Jiang Lu, Zhao Haitao, Cao Biao, He Wei, Yun Zengxin, Cheng Chen
School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China.
Sensors (Basel). 2024 Sep 27;24(19):6267. doi: 10.3390/s24196267.
UAV thermal infrared remote sensing technology, with its high flexibility and high temporal and spatial resolution, is crucial for understanding surface microthermal environments. Despite DJI Drones' industry-leading position, the JPG format of their thermal images limits direct image stitching and further analysis, hindering their broad application. To address this, a format conversion system, ThermoSwitcher, was developed for DJI thermal JPG images, and this system was applied to surface microthermal environment analysis, taking two regions with various local zones in Nanjing as the research area. The results showed that ThermoSwitcher can quickly and losslessly convert thermal JPG images to the Geotiff format, which is further convenient for producing image mosaics and for local temperature extraction. The results also indicated significant heterogeneity in the study area's temperature distribution, with high temperatures concentrated on sunlit artificial surfaces, and low temperatures corresponding to building shadows, dense vegetation, and water areas. The temperature distribution and change rates in different local zones were significantly influenced by surface cover type, material thermal properties, vegetation coverage, and building layout. Higher temperature change rates were observed in high-rise building and subway station areas, while lower rates were noted in water and vegetation-covered areas. Additionally, comparing the temperature distribution before and after image stitching revealed that the stitching process affected the temperature uniformity to some extent. The described format conversion system significantly enhances preprocessing efficiency, promoting advancements in drone remote sensing and refined surface microthermal environment research.
无人机热红外遥感技术具有高度灵活性以及高时空分辨率，对于理解地表微热环境至关重要。尽管大疆无人机在行业中处于领先地位，但其热图像的JPG格式限制了直接图像拼接和进一步分析，阻碍了其广泛应用。为解决这一问题，针对大疆热JPG图像开发了一种格式转换系统ThermoSwitcher，并将该系统应用于地表微热环境分析，以南京两个具有不同局部区域的地区作为研究区域。结果表明，ThermoSwitcher能够快速且无损地将热JPG图像转换为Geotiff格式，这进一步便于生成图像镶嵌图以及提取局部温度。结果还表明，研究区域的温度分布存在显著的异质性，高温集中在阳光照射的人工表面，而低温对应于建筑物阴影、茂密植被和水域。不同局部区域的温度分布和变化率受到地表覆盖类型、材料热特性、植被覆盖度和建筑物布局的显著影响。在高层建筑和地铁站区域观察到较高的温度变化率，而在水域和植被覆盖区域则观察到较低的变化率。此外，比较图像拼接前后的温度分布发现，拼接过程在一定程度上影响了温度均匀性。所描述的格式转换系统显著提高了预处理效率，推动了无人机遥感以及精细化地表微热环境研究的进展。
