京津冀地区气溶胶时空分布及与城市化关系的研究

利用AERONET（AErosol RObotic NETwork）数据对2008~2012年Terra MODIS（MOderate-resolutionImaging Spectroradiometer）C006 3 km卫星遥感气溶胶产品在京津冀地区的适用性进行了验证,分析京津冀地区3km分辨率气溶胶光学厚度（AOD）的时空分布和变化特征。利用DMSP（Defense Meteorological Satellite System）/OLS（Operational Linescan System）夜间灯光数据作为城市化评价手段,对京津冀地区城市化与AOD时空分布之间的关系进行了研究。结果表明:（1）MODIS 3 km气溶胶产品遥感反演数据和同期AERONET监测数据在研究区具有很好的一致性,相关系数达0.91,满足期望要求;（2）时间上,2008~2012年研究区年平均AOD值在0.361~0.453之间变化,年际间变化浮动大,总体呈下降趋势;AOD春季呈明显下降趋势,夏季总体呈微弱上升趋势,秋季和冬季呈明显上升趋势;（3）空间上,2008~2012年北京、天津和河北中南部的AOD值较高,河北北边AOD值较低;四季AOD空间分布呈现较强烈季节变化,夏季最高,冬季最低;（4）夜间灯光数据和AOD时空分布不仅在空间分布上呈现较好的一致性,且2008~2012年二者的地理权重回归（GWR）模型拟合度R2达0.8左右。研究区内AOD与夜间灯光数据二者相关性显著,城市化发展水平和人类活动对气溶胶的分布有着明显的影响。     

100 global bright spots of green growth: Co-occurrence of nighttime light gain and forest gain, 1990–2015

Economic growth commonly occurs at the expense of environmental quality, but there are exceptions. Here we use satellite data to identify places where exceptional economic growth and exceptional environmental improvement co-occurred between 1990 and 2015. We term as “bright spots of green growth” those spatial clusters with the most cells above the 95th percentile within their world region in both economic growth (as proxied by increase in nighttime lights) and one aspect of environmental improvement (forest area). Because the locations of bright spots are sensitive to methodological choices, we applied two different approaches to identifying bright spots. The two approaches differed in their choice of nighttime lights data (DSMP-OLS in Approach A vs. DSMP-VIIRS composite in Approach B); choice of forest area data (forest cover vs. forest land-use); time period (2000–2010 vs. 1990–2015); and clustering technique (visual inspection vs. HDBSCAN algorithm). We identified the top five bright spots in each of ten world regions using each of two approaches, for a total of 100 global bright spots of green growth. We then tested the extent to which the attributes of bright spots were consistent with four non-mutually exclusive theories of green growth. Of the bright spots we identified, around two-thirds (65% using Approach A; 71% using Approach B) had significantly higher-than-regional-average growth in the share of labor employed in services, consistent with sectoral shift and “tertiarization.” Fewer than half (38%; 46%) had significantly higher growth in income, consistent with the “Environmental Kuznets Curve” theory. Some (54%; 29%) had significantly higher growth in timber plantation area, consistent with “eco-industry”-driven rural development. Few (0%; 10%) had significantly higher growth in protected area coverage, consistent with public policy-induced forest conservation. Our findings suggest sectoral shift toward services, rather than rising income per se, may be a promising pathway for other regions seeking to combine economic growth and environmental improvement.     

基于复合指数模型的DMSP/OLS夜间灯光影像饱和校正方法

由于OLS传感器航行过程中增益记录和交叉定标的缺失,使得DMSP夜光影像在城市中心出现过度饱和等问题,因此探讨灯光数据去饱和方法在人类活动强度评估和城市时空演化分析等方面具有重要意义。为了解决这一难题,有学者提出使用NDVI修正饱和灯光数据的VANUI指数,为研究灯光数据去饱和提供了简单便捷的思路,然而该指数在部分城市中较难有明显的校正效果。本文在VANUI指数思想的基础上,顾及到人口密度随着郊区到城市中心距离的增加呈现指数型增长,提出了基于复合指数模型校正夜间灯光指数CEANI,为人类活动强度评价等研究提供更准确的结果。研究表明:① 与VANUI相比,CEANI在刻画城市内部饱和区域特征时具有更好的细节,较好地凸显城市内部空间异质性;② 在25组随机样本的相关对比中,CEANI（R²mean=0.79）与辐射定标产品比VANUI（R²mean=0.68）具有更高的相关性;③ 三大城市群中CEANI与常住人口的R²分别为0.767、0.676和0.841,比VANUI（R²分别为0.640、0.553和0.775）分别提高了0.127、0.123、0.066,相较于VANUI,CEANI与常住人口具有更强的相关性,对于人口指标的估算能力更强。     

