Monitoring vegetation dynamics using the universal normalized vegetation index (UNVI): An optimized vegetation index-VIUPD-Reference-Cited by-同舟云学术

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Monitoring vegetation dynamics using the universal normalized vegetation index (UNVI): An optimized vegetation index-VIUPD

Published:2019-03-27 Issue:7 Volume:10 Page:629-638
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

Zhang Lifu¹²,Qiao Na²³^ORCID,Baig Muhammad Hasan Ali⁴,Huang Changping²,Lv Xin¹,Sun Xuejian²,Zhang Ze¹

Affiliation:

1. Key Laboratory of Oasis Eco-agriculture, Xinjiang Production and Construction Corps, Shihezi University, Shihezi, China

2. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China

3. University of Chinese Academy of Sciences, Beijing, China

4. Institute of Geo-Information and Earth Observation, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, Pakistan

Funder

National Natural Science Foundation of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Earth and Planetary Sciences (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2019.1597298

Reference20 articles.

1. Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance

2. Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study

3. Monitoring fractional green vegetation cover dynamics over a seasonally inundated alpine wetland using dense time series HJ-1A/B constellation images and an adaptive endmember selection LSMM model

4. MODIS time-series-derived indicators for the beginning of the growing season in boreal coniferous forest — A comparison with CO2 flux measurements and phenological observations in Finland

5. Comparison of the sensor dependence of vegetation indices based on Hyperion and CHRIS hyperspectral data

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