Remote Sensing Data for California Rim and King Megafire Analysis

Multi-sensor remote sensing data captures landscape conditions before and after the 2013 Rim and 2014 King mega forest fires in California's Sierra Nevada. The dataset includes high-resolution surface reflectance, thermal imagery, burn severity metrics, and LiDAR-derived structural measures. Data is provided by ORNL_CLOUD and spans from 2010 to 2015.

Use Cases

• Comparing field-estimated fire severity with derived remote sensing indices like burn severity metrics.
• Analyzing changes in vertical vegetation structure using LiDAR-derived summary statistics.
• Assessing pre- and post-fire landscape characteristics with multi-band geotiffs from AVIRIS and MASTER sensors.
• Studying topographic changes via first order topographic indices from LiDAR point data.
• Modeling fire impact on forest ecosystems using paired surface reflectance and thermal imagery.

Strengths

• Data pairs pre-fire and post-fire collections for two distinct mega fires (2013 Rim and 2014 King), enabling temporal change analysis.
• Includes field estimates of fire severity for validation against remote sensing indices.
• Provides multi-sensor data from spectroscopic (AVIRIS) and thermal (MASTER) instruments, plus LiDAR structural measures.

Limitations

• Conflicting 'last updated' dates exist between platforms (2015-01-15 and 2026-03-12), creating uncertainty about metadata freshness.
• Specific row counts, file sizes, and detailed column names are not provided across any source.
• License is ambiguously listed as 'other-license-specified' or 'None', requiring user verification.

Provenance

Source

ORNL_CLOUD

Collection Method

Collected via airborne remote sensing platforms (AVIRIS, MASTER, LiDAR) and paired with field estimates of fire severity.

Time Range

2010-2015

Freshness

2026-03 12 22:30:28.417875

Geography

Forested areas in the Sierra Nevada Mountains, California, USA.