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  • 2015 Volume 17 Issue 11
    Published: 11 November 2015
      

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  • TANG Shihao,LIU Ronggao
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    Climate dataset is the basis of satellite-based climate research. This paper formalizes some basic concepts of satellite data from the view of climate study first. On that basis, the classification problem of Climate Data Records(CDR) is discussed. The authors proposed that current classification method, which classifies CDR into two categories, FCDR(Fundamental Climate Data Record)and TCDR(Thematic Climate Data Record), is not enough to reflect the characteristics of remote sensing dataset. It‘s necessary to further classify TCDR into three categories, including dataset generated from single instrument, dataset generated from multiple instruments, and dataset generated from multiple sources. The advantage of this classification scheme is that it’s helpful to discriminate climate datasets which have the same name but generated from different data sources or by different algorithms. In this manner, users can understand and utilize the data more easily and correctly. Then, this paper introduces Essential Climate Variables (ECV), essential satellite-based climate variables and the guideline for the generation of satellite-based climate datasets respectively, and reviews the recent progresses made by NOAA, NASA, ESA and other international remote sensing organizations. The author especially emphasized that some guidelines and principles for the generation of satellite-based climate data records have been proposed and made common senses among the majority of international remote sensing organizations, and new climate data records following international standards are being produced. Finally, the paper discusses some issues faced during the construction and application of satellite-based climate datasets, and gives some specific suggestions on the development of China's satellite-based climate datasets.

  • ZHOU Cong,SHI Runhe,GAO Wei
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    Recently, direct observational radiance evidence at two ground-based stations in Southern Great Plains and the North Slope of Alaska confirmed that the theoretical predictions of the atmospheric greenhouse effect due to anthropogenic emissions and provided empirical evidence of how the rising CO2 levels affected the surface energy balance. Therefore, it is important to retrieve CO2 concentration with high precision globally and further to analyze its sources and sinks. This research focuses on the comparison between near-surface and mid-tropospheric CO2 difference characteristics. First, the CO2 products from AIRS (Atmospheric Infrared Sounder) and GOSAT (Greenhouse gases Observing SATellite) were compared globally during 2010 to 2013. Time series result showed that the mid-tropospheric CO2 concentrations in each month from AIRS were all higher than the near-surface CO2 retrieved from GOSAT, which maybe because of the well-mixed of CO2 in mid-troposphere. And the spatial distribution of four year average CO2 was different between AIRS and GOSAT. As for AIRS, the high value region was between 30°N to 90°N, which affected by large amount of land and high human activity. However, the high value region for GOSAT CO2 occurred in tropical and subtropical area, such as Africa and Eastern China with a large population, which is not revealed by AIRS mid-troposphere CO2. The result demonstrates the significance of satellite sensitive to near-surface CO2 like GOSAT, which can provide important information in near-surface to make up the lack of ground-based stations. Moreover, the differences of CO2 between ocean and land, North Hemisphere (NH) and South Hemisphere (SH) were analyzed. The seasonal features of mean CO2 in ocean and land were similar, while CO2 value of land were higher than that of ocean due to human activity. In addition, different characteristics of CO2 in NH and SH was related to the opposite seasonal patterns in both hemispheres. And higher CO2 value occurred in NH because of the burn of fossil fuel. With the degradation of AIRS, CrIS (Cross-track Infrared Sounder) instrument on Suomi NPP (National Polar-orbiting Partnership) was launched in 2011, and promises to provide high quality data like AIRS. Therefore, the CO2 column average and vertical profile products that generated from CSPP (Community Satellite Processing Package) NUCAPS (NOAA/NESDIS/STAR NOAA Unique CrIS/ATMS Processing System) were analyzed for the first time and found consistent conclusions with the comparison between AIRS and GOSAT CO2.

