基于随机森林回归的茶园扩张驱动机制分析

doi:10.19741/j.issn.1673-4831.2019.0334

Abstract

Abstract: Tea plantation and expansion, a typical process of regional land use/cover change (LUCC), is closely related to agricultural development and sustainable land use. Taking the Shihe District of Xinyang City, the main producing area of high quality green tea in China, as an example, the spatio-temporal evolution in the distribution pattern of tea plantations from 1990 to 2015 was explored by coupling with multi-source data such as remote sensing images and land use data, etc. Random forest (RF) regression was used to explore driving mechanism of tea production expansion over two periods (1990-2000 and 2000-2015). Twenty-six exploratory variables, such as topography, land use, soil types, etc. were classified into biophysical and socioeconomic categories at the levels of pixel and village; and treated as the factors driving tea plantation expansion. The results show that tea plantations in the Shihe District are mainly distributed in hilly areas and shallow mountainous areas. From 1990 to 2000, the area of tea plantation expanded rapidly with a growth rate of 65.2%, while the expansion rate slowed down during 2000-2015. Tea plantations mainly expanded in the northwest and southeast directions, growing towards water sources and roads. The results indicate that driving factors of high importance can be divided into two scales:distance between tea garden and urban center/rural residential area at pixel scale, and soil types, slope and mean elevation at rural scale. Economic and technological development reduced restrictions imposed by biophysical driving factors such as land use and soil conditions. Spatial socio-economic conditions are increasingly essential for tea plantation expansion. The tea plantation expansion has a strong marginal dependence on the main driving determinants as growth tends to occur within 2 km from the rural settlements, where the average slope is 16-18° at village pixel region. Random forest regression is an efficient and effective means to explore the mechanisms of tea plantation expansion, which could provide guidance for sustainable land use planning.

Key words: land use/cover change, tea plantation, random forest regression, driving factors, Shihe District

CLC Number:

LI Xue-rou, CHEN Fei-yan, LIN Ai-wen, ZOU Jian-cheng, ZHOU Zhi-gao. Driving Mechanism of Tea Plantation Expansion Using a Random Forest Regression Model[J]. Journal of Ecology and Rural Environment, 2020, 36(1): 44-52.

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Driving Mechanism of Tea Plantation Expansion Using a Random Forest Regression Model

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