Spatiotemporal Evolution of West Africa's Urban Landscape Characteristics Applying Harmonized DMSP-OLS and NPP-VIIRS Nighttime Light(NTL)Data

Investigating urban expansion patterns aids in the management of urbanization and in ameliorating the socioeconomic and environmental issues associated with economic transformation and sustainable development.Applying Harmonized Defense Meteorological Satellite Program-Operational Line-scan System(DMSP-OLS)and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imagery Radiometer Suite(NPP-VIIRS)Nighttime Light(NTL)data,this paper investigated the characteristics of urban landscape in West Africa.Using the harmonized NTL data,spatial comparison and empirical threshold methods were employed to detect urban changes from 1993 to 2018.We examined the rate of urban change and calculated the direction of the urban expansion of West Africa using the center-of-gravity method for urban areas.In addition,we used the landscape expansion index method to assess the processes and stages of urban growth in West Africa.The accuracy of urban area extraction based on NTL data were R^(2)=0.8314 in 2000,R^(2)=0.8809 in 2006,R^(2)=0.9051 in 2012 for the DMSP-OLS and the simulated NPP-VIIRS was R^(2)=0.8426 in 2018,by using Google Earth images as validation.The results indicated that there was a high rate and acceleration of urban landscapes in West Africa,with rates of 0.0160,0.0173,0.0189,and 0.0686,and accelerations of 0.31,0.42,0.54,and 0.90 for the periods of 1998–2003,2003–2008,2008–2013,and 2013–2018,respectively.The expansion direction of urban agglomeration in West Africa during 1993–2018 was mainly from the coast to inland.However,cities located in the Sahel Region of Africa and in the middle zone expanded from north to south.Finally,the results showed that the urban landscape of West Africa was mainly in a scattered and disordered’diffusion’process,whereas only a few cities located in coastal areas experiencing the process of’coalescence’according to urban growth phase theory.This study provides urban planners with relevant insights for the urban expansion characteristics of West Africa.

Assessment of Human Impacts on Vegetation in Built-up Areas in China Based on AVHRR,MODIS and DMSP_OLS Nighttime Light Data,1992–2010

Since the reform and opening-up program started in 1978,the level of urbanization has increased rapidly in China.Rapid urban expansion and restructuring have had significant impacts on the ecological environment especially within built-up areas.In this study,ArcGIS 10,ENVI 4.5,and Visual FoxPro 6.0 were used to analyze the human impacts on vegetation in the built-up areas of 656Chinese cities from 1992 to 2010.Firstly,an existing algorithm was refined to extract the boundaries of the built-up areas based on the Defense Meteorological Satellite Program Operational Linescan System(DMSP_OLS)nighttime light data.This improved algorithm has the advantages of high accuracy and speed.Secondly,a mathematical model(Human impacts(HI))was constructed to measure the impacts of human factors on vegetation during rapid urbanization based on Advanced Very High Resolution Radiometer(AVHRR)Normalized Difference Vegetation Index(NDVI)and Moderate Resolution Imaging Spectroradiometer(MODIS)NDVI.HI values greater than zero indicate relatively beneficial effects while values less than zero indicate proportionally adverse effects.The results were analyzed from four aspects:the size of cities(metropolises,large cities,medium-sized cities,and small cities),large regions(the eastern,central,western,and northeastern China),administrative divisions of China(provinces,autonomous regions,and municipalities)and vegetation zones(humid and semi-humid forest zone,semi-arid steppe zone,and arid desert zone).Finally,we discussed how human factors impacted on vegetation changes in the built-up areas.We found that urban planning policies and developmental stages impacted on vegetation changes in the built-up areas.The negative human impacts followed an inverted′U′shape,first rising and then falling with increase of urban scales.China′s national policies,social and economic development affected vegetation changes in the built-up areas.The findings can provide a scientific basis for municipal planning departments,a decision-making reference for government,and scientific guidance for sustainable development in China.

Quantifying urbanization levels on the Tibetan Plateau with high-resolution nighttime light data

