusing on resilience. This knowledge can ameliorate theoretical and empirical flaws in current macro assessments, if adequate scaling up methods were to exist.

SCALAR aims to bridge the gap between micro and macro research traditions by modeling the behavioral aspects of autonomous adaptation processes of heterogeneous agents, and integrating them into macro level climate policy models.