结合RF和LandTrendr算法的黄河流域下游撂荒耕地提取与时空变化分析

    Extraction and spatiotemporal analysis of abandoned cultivated land in the Lower Reaches of Yellow River Basin using RF and LandTrendr algorithms

    • 摘要: 耕地撂荒是一种常见的土地利用与覆被变化现象,深刻影响着全球的农业生产和粮食安全。黄河流域作为中国重要的粮食生产基地,监测其撂荒耕地时空动态变化并分析其原因具有重要的现实意义。该研究以黄河流域下游兰考县、长垣县、封丘县和东明县为研究区,依托 Google Earth Engine(GEE)云平台,结合Landsat长时间序列影像,并通过分层随机采样与目视解译相结合的方式构建样本集,结合多维度特征,综合应用随机森林概率模型及LandTrendr变化检测方法,系统地提取2004—2022年撂荒耕地与休耕地,并对其动态变化进行深入分析。结果表明:1)基于土地覆被变化提取2022年撂荒耕地与非撂荒耕地的F1分数分别为0.80和0.87,而结合变化检测方法提取2004—2022年撂荒耕地,撂荒耕地与非撂荒耕地的平均F1分数分别达到0.87和0.89,精度显著提升;2)研究区撂荒耕地面积在2004—2022年间呈现先上升后波动式下降的趋势,平均面积为28.24 km2,2007年达到峰值49.35 km2,而休耕地分布零散且面积较小;3)农业机械化水平的提升有效遏制了撂荒现象,而粮食产量的提升可能会带来撂荒风险的增加,第一产业就业人数对撂荒影响有限。该研究通过结合随机森林与LandTrendr算法,实现了对撂荒耕地的精准提取,并揭示其变化趋势及影响因素,这为黄河流域下游制定针对性的农业政策,保障国家粮食安全提供了参考。

       

      Abstract: Cultivated land is one of the most basic natural resources in agricultural production for human survival. However, the large-scale cultivated land has been abandoned in China, due to the rural migration to the non-agricultural employment in the urban areas during rapid urbanization in recent years. Taking the vital grain production base in the Yellow River basin as the study area, this study aims to accurately and efficiently obtain the spatial distribution of abandoned cultivated land, particularly for national agricultural production and food security. The downstream regions of the Yellow River were specifically selected as Lankao, Changyuan, Fengqiu, and Dongming County. Landsat imagery was utilized to collect the image data from March to October, covering the years 2003 to 2023. The images were then preprocessed in this period. According to the differences among cultivated land and the rest land types, the vegetation indices, spectral, texture, topographic, and Kauth-Thomas features were extracted to construct the datasets for each year. Stratified sampling and visual interpretation were combined to obtain the sample datasets. The random forest and LandTrendr models were employed to extract the abandoned and fallow lands, excluding urban areas. The accuracy of the improved model was then validated on the abandoned cultivated land using F1-Score. The influencing factors were finally determined on the abandoned cultivated land. The results indicate that the EVI_p80, NDVI_p80EVI, and nir variables shared high importance and discriminability in the output using random forest. Statistical analysis was also performed on the area of abandoned and fallow land within the study area from 2004 to 2022. The results revealed that the area of abandoned cultivated land was found as a trend of initial increase followed by fluctuating decline, with an average area of abandoned cultivated land of 28.24 km². The maximum area of abandoned cultivated land was reached in 2007, amounting to 49.35 km². The abandonment area was effectively controlled after 2020. The area of fallow land was found to be relatively small and scattered. Furthermore, the F1-score values of 0.87 and 0.89 were achieved in the abandoned and non-abandoned cultivated land, respectively, indicating higher accuracy, compared with the land use/cover change extraction. A multivariate regression analysis was conducted to investigate the influencing factors on the abandoned cultivated land. A systematic investigation was implemented to incorporate the total agricultural production value, total mechanical power, grain production, and the number of employed individuals in the primary industry, particularly in relation to the area of abandoned cultivated land. The increasing level of agricultural mechanization can reduce the abandonment of cultivated land, while grain production can raise the risk of abandonment. Some regulations are required to prevent land abandonment. The cultivated land can be effectively protected to reduce the area of abandoned cultivated land, in order to ensure the national food security and the sustainable development of agriculture. This finding can provide an effective technical approach to monitoring the abandoned cultivated land in the Yellow River basin. The spatiotemporal patterns and driving factors of cultivated land abandonment can also offer valuable references to formulate the decision-making on agricultural production in China.

       

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