南加州烧毁区域绘图的机器学习方法

IF 3 3区地球科学 Q2 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

International Journal of Remote Sensing Pub Date : 2024-07-31 DOI:10.1080/01431161.2024.2380543

Chandler Ross, Douglas Stow, Daniel Sousa, Megan Jennings, Atsushi Nara, Philip Riggan

引用次数: 0

摘要

准确表示烧毁区域的位置和数量对于了解火灾的模式和影响至关重要。一些现存的烧毁面积地图似乎存在很大的误差...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Machine learning approach to burned area mapping for Southern California

Accurate representation of the location and amount of burned areas is vital to the understanding of patterns and impacts of fires. Some extant burned area maps appear to have high commission errors...

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来源期刊

International Journal of Remote Sensing 工程技术-成像科学与照相技术

CiteScore

7.00

自引率

5.90%

发文量

219

审稿时长

4.8 months

期刊介绍： The International Journal of Remote Sensing ( IJRS) is concerned with the theory, science and technology of remote sensing and novel applications of remotely sensed data. The journal’s focus includes remote sensing of the atmosphere, biosphere, cryosphere and the terrestrial earth, as well as human modifications to the earth system. Principal topics include: • Remotely sensed data collection, analysis, interpretation and display. • Surveying from space, air, water and ground platforms. • Imaging and related sensors. • Image processing. • Use of remotely sensed data. • Economic surveys and cost-benefit analyses. • Drones Section: Remote sensing with unmanned aerial systems (UASs, also known as unmanned aerial vehicles (UAVs), or drones).