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Lin, Y., Xin, X., Zhang, H. and Wang, X. (2015) The Implications of Serial Correlation and Time-Lag Effects for the Impact Study of Climate Change on Vegetation Dynamics—A Case Study with Hulunber Meadow Steppe. Inner Mongolia. International Journal of Remote Sensing, 36, 5031-5044.
https://doi.org/10.1080/01431161.2015.1093196

has been cited by the following article:

• TITLE: Analysis of Climate Variability and Relation to Vegetation in Garamba National Park from 1990-2020

  AUTHORS: Lutumba Suika Achille, Kebin Zhang, Christian Jonathan Kouassi Anoma

  KEYWORDS: Remote Sensing, Correlation Coefficient, Vegetation, Land Surface Temperature, Enhanced Vegetation Index, Normalized Difference Vegetation Index

  JOURNAL NAME: Open Journal of Ecology, Vol.11 No.10, October 29, 2021

  ABSTRACT: Climatic factors impact vegetation. Our study was to examine and analyze the climate variability and relationship to vegetation in Garamba National Park of the Democratic Republic of the Congo over the past 30 years (1990 to 2020), then to relate the climatic variables. Mann Kendall’s non parametric test, ANOVA, and p-value tests are used to analyze existing trends and relationships between vegetation cover, climatic factors, land surface temperature (LST) and normalized difference in temperature Vegetation index (NDVI), Enhanced vegetation index (EVI) in Garamba national park which is of particular importance for the network of protected areas of the Democratic republic of Congo because its position at the northern limit of the savanna-forest mosaics gives it a unique biodiversity. The southern part of the park is dominated by grassy shrub savannas. The results showed that: 1) In Garamba, the monthly correlation coefficient of Kendall and Pearsan between temperature and precipitation are negative respectively 0.763 and −0.876 (p-value