The Tibetan Plateau(TP)is undergoing rapid urbanization.To improve urban sustainability and construct eco-logical security barriers,it is essential to quantify the spatial patterns of urbanization level on the TP,but the existing studies on the topic have been limited by the lack of socioeconomic data.This study aims to quantify the urbanization level on the TP in 2018 with Luojia1-01(LJ1-01)high-resolution nighttime light(NTL)data.Specifically,the compounded night light index is used to quantify spatial patterns of urbanization level at mul-tiple scales.The results showed that the TP had a low overall urbanization level with a large internal difference.The urbanization level in the northeast,southeast and south of the TP was relatively high,forming three hotspots centered in Xining City,Lhasa City and Shangri-La City,while the urbanization level in the central and western regions was relatively low.The analysis of influencing factors,based on the random forest model,showed that transportation and topography were the main factors affecting the TP’s spatial patterns of urbanization level.The comparison analysis with socioeconomic statistics and traditional NTL data showed that LJ1-01 NTL data can be used to more effectively quantify the urbanization level since it is more advantageous for reflecting the spatial extent of urban land and describing the spatial structure of socioeconomic activities within urban areas.These advantages are attributed to the high spatial resolution of the data,appropriate imaging time and unaf-fected by saturation phenomena.Thus,the proposed LJ1-01 NTL-based urbanization level measurement method has the potential for wide applications around the world,especially in less-developed regions lacking statistical data.Using this method,we refined the measurement of the TP’s urbanization level in 2018 for multiple scales including the region,basin,prefecture and county levels,which provides basic information for the further urban sustainability research on the TP.

Spatiotemporal Measurement of Regional Expansion in Changsha-Zhuzhou-Xiangtan Metropolitan Area Based on Nighttime Light Data

The research purpose is to accurately reveal the temporal and spatial law of the urban expansion of Changsha-Zhuzhou-Xiangtan, one of the seven major urban agglomeration areas in China, and provide decision-making basis for the future urban construction land layout and regional development policy-making. Based on the night lighting data (DMSP/OLS), this paper extracts the boundary of the urban construction land of Changsha-Zhuzhou-Xiangtan urban agglomeration from 1993 to 2017, and quantitatively studies the spatial and temporal characteristics of the expansion of the metropolitan area in the past 25 years according to the methods of spatial expansion analysis, center of gravity migration measurement, landscape pattern index, spatial autocorrelation, etc. The results show that: 1) it is scientific and feasible to extract urban agglomeration construction land by the method of auxiliary data comparison for the study of urban expansion;2) the expansion of regional space in Changsha-Zhuzhou-Xiangtan metropolitan area shows a trend of “weakening first and strengthening later”. The construction land keeps increasing, and the expansion form gradually changes from extensive type to intensive type;3) the center of gravity of the metropolitan area fluctuated and repeated in part during the past 25 years, but it was always located in the municipal district of Changsha city. The eastern region, mainly Changsha city, was still the core area of urban agglomeration expansion;4) strengthening the territorial space protection and control of ecological green core in the metropolitan area is a key measure for the high-quality development of urban agglomeration.

DMSP-OLS与NPP-VIIRS夜间灯光遥感影像数据整合

DMSP-OLS夜间灯光遥感数据截至2013年,现已被NPP-VIIRS夜间灯光数据取代。因此,要获得长时间序列且稳定的夜间灯光数据集,需要整合两类夜间灯光数据。基于此,本文提出了基于重采样的两类数据整合方法,对2013—2020年NPP-VIIRS数据进行模拟,最终建立了1992—2020年长时间序列校正—模拟DMSP-OLS夜光遥感数据集。结果表明,基于重采样的整合方法效果良好(城市区域Pearson相关系数ρ=0.985 2,RMSE=3.460 7),整合数据集与相关社会经济参考量高度契合(影像DN值总和与GDP的相关系数ρ=0.946,与人口的相关系数ρ=0.971,二次多项式模型拟合R~2≈0.98,RMSE<5.55),优于已有研究。因此,利用该方法整合后的数据集能更好地支撑基于夜间灯光影像的长时间序列研究。

Population Spatial Distribution Based on Luojia 1-01 Nighttime Light Image:A Case Study of Beijing

With the continuous development of urbanization in China,the country’s growing population brings great challenges to urban development.By mastering the refined population spatial distribution in administrative units,the quantity and agglomeration of population distribution can be estimated and visualized.It will provide a basis for a more rational urban planning.This paper takes Beijing as the research area and uses a new Luojia1-01 nighttime light image with high resolution,land use type data,Points of Interest(POI)data,and other data to construct the population spatial index system,establishing the index weight based on the principal component analysis.The comprehensive weight value of population distribution in the study area was then used to calculate the street population distribution of Beijing in 2018.Then the population spatial distribution was visualize using GIS technology.After accuracy assessments by comparing the result with the WorldPop data,the accuracy has reached 0.74.The proposed method was validated as a qualified method to generate population spatial maps.By contrast of local areas,Luojia 1-01 data is more suitable for population distribution estimation than the NPP/VIIRS(Net Primary Productivity/Visible infrared Imaging Radiometer)nighttime light data.More geospatial big data and mathematical models can be combined to create more accurate population maps in the future.

