<b>Characterizing dynamics of building height in China from 2005 to 2020 based on GEDI, Landsat, and PALSAR data</b>

The unprecedented urbanization in China has driven rapid urban and rural development in recent decades. While existing studies have extensively focused on horizontal urban expansion, research on vertical urban expansion patterns in China remains limited. To address this gap, we proposed a Multi-Temporal Building Height estimation network (MTBH-Net) to estimate building heights at a 30 m spatial resolution in China for 2005, 2010, 2015, and 2020 by integrating Global Ecosystem Dynamics Investigation (GEDI), Landsat, and PALSAR data. Specifically, we introduced sample migration to generate reference building height data and utilized the Continuous Change Detection and Classification (CCDC) disturbance feature to ensure consistency in unchanged built-up areas. Validation with GEDI L2A V2 data demonstrated that MTBH-Net achieved RMSEs of 5.38 m, 5.73 m, 6.26 m, and 6.36 m for the respective years. Further validation with field-measured data and GF-7 building height data yielded RMSEs of 9.13 m and 10.99 m, respectively. The proposed 30-m China Multi-Temporal Building Height (CMTBH-30) dataset reveals an increase in average building heights in China from 10.48 m in 2005 to 11.37 m in 2020, reflecting an upward trend in urban development. Additionally, the standard deviation of building heights rose from 3.87 m in 2005 to 6.35 m in 2020, indicating increased height variation nationwide. Regional analysis from 2005 to 2020 shows notable vertical growth on newly expanded impervious surfaces in Macau (+14.9 m), Hong Kong (+13.9 m), and Guangdong (+13.5 m), while Chongqing (+3.6 m), Guizhou (+3.0 m), and Qinghai (+3.0 m) also experienced significant growth on stable impervious surfaces. Minimal growth was observed in Jilin, Heilongjiang, and Xinjiang. CMTBH-30 offers a more refined and accurate depiction of building heights, effectively capturing height variations and mitigating the underestimation of high-rise buildings. It fills the gap in multi-temporal building height estimation. Overall, this study provides a new dime

近数十年来，中国史无前例的城镇化进程推动了城乡的快速发展。现有研究已广泛关注城市的横向扩张，但针对中国城市垂直扩张模式的相关研究仍较为匮乏。为填补这一研究空白，本研究提出了多时序建筑高度估算网络（Multi-Temporal Building Height estimation network, MTBH-Net），通过整合全球生态系统动态调查（Global Ecosystem Dynamics Investigation, GEDI）、Landsat与PALSAR数据，对中国2005、2010、2015及2020年的建筑高度开展30米空间分辨率的估算。具体而言，本研究引入样本迁移方法生成参考建筑高度数据集，并利用持续变化检测与分类（Continuous Change Detection and Classification, CCDC）扰动特征，保障建成区未变化区域的一致性。通过GEDI L2A V2数据开展验证，结果表明MTBH-Net在对应年份的均方根误差（Root Mean Square Error, RMSE）分别为5.38米、5.73米、6.26米与6.36米。进一步采用野外实测数据与高分七号（GF-7）建筑高度数据进行验证，其均方根误差分别为9.13米与10.99米。本研究构建的30米分辨率中国多时序建筑高度数据集（CMTBH-30）显示，中国建筑平均高度从2005年的10.48米提升至2020年的11.37米，反映出城市发展的上升态势。此外，建筑高度的标准差从2005年的3.87米升至2020年的6.35米，表明全国范围内建筑高度的差异持续扩大。2005至2020年的区域分析结果显示，澳门（+14.9米）、香港（+13.9米）与广东（+13.5米）的新增不透水面区域实现了显著的垂直增长；重庆（+3.6米）、贵州（+3.0米）及青海（+3.0米）的稳定不透水面区域也呈现出显著增长。吉林、黑龙江与新疆的建筑高度增长则较为有限。CMTBH-30数据集能够更精细、准确地刻画建筑高度分布，有效捕捉高度差异并缓解了对高层建筑的低估问题，填补了多时序建筑高度估算领域的研究空白。总体而言，本研究为相关领域提供了新的维度

搜集汇总

背景与挑战

背景概述

该数据集通过整合GEDI、Landsat和PALSAR数据，使用MTBH-Net方法估算了2005-2020年中国30米分辨率的建筑高度变化，显示全国平均建筑高度从10.48米增至11.37米，并揭示了不同地区的垂直增长差异，为研究中国城市化进程提供了新的维度。