New Generation and Old Generation Hyperspectral Remote Sensing Data and their Comparisons with Multispectral Data in the Study of Global Agriculture and Vegetation

被引：0

作者：

Thenkabail, Prasad S. ^{[1
]}

Aneece, Itiya ^{[1
]}

Teluguntla, Pardhasaradhi ^{[1
]}

Oliphant, Adam ^{[1
]}

Foley, Daniel ^{[1
]}

机构：

[1] US Geol Survey, Flagstaff, AZ 86001 USA

来源：

2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年

关键词：

hyperspectral; DESIS; PRISMA; Hyperion; Machine Learning;

D O I：

10.1109/IGARSS46834.2022.9883556

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Great advances in remote sensing are taking place with new generation of spaceborne hyperspectral sensors such as the DESIS and PRISMA which are already acquiring data for over a year now and the upcoming launch of EnMAP. Understanding the characteristics of these data for a wide array of applications is of great importance to advance the twenty-first century satellite remote sensing. In this paper we will make a comprehensive assessment of new generation hyperspectral sensors such as the DESIS and the PRISMA and compare the same with the older generation hyperspectral sensors such as the Hyperion as well as with various multispectral sensors in study of major world agricultural crops.

引用

页码：5744 / 5745

页数：2

共 3 条

[1] Classifying Crop Types Using Two Generations of Hyperspectral Sensors (Hyperion and DESIS) with Machine Learning on the Cloud [J].