基于机器学习算法的巴西对流层平均温度新模型

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

International Journal of Remote Sensing Pub Date : 2024-04-08 DOI:10.1080/01431161.2024.2334197

Diego Brum, Vinicius Francisco Rofatto, Leonardo Scalco, Luiz Gonzaga Jr, Rafaela de Oliveira Pena, Lucas Schroeder, Luiz Fernando Sapucci, Mauricio Roberto Veronez

引用次数: 0

摘要

可降水汽（PWV）在大气科学中发挥着至关重要的作用。气象站与全球导航卫星系统（GNSS）接收器之间的集成使得高精度的水蒸气测量成为可能。

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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New mean tropospheric temperature models based on machine learning algorithms for Brazil

Precipitable Water Vapour (PWV) plays an essential role in atmospheric science. Integration between meteorology stations and Global Navigation Satellite Systems (GNSS) receivers has enabled high-re...

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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).