Flood Detection / Insurance report
GeoPard software helps detecting flood cases to assess damage to file insurance damage reports and verify claims remotely
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GeoPard software helps detecting flood cases to assess damage to file insurance damage reports and verify claims remotely
Last updated
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This tutorial provides a step-by-step guide on using the GeoPard Agriculture platform for flood detection and insurance reporting. It is based on a real-world example from Salinas Valley, California, following a flood event in March 2023. The GeoPard platform's flood map analysis helps identify areas with excess water that may lead to crop damage, enabling farmers to claim insurance and allowing insurance companies to assess flood cases efficiently.
Farmers: To document flood damage and submit insurance claims.
Insurance Companies: To detect flood cases, verify claims, and assess the extent of crop damage.
GeoPard's flood map analysis uses advanced remote sensing and analytics to identify flooded areas, track flood progression, and quantify damage. This tutorial demonstrates how to leverage these tools to:
Detect flooding in agricultural fields.
Analyze flood severity using data layers and statistics.
Generate reports for insurance claims.
Plan corrective actions to mitigate future risks.
The example focuses on the "Potter Rd (342.93 ha)" field in Salinas Valley, comparing flood maps from March 15, 2023, and March 25, 2023, to visualize flood progression.
Navigate to the "Fields" section in the sidebar.
Select the specific field or area you want to analyze. For this example, choose the "Potter Rd (342.93 ha)" field in Salinas Valley.
GeoPard offers various data layers for remote sensing and analytics. For flood detection, the NDWI (Normalized Difference Water Index) layer is ideal, as it highlights areas with high water content.
Select satellite imagery date
Select the NDWI layer.
Optionally, explore other layers like RGB or NDVI for additional insights into crop health post-flood.
Use the "Compare Layers" feature to analyze flood progression over time.
Select up to four layers for comparison. In this example, compare NDWI layers from:
March 15, 2023 (before peak flooding).
March 25, 2023 (after peak flooding).
This comparison visualizes how the flood evolved, with flooded areas highlighted in light blue/blue.
The flood maps display areas of excess water in light blue, with a color scale ranging from black (no water) to light blue (high water presence).
Use the zoom feature to focus on specific areas, such as fields near the Salinas River.
Refer to the legend for the color scale, which shows water intensity values (e.g., 0 to 1). Where blur
Review the statistical data provided:
Average: 0.067
Median: 0.035
Standard deviation: 0.095 These metrics quantify the flood's severity.
If NDWI > 0 -> flood event
Farmers:
Use the flood maps and statistical data to document crop damage for insurance claims.
Use the "Export Data" feature to download the flood maps and relevant analytics.
Options: PDF, Shapefile or GeoJson
Submit the exported reports to your insurance provider as evidence of flood damage.
In the case below - not all farm areas where damaged
Insurance Companies:
Use the same data to verify claims, assess the extent of damage, and expedite the claims process.
Optimize processes by using reliable remote sensing software & analytics of any area (we support 50+ countries)
Beyond insurance reporting, use the flood maps to identify areas needing immediate attention, such as persistent waterlogging.
Plan corrective measures, such as:
Improving drainage systems.
Adjusting crop management practices to mitigate future risks.
Analyze Historical field productiovity & Topography of the field
NDWI Layer: Essential for detecting water presence and flood extent.
Layer Comparison: Allows tracking of flood progression over time.
Statistical Data: Provides quantitative insights into flood severity.
Export Functionality: Enables easy sharing of data for insurance claims.
Timely Analysis: Early detection of flooding allows for faster response times, reducing crop losses.
Insurance Efficiency: Streamlines the claims process for both farmers and insurers.
Risk Mitigation: Helps farmers and local agencies take proactive steps to protect crops and ensure food security.
External Articles about the case:
GeoPard's flood detection and insurance reporting tools empower farmers and insurance companies to respond effectively to natural disasters. By leveraging advanced remote sensing and analytics, users can detect floods early, assess damage accurately, and take corrective actions to protect agricultural productivity and livelihoods. This tutorial provides a clear, actionable guide for using the GeoPard platform in real-world applications, ensuring users can maximize its capabilities for flood management and insurance reporting.
Log in to the GeoPard Agriculture platform using your credentials at .
Discusses the impact of flooding on farm workers in Pajaro, California.
Covers flood preparation and crop losses near the Salinas River.
YouTube Video: Provides insights into the flood's impact on Salinas Valley agriculture.
