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Remote SensingRemote Sensing
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14 March 2024

Correction: Amantai et al. Spatial–Temporal Patterns of Interannual Variability in Planted Forests: NPP Time-Series Analysis on the Loess Plateau. Remote Sens. 2023, 15, 3380

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1
Institute of Ecology, College of Urban and Environmental Sciences and Key Laboratory for Earth Surface Processes, Peking University, Beijing 100871, China
2
School of Information Engineering, China University of Geosciences, Beijing 100083, China
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Author to whom correspondence should be addressed.
This article belongs to the Section Forest Remote Sensing

Text Correction

There was an error in the original publication [1]. The unit for NPP was incorrectly stated.
A correction has been made to 3. Results, 3.1. Dynamic Characteristics of NPP before and after Planting, second paragraph, from 2nd to 4th sentences:
The NPP values of the entire Loess Plateau and the planted forest both showed significant increase trends, with increasing rates of 68.45 and 92.88·10−4 kg·C/m2·year−1, respectively. The increase rates of NPP varied across provinces. Among them, the NPP in Shaanxi Province increased the fastest, with a rising rate of 91.95·10−4 kg·C/m2·year−1, followed by Gansu (81.08·10−4 kg·C/m2·year−1), Shanxi (72.87·10−4 kg·C/m2·year−1), Henan (53.23·10−4 kg·C/m2·year−1), Ningxia (51.52·10−4 kg·C/m2·year−1), Inner Mongolia (35.49·10−4 kg·C/m2·year−1), and Qinghai (33.49·10−4 kg·C/m2·year−1).
The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

  1. Amantai, N.; Meng, Y.; Song, S.; Li, Z.; Hou, B.; Tang, Z. Spatial–Temporal Patterns of Interannual Variability in Planted Forests: NPP Time-Series Analysis on the Loess Plateau. Remote Sens. 2023, 15, 3380. [Google Scholar] [CrossRef]
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