地理学报 ›› 2022, Vol. 77 ›› Issue (4): 835-851.doi: 10.11821/dlxb202204005
李郇1(), 许伟攀1, 黄耀福1, 陈浩辉2, 秦小珍1, 李颖3, 邓明亮3, 姜俊浩1, 秦雅雯1
收稿日期:
2021-08-23
修回日期:
2022-02-28
出版日期:
2022-04-25
发布日期:
2022-06-20
作者简介:
李郇(1964-), 男, 江西南昌人, 教授, 博导, 研究方向为经济地理、城市规划和乡村建设。E-mail: lixun@mail.sysu.edu.cn
基金资助:
LI Xun1(), XU Weipan1, HUANG Yaofu1, CHEN Haohui2, QIN Xiaozhen1, LI Ying3, DENG Mingliang3, JIANG Junhao1, QIN Yawen1
Received:
2021-08-23
Revised:
2022-02-28
Published:
2022-04-25
Online:
2022-06-20
Supported by:
摘要:
中国农房分布研究是乡村振兴的基础性工作之一。本文利用Mask R-CNN深度学习框架,采用亚米级遥感影像,基于中国各省农房的人文地理特征,分省训练出适用于本地的农房遥感解译模型,共识别1484个县的1.54亿栋农房,总建筑面积达298.2亿m2,创建出以单体农房为基础的多尺度中国农房数据库。本文分别以县域、镇域和聚落为单元进行农房密度分析:县域单元的农房密度呈现“东密西疏”的分布特征,与胡焕庸线揭示的人口分布格局相符;镇域单元的农房密度沿三大地形阶梯自西向东递增,分布从集中走向平均,与农业区划的农业生产力、地形地貌特征高度耦合;聚落单元的农房分布则呈现“南密北疏”特征形态,与气候条件、地形地貌、人均耕地等相关联。中国农房数据库的建设将为“可计算的”乡村研究奠定基础。
李郇, 许伟攀, 黄耀福, 陈浩辉, 秦小珍, 李颖, 邓明亮, 姜俊浩, 秦雅雯. 基于遥感解译的中国农房空间分布特征分析[J]. 地理学报, 2022, 77(4): 835-851.
LI Xun, XU Weipan, HUANG Yaofu, CHEN Haohui, QIN Xiaozhen, LI Ying, DENG Mingliang, JIANG Junhao, QIN Yawen. Spatial distribution of rural building in China: Remote sensing interpretation and density analysis[J]. Acta Geographica Sinica, 2022, 77(4): 835-851.
表1
中国九大农业区基本信息与农房分布特征(仅包含农业县)
密度 梯队 | 农业区划 (仅包括有效识别 的1409个农业县) | 农业区基本信息 | 农房分布特征 | |||||||
---|---|---|---|---|---|---|---|---|---|---|
国土面积 占比(%) | 户籍人口 占比(%) | 耕地面积 占比(%) | 人均耕地 (m2/人) | 建筑面积 占比(%) | 农房栋数 占比(%) | 镇域农房面积 密度平均值 (m2/km2) | 农房基 尼系数 | |||
一 | 黄淮海区 | 4.50 | 24.50 | 18.80 | 1311 | 23.10 | 31.90 | 31311 | 0.31 | |
二 | 长江中下游区 | 9.70 | 23.80 | 14.10 | 1012 | 28.30 | 19.20 | 20660 | 0.51 | |
华南区 | 5.50 | 8.70 | 3.90 | 767 | 9.30 | 8.50 | 15363 | 0.58 | ||
三 | 西南区 | 13.30 | 21.80 | 8.00 | 628 | 20.90 | 16.30 | 12162 | 0.53 | |
黄土高原区 | 7.10 | 9.50 | 10.10 | 1811 | 8.40 | 9.60 | 11944 | 0.60 | ||
四 | 甘新区 | 32.00 | 2.80 | 10.50 | 6510 | 3.80 | 4.90 | 6972 | 0.72 | |
内蒙古及长城沿线区 | 5.90 | 3.70 | 15.10 | 7033 | 2.50 | 4.00 | 4660 | 0.62 | ||
东北区 | 7.00 | 4.40 | 18.40 | 7087 | 2.90 | 5.20 | 4550 | 0.55 | ||
五 | 青藏区 | 15.10 | 0.90 | 1.10 | 2135 | 0.70 | 0.50 | 713 | 0.72 |
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