Consistent nighttime light time series in 1992–2020 in Northern Africa by combining DMSP-OLS and NPP-VIIRS data

Human activities modulate the impact of environmental forcing in general and of climate in particular.Information on the spatial and temporal patterns of human activities is in high demand,but scarce in sparsely populated and data-poor regions such as Northern Africa.The intensity and spatial distribution of nighttime lights provide useful information on human activities and can be observed by space-borne imaging radiometers.Our study helps to bridge the gap between the DMSP-OLS data available until 2013 and the NPP-VIIRS data available since 2013.The approach to calibrate the OLS data includes three steps:a)inter-calibrate the OLS DN data acquired by different sensors in 1992-2013;b)cali-brate the OLS DN data using VIIRS data in 2013;c)generate syn-thetic OLS radiance data by degrading the VIIRS data in 2013-2020.We generated a)a time series of calibrated OLS nighttime light radiance data(1992-2013);b)mean annual VIIRS radiance on stable lights at the OLS spatial resolution for 2013-2020;c)synthetic OLS radiance data generated using VIIRS radiance data degraded to match the radiometric specifications of OLS for 2013-2020.The evaluation of these data products in 2013 documented their accu-racy and consistency.

基于DMSP-OLS夜间灯光数据的中国城市扩张规律研究

分别以1992年、1998年、2003年、2008年和2013年的DMSP-OLS稳定夜间灯光数据为基础,提取出我国八大综合经济区范围内的城市建成区范围,并从城市面积变化、扩张类型、扩张强度3方面对不同经济区城市扩张特征进行了分析研究。结果表明:北部沿海、东部沿海、南部沿海综合经济区城市扩张相似,其中东部沿海综合经济区是城市扩张最快的综合经济区;东北综合经济区和黄河中游综合经济区在1992~2003年城市扩张缓慢,2003~2013年城市扩张开始加速;长江中游、大西南和大西北3大综合经济区城市扩张速度稳定,但扩张速度较沿海地区较为缓慢。

中国电力消费多尺度时空格局分析--基于DMSP-OLS夜间灯光数据

对美国国防气象卫星计划(defense meteorological satellite program, DMSP)上的操作线性扫描系统(operational linescan system, OLS)所获取的夜间灯光数据进行校正,结合省级电力消费量构建2000—2013年省级尺度电力消费模拟模型。模型的拟合优度为0.714 9,这表明模拟模型有效。在此基础上反演出市级、县级和栅格级电力消费量,最后采用全局空间自相关和局部空间自相关分析多尺度电力消费时空演变格局。结果表明:2000—2013年中国电力消费呈现显著增长趋势。电力消费总量由2000年的13 606.29亿k Wh增加为2013年的53 423.39亿k Wh。京津冀地区、长三角地区和珠三角地区是高电力消费聚集区域,西部地区则呈现低电力消费集聚态势,可见电力消费量分布呈现胡焕庸线特征。栅格、省级、市级和县级尺度电力消费量呈现出一致的分布趋势,不同地区电力消费存在着差异性。市级尺度是模拟电力消费的有效行政单元。2013年12.9%的省份、16.56%的城市和40.95%的县域电力消费呈现出局域空间相关性。

基于夜光数据的昆明市城市扩张格局演变分析

基于夜光数据采用POI&NPP综合指数提取建成区,然后进行建成区面积精度评定,从定性和定量两个角度进行城市扩张空间形态及格局演变分析。结果表明:1)POI融入夜光数据后,提高了提取的精度,提取边界与实际的分布范围更为接近。2)扩张速度和强度较快区域主要集中在呈贡区、嵩明县等,而较慢区域集中在北部的禄劝县、东川区、寻甸县等;嵩明县的动态变化率最高,中心城区的区域动态变化率较低,北部的寻甸县、东南部的宜良县、石林县动态变化率反而较高。3)昆明市整体上经济重心经度方向为向东偏移,纬度方向为向南偏移。

上海市郊区地铁站对周边地区的经济效应研究

以上海市外环线外的60个郊区地铁站为研究对象,探讨郊区地铁站对周边地区经济的影响。采用夜间灯光数据,并结合断点回归方法进行分析。结果表明:地铁站的开通对周边地区产生显著的经济效应,这种效应具有显著的距离衰减特性。地铁站半径1200 m以内的区域灯光亮度显著提升,超出此范围则无明显的断点处理效应。此外,这种空间经济效应表现出显著的异质性。对于距离市中心适中的地铁站,地铁开通存在显著的断点处理效应,而对于其他距离分组则不存在。