  • SHI Xueli,ZHANG Fang,ZHOU Wenyan,ZHANG Yanwu
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    The land cover (LC) datasets of CG-LTDR was applied in the Beijing Climate Center Land Model (BCC_AVIM 1.0). The impacts of different LC type updates on the ground temperature (Tg) were investigated through several numerical simulations. The results show that the CG-LTDR can reasonably describe the LC features. Compared with the original LC rawdata, the glacier fraction of the new CG-LTDR datasets were extensively increased in the high-latitude regions of the Greenland Island and Europe, as well as the Tibetan Plateau; the fraction of wetland was decreased in the major water body areas of North America and Europe; and the percentage of lake was also majorly decreased in the North American inland water area, but slightly increased around the Tibetan Plateau. The PFT present the largest differences between the new and original datasets. Besides the control runs with the original LC dataset (CTL), five simulations were conducted to compare different impacts of LC types (the glacier, wetland, lake, PFT and all types) on Tg. The changes of Tg due to LC dataset updates majorly constrained in the areas where the LC types (fraction) were modified. With the individual updates of glacier (rGlacier), the simulated Tg was lowered in the high-latitude areas. The simulated Tg with new wetland (rWetland) was increased, while the simulated Tg with the new lake (rLake) datasets were effectively decreased in the Tibetan Plateau. These changes were helpful to improve the model performances on Tg simulations. The most significant and extensive changes among the 4 LC types occurred when updating the PFT (rPFT), which were helpful for reducing the errors in the south and east Asian areas, but enlarged the biases in the other regions. The LC dataset updates of all types (rALL) show the most significant impacts on the Tg simulations, which was not simply the linear sum of the individual updates of LC types, especially in the areas having complex types. Therefore, proper introductions of new CG-LTDR land cover datasets were useful to improve the model performance in Tg simulations.

  • LIU Yang,LIU Ronggao
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    Leaf area index (LAI) is a primary parameter for charactering the water, carbon and energy exchanges among soil, vegetation and the atmosphere. Global long-term LAI datasets help to understand the response and feedback of vegetation to climate change. In this paper, the global LAI was retrieved during a 32-year period from 1981 to 2012 by utilizing a combination of MODIS measurements and reprocessed long-term data record (LTDR) AVHRR observations. The high-quality MODIS observations were used to constrain the LAI retrieval from historical AVHRR data, by establishing the pixel-by-pixel relationship between them directly. Thus, the inconsistency of LAI derived from these two notably different sensors could be reduced, and the quality of LAI derived from AVHRR data could be improved. Firstly, MODIS LAI series (2000-2012) were generated from high-quality MODIS land surface reflectance based on the GLOBCARBON LAI algorithm. Then, the relationships between AVHRR Simple Ratio (SR) and MODIS LAI were regressed pixel-by-pixel using the multi-year average values of these two data for each 8-day period. After that, the AVHRR LAI was estimated from historical AVHRR observations based on these pixel-level relationships from 1981 to 1999. The retrieved LAI could represent the spatial distribution of global vegetation and the seasonal characteristics of the major biomes. The LAI derived from AVHRR was inter-compared with that from MODIS. The results demonstrate a good consistency between the LAIs from these two different sensors. The comparison with NASA MODIS standard products of MOD15A2 shows that our results are consistent with MOD15A2 in both spatial pattern and seasonal cycle.

  • SHANG Rong,LIU Ronggao,LIU Yang
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    Global continuous long-term surface albedo products are of great importance to land surface process and climate modeling research. Problems such as severe data missing and low effective retrieval percentage in the current albedo products made them difficult to meet the requirements of climate modeling perfectly. To solve those problems, this paper made two improvements on MODIS albedo product algorithm. One improvement was to modify the way of composing and selecting enough directional reflectance, which were used for the generation of background BRDF parameters. We assumed that the surface would change little in the same time period during different years. Therefore, all directional reflectance of multi-years for each time period could be used for the composition and selection, in which at least 7 valid directional reflectance for each pixel were used to conduct the BRDF retrieval. Another improvement was the quantitative data fusion between MODIS and AVHRR data, which helped to expand the temporal coverage of albedo products to 30 years. Validation results showed that this new albedo product kept great consistency with the relatively homogeneous SURFRAD site albedos and was almost the same with MODIS snow-free albedo product. These were no spatial or temporal data missing in this new albedo product and the temporal coverage had been greatly improved. Therefore, this new albedo product would be more suitable for the applications of land surface process and climate modeling research.

