ScholarLens Back to search
2019•Unpublished venueRequires access

Detecting Active Fires with Himawari-8 Geostationary Satellite Data

Soo Chin Liew

Open publisher page 9 citations

Abstract

We developed an algorithm for active fire detection using the Advanced Himawari Imager (AHI) on the Himawari-8 geostationary satellite. The algorithm is based on a stochastic detection model that aims to minimize a cost function derived from the probability density functions of the fire and background pixels. Using MODIS active fire product as the reference data, the optimal threshold was derived and the omission and commission errors were found to be 0.66 and 0.16, respectively.

About this research paper

What this paper is about

We developed an algorithm for active fire detection using the Advanced Himawari Imager (AHI) on the Himawari-8 geostationary satellite. The algorithm is based on a stochastic detection model that aims to minimize a cost function derived from the probability density functions of the fire and background pixels. Using MODIS active fire product as the reference data, the optimal threshold was derived and the omission and commission errors were found to be 0.66 and 0.16, respectively.

Why it matters

OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

We developed an algorithm for active fire detection using the Advanced Himawari Imager (AHI) on the Himawari-8 geostationary satellite. The algorithm is based on a stochastic detection model that aims to minimize a cost function derived from the probability density functions of the fire and background pixels. Using MODIS active fire product as the reference data, the optimal threshold was derived and the omission and commission errors were found to be 0.66 and 0.16, respectively.

Key concepts: Geostationary orbit, Meteorological satellite, Geostationary Operational Environmental Satellite, Satellite, Remote sensing, Pixel, Computer science, Meteorology

Related papers

Related paper 1Related paper 2
Back to paper searchBrowse research topicsOriginal source
Detecting Active Fires with Himawari-8 Geostationary Satellite Data — Research Paper | ScholarLens