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中国西部地区历史草地面积重建的方法——以甘宁青新区为例
引用本文:杨帆,何凡能,李美娇. 中国西部地区历史草地面积重建的方法——以甘宁青新区为例[J]. 地理研究, 2020, 39(7): 1667-1679. DOI: 10.11821/dlyj020190588
作者姓名:杨帆  何凡能  李美娇
作者单位:1. 中国科学院地理科学与资源研究所 陆地表层格局与模拟重点实验室,北京 1001012. 中国科学院大学,北京1000493. 山西财经大学资源环境学院,太原 030006
基金项目:国家自然科学基金项目(41671149);国家重点研发计划(2017YFA0603304);中国科学院战略性先导科技专项(XDA19040101)
摘    要:历史草地面积重建作为历史土地利用与土地覆被变化研究的重要组成部分,可为区域乃至全球环境变化研究提供重要的基础数据。但受研究客体特性与重建资料多寡的制约,目前无论是数量估算上还是空间格局重建上均非常薄弱。本文试图在客观把握中国西部地区历史草地变化趋势与特征的基础上,利用现代遥感土地利用数据和潜在植被数据,确定土地垦殖前草地植被潜在分布范围;并结合历史耕地网格数据,构建以间接扣减为核心的草地面积重建方法;重建甘肃、宁夏、青海和新疆等省区过去300年的草地网格数据。结果表明:土地垦殖前,案例区草地覆被率高达40.87%。受土地垦殖的影响,在过去300年草地面积呈持续减少的态势。草地面积由1661年的1.11亿 hm2下降到1980年的1.03亿 hm2,并经历了1661—1724年的急剧减少、1724—1873年的缓慢减少和1873—1980年的快速减少三个时段,草地年均减少量分别为4.76万 hm2、0.75万 hm2和3.38万 hm2。在空间上,研究时段内草地垦殖区呈现出由甘肃、宁夏向青海、新疆转移的特点。以历史文献资料和1980年遥感草地网格数据为基础,对重建的草地数据开展了可靠性评估。评估显示,重建结果能够较好的再现草地变迁过程。本文构建的重建方法可被用于中国西部地区长时段的草地面积重建。

关 键 词:土地利用/覆被变化  草地覆被  面积重建  土地垦殖  中国西部  历史时期  
收稿时间:2019-07-11
修稿时间:2019-12-11

Methods for reconstructing historical grassland cover across western China: A case study in Gansu,Ningxia, Qinghai and Xinjiang
YANG Fan,HE Fanneng,LI Meijiao. Methods for reconstructing historical grassland cover across western China: A case study in Gansu,Ningxia, Qinghai and Xinjiang[J]. Geographical Research, 2020, 39(7): 1667-1679. DOI: 10.11821/dlyj020190588
Authors:YANG Fan  HE Fanneng  LI Meijiao
Affiliation:1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China2. University of Chinese Academy of Sciences, Beijing 100049, China3. College of Resources and Environment, Shanxi University of Finance and Economics, Taiyuan 030006, China
Abstract:Spatially explicit reconstruction of historical grassland cover can provide significant data for studies on the global and regional environmental change. However, being subject to the attribute of study objective and materials for reconstruction, progresses were rarely made both in the estimates of grassland area and the reconstruction of spatial patterns. Based on a good understanding of the grassland change history across western China, we attempted to determine the potential distribution extent of grassland cover without land reclamation using remote sensing-derived land use data and potential vegetation data. Then by overlaying Chinese historical cropland data over a map of the potential distribution extent of grassland vegetation, we proposed a reconstruction method of historical grassland cover across western China. Subsequently, as a case study, grassland cover maps in Gansu, Ningxia, Qinghai, and Xinjiang provinces during AD 1661 to AD 1980 were complied using this approach. The results show that: (1) the grassland coverage across the case area was 40.87% without land reclamation. However, due to the expansion of land reclamation, the amount of grassland decreased continuously, especially over the past 300 years. (2) The total area of grassland across this region decreased from 110.86 million ha in 1661 to 103.14 million ha in 1980. And changes in grassland area went through three phases over this study period, including a sharp decrease between 1661 and 1724, a slow decrease between 1724 and 1873, and a rapid decrease between 1873 and 1980. The average annual losses of grassland area in the three stages were 47.6 thousand ha, 7.5 thousand ha, and 33.8 thousand ha, respectively. Spatially, the main areas of grassland reclamation gradually transferred from Gansu and Ningxia to Qinghai and Xinjiang during the study period. (3) Based on historical archives and remote sensing-derived grassland data in 1980, we evaluated the reliability of the reconstructed grassland cover. Evaluations suggest that the reconstruction results captured the amounts and spatial distribution patterns of historical grassland cover well. Our methods can be used for the long-term reconstruction of grassland cover across western China.
Keywords:land use and land cover change  grassland cover  area estimation  land reclamation  western China  historical period  
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