  • HE Huijuan,SHI Xueli
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    Based on CG-LTDR datasets, the land cover change and distribution characteristics during 1990-2010 were analyzed in China using the GIS spatial statistical analysis and other mathematical statistics methods. Compared with the reference data of CLUD, CG-LTDR land cover data has a higher classification precision. The new datasets show that the land cover indicates obvious interannual evolutions due to the climate and human activities, especially in the semi-arid and semi-humid areas distributed along Inner Mongolia to Yunnan Province. The synthetic land cover data for 5 years were used to eliminate the interannual fluctuations and to increase accuracy. The results show that the land cover types in China had changed dramatically during 1990-2000 and indicated a relatively smooth pattern during 2000-2010, which is related to the application of national policy and economic development. Among the four major land cover types, the increase of woodland area was the most significant, which is mainly due to the land use transformation from farmland to woodland in the Southeast China, and grassland into woodland in the southwest and northeast part of China. But due to the deforestation and cropland expansion, the coverage of woodland was decreased in some of the Northeast and Northwest China regions. Farmland has the largest coverage in China, while its decreasing trend is mainly caused by its transformation toward woodland and grassland. The most significant decrease of farmland appeared in the south part of China, while a slight increase was revealed in some of the Northern China. The increase of woodland and decrease of farmland were related to the national policy of "returning farmland to forest" and relevant ecological environment constructions. Grassland was mainly distributed in the ecological fragile region, and was prone to convert into other land cover types. Moreover, grassland decreased most evidently around China, because of the changes among different land cover types. To be specific, grassland was turned into woodland in Southwest China. And, grassland and farmland was interactively converted into each other along the conjunction areas from the middle east of Inner Mongolia to the north of Shaanxi Province. Additionally, grassland and bareland was converted interactively along the regions from the northern of Inner Mongolia to Tibetan Plateau. The bareland was mainly located in the Northwest China, while showing an increasing trend due to the degradation of grassland.

  • WANG Yuanxiang,TANG Shihao,ZHENG Zhaojun
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    Vegetation is an important part of the terrestrial ecosystem, and it is the natural bond for linking land, atmosphere and ecosphere. Vegetation changes with climate and human activity, thus, studying its sudden and trend changes is an important subject. Using the methods of 3-year moving t-test, Mann-Kendall test (MK-test) and anomaly analysis, the sudden and trend changes of the normalized difference vegetation index (NDVI of AVHRR GIMMS) in China from May to September during 1982 to 2006, as well as their causes were analyzed. The t-test and MK-test results show that there was a sudden change of NDVI in the eastern China in 1998, and there couldn’t be a sudden change of NDVI in the northeast China and the Tibetan Plateau during 1982 to 2006. The changing trend of NDVI indicates that there was an increasing trend during 1982 to 1998, and then a decreasing trend from 1999 to 2006 in the eastern China. The causes of the sudden and trend changes of NDVI reveal that with the massive urbanization process in China that started in the late 1990s, the city and built-ups increased and the arable area decreased, and the NDVI indicated a sudden change with the vegetation decreased in the eastern China. Moreover, the satellite instruments and climate factors couldn’t be the main causes of the decreasing vegetation in the eastern China.

  • CAO Dongjie,ZHENG Zhaojun,TANG Shihao,WANG Yuanxiang
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    Comparing with other satellite sensors, AVHRR has the capability to analyze more than 10 years of medium-resolution satellite imagery on a daily basis. AVHRR thereby holds a great potential to detect, map and quantify long-term environmental changes. However, different satellites use different retrieval algorithms, wavelength bandwidths and atmospheric validations. So it is important to compare different snow cover products retrieved by different satellites. Here, we describe and extensively validate the snow cover products of the historical 0.05°×0.05° AVHRR data. The spatial and seasonal validation includes a comparison with IMS and MOD10A1. It is found that the AVHRR snow products are in good accordance with the MODIS snow products. The influence of acquisition geometry and the sensor-to-sensor consistency will be discussed in future.

