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Figure/Table detail
An explanation of conversion of cultivated land into forestland from the perspective of non-agricultural employment for rural labor force: A case study of Xintai City, Shandong Province
MA Huiwen, WANG Maojun, LIU Tao, CAO Guangzhong
PROGRESS IN GEOGRAPHY
, 2024, 43(
4
): 709-726. DOI:
10.18306/dlkxjz.2024.04.007
Fig.8
Comparison of cultivated land use patterns between villages in the Chaiwen River basin and villages far from the Chaiwen River Basin in Xintai City
Other figure/table from this article
Fig.1
A framework of analysis for the relationship between rural labor non-agricultural employment and conversion of cultivated land into forestland
Fig.2
Location and geographical conditions of Xintai City, Shandong Province of China
Tab.1
Village population migration and employment section of the questionnaire
Tab.2
The area of conversion of cultivated land into forestland and its proportion in cultivated land reduction in 14 villages of Xintai City
Fig.3
Spatial distribution of the scale of conversion of cultivated land into forestland in villages in Xintai City
Fig.4
Statistics of the area and the number of patches of converted cultivated land into forestland in villages of different towns of Xintai City
Fig.5
Spatial distribution of the scale of all-household emigration, partial emigration, and living in the village for non-farming employment types of households
Fig.6
Spatial distribution of population scale at different migration destinations and destinations of living in the village for non-farming employment
Tab.3
Descriptive statistics and expected effects of variables
Fig.7
Correlation coefficient matrix between variables
Tab.4
Model regression results of influencing factors of the conversion of cultivated land into forestland
Fig.9
Spatial distribution of cultivated land transfer and the relationship between the proportion of cultivated land transfer and the proportion of conversion of cultivated land into forestland in villages in Xintai City, China
Tab.5
Estimated results of the instrumental variables model