利用合成孔径雷达数据进行基于迁移学习的局部尺度地表土壤湿度检索

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

International Journal of Remote Sensing Pub Date : 2024-03-21 DOI:10.1080/01431161.2024.2329529

Emadoddin Hemmati, Mahmod Reza Sahebi

引用次数: 0

摘要

利用合成孔径雷达（SAR）数据和深度学习（DL）模型在局部范围内检索地表土壤湿度需要大量数据，而这些数据在其他地方可能无法获得。

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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Surface soil moisture retrieval based on transfer learning using SAR data on a local scale

Retrieving surface soil moisture on a local scale using Synthetic Aperture Radar (SAR) data and Deep Learning (DL) models necessitates a substantial volume of data, which may not be available in al...

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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).