  • SHI Jun,CUI Linli,YANG Hanwei,SUN Landong
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    Based on the temperature, precipitation data and main weather phenomenon records from 11 meteorological stations, the spatial and temporal distributions and the changes of main climate elements and the weather phenomena in Shanghai were analyzed using climate statistical diagnosis technology. The results indicate that the annual average temperature in Shanghai was higher in the urban areas and lower in the surrounding suburbs, with a maximum difference of 0.9 ℃; and the precipitation was heavier in the urban areas and southern suburbs, while less in the northern and western surrounding suburbs. The annual high temperature days were also greater in the urban areas than in the eastern and southern coastal areas, with a maximum difference of 9.5 days; and the annual torrential rain days were greater in the urban areas and Pudong region, but less in the western regions of Shanghai. The number of thunderstorm, gale and fog days did not show significant differences between the urban areas and suburbs. The annual haze days in the urban areas were evidently greater than those in the suburbs, with a maximum difference of 49.2 days. During the period from 1961 to 2013, the annual average temperature increased significantly while the annual precipitation increased slightly in Shanghai. The annual high temperature days and haze days increased with a linear rate of 2.7 and 11.3 days per decade respectively, while the annual thunderstorm, gale and fog days decreased with a linear rate of 1.9, 3.7 and 5.2 days per decade respectively in the past 53 years in Shanghai.

  • WANG Meng,LI Guicai,WANG Junbang,SUN Xiaofang,GUO Zhaodi
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    Net primary production (NPP) quantifies the net carbon contained by plants, which is of great importance to estimate the terrestrial carbon sink. Monitoring regional carbon storage in the form of NPP is, therefore, indispensable for improving the health state of the biosphere and system for carbon credit trading. In this study, the spatial and temporal patterns of NPP and their climatic controls in the ecosystems of India for the period of 1983-2008 were analyzed using a remote sensing based GLOPEM-CEVSA carbon model and piecewise regression methods. Results showed that the average annual NPP of the study area from 1983 to 2008 was 414.29 gC·m-2·a-1. The mean NPP of forest, cropland and grassland were 1002.32 gC·m-2·a-1, 485.98 gC·m-2·a-1, and 631.39 gC·m-2·a-1 respectively. At the national scale, a statistically insignificant positive trend of NPP was observed during 1983-2008. However, the increasing trend in NPP was not continuous throughout the 26-year period at the national scale. There were two distinct periods with opposite trends in NPP during 1983-2008. A significant turning point in 1996 was detected by the piecewise regression method. Firstly, NPP increased significantly from 1983 to 1996, while it then decreased from 1996 to 2008. The increase in NPP was primarily due to the enhancement of productivity over agricultural lands in the country. There are further spatial analyses supporting the concluded trend of average NPP. At the regional scale, the turning points appeared mostly in the 1991-2000 period. Savanna experienced the earliest trend of change. Climate had a strong impact on NPP during the period. The correlation coefficients indicated that the inter-annual variability in NPP was primarily driven by the precipitation and temperature variability. NPP in the northwest India was negatively correlated to temperature and positively correlated to precipitation. NPP in south Himalaya forest was positively correlated to temperature. NPP in southern region of India was negatively correlated to precipitation. These results are critical to understand the response of vegetation growth and carbon cycle to environmental change.

  • ZHOU Jing,ZHANG Shuliang,ZHANG Xiaobo
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    :With the popularization of online map application, place name information retrieval has become a key issue in the related study areas and many promising findings have been achieved. However, these studies mainly focused on the efficiency of retrieval and the matching quality of text information, without considering possible contradictories between the practical application requirements and place name retrieval methods. Currently, many online map platforms generally take POI or point of place name as the retrievable objects, and get results through retrieving text key words. However, this approach ignores the spatial information of place name. This paper studies the forms and methods of place name information retrieval by combining geographic entity and place name based on analyzing the relationship between them. From the view of data feature and application scenes, a new place name information retrieval mode is proposed, which can fully express the structure of geographic entity. This retrieval mode takes geographic entities' attributes and their spatial relationship as the retrieval feature items. With this mode, this paper proposes a place name information retrieval model based on geographic entity similarity. In the meantime, the similarity calculation method for attribute that integrates text attribute and number attribute, and the similarity calculation method for spatial relationship that integrates qualitative spatial filtration and quantitative distance calculation are also presented. Finally, a series of validation experiments are conducted to test the practicability and accuracy of the proposed model. Results show that the retrieval method not only considers the details and spatial characteristics of the retrieval objects, but also ensures the accuracy as well as the quality of the search results.

