| 民国中期湖南洞庭湖区耕地空间格局重建 |
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| 引用本文： | 连丽聪,万智巍,鞠民,贾玉连,洪祎君,蒋梅鑫,曾峰海.民国中期湖南洞庭湖区耕地空间格局重建[J].地球信息科学,2020,22(5):989-996. |
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| 作者姓名： | 连丽聪 万智巍 鞠民 贾玉连 洪祎君 蒋梅鑫 曾峰海 |
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| 作者单位： | 1.江西师范大学地理与环境学院 鄱阳湖湿地与流域研究教育部重点实验室,南昌 3300222.中国科学院地理科学与资源研究所 陆地表层格局与模拟院重点实验室,北京 100101 |
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| 基金项目： | 国家自然科学基金项目(41761045) |
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| 摘 要： | 土地覆被变化是影响气候系统的重要因素,在全球气候变化研究中具有重要的研究意义,网格化的历史土地利用数据集广泛应用于各类全球变化模式。本文以民国中期军事地形图为基础数据源,以现代行政区划为底图,重建了该时期湖南洞庭湖地区耕地的空间分布。同时为了与最新的HYDE 3.1数据集进行对比,在此基础上获得空间分辨率为10 km×10 km的耕地数据,结果表明：① 民国中期湖南洞庭湖区总耕地面积约为11 432.01 km 2,占研究区域面积的44%,其中汉寿县、华容县、鼎城区和澧县等地耕地面积分布最多,且以围堤耕地为主。分布相对较少的地区有临澧县、汨罗市、岳阳县,以非围堤耕地为主;② 该时段内洞庭湖区耕地垦殖率较大,最大值超过90%,其中高垦区（垦殖率>40%）范围占研究区面积61%,且主要分布在河湖港汊和冲积平原地貌单元上;中低垦区（<=40%）范围占研究区面积39%,主要分布在环湖丘陵地貌单元上;③ 与HYDE 3.1数据对比发现,单位格网（10 km×10 km）内重建的耕地面积结果误差大于40%的比例为17%,且表现为受河流分布影响为主。湖区相对周围重建结果差异更大,HYDE 3.1数据集重建区域尺度较大,较难考虑到小区域范围的水系分布状况,导致其在湖南洞庭湖区重建精度相对较低。
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| 关 键 词： | 民国中期 湖南 洞庭湖区 耕地空间分布 格局变化 网格化重建 历史地形图 土地利用 |
| 收稿时间： | 2019-09-25 |
Reconstruction of the Cropland Area and Its Spatial Distribution Pattern at Dongting Lake District of Hunan Province in the Middle of the Republic of China |
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| LIAN Licong,WAN Zhiwei,JU Min,JIA Yulian,HONG Yijun,JIANG Meixin,ZENG Fenghai.Reconstruction of the Cropland Area and Its Spatial Distribution Pattern at Dongting Lake District of Hunan Province in the Middle of the Republic of China[J].Geo-information Science,2020,22(5):989-996. |
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| Authors: | LIAN Licong WAN Zhiwei JU Min JIA Yulian HONG Yijun JIANG Meixin ZENG Fenghai |
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| Institution: | 1. Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China2. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China |
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| Abstract: | Land cover change is an important factor affecting the climate system and has important research significance in global climate change researches. Gridded historical land use data have been widely used in various global change models. This study used the military topographic map of the Republic of China as the basic data source and modern administrative divisions as the base map, to reconstruct the spatial distribution of croplands in the Dongting Lake district of Hunan during the period of Republic of China. To compare with the HYDE 3.1 data, the cropland data were constructed at a spatial resolution of 10 km×10 km. Results show that: (1) the total area of croplands in Dongting Lake district during the period of Republic of China was about 11432.01 km 2, accounting for 44% of the study area. The area of croplands in Hanshou, Huarong, Ding cheng, and Li xian, was the largest, dominated by dike farmland. Linli, Miluo, and Yueyang had less croplands, which were mainly non-dike cultivated land; (2) the land reclamation rate of Dongting Lake district during this period was large, with the maximum value greater than 90%. High reclamation areas with reclamation rate >40% accounted for 61%, and mainly occurred in the river estuary regions or alluvial plain. Low reclamation areas with <=40% accounted for 39%, and mainly distributed in the hilly landscape area; (3) compared to the HYDE 3.1 dataset, the error of constructed cropland area within a grid (10 km×10 km) greater than 40% accounted for 17%, which was mainly affected by the distribution of rivers. The reconstruction area in the HYDE 3.1 dataset was relatively large. It was difficult to consider the distribution of water systems in a small area, which leads to a relatively low reconstruction accuracy in the Dongting Lake district of Hunan. This paper uses the measured maps of the Republic of China to reconstruct the spatial distribution of croplands in the embankment area of the Dongting lake during this period, which provides basic data for land use and regional sustainable development in the lake area. |
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| Keywords: | Republic of China Hunan province Dongting lake district cropland spatial distribution pattern change grid reconstruction military topographic map land use |
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