Coupling Physical Model and Deep Learning for Near Real-Time Wildfire Detection-Reference-Cited by-同舟云学术

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Coupling Physical Model and Deep Learning for Near Real-Time Wildfire Detection

Published:2023 Issue: Volume:20 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Ji Fengcheng¹^ORCID,Zhao Wenzhi¹^ORCID,Wang Qiao¹,Chen Jiage²^ORCID,Li Kaiyuan¹,Peng Rui¹^ORCID,Wu Jichao³

Affiliation:

1. State Key Laboratory of Remote Sensing Science, and the Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing, China

2. National Geomatics Center of China, Beijing, China

3. Alibaba DAMO Academy, Hangzhou, China

Funder

National Natural Science Foundation of China Major Program

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10034981/10225592.pdf?arnumber=10225592

Reference17 articles.

1. BRDF models to predict spectral reflectance and emissivity in the thermal infrared

2. Improving Land Cover Change Detection and Classification With BRDF Correction and Spatial Feature Extraction Using Landsat Time Series: A Case of Urbanization in Tianjin, China

3. Stagewise Unsupervised Domain Adaptation With Adversarial Self-Training for Road Segmentation of Remote-Sensing Images

4. Artificial Intelligence for Remote Sensing Data Analysis: A review of challenges and opportunities

5. Development of a snow kernel to better model the anisotropic reflectance of pure snow in a kernel-driven BRDF model framework

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1. Tiny-Object Detection Based on Optimized YOLO-CSQ for Accurate Drone Detection in Wildfire Scenarios;Drones;2024-09-02

2. Advancements in remote sensing for active fire detection: A review of datasets and methods;Science of The Total Environment;2024-09

3. LEO Satellite Oriented Wildfire Detection Model Using Deep Neural Networks: A Transfer Learning Based Approach;2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT);2024-05-02

4. A Novel Spectral Index for Vegetation Destruction Event Detection Based on Multispectral Remote Sensing Imagery;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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