DMSP/OLS夜间灯光数据应用研究综述

DMSP/OLS以其独特的光电放大特性与对夜间灯光的获取能力,成为人类活动监测的良好数据源。回顾了DMSP/OLS夜间灯光数据在城镇信息提取、社会经济因子估计及光污染、火灾、渔火、天然气燃烧监测等方面的应用,其中重点介绍了利用灯光数据估算城市化水平和人口的方法和步骤,并总结了DMSP/OLS夜间灯光数据在应用中的优越性与局限性,最后对其未来应用方向进行了展望。      

基于图像分析的中国城市化空间过程研究

针对城市扩张的加速引起的一系列问题,利用DMSP/OLS夜间灯光图像采用图像处理技术分析了中国大陆在省级尺度上的城市化空间过程。基于区域标记的种子填充算法从全球夜间灯光图像中提取各省市灯光图像;以1992、1996、1998年为例基于统计数据,利用直方图结合二分法快速确定各省市城镇可用地面积的阈值,提取城镇可用地面积,证明与统计数据的相对误差不超过10%;分析1992—2010年夜间灯光图像亮度总值与地区生产总值、人口之间在省级尺度上的相关性,构建相应的模型,证明各省灯光亮度值与其地区生产总值、人口之间存在较强的相关性且不同城市化空间扩展模式的灯光亮度值与其地区生产总值、人口之间存在不同的相关性。     

夜间灯光数据估算中国省域碳排放与国际碳数据库分配的碳排放比较

快速准确获取省域碳排放数据是实时制定差异化碳减排政策的前提。基于DMSP/OLS和NPP-VIIRS夜间灯光数据,采用统计数据比较法提取1997～2017年中国大陆各省域（不包括西藏）建成区的夜间灯光总值（用TDN表示）,并利用1997～2014年各省域的TDN值与同期核算的碳排放量建立各省域碳排放预测模型。然后,以2015～2017年的TDN值为自变量估算中国各省域的碳排放量;同时,利用熵值法和碳排放分配模型将四大国际权威数据库（IEA、EIA、EDGAR和CEADs）发布的中国碳排放量分配至各省;最后,将估算结果与四大典型碳数据库分配的省域碳排放值进行比较。研究表明：估算的省域碳排放量与分配的省域碳排放量大体一致,平均绝对百分比误差（MAPE）为6.45%～9.12%,并且基于夜间灯光数据估算的省域碳排放量与IEA和EIA数据库分配的碳排放量更为接近;各省域估算的碳排放量与分配的碳排放量均落在1∶1线附近;单个省域的MAPE值变化在0.68%～14.85%,且多数省域的MAPE值均在10.0%以内。上述结果证明,基于夜间灯光数据通过提取TDN值估算省域碳排放量具有可行性和准确性。     

利用DMSP/OLS稳定夜间灯光数据提取城镇用地信息的分层阈值法研究

DMSP/OLS夜间灯光数据是提取大尺度城镇用地信息的有效数据手段。利用DMSP/OLS稳定夜间灯光数据,在传统二分比较法的基础上,发展一种提取城镇用地信息的新方法——分层阈值法。该方法采用分层分类的思想,不断地将灯光阈值相近的行政单元划分到相同的集合,直至集合内各行政单元的灯光阈值完全相同为止。基于分层阈值法,从2002年DMSP/OLS稳定夜间灯光数据中提取中国内地的城镇用地信息,并利用统计数据和Landsat ETM+数据分别从数量特征和空间格局上对提取结果进行精度评价。研究结果表明,分层阈值法不仅克服了传统二分比较法需要逐个行政单元求取阈值导致计算效率较低的缺陷,优化了阈值求解过程,提高了城镇用地信息提取效率,而且具有较高的可靠性和推广应用价值。     

结合Landsat数据的DMSP/OLS夜间灯光影像去饱和方法研究

DMSP/OLS夜间灯光数据是表征人类活动强度的数据源之一,被广泛应用于城市提取与扩展研究中。城市灯光指数(VANUI)提供了一种简单、方便且结果良好的DMSP/OLS夜光影像去饱和方法,但该方法为剔除水体直接去除数值为负的区域,不仅过度剔除桥体等水面建筑,也提取出沿海区域的水产养殖区,降低提取精度。基于此,结合DMSP/OLS夜光数据与Landsat数据构建的植被指数(NDVI)和水体指数(MNDWI),提出了一种新的去饱和指数RwNTLI,以广州市为试验区,从城市识别能力和夜光饱和缓解效果方面对比了两种指数。结果表明:RwNTLI指数不仅可以有效缓解夜光饱和效应,同时能够解决VANUI存在问题,且其与辐射定标数据(RCNTL)的相关性高于VANUI指数与RCNTL的相关性。因此,该指数是一种简单有效的夜光去饱和指数,能够更好地描述城市夜间灯光特征,将来在城市建成区提取上具有较高的应用价值。     