Remote sensing of human beings – a perspective from nighttime light

City lights, fishing boats, and oil fields are the major sources of nighttime lights, therefore the nighttime light images provide a unique source to map human beings and their activities from outer space. While most of the scholars focused on application of nighttime light remote sensing in urbanization and regional development, the actual fields are much wider. This paper summarized the applications of nighttime light remote sensing into fields such as the estimation of socioeconomic parameters, monitoring urbanization, evaluation of important events, analyzing light pollution, fishery, etc. For estimation of socioeconomic parameters, the most promising progress is that Gross Domestic Product and its growth rate have been estimated with statistical data and nighttime light data using econometric models. For monitoring urbanization, urban area and its dynamics can be extracted using different classification methods, and spatial analysis has been employed to map urban agglomeration. As sharp changes of nighttime light are associated with important socioeconomic events, the images have been used to evaluate humanitarian disasters, especially in the current Syrian and Iraqi wars. Light pollution is another hotspot of nighttime light application, as the night light is related to some diseases and abnormal behavior of animals, and the nighttime light images can provide light pollution information on large scales so that it is much easier to analyze the effects of light pollutions. In each field, we listed typical cases of the applications. At last, future studies of nighttime light remote sensing have been predicted.     

Observational study of surface ozone at an urban site in East China

In this study, we present the observational data of near surface ozone and some meteorological parameters during 2004, at an urban site (36°42′ N, 117°08′ E, 34.5 m a.s.l.) of Jinan, China. Hourly ozone concentrations exceeding the standard value of China, 100 ppbv, were observed for 65 h (in 23 days) from April to October, and values exceeding US NAAQS (National Ambient Air Quality Standard) for 1 h ozone, 120 ppbv, were observed for 15 h (in 7 days) from late May to early July. Ozone formation presented the phenomenon of “weekend effect”, especially in summer. Monthly variation of ozone coincided with temperature except for July and August. The low ozone levels in July and August may be due to the short sunshine duration and much rainfall during this period. Among these meteorological parameters, daily averaged ozone shows a significant correlation with temperature (r = 0.66) in the year and with relative humidity (r = − 0.75) in summer. Throughout the year, high ozone concentrations were mainly associated with the wind from 180 to 247.5°, while high ozone concentration seemed to have no obvious correlation with a given wind direction in summer. An anomalous nocturnal high ozone episode during 23–25 May 2004 was investigated. Growth fractions of ozone during the nighttime episode were 62.2% and 71.1% for 23 and 24 May, respectively. Synoptic analysis shows that favorable synoptic condition had presumably elevated the background ozone level in this region. Backward trajectory analysis shows that the increase of ozone concentration and the relatively constant high ozone concentrations during the night of May 23 might originate from the transport of ozone rich air mass above boundary layer. Transport of ozone from Yangtze Delta and East Central China might be a significant process for the high ozone level during night May 24 at Jinan.     

基于夜光遥感影像的粤港澳地区城市发展时空格局演变

将VIIRS时间序列夜光遥感影像首次应用于粤港澳地区,结合LandScan ^TM人口分布图等辅助数据,采用夜间灯光统计、位序-规模法则以及由基尼系数构建的夜光发展指数等方法,在地市级、区县级2种尺度上对其城市发展空间格局进行分析,探究其城市规模的时空演变情况。结果发现,2012—2018年粤港澳地区所有城市的夜光总量均呈现出增长的态势,但中小城市的增速明显高于大城市,汕尾市的夜光增长率高达310.35%。在位序-规模分析中,地市级与区县级的q值在2012—2018年分别下降了16.86%和13.52%,城市规模分布趋于分散的力量大于趋于集中的力量,城市间规模发展日趋平衡。夜光发展指数同样随时间的变化逐渐降低,城市内部夜光与人口之间的分配水平差距正逐渐弥合,中小城市的发展相对更快。同时,夜光发展指数下降最为显著的几个地级市均位于粤东地区,说明粤东地区近年来正展现出强劲的发展态势。     

Observations of urban and suburban environments with global satellite scatterometer data

A global and consistent characterization of land use and land change in urban and suburban environments is crucial for many fundamental social and natural science studies and applications. Presented here is a dense sampling method (DSM) that uses satellite scatterometer data to delineate urban and intraurban areas at a posting scale of about 1 km. DSM results are analyzed together with information on population and housing censuses, with Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, and with Defense Meteorological Satellite Program (DMSP) night-light data. The analyses include Dallas-Fort Worth and Phoenix in the United States, Bogotá in Colombia, Dhaka in Bangladesh, Guangzhou in China, and Quito in Ecuador. Results show that scatterometer signatures correspond to buildings and infrastructures in urban and suburban environments. City extents detected by scatterometer data are significantly smaller than city light extents, but not all urban areas are detectable by the current SeaWinds scatterometer on the QuikSCAT satellite. Core commercial and industrial areas with high buildings and large factories are identified as high-backscatter centers. Data from DSM backscatter and DMSP nighttime lights have a good correlation with population density. However, the correlation relations from the two satellite datasets are different for different cities indicating that they contain complementary information. Together with night-light and census data, DSM and satellite scatterometer data provide new observations to study global urban and suburban environments and their changes. Furthermore, the capability of DSM to identify hydrological channels on the Greenland ice sheet and ecological biomes in central Africa demonstrates that DSM can be used to observe persistent structures in natural environments at a km scale, providing contemporaneous data to study human impacts beyond urban and suburban areas.     