  • CHEN Qing,HOU Xiyong
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    Population spatialization could effectively remove the obstacles for data fusion between census data and geographic data. With the rapid development of RS and GIS techniques, the research methods of population spatialization have been updated greatly, and among them, both land use data and DMSP/OLS data are the most widely used data sources for population spatialization. However, both of them have advantages and disadvantages, in specific, the patches of cities and rural settlements in land use data indicate the area of population distribution accurately, but land use data lacks detailed features of population distribution, especially for that existing in the same type of land use; DMSP/OLS data manifests the spatial variations of population density, however it often overestimates the distribution area of population due to its 'overglow' effect, and at the same time, the problem of pixel saturation in DMSP/OLS data also impairs the fitness of this data. In this paper, land use data and DMSP/OLS data are combined together to distinguish the night light data value of populated area, and the methodologies of population spatialization are improved by introducing the precision threshold and dynamic regionalization method. Census data in 2000, 2005 and 2010 for China’s coastal area are taken as examples to test the outcomes of the improved methodologies for population spatialization. The results show that: (1) due to the prominent spatial heterogeneity of population distribution in China’s coastal area, unitary model based on DMSP/OLS data for the whole study area exhibits very poor precision, therefore, land use maps are utilized to distinguish the populated and non-populated area based on DMSP/OLS images. Compared with the threshold method, land use maps more effectively removes the ‘overglow’ effect of DMSP/OLS data; (2) precision threshold of the regression model is adopted to dynamically divide the whole study area into several sub-regions, in specific, only counties that meet the testing accuracy defined by the precision threshold could retain in the regression model, otherwise, they should be regrouped into a new set of samples and be fitted by a new regression model. It is named as ‘dynamic regionalization’ method in this paper. The results show that this method further improves the overall accuracies of population spatialization data.

  • MA Mingjuan,WANG Liming,DONG Nan
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    With the acceleration of urbanization in China, it has become increasingly urgent to analyze city space structure, explore spatial difference of urban development, and make regional development policy. Therefore, the research on urban spatial interaction has great instructive significance. Urban potential is a representative index of urban spatial interaction. It reflects the spatial interactions between one city and the other cities from the same urban system. In fact, urban potential indicates the city’s capability of agglomeration. Previous studies on urban potential mostly focused on using point data to represent the spatial position of a city, and then simulate its urban potential. However, simulations based on this method would deviate from the real situations to some extent. The reason is that, on one hand, the geographic coordinates of the administrative center do not coincide with the urban center; on the other hand, most cities are composed of several separated urban patches, and these patches may also interact with each other. To solve the problems caused by using point data in representing city’s spatial position in the urban potential researches, we took 26,619 urban patches extracted from Globcover data sets as the fundamental research objects. In this way, not only the spatial interactions between different cities, but also the spatial interactions between different urban patches within the same city could be taken into consideration. We adopted DMSP/OLS stable nighttime light data as the data source to attain the size of urban patches, which is taken as one variable in the potential model. The DMSP/OLS stable nighttime light data has advantages including the rapid update frequency and the wide coverage. The total night light index derived from the image reflects the social economic activities of human comprehensively. A raster map, in which its cell value represents urban potential, was produced by using a potential model that is one of the typical spatial interactive models after assigning values to its two variables. Based on the map, we analyzed the spatial differentiation of urban potential. As a conclusion, this paper provided a method for using new data sources to simulate urban potential.

