结合遥感和统计数据的家畜分布网格化方法研究

Mapping Grid Livestock Distribution with Remote Sensing and Statistical Data

家畜的空间分布对于粮食安全、农业社会经济、环境影响评估和人畜共患病的研究等方面至关重要。选取甘肃省作为典型研究区,以羊为研究对象,基于随机森林回归算法构建了融合遥感数据和统计数据的家畜分布网格化估算模型,获得甘肃省1 km×1 km尺度上羊的空间分布信息。结果表明:基于随机森林回归的家畜分布网格化估算模型,结合了遥感数据和统计数据的优势,可以较准确地估算1 km×1 km尺度上家畜的空间分布情况,估算结果与统计数据之间的相关系数(R)达到0.88,均方根误差(RMSE)为0.24,相对均方根误差(RRMSE)为15.1%。甘肃省的羊主要分布在河西走廊戈壁区、甘南高原草原草甸区、黄土高原丘陵区的西南部以及黄土高原沟壑区的北部。对羊的空间分布影响较大的环境因子依次是:耕地百分比、海拔、地表温度和坡度。

The livestock’s distribution across space is essential to the research on food safety,agricultural society economy,environmental influence assessment and zoonosis.In this study,an approximation model of livestock’s distribution across space was constructed on the basis of Random Forest(RF)regression algorithm to combine remote sensing data and statistical data.In order to test and validate the proposed method,statistics for sheep in 87 counties of Gansu Province was collected in 2010 and 11 environmental factors were considered in this scheme.Finally,the spatial distribution information of sheep on the scale of 1 km×1 km in Gansu Province is obtained by the model.As is indicated by the results,the grid model of livestock’s spatial distribution based on the RF regression has included the advantages of both remote sensing data and statistical data.It is able to estimate the spatial distribution situation of sheep on the scale of 1 km×1 km with certain accuracy.The correlation coefficient(R)between estimated results and statistical data reached 0.88,the Root Mean Square Error(RMSE)was 0.24,and the Relative Root Mean Square Error(RRMSE)was 15.1%.Sheep in Gansu Province are mainly distributed in the Gobi area of the Hexi Corridor,the grassland and meadow area of the Gannan Plateau,the southwestern part of the hilly area of the Loess Plateau,and the northern part of the gully area of the Loess Plateau.The environmental factors that have a greater impact on the spatial distribution of sheep are:percentage of cultivated land,altitude,surface temperature,and slope.