The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and i...The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources,waste,and climate strategies.However,our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited,largely owing to the lack of sufficient high spatial resolution data.This study leveraged multi-source big geodata,machine learning,and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels.The per capita built environment stock of many cities(261 tonnes per capita on average)is close to that in western cities,despite considerable disparities across cities owing to their varying socioeconomic,geomorphology,and urban form characteristics.This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades.China’s urban expansion tends to be more“vertical”(with high-rise buildings)than“horizontal”(with expanded road networks).It trades skylines for space,and reflects a concentration-dispersion-concentration pathway for spatialized built environment stocks development within cities in China.These results shed light on future urbanization in developing cities,inform spatial planning,and support circular and low-carbon transitions in cities.展开更多
Airborne laser scanning （ALS） is a technique used to obtain Digital Surface Models （DSM） and Digital Terrain Models （DTM） efficiently, and filtering is the key procedure used to derive DTM from point clouds. Gen...Airborne laser scanning （ALS） is a technique used to obtain Digital Surface Models （DSM） and Digital Terrain Models （DTM） efficiently, and filtering is the key procedure used to derive DTM from point clouds. Generating seed points is an initial step for most filtering algorithms, whereas existing algorithms usually define a regular window size to generate seed points. This may lead to an inadequate density of seed points, and further introduce error type I, especially in steep terrain and forested areas. In this study, we propose the use of object- based analysis to derive surface complexity information from ALS datasets, which can then be used to improve seed point generation. We assume that an area is complex if it is composed of many small objects, with no buildings within the area. Using these assumptions, we propose and implement a new segmentation algorithm based on a grid index, which we call the Edge and Slope Restricted Region Growing （ESRGG） algorithm. Surface complexity information is obtained by statistical analysis of the number of objects derived by segmentation in each area. Then, for complex areas, a smaller window size is defined to generate seed points. Experimental results show that the proposed algorithm could greatly improve the filtering results in complex areas, especially in steep terrain and forested areas.展开更多
The continuous, over two-decade data record from the Multi-Filter Rotating Shadowband Radiometer （MFRSR） is ideal for climate research which requires timely and accurate information of important atmospheric componen...The continuous, over two-decade data record from the Multi-Filter Rotating Shadowband Radiometer （MFRSR） is ideal for climate research which requires timely and accurate information of important atmospheric components such as gases, aerosols, and clouds. Except for parameters derived from MFRSR measurement ratios, which are not impacted by calibration error, most applications require accurate calibration factor（s）, angular correction, and spectral response function（s） from calibration. Although a laboratory lamp （or reference） calibration can provide all the information needed to convert the instrument readings to actual radiation, in situ calibration methods are implemented routinely （daily） to fill the gaps between lamp calibrations. In this paper, the basic structure and the data collection and pretreatment of the MFRSR are described. The laboratory lamp calibration and its limita- tions are summarized. The cloud screening algorithms for MFRSR data are presented. The in situ calibration methods, the standard Langley method and its variants, the ratio-Langley method, the general method, Alexandrov＇s comprehensive method, and Chen＇s multi-channel method, are outlined. The reason that all these methods do not fit for all situations is that they assume some properties, such as aerosol optical depth （AOD）, total optical depth （TOD）, precipitable water vapor （PWV）, effective size of aerosol particles, or angstrom coefficient, are invariant over time. These properties are not universal and some of them rarely happen. In practice, daily calibration factors derived from these methods should be smoothed to restrain elTor.展开更多
The concern about the role of aerosols as to their effect in the Earth-Atmosphere system requires observation at multiple temporal and spatial scales. The Moderate Resolution Imaging Spectroradiameters （MODIS） is th...The concern about the role of aerosols as to their effect in the Earth-Atmosphere system requires observation at multiple temporal and spatial scales. The Moderate Resolution Imaging Spectroradiameters （MODIS） is the main aerosol optical depth （AOD） monitoring satellite instrument, and its accuracy and uncertainty need to be validated against ground based measurements routinely. The comparison between two ground AOD measurement programs, the United States Department of Agriculture （USDA） Ultmviolet-B Monitoring and Research Program （UVMRP） and the Aerosol Robotic Network （AERONET） program, confirms the consistency between them. The intercomparison between the MODIS AOD, the AERONET AOD, and the UVMRP AOD suggests that the UVMRP AOD measurements are suited to be an alternative ground-based validation source for satellite AOD products. The experiments show that the spatial-temporal dependency between the MODIS AOD and the UVMRP AOD is positive in the sense that the MODIS AOD compare more favorably with the UVMRP AOD as the spatial and temporal intervals are increased. However, the analysis shows that the optimal spatial interval for all time windows is defined by an angular subtense of around 1° to 1.25°, while the optimal time window is around 423 to 483 minutes at most spatial intervals. The spatial-temporal approach around 1.25° ＆ 423 minutes shows better agreement than the prevalent strategy of 0.25° ＆ 60 minutes found in other similar investigations.展开更多
基金supported by the National Natural Science Foundation of China (71991484,42271471,72088101,and 41830645)Danish Agency for Higher Education and Science (International Network Project,0192-00056B)the Fundamental Research Funds for the Central Universities (Peking University).
