Fire Radiative Power Correction and Spatiotemporal Fusion Based on MYD14 and VNP14IMG.
Saved in:
| Title: | Fire Radiative Power Correction and Spatiotemporal Fusion Based on MYD14 and VNP14IMG. |
|---|---|
| Authors: | Zheng, Yang1,2,3 (AUTHOR), Ding, Ke1,2,3 (AUTHOR) kding@nju.edu.cn, Xue, Lian1,3,4 (AUTHOR), Wang, Zilin1,2,3,4 (AUTHOR), Jiao, Guanjie1,2,3 (AUTHOR), Zhu, Yifan1,2,3 (AUTHOR), Zhang, Jinying1,2,3 (AUTHOR), Ren, Qianyu1,2,3,4 (AUTHOR) |
| Source: | Remote Sensing. May2026, Vol. 18 Issue 10, p1650. 28p. |
| Subjects: | Multisensor data fusion, MODIS (Spectroradiometer), Biomass burning, Zenith distance, Remote sensing |
| Abstract: | Highlights: What are the main findings? An empirical viewing zenith angle (VZA)-dependent correction model was developed using cloud-corrected VIIRS fire radiative power (FRP) as the cross-sensor reference, reducing the systematic underestimation of MODIS FRP under large-VZA conditions and improving MODIS-VIIRS FRP consistency. A correction-before-fusion framework for MYD14 and VNP14IMG was proposed by integrating duplicate-detection correction, footprint-scale MODIS-VIIRS matching, area-based VIIRS cloud correction, VZA-dependent MODIS FRP calibration, and quality-prioritized fusion. The fused product improves spatial continuity, temporal completeness, and low-intensity fire detection relative to the original MODIS product. What are the implications of the main findings? The resulting long-term fused FRP dataset provides a more internally consistent observational record at the native MODIS footprint scale, supporting more reliable extraction and spatial characterization of active burning fronts and active-fire clusters, as well as regional FRP analysis. The proposed correction-before-fusion framework provides a methodological basis for developing internally consistent multi-sensor active fire products, with potential applications in fire dynamics analysis, biomass-burning emission estimation, long-term fire climatology, and assessments of fire-climate interactions. Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) active fire products are widely used for global fire monitoring, but single-sensor records are limited by differences in observation geometry, spatial resolution, detection sensitivity, and swath coverage. To combine the long-term continuity of Aqua MODIS with the higher sensitivity of Suomi NPP VIIRS, this study developed a correction-before-fusion framework for MYD14 and VNP14IMG and generated a daily fused fire radiative power (FRP) dataset at the native MODIS footprint scale. MYD14 and VNP14IMG observations from 2012 to 2024 were processed using duplicate-detection correction, footprint-scale near-synchronous matching, area-based VIIRS cloud correction, and anomalous-sample screening. Cloud-corrected VIIRS FRP was then used as the reference to develop an empirical viewing zenith angle (VZA)-dependent correction model for MODIS FRP. Finally, VZA-corrected MODIS FRP and cloud-corrected VIIRS FRP were integrated using a quality-prioritized fusion strategy. The correction model achieved high fitting accuracy ( R 2 ≥ 98.18 % ) and reduced MODIS underestimation under large-VZA conditions. Compared with the original MODIS product, the fused product increased detected fire pixels by approximately 3.82-fold, improved spatial continuity, and reduced temporal data gaps. Landsat-based validation showed improved low-intensity fire detection while maintaining low commission error. This framework provides a harmonized long-term FRP dataset for fire monitoring, emission estimation, and fire-climate studies. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | Highlights: What are the main findings? An empirical viewing zenith angle (VZA)-dependent correction model was developed using cloud-corrected VIIRS fire radiative power (FRP) as the cross-sensor reference, reducing the systematic underestimation of MODIS FRP under large-VZA conditions and improving MODIS-VIIRS FRP consistency. A correction-before-fusion framework for MYD14 and VNP14IMG was proposed by integrating duplicate-detection correction, footprint-scale MODIS-VIIRS matching, area-based VIIRS cloud correction, VZA-dependent MODIS FRP calibration, and quality-prioritized fusion. The fused product improves spatial continuity, temporal completeness, and low-intensity fire detection relative to the original MODIS product. What are the implications of the main findings? The resulting long-term fused FRP dataset provides a more internally consistent observational record at the native MODIS footprint scale, supporting more reliable extraction and spatial characterization of active burning fronts and active-fire clusters, as well as regional FRP analysis. The proposed correction-before-fusion framework provides a methodological basis for developing internally consistent multi-sensor active fire products, with potential applications in fire dynamics analysis, biomass-burning emission estimation, long-term fire climatology, and assessments of fire-climate interactions. Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) active fire products are widely used for global fire monitoring, but single-sensor records are limited by differences in observation geometry, spatial resolution, detection sensitivity, and swath coverage. To combine the long-term continuity of Aqua MODIS with the higher sensitivity of Suomi NPP VIIRS, this study developed a correction-before-fusion framework for MYD14 and VNP14IMG and generated a daily fused fire radiative power (FRP) dataset at the native MODIS footprint scale. MYD14 and VNP14IMG observations from 2012 to 2024 were processed using duplicate-detection correction, footprint-scale near-synchronous matching, area-based VIIRS cloud correction, and anomalous-sample screening. Cloud-corrected VIIRS FRP was then used as the reference to develop an empirical viewing zenith angle (VZA)-dependent correction model for MODIS FRP. Finally, VZA-corrected MODIS FRP and cloud-corrected VIIRS FRP were integrated using a quality-prioritized fusion strategy. The correction model achieved high fitting accuracy ( R 2 ≥ 98.18 % ) and reduced MODIS underestimation under large-VZA conditions. Compared with the original MODIS product, the fused product increased detected fire pixels by approximately 3.82-fold, improved spatial continuity, and reduced temporal data gaps. Landsat-based validation showed improved low-intensity fire detection while maintaining low commission error. This framework provides a harmonized long-term FRP dataset for fire monitoring, emission estimation, and fire-climate studies. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 20724292 |
| DOI: | 10.3390/rs18101650 |
