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Dataset of the Upper Limit of Montane Deciduous Broad-leaved Forests in the East Monsoon Realm of China


WANG Zhiyong1HAN Fang*1LI Chuanrong2LI Kun2MU Haoxiang1WANG Zhe1
1 School of Civil Engineering and Geomatics,Shandong University of Technology,Zibo 255049,China2 College of Forestry,Shandong Agricultural University,Tai’an 271018,China

DOI:10.3974/geodb.2023.11.09.V1

Published:Nov. 2023

Visitors:2064       Data Files Downloaded:41      
Data Downloaded:21.93 MB      Citations:

Key Words:

climatic factors,terrain factors,distribution of upper limit,montane deciduous broad-leaved forests,the east monsoon realm of China

Abstract:

The montane deciduous broad-leaved forests are typical vegetation in the eastern monsoon realm of China. The fine classification data of surface coverage of composite elevation information and Google Earth image are used to identify the upper limit samples points of montane deciduous broad-leaved forests. The correlation coefficient between the extracted value and the literature value is 0.698, and the slope of the fitting line is 0.959, both of which are significant at the 0.001 level. In order to compare and analyze the scale changes and spatial differentiation of the impact factors on the upper limit distribution height and impact factors of deciduous broad-leaved forests, a cloud model, a multi-scale multiple linear regression model, and a weight matrix of the impact factors were constructed for the upper limit distribution height and impact factors of deciduous broad-leaved forests. The dataset includes : (1) geographical overview of nine mountains; (2) verification of upper limit distribution height and downscale temperature data in deciduous broad-leaved forests; (3) expectation, entropy, and hyper entropy of the influencing factor values and the upper limit distribution heights of deciduous broad-leaved forests of the nine mountains; (4) cloud diagram for the distribution height of the upper limit of montane deciduous broad-leaved forests; (5) summary of regression models, analysis of variance, regression analysis, and significance test results at different scales; (6) expectation, entropy, and hyper entropy of the weight coefficients of the influencing factors on the upper limit of the deciduous broad-leaved forests at different scales; (7) weights of the main influencing factors on the upper limit of the deciduous broad-leaved forests at the local scale; (8) 6800 points distributed in the upper limit of the deciduous broad-leaved forests. The dataset is archived in .shp and .xlsx data formats, and consists of 8 data files with data size of 4.52 MB (Compressed into one file with 547 KB). The analysis paper based on the dataset will be coordinated to be published at Acta Geographica Sinica in Vol. 78, No. 11, 2023.

Foundation Item:

National Natural Science Foundation of China (41401111); Natural Science Foundation of Shandong Province (ZR2021MD080); Shandong Provincial Key Laboratory of Eco-Environmental Science for Yellow River Delta (2022KFJJ03)

Data Citation:

WANG Zhiyong, HAN Fang*, LI Chuanrong, LI Kun, MU Haoxiang, WANG Zhe. Dataset of the Upper Limit of Montane Deciduous Broad-leaved Forests in the East Monsoon Realm of China[J/DB/OL]. Digital Journal of Global Change Data Repository, 2023. https://doi.org/10.3974/geodb.2023.11.09.V1.

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Data Product:

ID Data Name Data Size Operation
1 UpperlimitMontaneDBLF_EasternChina.rar 547.75KB
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