大面积建成区建筑密度遥感制图产品的精度验证

doi:10.7523/j.issn.2095-6134.2020.01.010

中国科学院大学学报 ›› 2020, Vol. 37 ›› Issue (1): 83-92.DOI: 10.7523/j.issn.2095-6134.2020.01.010

大面积建成区建筑密度遥感制图产品的精度验证

王帅^1,2, 覃驭楚¹, 杨富坤^1,2

1 中国科学院遥感与数字地球研究所遥感科学国家重点实验室, 北京 100101;
2 中国科学院大学资源与环境学院, 北京 100049

收稿日期:2018-10-10 修回日期:2018-12-25 发布日期:2020-01-15
通讯作者: 覃驭楚
基金资助:
中国科学院战略性先导专项（XDA19030102）和中国科学院百人计划项目资助

Validation for building density remote sensing products of built-up areas at large scale

WANG Shuai^1,2, QIN Yuchu¹, YANG Fukun^1,2

1 State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;
2 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

Received:2018-10-10 Revised:2018-12-25 Published:2020-01-15

摘要/Abstract

摘要： 大面积建成区建筑密度遥感制图产品能够提供土地开发强度与人类居住环境的基础信息，是支撑人居环境研究和土地利用规划的重要数据。全球人类居住区层（global human settlement layer，GHSL）是由欧盟联合研究中心负责的大面积人居环境制图项目，建成区建筑密度遥感制图产品是GHSL重要的组成部分。目前该产品在欧美地区已经完成了GHSL建成区建筑密度遥感制图产品的验证。然而以中国为代表的东亚区域的建筑物形态和城市布局与欧美等区域有较大的差别，有必要在亚洲地区对其进一步验证。以中国的5个典型城市（上海、西安、长春、昆明和乌鲁木齐）大面积单体建筑物分布图为基础，通过聚合分析和邻域关键点搜寻匹配等算法，生成中国建成区建筑密度栅格图像产品作为验证数据，然后通过回归分析等方法，在像元尺度上对GHSL建成区遥感制图产品进行评价验证。结果显示，GHSL建成区建筑密度产品在较低分辨率下可以反映中国地区建筑密度情况，但在较高分辨率下在高值区过高估计密度。本研究可以为中国地区研发建成区建筑面积密度产品提供依据。

关键词: 全球人类居住区层, 建成区面积, 单体建筑分布图, 验证

Abstract: Building density map (BDM) product derived from remotely sensed imagery over large areas is the vital data set for supporting studies of human settlement environment and land use planning. GHSL (global human settlement layer) is a mapping project for developing human settlement map product with remotely sensed data. It is sponsored by the Joint Research Center of European Commission. The BDM is an important component of GHSL. Currently, the BDM of GHSL has been validated over Europe and America. However, the shapes of buildings and the landscape patterns of urban areas in East Asia, especially in China, are significantly different from those in the EU and US, and the validation of BDM over Asia is vital for further applications of the GHSL products. This study takes large area individual building footprint data sets over 5 typical mega cities (Shanghai, Xi'an, Changchun, Kunming and Urumqi) as ground truth through the pixel aggregation and the neighboring points searching and location matching, and the ground truth map of the building density is produced as the validation data set. With regression analysis, the method for BDM assessment is explored by calculating accuracy indicators over large metro-areas in China. The results show that the GHSL building density products of built-up areas reflect the densities of buildings in China at lower resolutions, but at higher resolutions they overestimate the densities in high-value areas. This study provides a basis for research and development of built-up area density products in China.

Key words: GHSL(global human settlement layer), built-up area, individual building footprint data, validation

中图分类号:

P237
TP75

王帅, 覃驭楚, 杨富坤. 大面积建成区建筑密度遥感制图产品的精度验证[J]. 中国科学院大学学报, 2020, 37(1): 83-92.

WANG Shuai, QIN Yuchu, YANG Fukun. Validation for building density remote sensing products of built-up areas at large scale[J]. , 2020, 37(1): 83-92.

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大面积建成区建筑密度遥感制图产品的精度验证

Validation for building density remote sensing products of built-up areas at large scale

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