Classification of Vertical Wind Speed Profiles Observed Above a Sloping Forest at Nighttime Using the Bulk Richardson Number

Wind speed profiles above a forest canopy relate to scalar exchange between the forest canopy and the atmosphere. Many studies have reported that vertical wind speed profiles above a relatively flat forest can be classified by a stability index developed assuming wind flow above a flat plane. However, can such a stability index be used to classify vertical wind speed profiles observed above a sloping forest at nighttime, where drainage flow often occurs? This paper examines the use of the bulk Richardson number to classify wind speed profiles observed above a sloping forest at nighttime. Wind speed profiles above a sloping forest were classified by the bulk Richardson number Ri _B . Use of Ri _B distinguished between drainage flow, shear flow, and transitional flow from drainage flow to shear flow. These results suggest that Ri _B is useful to interpret nighttime CO₂ and energy fluxes above a sloping forest. Through clear observational evidence, we also show that the reference height should be high enough to avoid drainage-flow effects when calculating Ri _B .     

Luojia-01夜光数据和“点轴发育”理论支持下的夜间经济集聚区定量识别与分类方法

“夜间经济”蕴含巨大的消费潜能和市场空间,夜间经济集聚区作为其载体,其准确识别、合理分类和科学布局是发展夜间经济的切入点和主要抓手,更是夜间经济可持续发展的保障。本文在“点轴发育、定量识别”的认知框架下,在定量表达夜间经济活力测度的基础上,利用焦点统计和ISO聚类分析方法提取和识别夜间经济集聚中心和集聚区,并根据区位熵及其变异系数对识别结果进行类型划分,克服了目前夜间经济实践中存在的集聚区范围划定主观随意、类型标准不一的问题,为夜间经济定量化研究开辟了新的思路。研究表明：① 相较于DMPS/OLS及NPP-VIIRS等夜光遥感数据,Luojia1-01数据的空间分辨率高,溢出效应低,更适合于“夜间经济区”这种小尺度的精细化研究。② 夜间灯光和兴趣点数据是夜间社会活力和功能活力的良好表征,其综合影响可通过夜间经济活力测度来定量表达;③ 上海推出的12个地标性夜生活集聚区中,有11个被识别,识别率达91.7%;④ 根据集聚区的功能结构差异,可将其划分为非平衡发展-起步型、平衡发展-起步型、非平衡发展-成熟型、平衡发展-成熟型4种类型,该分类方式具有普适性;⑤ 在起步阶段,上海中心城区夜间经济集聚区主导功能为购物、餐饮;在成熟阶段,其特色发展方向为住宿、科教文化和体育休闲功能。四大集聚区类型在空间分布上形成明显的圈层结构。     

基于2种夜间灯光影像亮度修正指数的城市建成区提取研究

夜间灯光影像容易受到道路灯光、水面散射等影响而产生背景噪声,这一定程度上影响了利用夜间灯光数据提取建成区的精度。本文基于夜间灯光影像的DN（Digital Number）值与路网密度正相关、与EVI指数（Enhanced Vegetation Index,增强型植被指数）呈负相关的规律,提出了2种可用于建成区提取的夜间灯光亮度修正指数：EVI夜间灯光亮度修正指数EANI (EVI Adjusted Nighttime Light(NTL) Index)和基于道路网密度与EVI指数的夜间灯光亮度修正指数REANI (Road Density & EVI Adjusted NTL Index),并利用珞珈1号卫星（LJ1-01,分辨率约130 m）影像和NPP-VIIRS影像（分辨率约 500 m） 2种不同空间分辨率夜间灯光遥感影像进行验证。以2018年徐州市建成区为研究对象,分区域（主城区、外围区）利用阈值法对2种原始夜间灯光影像、经EANI指数和REANI指数处理后的影像进行建成区提取,得到6种建成区提取的结果。研究表明： ① EANI指数和REANI指数能够有效抑制夜间灯光影像的背景噪声,建成区提取的结果均优于直接利用原始影像的结果,特别是对于城市化水平较低地区的建成区提取效果更佳;② 相较于NPP-VIIRS影像,利用LJ1-01影像提取建成区的效果提高6%左右,说明我国的LJ1-01夜间灯光影像在建成区提取方面有广阔的应用前景。EANI和REANI为建成区提取提供了有效工具,并可应用于城市规划和城市扩张等研究领域。