黑龙江省耕地时空变化及驱动因素分析

以黑龙江省1980年、1990年、2000年、2010年、2015年5期土地利用数据为基础，综合利用GIS手段和地理探测器模型，确定1980—2015年4个时期黑龙江省耕地变化的时空分异特征及主要驱动因素。研究结果表明，1980—2015年黑龙江省耕地数量总体增加，增加的耕地主要来源于林地、草地和未利用地。各时期耕地数量变化具有明显差异，以1990—2000年耕地数量变化最多。各时期耕地变化空间差异特征明显。1980—2015年黑龙江省耕地利用动态度呈现出先升高后降低的趋势，耕地利用动态度活跃区域集中在三江平原和松嫩平原地区。各时期驱动因子的解释能力不同，人口数量、政策因素、GDP以及城镇化水平是解释能力较强的驱动力因子。驱动因子对耕地时空变化的影响是通过各个因子之间的交互作用实现的，表现为双因子增强和非线性增强。

Spatial and Temporal Changes and Driving Factors of Cultivated Land in Heilongjiang Province

It is of great practical significance for protecting cultivated land and guaranteeing national food security to thoroughly explore the spatio-temporal variation characteristics and driving factors of cultivated land. Based on the land use data of Heilongjiang Province in 1980, 1990, 2000, 2010 and 2015, this article determined the spatiotemporal differentiation characteristics and main driving factors of cultivated land change in Heilongjiang Province in the four periods from 1980 to 2015 by using GIS and geographical detector model. The results show that from 1980 to 2015, the cultivated land quantity in Heilongjiang Province increased, and the increased cultivated land mainly came from forest land, grassland and unused land. The variation of cultivated land quantity in each period was obviously different, with the largest variation from 1990 to 2000. The spatial difference of cultivated land change in each period was obvious. From 1980 to 2015, the dynamic degree of cultivated land use in Heilongjiang Province showed a trend of increasing first and then decreasing, and the regions with active dynamic degree of cultivated land use were concentrated in the Sanjiang Plain and the Songnen Plain. The explanatory ability of drivers factors are different in each period. Population size, policy factors, GDP and urbanization level are the driving factors with strong explanatory ability. The influence of driving factors on the spatiotemporal change of cultivated land is realized through the interaction of various factors, which is manifested as double factor enhancement and nonlinear enhancement.