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。

基于NPP-VIIRS夜间灯光数据的福建省县域经济发展时空演化研究

基于福建省县域统计经济数据和校准预处理后的NPP-VIIRS夜间灯光数据,揭示县域统计经济数据与夜间灯光数据的关联,在此基础上探讨县域经济发展时空演化特征。结果表明:(1)夜间灯光总量与地区生产总值(GDP)高度相关,县域夜间灯光总量集中分布在东南沿海地区,沿海县(市)单位面积夜间灯光总量高于内陆县(市),夜间灯光总量空间分布呈现高度不均衡性;(2)县域GDP全局自相关指数以及夜间灯光全局自相关指数呈显著正相关水平,县域夜间灯光数据空间集聚水平低于县域GDP空间集聚水平,夜间灯光数据高高聚类区域相比县域GDP高高聚类区域呈扩张趋势;(3)夜间灯光数据和经济指数热点区域均分布在东南部沿海地区,冷点区域主要分布在三明和南平等地区部分县(市),夜间灯光数据和统计经济数据冷热点之间存在一致性。为缩小区域发展差异,需加大经济政策扶持,促进区域经济交流,带动经济同步增长,研究结果可为县域经济发展政策制定提供参考借鉴。

基于NPP-VIIRS夜间灯光数据的广西西江流域城市扩张时空格局演变研究

基于2012年、2014年、2016年、2018年、2020年的年度NPP-VIIRS夜间灯光数据,运用统计数据比较法提取广西西江流域城市建成区,并计算城市建成区的扩张速度、扩张强度指数、平均灯光强度指数、紧凑度指数、城市中心迁移距离、角度和速度,分析2012—2020年广西西江流域城市扩张动态变化情况。结果表明:1)统计数据比较法的平均总体分类精度在97%以上,能精确反映西江流域城市建成区发展的实际情况。2)2012—2020年广西西江流域城市建成区平均扩张速度为4.61 km^(2)/a,呈现先快速发展后减缓的扩张趋势。扩张强度与平均灯光强度的变化趋势与扩张速度基本保持一致。3)广西西江流域城市建成区整体的紧凑度和分形维数均呈现降低的趋势,说明广西西江流域城市扩张较为平衡,存在内部建设和外部扩张两种扩张发展形式。4)2012—2020年河池市与南宁市因城市发展建设使城市中心迁移距离较大,其余各市的城市中心迁移距离平缓,稳定扩张;各城市中心迁移速度与城市中心迁移距离和方向的发展情况基本保持一致。

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.

基于Sentinel-2A与NPP-VIIRS夜间灯光数据的城市建成区提取

利用夜间灯光数据(nighttime light data,NTL)与光学遥感影像提取城市建成区是当今的一个研究热点,其中基于植被校正的城市夜间灯光指数(vegetation adjusted NTL urban index,VANUI)被学者广泛利用,但它容易混淆城市边缘的建筑、水体,空间分辨率较低。对VANUI做出改进,提出基于建筑校正的城市夜间灯光指数(building adjusted NTL urban index,BANUI)。利用该指数对包头市南部的城市建成区进行提取,首先,借助Sentinel-2A遥感影像数据提取研究区的归一化建筑指数;然后,将其与NTL数据结合得到BANUI(空间分辨率为20 m),并由此得到空间分辨率更高、建筑信息更丰富的BANUI图像;最后,利用分水岭分割算法从BANUI,VANUI和NTL中提取出城市建成区并进行对比。结果表明,由BANUI提取的城市建成区总体精度可达93.61%,Kappa系数为0.7934,用户精度为81.34%,生产者精度为85.34%,提取结果与实际城市建成区的分布较吻合、提取精度较高,且优于另外2种数据。此方法可为NTL在城市建成区提取的研究中提供参考意见,也可用于对城市规划发展的监测。

基于SNPP-VIIRS夜间灯光数据的GDP预测模型对比

由于基于夜光遥感数据的GDP预测多采用单一函数模型,缺乏对比和可行性验证,因此利用校正后的夜光影像对比多种函数模型的预测效果具有实际价值。鉴于此,选择SNPP-VIIRS作为基础数据,经过消除负值和背景噪声等校正处理,对线性函数等6种预测模型进行GDP估算效果对比。结果表明:在省级尺度下,二项式函数拟合优度最高,Gaussian函数预测效果最好;市级尺度下,二项式函数均优于其他函数模型。校正方法合理科学,校正后的影像可用于GDP预测研究。

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.

川南四市县域NPP-VIIRS数据信息提取及应用

以川南四市28个区县为研究区,在分析QGIS提取面积、有效光源数、灯光总量、灯光均值、灯光标准差、灯光最小值、灯光最大值、极差等8个指标的基础上,利用主成分分析法对研究区的NPP-VIIRS夜间灯光数据信息进行提取,发现利用“整体”“明”“暗”3个主成分即可以有效地反馈原有的8个指标所提供的信息;利用各主成分的贡献率对所得的主成分得分进行加权求和,得到28个区县NPP-VIIRS夜间灯光数据的综合得分并从大到小进行排序,排序结果与区县建设的实际情况相符,充分揭示了研究区城市扩张及各区县经济社会的发展状况.

基于NPP-VIIRS灯光数据对收缩背景下县级城镇规模分布特征及演变分析--以黑龙江省为例

城镇体系是人口、经济、资源等集聚的空间载体,在城镇收缩背景下,对区域规模分布特征及演变趋势进行探讨是促进区域协调发展的前提。本文以黑龙江省为例,基于2012—2019年校正后NPP-VIIRS夜间灯光数据,利用首位度指数、Zipf位序-规模法则等方法探究收缩背景下县级城镇规模分布特征及其演变趋势。结果表明:1)省内县级城镇规模分布处于相对集中、稳定的状态。从演变趋势上看,城镇体系朝着合理缓慢转变。2)哈尔滨市自身规模的上涨以及省内第二大城市大庆的明显收缩,导致省内首位度指数占比已远超于理想状态,进入剥夺周边城镇资源、自身无序扩张的恶性循环。3)哈尔滨市外的高位序城市,与中、低位序城镇间规模差距正在减小,但大、中、小城镇规模差距依旧明显,短期内无法缩小,省内同时还存在中等规模过度城镇数量断层现象。

中国三大城市群公路货运碳排放时空特征分析--基于NPP-VIIRS数据的研究

以美国国家极轨运行环境卫星系统预备计划可见光红外成像辐射仪(national polar-orbiting operational environmental satellite system preparatory project—visible infrared imaging radiometer suite,NPP-VIIRS)夜间灯光数据为基础,经过影像重投影、稳定性校正和时间序列校正后,结合统计数据,构建三大城市群公路货运碳排放估算模型。在此基础上,从栅格尺度和市级尺度进行公路货运碳排放时空特征分析。分析结果如下:(1)估算模型的拟合优度分别为0.6762、0.9362和0.5585,估计效果良好,结果有效;(2)2012-2020年三大城市群货运碳排放由1599.25万t增长为1830.31万t,呈现散发增强趋势,京津冀城市群碳排放最高的城市为唐山市,长三角城市群碳排放高的城市为合肥市、上海市、舟山市和苏州市,珠三角城市群碳排放最高的城市为广州市,其次为佛山市、东莞市和深圳市;(3)三大城市群中保定市为碳排放较快增长型,京津冀城市群碳排放重心整体向西北方向移动,长三角和珠三角城市群碳排放重心整体向东北方向移动。

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.

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。

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。

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。