中国地理科学 ›› 2018, Vol. 28 ›› Issue (6): 946-956.doi: 10.1007/s11769-018-1004-0

• 论文 • 上一篇    下一篇

An Assessment of Snow Cover Duration Variability Among Three Basins of Songhua River in Northeast China Using Binary Decision Tree

YANG Qian1,2, SONG Kaishan1, HAO Xiaohua3, CHEN Shengbo4, ZHU Bingxue4   

  1. 1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;
    2. College of Geomatics and Prospecting Engineering, Jilin Jianzhu University, Changchun 130000, China;
    3. China Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China;
    4. College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China
  • 收稿日期:2017-09-28 修回日期:2018-01-16 出版日期:2018-12-27 发布日期:2018-11-01
  • 通讯作者: SONG Kaishan.E-mail:songks@neigae.ac.cn E-mail:songks@neigae.ac.cn
  • 基金资助:

    Under the auspices of National Natural Science Foundation of China (No. 41471291, 41801283, 41070104), Startup Foundation for Doctors of Jilin Jianzhu University (No. 861111), 13th Five-Year Plan of Technical and Social Research Project for Jilin Colleges (No. JJKH20170257KJ)

An Assessment of Snow Cover Duration Variability Among Three Basins of Songhua River in Northeast China Using Binary Decision Tree

YANG Qian1,2, SONG Kaishan1, HAO Xiaohua3, CHEN Shengbo4, ZHU Bingxue4   

  1. 1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;
    2. College of Geomatics and Prospecting Engineering, Jilin Jianzhu University, Changchun 130000, China;
    3. China Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China;
    4. College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China
  • Received:2017-09-28 Revised:2018-01-16 Online:2018-12-27 Published:2018-11-01
  • Contact: SONG Kaishan.E-mail:songks@neigae.ac.cn E-mail:songks@neigae.ac.cn
  • Supported by:

    Under the auspices of National Natural Science Foundation of China (No. 41471291, 41801283, 41070104), Startup Foundation for Doctors of Jilin Jianzhu University (No. 861111), 13th Five-Year Plan of Technical and Social Research Project for Jilin Colleges (No. JJKH20170257KJ)

摘要:

The dynamics of snow cover differs greatly from basin to basin in the Songhua River of Northeast China, which is attributable to the differences in the topographic shift as well as changes in the vegetation and climate since the hydrological year (HY) 2003. Daily and flexible multi-day combinations from the HY 2003 to 2014 were produced using Moderate Resolution Imaging Spectroradiometer (MODIS) from Terra and Aqua remote sensing satellites for the snow cover products in the three basins including the Nenjiang River Basin (NJ), Downstream Songhua River Basin (SD) and Upstream Songhua River Basin (SU). Snow cover duration (SCD) was derived from flexible multiday combination each year. The results showed that SCD was significantly associated with elevation, and higher SCD values were found out in the mountainous areas. Further, the average SCDs of NJ, SU and SD basins were 69.43, 98.14 and 88.84 d with an annual growth of 1.36, 2.04 and 2.71 d, respectively. Binary decision tree was used to analyze the nonlinear relationships between SCD and six impact factors, which were successfully applied to simulate the spatial distribution of depth and water equivalent of snow. The impact factors included three topographic factors (elevation, aspect and slope), two climatic factors (precipitation and air temperature) and one vegetation index (Normalized Difference Vegetation Index, NDVI). By treating yearly SCD values as dependent variables and six climatic factors as independent variables, six binary decision trees were built through the combination classification and regression tree (CART) with and without the consideration of climate effect. The results from the model show that elevation, precipitation and air temperature are the three most influential factors, among which air temperature is the most important and ranks first in two of the three studied basins. It is suggested that SCD in the mountainous areas might be more sensitive to climate warming, since precipitation and air temperature are the major factors controlling the persistence of snow cover in the mountainous areas.

关键词: Binary decision tree, MODIS, snow cover duration, topography, climate changes

Abstract:

The dynamics of snow cover differs greatly from basin to basin in the Songhua River of Northeast China, which is attributable to the differences in the topographic shift as well as changes in the vegetation and climate since the hydrological year (HY) 2003. Daily and flexible multi-day combinations from the HY 2003 to 2014 were produced using Moderate Resolution Imaging Spectroradiometer (MODIS) from Terra and Aqua remote sensing satellites for the snow cover products in the three basins including the Nenjiang River Basin (NJ), Downstream Songhua River Basin (SD) and Upstream Songhua River Basin (SU). Snow cover duration (SCD) was derived from flexible multiday combination each year. The results showed that SCD was significantly associated with elevation, and higher SCD values were found out in the mountainous areas. Further, the average SCDs of NJ, SU and SD basins were 69.43, 98.14 and 88.84 d with an annual growth of 1.36, 2.04 and 2.71 d, respectively. Binary decision tree was used to analyze the nonlinear relationships between SCD and six impact factors, which were successfully applied to simulate the spatial distribution of depth and water equivalent of snow. The impact factors included three topographic factors (elevation, aspect and slope), two climatic factors (precipitation and air temperature) and one vegetation index (Normalized Difference Vegetation Index, NDVI). By treating yearly SCD values as dependent variables and six climatic factors as independent variables, six binary decision trees were built through the combination classification and regression tree (CART) with and without the consideration of climate effect. The results from the model show that elevation, precipitation and air temperature are the three most influential factors, among which air temperature is the most important and ranks first in two of the three studied basins. It is suggested that SCD in the mountainous areas might be more sensitive to climate warming, since precipitation and air temperature are the major factors controlling the persistence of snow cover in the mountainous areas.

Key words: Binary decision tree, MODIS, snow cover duration, topography, climate changes