Extended Attribute Profiles for Precise Crop Classification in UAV-Borne Hyperspectral Imagery-Reference-Cited by-同舟云学术

Extended Attribute Profiles for Precise Crop Classification in UAV-Borne Hyperspectral Imagery

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Lu Qikai¹^ORCID,Xie Youping²,Wei Lifei¹,Wei Zeyang³,Tian Shuang³,Liu Hui³,Cao Li²

Affiliation:

1. Faculty of Recourses and Environmental Science, and Hubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan, China

2. Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region, Ministry of Natural Resources, Second Surveying and Mapping Institute of Hunan Province, Changsha, China

3. Faculty of Resources and Environmental Science, Hubei University, Wuhan, China

Funder

Natural Science Foundation of Hubei Province

Open Fund of Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region, Ministry of Natural Resources

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10378649.pdf?arnumber=10378649

Reference18 articles.

1. Stacked spectral feature space patch: An advanced spectral representation for precise crop classification based on convolutional neural network

2. A review of remote sensing applications in agriculture for food security: Crop growth and yield, irrigation, and crop losses

3. Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture

4. Evaluating satellite hyperspectral (Orbita) and multispectral (Landsat 8 and Sentinel-2) imagery for identifying cotton acreage

5. New Generation Hyperspectral Data From DESIS Compared to High Spatial Resolution PlanetScope Data for Crop Type Classification

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