陕西省碳排放时空格局演变及其影响因素

基于DMSP/OLS和NPP/VIIRS夜间灯光数据,运用探索性空间分析、冷热点分析和标准差椭圆分析等方法,估算了2000~2020年陕西省碳排放量,探讨了陕西省碳排放的时空演化特征,并构建了空间杜宾面板模型分析其影响因素.结果表明:(1)2000~2020年陕西省碳排放总量呈现持续增长趋势;碳排放分布具有显著的地域差异规律,呈现“陕北>关中>陕南”的分布态势.(2)碳排放重心向陕西东北方向移动,说明陕西东部地区和北部地区对全省碳排放量的影响作用加强;碳排放具有显著的空间正自相关性,即表现为集聚效应;碳排放的冷热点转化较为明显,热点在陕北地区扩张,冷点逐渐消失.(3)陕西省碳排放的直接正向影响因素有城镇化率、人口数量、单位GDP能耗、产业结构和经济增长,其中城镇化快速发展和人口规模扩大是陕西省碳排放持续增长的主要推动力.

减污降碳协同效应空间关联关系及驱动因素研究

剖析减污降碳协同效应的空间关联特征及成因是引导区域协同共治的前提,对推动新质生产力发展具有重要意义。基于耦合协调模型测度2011-2021年环渤海地区43个城市的减污降碳协同效应,应用社会网络分析法和二次指派程序探究其空间关联网络特征及驱动因素。结果表明:①研究期间,环渤海地区减污降碳协同效应的最高值为0.43,尚未进入高质量协调发展阶段,超过80%的城市处于降碳滞后型失调阶段。②减污降碳协同效应空间关联网络呈以天津市为主核心的“局部集聚”和“全局关联”并存特征,个体中心性差异突出,网络结构稳定性亟待提升。③各板块内部成员相对较为稳定,板块间存在更为显著的溢出效应。④地理邻近、产业结构合理化、能源利用、经济发展、节能环保、技术水平的差异对减污降碳协同效应空间关联关系的形成发挥促进作用,而通风系数的差异起抑制作用。研究显示,环渤海地区减污降碳协同效应的空间关联程度较低,建议通过强化核心主体的稳定作用、实施社团差异化的减排措施、拓展区域合作等路径推进减污降碳协同增效。

黄土高原人类活动强度与植被覆盖的时空关联

人类活动强度(Human Activity Intensity,HAI)是表征人类活动对自然环境作用程度的客观指标,植被作为生态环境变化的综合指示器,对人类活动变化十分敏感,深入探究HAI与NDVI(Normalized Difference Vegetation Index,归一化植被指数)时空分异及其关联性,对维稳自然环境、合理控制人类活动以及协调人地关系具有重要意义。以黄土高原为研究区域,使用夜间灯光、人口密度及土地利用数据表征人类活动强度,分析2000—2020年HAI与NDVI的时空分及其关联性。结果显示:(1)2000—2020年黄土高原HAI整体变化较缓(年均速为1.39%),空间呈现“七点一圈一带”的分布格局,呼包鄂榆及晋中城市群HAI强度变化较频繁,高强度区向西北方向呈集中分布态势。(2)2000—2013年NDVI增速较快(2.11%/a),2014—2020年增速放缓至0.82%,整体呈现东南高西北低分布,高植被覆盖区域向西北移动且多方向扩张。(3)HAI与NDVI相关性空间分异明显,且在关中、呼包鄂及晋中城市群呈空间聚集分布。人类活动对植被覆盖的作用具有双向性,高强度人类活动致使植被覆盖锐减,退耕还林等工程有效抑制植被退化,生态环境有所改善。研究结果可为精细量化人类活动强度、黄土高原未来国土空间规划及生态环境修复与维稳提供一定理论依据与参考。

基于夜光遥感数据的广西县域农村多维脱贫分析

巩固脱贫攻坚成果,衔接乡村振兴战略,防止返贫是我国目前经济建设的重要任务。2022年中央农村工作会议重点强调了要“坚决守住不发生规模性返贫底线”。在多维贫困的基础上,动态客观地监测县域农村贫困程度的时空演变,对国家防返贫工作十分重要。随着遥感卫星的快速发展,高信息量和高质量的遥感数据影像逐渐丰富并被广泛应用,相比于传统的统计类数据,夜光遥感数据具有与社会经济要素高度相关、相对客观性强和时间跨度相对较长等优点。该文以DMSP/OLS和NPP/VIIRS夜光遥感数据为基础,提取夜间灯光强度指数,结合多维脱贫指数构建两者关系模型,对2010—2020年广西县域农村贫困程度进行时空演变研究,分析存在的返贫原因,为乡村振兴和脱贫攻坚提供科学参考和预防措施。

