STEP 3: Data Collection

Impact data in the agricultural value chain are usually interconnected with impact data from other sectors. For example, damage to transport infrastructure affects sectors beyond agriculture. This can make it difficult to distinguish data from the general disaster impact assessment and the impact assessment for the agricultural sector.

Nevertheless, direct and indirect impact data that are categorized under ‘exposure and vulnerability assessment’ should be collected. This includes damage to crops/livestock, productive assets, storage facilities and stock, shops and infrastructure. Furthermore, the analysis should be conducted on the insured and uninsured financial losses of agricultural producers, food processors and trade entrepreneurs, as well as the related ministries such as trade and industry.

The collection should include data of ‘potential amplifiers’ − factors that can accelerate, intensify or spread impacts. For example, small and medium-sized enterprises (SMEs) will incur income losses due to damaged critical infrastructure and services, such as disruption of energy or water supply, transport or agricultural inputs.

In addition, data collection implies information regarding ‘potential interdependencies and spill-over effects’. For example, agricultural producers can be affected by increased food prices after disasters and temporary dysfunctional networks (e.g. covariant shocks affect neighbours, causing restraints to borrowing within the community), while perishable agricultural products become rotten due to damaged cooling facilities/warehouses, leading to loss of income.

Guiding Questions and Tools

Guiding Questions

What are the impacts of extreme weather events on agricultural production (e.g. farmers/herders), the agricultural value chain (e.g. processing, transport, trade), and the government?

What are the direct and indirect disaster impacts to take into account?

Global databases

FAO Statistical Database on food and agriculture (FAOSTAT): Quantitative assessment of production losses by analysing yields and production time series at the country level

FAO MOSAICC (Modelling System for Agricultural Impacts of Climate Change): System of models and utilities designed to carry out inter-disciplinary climate change impact assessment on agriculture through simulations

Global databases

EM-DAT/CRED: Data on the occurrence, losses and effects of over 18,000 mass disasters from 1900 to present

UN Disaster Information Management System (DesInventar): Online platform hosted by UNISDR on e.g. economic, financial and insured losses


FAO Statistical Database on food and agriculture (FAOSTAT): Quantitative assessment of production losses by analysing yields and production time series at the country level

Guiding Questions

How to analyse data?


Australian Institute for Disaster Resilience (2002): Disaster Loss Assessment Guidelines

EU online platform with guidelines for impact assessment (last update 2015)

World Bank (2017): Unbreakable − Building the Resilience of the Poor in the Face of Natural Disasters

Expected Outputs When Using the Tools

  • Impact reports quantify exposed direct and indirect losses of governments, agricultural entrepreneurs (SMEs), and the affected agricultural population − occasionally also financial institutions.
  • Based on the loss and damage data the government can review the appropriateness of its DRM strategies.
  • Data from the impact assessment provides valuable information for the next step when analysing the performance of applied DRM mechanisms and identifying protection gaps.
  • Insurance-related outputs (see ‘Synergies: Insurance and DRM Analysis).