Title of article :
Field work and statistical analyses for enhanced interpretation of satellite fire data
Author/Authors :
Cardoso، نويسنده , , Manoel F. and Hurtt، نويسنده , , George C. and Moore III، نويسنده , , Berrien and Nobre، نويسنده , , Carlos A. and Bain، نويسنده , , Heather، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2005
Pages :
16
From page :
212
To page :
227
Abstract :
Because their broad spatial and temporal coverage, satellites provide the main source of fire data for Amazonia. A key to the application of these tools for environmental studies is the appropriate interpretation of the data they provide. To enhance the interpretation of satellite fire data for this region, we collected ground-based data on fires in 2001 and 2002 using a simple and passive method, and statistically related these data to corresponding estimates from AVHRR and MODIS fire products using error matrices. Multiple methods of analyses from simple to complex produced qualitatively similar results. Total accuracies for both fire products were very high (> 99%) and dominated by accurate (> 99%) non-fire detection. Kappa statistics and fire-detection accuracies were substantially lower, with omission errors higher than commission errors. Results calculated using several different sets of spatial-matching parameters of analysis showed that Kappa was 1–10.6% for AVHRR, and 0–1.4% for MODIS. Userʹs accuracy for fires was 0–40% for AVHRR and 3–100% for MODIS. Producerʹs accuracy for fires was 0–8% for AVHRR and 0–1% for MODIS. Statistical evaluations of potential explanatory factors showed that fire size and sampling time were dominant factors for low accuracies. Results from this study indicate that current satellite fire products are providing a limited sample of the fire activity in the region, and that ground-based analyses can substantially contribute to the interpretation of these products.
Keywords :
accuracy , Large-scale biosphere–atmosphere experiment in Amazonia , Amazonia , LBA , fire , Satellite
Journal title :
Remote Sensing of Environment
Serial Year :
2005
Journal title :
Remote Sensing of Environment
Record number :
1574648
Link To Document :
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