从夜间灯光数据中提取城市建成区的改进方法

为提高夜间灯光影像中城市建成区的提取精度,对多源遥感数据融合方法进行了改进。以武汉市1992—2020年3类夜间灯光数据为数据源,在调整多源数据融合方法步骤顺序的基础上,加入了突变检测法,从而过滤出影像中较小的建筑物,使其能更好地反映建成区范围。结果表明:①改进方法保留了多源遥感数据融合方法提取的建成区的城市细节,从影像对比图中能明显看出建成区的划分情况;②改进方法的提取精度从85.76%提高至98.84%,能更精确地反映城市建成区范围;③改进方法去除了冗余步骤,提高了研究效率。

浙江省县域碳排放时空格局及影响因素研究

准确估算区域碳排放,分析其时空演变特征,可为区域持续发展和节能减排提供理论参考。基于DMSP/OLS和NPP-VIIRS两类夜间灯光整合的数据集,结合能源消费统计数据,构建浙江省碳排放估算模型,模型拟合优度达到91.5%。利用空间自相关等空间分析方法对2000—2020年浙江省县级碳排放时空特征进行研究,利用地理加权回归模型探究影响因素。结果表明:浙江省县级碳排放量显著增长,高碳排放区域呈扩张趋势,且南北差异明显。80%区县的碳排放量处于中高速增长阶段。浙江省县级碳排放具有空间正相关性和区域聚集特征。浙江省北部高碳区县聚集,南部低碳区县聚集。探究影响碳排放空间分异的4种因素,贡献度依次为:人口>第二产业占比>人均可支配收入>人均生产总值。

基于夜间灯光数据的西兰高速铁路站点区域经济影响分析

高速铁路的发展带动了沿线区域经济的飞速增长,夜光遥感数据相比传统统计数据具有客观性、地理空间特性和易获取等特点,能够有效衡量高速铁路沿线区域经济表现。以西兰高速铁路(西安—兰州)为例,基于夜间灯光数据分析其沿线高铁站的区域经济影响。利用整合夜间灯光数据和站点区位,通过距离圈层法将高铁站点按等级分类,分析高铁站区域的虹吸效应和集聚效应,以及高铁站点与城市中心对高铁站区域经济影响的差异。结果表明:高铁站点与城市中心均对高铁站区域有经济带动作用,且不同区位等级的高铁站点对高铁站区域的经济影响存在异质性,高铁站点对站区经济的负梯度效应与高铁站点的区位等级呈正比,城市中心的负梯度效应与高铁站点的区位等级呈反比。

基于DMSP/OLS与NPP/VIIRS夜间灯光数据的江西省城市扩展研究

夜间灯光数据被广泛用于城市扩展监测研究。利用2001—2021年DMSP/OLS和NPP/VIIRS 2种夜光数据,采用统计数据比较阈值法得到江西省建成区范围空间分布,分析了江西省城市扩展特征。主要结论如下:1)采用统计数据比较阈值法可以很好地从DMSP/OLS和NPP/VIIRS数据中提取江西省城市建成区信息,可以满足长时间序列的要求。2)2001—2021年间江西省各城市扩展逐渐加速,但有快有慢。

高度城市化地区的降水集中度研究——以长三角城市群为例

在全球变暖和人类活动的背景下,降水在年内分布上发生了比较大的变化,对人民生产生活产生了巨大的影响,这一影响在城市化较高的地区尤为明显。基于多源降水数据(降水产品数据和气象站点数据)和夜间灯光数据,选定中国的长三角城市群作为研究区域,将基尼系数(Gini Index,GI)作为降水集中度的指标,利用Theil-Sen Median斜率估计和Mann-Kendall显著性检验进行趋势分析,最后通过相关性分析探究城市化程度与降水集中度的关系。研究结果表明:(1)CHIRPS(Climate Hazards Group InfraRed Precipitation with Station Data)数据计算得到的GI与站点数据结果的均方根误差为0.036,远小于CMFD数据(0.067)和MSWEP数据(0.083)的结果,表明CHIRPS数据具有最佳的适用性;(2)长三角城市群的降水不均匀性从南向北逐渐增加,并在城市群中部和西部呈现出显著上升的趋势,研究区域内的降水年内分布将会朝着集中分布的方向发展,极端降水事件出现的可能性增加;(3)城市化对降水集中度主要起到促进作用,城市的快速发展使得降水不均匀性增强,并且在城市群内的南京市、无锡市和镇江市等地区更为显著,更有可能发生城市内涝等灾害。研究对于城市的防洪设计、城市道路排水管道的设计和城市防洪应急响应预案的编制具有参考意义。