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遥感技术与应用  2022, Vol. 37 Issue (1): 262-271    DOI: 10.11873/j.issn.1004-0323.2022.1.0262
草地遥感专栏     
结合遥感和统计数据的家畜分布网格化方法研究
李翔华1,2(),黄春林1(),侯金亮1,韩伟孝1,2,冯娅娅1,2,陈彦四1,2,王静3
1.中国科学院西北生态环境资源研究院 甘肃省遥感重点实验室,甘肃 兰州 730000
2.中国科学院大学,北京 100049
3.甘肃省食品检验研究院,甘肃 兰州 730000
Mapping Grid Livestock Distribution with Remote Sensing and Statistical Data
Xianghua Li1,2(),Chunlin Huang1(),Jinliang Hou1,Weixiao Han1,2,Yaya Feng1,2,Yansi Chen1,2,Jing Wang3
1.Key Laboratory of Remote Sensing of Gansu Province,Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China
2.University of Chinese Academy of Sciences,Beijing 100049,China
3.Gansu Food Inspection and Research Institute,Lanzhou 730000,China
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摘要:

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。

关键词: 随机森林回归空间降尺度家畜遥感    
Abstract:

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.

Key words: Random forest regression    Spatial downscaling    Livestock    Remote sensing
收稿日期: 2020-09-08 出版日期: 2022-04-08
ZTFLH:  TP79  
基金资助: 中国科学院战略性先导科技专项(A类)(XDA19040500);甘肃省重点研发计划项目(17YF1FA134)
通讯作者: 黄春林     E-mail: lixianghua@lzb.ac.cn;huangcl@lzb.ac.cn
作者简介: 李翔华(1996-),女,河南商丘人,硕士研究生,主要从事遥感大数据与数据空间化研究。E?mail: lixianghua@lzb.ac.cn
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引用本文:

李翔华,黄春林,侯金亮,韩伟孝,冯娅娅,陈彦四,王静. 结合遥感和统计数据的家畜分布网格化方法研究[J]. 遥感技术与应用, 2022, 37(1): 262-271.

Xianghua Li,Chunlin Huang,Jinliang Hou,Weixiao Han,Yaya Feng,Yansi Chen,Jing Wang. Mapping Grid Livestock Distribution with Remote Sensing and Statistical Data. Remote Sensing Technology and Application, 2022, 37(1): 262-271.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2022.1.0262        http://www.rsta.ac.cn/CN/Y2022/V37/I1/262

图1  研究区概况 审图号:GS (2019)1823
数据描述来源
水体>50%的区域为水体的像元CNLUCC[13]
核心城区人口密度≥10 000/km2付晶莹[14]
保护区生态系统类型保护区、生物物种保护区、自然遗迹保护区WDPA[15]
表1  适宜性掩蔽区域
类型数据来源
土地覆被林地百分比CNLUCC[20]
草地百分比CNLUCC[20]
耕地百分比CNLUCC[20]
荒漠百分比CNLUCC[20]
地形海拔汤国安[23]
坡度汤国安[23]
植被归一化植被指数MODND1F
气候白天地表温度MODLT1M
年降水量ITPCAS CMFD[25-27]
人类活动城市可达性Weiss等[28]
人口密度付晶莹[21]
表2  所选取的环境因子
图2  部分环境因子审图号:GS(2019)1823
图3  家畜分布网格化估算模型
图4  随机森林参数选择
图5  影响羊空间分布的环境因子重要性
图6  甘肃省羊的统计数据与预测结果对比图审图号:GS (2019)1823
RRMSERRMSE
训练数据0.960.138.2%
预测结果0.770.3723.3%
校正结果0.880.2415.1%
表3  模型预测精度评估
图7  县区尺度羊的统计与预测对比图
图8  不同生态区内县区面积与模型表现
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