文摘The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources,waste,and climate strategies.However,our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited,largely owing to the lack of sufficient high spatial resolution data.This study leveraged multi-source big geodata,machine learning,and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels.The per capita built environment stock of many cities(261 tonnes per capita on average)is close to that in western cities,despite considerable disparities across cities owing to their varying socioeconomic,geomorphology,and urban form characteristics.This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades.China’s urban expansion tends to be more“vertical”(with high-rise buildings)than“horizontal”(with expanded road networks).It trades skylines for space,and reflects a concentration-dispersion-concentration pathway for spatialized built environment stocks development within cities in China.These results shed light on future urbanization in developing cities,inform spatial planning,and support circular and low-carbon transitions in cities.
基金Acknowledgements The authors would like m thank the anonymous reviewers for providing comments to improve the quality of this paper, and iSPACE of Research Studios Austria FG （RSA） （http：//ispace.researchstudio. at/） for providing the ALS datasets. The study described in this paper is funded by the National Natural Science Foundation of China （Grant No. 41301493）, the High Resolution Earth Observation Science Foundation of China （GFZX04060103-5-17）, and Special Fund for Surveying and Mapping Scientific Research in the Public Interest （201412007）.
文摘Airborne laser scanning （ALS） is a technique used to obtain Digital Surface Models （DSM） and Digital Terrain Models （DTM） efficiently, and filtering is the key procedure used to derive DTM from point clouds. Generating seed points is an initial step for most filtering algorithms, whereas existing algorithms usually define a regular window size to generate seed points. This may lead to an inadequate density of seed points, and further introduce error type I, especially in steep terrain and forested areas. In this study, we propose the use of object- based analysis to derive surface complexity information from ALS datasets, which can then be used to improve seed point generation. We assume that an area is complex if it is composed of many small objects, with no buildings within the area. Using these assumptions, we propose and implement a new segmentation algorithm based on a grid index, which we call the Edge and Slope Restricted Region Growing （ESRGG） algorithm. Surface complexity information is obtained by statistical analysis of the number of objects derived by segmentation in each area. Then, for complex areas, a smaller window size is defined to generate seed points. Experimental results show that the proposed algorithm could greatly improve the filtering results in complex areas, especially in steep terrain and forested areas.
文摘The continuous, over two-decade data record from the Multi-Filter Rotating Shadowband Radiometer （MFRSR） is ideal for climate research which requires timely and accurate information of important atmospheric components such as gases, aerosols, and clouds. Except for parameters derived from MFRSR measurement ratios, which are not impacted by calibration error, most applications require accurate calibration factor（s）, angular correction, and spectral response function（s） from calibration. Although a laboratory lamp （or reference） calibration can provide all the information needed to convert the instrument readings to actual radiation, in situ calibration methods are implemented routinely （daily） to fill the gaps between lamp calibrations. In this paper, the basic structure and the data collection and pretreatment of the MFRSR are described. The laboratory lamp calibration and its limita- tions are summarized. The cloud screening algorithms for MFRSR data are presented. The in situ calibration methods, the standard Langley method and its variants, the ratio-Langley method, the general method, Alexandrov＇s comprehensive method, and Chen＇s multi-channel method, are outlined. The reason that all these methods do not fit for all situations is that they assume some properties, such as aerosol optical depth （AOD）, total optical depth （TOD）, precipitable water vapor （PWV）, effective size of aerosol particles, or angstrom coefficient, are invariant over time. These properties are not universal and some of them rarely happen. In practice, daily calibration factors derived from these methods should be smoothed to restrain elTor.
文摘The concern about the role of aerosols as to their effect in the Earth-Atmosphere system requires observation at multiple temporal and spatial scales. The Moderate Resolution Imaging Spectroradiameters （MODIS） is the main aerosol optical depth （AOD） monitoring satellite instrument, and its accuracy and uncertainty need to be validated against ground based measurements routinely. The comparison between two ground AOD measurement programs, the United States Department of Agriculture （USDA） Ultmviolet-B Monitoring and Research Program （UVMRP） and the Aerosol Robotic Network （AERONET） program, confirms the consistency between them. The intercomparison between the MODIS AOD, the AERONET AOD, and the UVMRP AOD suggests that the UVMRP AOD measurements are suited to be an alternative ground-based validation source for satellite AOD products. The experiments show that the spatial-temporal dependency between the MODIS AOD and the UVMRP AOD is positive in the sense that the MODIS AOD compare more favorably with the UVMRP AOD as the spatial and temporal intervals are increased. However, the analysis shows that the optimal spatial interval for all time windows is defined by an angular subtense of around 1° to 1.25°, while the optimal time window is around 423 to 483 minutes at most spatial intervals. The spatial-temporal approach around 1.25° ＆ 423 minutes shows better agreement than the prevalent strategy of 0.25° ＆ 60 minutes found in other similar investigations.