  • YANG Xunfeng,LI Lianfa,WANG Jinfeng,HUANG Jixia
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    The objectives of this study were to estimate the effects of temperature on cardiovascular mortality in three cities of Anhui Province from 2008 to 2011, including Chaohu city, Yushan district of Ma’anshan city and Tianchang city. A separate Poisson generalized additive model (GAM) was fitted on a daily basis to explore the relationship between cardiovascular mortality and temperature for each city. The model used smooth functions to model the nonlinear effects of temperature and humidity on cardiovascular mortality, and to take control for the seasonal factor using the calendar time variable. A J-shaped relationship between cardiovascular mortality and temperature was observed for each city, indicating that an increasing trend at high or low temperature condition is associated with an increase in cardiovascular mortality. The threshold temperatures were 29.0°C, 26.6°C and 26.9°C for Chaohu city, Yushan district and Tianchang city, respectively. The percentage increase in cardiovascular mortality for Chaohu city, Yushan district and Tianchang city were 1.06% (95%CI: 0.39%-1.74%), 2.18% (95% CI: 1.56%~2.81%) and 0.89% (95% CI: -0.11%~1.90%) respectively, with a decrease of 1°C below the threshold temperature. And the percentage increase were 2.92% (95%CI: -2.19%~8.30%), 4.87% (95%CI: -0.11%~10.10%) and 2.06% (95%CI: -2.57%~6.91%) respectively, with an increase of 1°C above the threshold temperature. The effects of temperature on cardiovascular mortality are heterogeneous across cities, which suggest that preventive steps or public health programs should take regional differences into consideration.

  • YUE Xiliu,HUANG Mei,XU Qingyong,CHEN Changyan,GU Xiaoping
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    Guizhou is a typical karst mountainous province in China, which has unique geological disaster mechanism due to its unique geological environment. In this study, 10 factors were selected as the possible impact factors, and the cluster analysis and correlation analysis methods were used to identify the main risks of debris flow factors. Based on the techniques of geo-information system, information model was used to evaluate the spatial pattern of debris flow susceptibility. Soil erosion is identified as the most important factor to influence the occurrence of native debris flow, while fault has little impact on debris flow. Factors of soil erosion, slop, aspect, rock characteristics, land use, NDVI, distance to gully and days of daily precipitation greater than 25mm are proved to be independent and representative factors, and they served as indices for susceptibility assessment. The results show that 29.51% of the regions in Guizhou are heavy susceptibility regions, which were located in western Guizhou and the mountainous area, such as Dalou mountain, Wuling mountain and Miaoling in northern Guizhou. The central and southeastern Guizhou is identified as relative less susceptibility region. Heavy susceptibility areas have common characteristics of steep slope, low vegetation coverage, featuring with dry land, industrial and mining land, and are subjected to serious soil erosion. The debris flow density in heavy susceptibility region is 19 times of that in the low susceptibility region. The effective way to decrease debris flow disaster is to strengthen the management of dry land, industrial and mining land, and the area with lower vegetation cover.

  • YE Juanjuan,YANG Xin,XIONG Liyang,YAN Yanzi,WANG Tingting
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    Urban architecture is an important ingredient of urban morphology, and the building height has an important influence on 3D urban morphology. Nowadays, many researches have focused on 2D urban morphology, but only a few studies focus on the 3D morphological characteristics and the spatial distribution pattern of urban cities. Also, studies on utilization and organization of the air space above cities are scarce. Based on urban digital elevation model (UDEM) of Nanjing old town, the urban architectures were simplified and transformed from rectangle representations into 3D point elements, and then were classified into four types of point groups according to the building height. The 3D macroscopic characteristics and spatial distribution pattern of the Nanjing old town architectures were studied using point pattern analysis method. The results showed that: (1) the building distribution pattern in Nanjing old town was clustered in the order shown as follows: low-rise buildings > high-rise buildings > multistory buildings>ultra-tall buildings. Except for super-tall buildings, the cluster degree for the other three types of buildings increased firstly and then decreased, and the highest value appeared at 1.5km, indicating that the block unit at this spatial scale was the most appropriate unit for urban planning in Nanjing old town. (2) The building height distribution in Nanjing old town showed three high-valued areas which were in the New Model Road, Xin Jiekou District and Zhu Jiang Road, and one low-valued area which appeared in the Jiqing Arch Street. All of them have good corresponding relations with the city center in different historical periods, and the distribution of building height also has a correlation with urban benchmark land price. The above results further demonstrated that the point pattern analysis is an effective method to analyze the characteristics of urban construction in planar and three-dimensional space, which is helpful for studying urban morphology characteristics.

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