NPP-VIIRS年度夜间灯光数据的合成方法与验证

针对缺乏NPP-VIIRS年度夜间灯光数据的情况,提出基于NPP-VIIRS月度夜间灯光数据合成年度夜间灯光数据的方法。用DMSP/OLS数据中的非负DN值与均值滤波消除数据中的负值与极高值并求出年度均值图像;将稳定夜间灯光数据二值化后与2016年度均值图像相乘,得到稳定的2016年度夜间灯光数据;用不变目标区域法进行相对辐射校正,以2016年稳定夜间灯光数据为基准数据进行逐年校正,利用各年二值图像消除不稳定光源,从而保证各年数据的可比性、稳定性,得到2012年到2016年的合成夜间灯光数据。验证表明,合成年度夜间灯光数据像元变化符合实际,经济参数拟合度在省、市级尺度上分别达到81.26%、75.90%,明显高于1月份的61.86%、54.81%,12月份的60.28%、57.71%,说明年度夜间灯光数据合成方法具有一定的科学性与必要性,可用于后续科学研究中。     

利用夜间灯光数据探究陕西经济发展时空变化

针对区域经济研究过程中社会经济统计数据存在数据缺失、尺度不统一等问题,利用连续易获取的夜间灯光数据探究区域经济发展时空格局特征.首先,对DMSP/OLS夜间灯光数据进行预处理,并与社会经济统计数据结合作相关分析;其次,采用重心、标准差椭圆、基尼系数、变异系数、局部莫兰指数等研究方法,从经济发展方向、差异性、空间集聚性的...     

利用DMSP/OLS夜间灯光影像模拟中国经济参量

鉴于传统统计调查方法难以准确、高效和客观揭示经济参量时空信息,提出结合DMSP/OLS夜间灯光数据和统计年鉴数据模拟中国经济参量。选取省级尺度地区生产总值(GDP)、第一产业生产总值(PI)、第二产业生产总值(SI)、第三产业生产总值(TI)4个经济参量,分别构建1992年、2002年和2012年3期DMSP/OLS夜间灯光总值参量与4个经济参量一元线性回归模型,遴选夜间灯光-经济敏感参量,构建空间化模型模拟经济参量。结果表明,地区生产总值(GDP)和第二产业生产总值为敏感参量,模拟结果表明过去21年中国经济参量主要围绕中心城市(省会城市和直辖市)快速增长,其中三大城市群(长三角城市群、珠三角城市群和京津冀城市群)形成高值绵延区,与实际情况相符合,展现了利用DMSP/OLS模拟时序经济参量的优势。     

基于夜间灯光数据的陕西省县域相对贫困水平时空差异分析

2020年中国消除了绝对贫困,但相对贫困还继续存在且长期存在,研究相对贫困对于巩固拓展脱贫攻坚成果和有效衔接乡村振兴具有重要意义。针对已有贫困研究中仍存在的贫困分类研究、动态研究等方面不足,从相对贫困角度入手,选取陕西省107个区县为研究对象,以2011—2020年为研究时段,基于夜间灯光数据、NDVI数据和社会经济统计数据,构建以夜间灯光指数为自变量的多维贫困指数估算模型来量化识别相对贫困县域,并综合运用锡尔指数、空间局部自相关等分析方法,对量化识别出的县域相对贫困水平时空动态差异进行研究。研究结果表明：(1)基于夜间灯光数据可以有效进行多维贫困指数估算且估算精度达84.62%,利用多维贫困指数均值序列的前50%作为区域相对贫困划分标准,适用于描述区域相对贫困水平,有利于探索建立解决相对贫困的长效机制。(2)时间上,从2011年到2020年陕西省相对贫困县个数总体下降,省内各市区间相对贫困水平的区域间差异增大直接导致了贫困县两极分化程度增强。(3)空间上,陕西省相对贫困县域呈现“陕南贫困程度深范围广,关中渭河沿岸次之,陕北无定河沿岸以北零星分布”的格局。     

中国夜间灯光与建设用地碳排放关系实证分析

为厘清建设用地碳排放与夜间灯光之间的关系,利用静态面板回归以及EKC模型,对1995年到2015年全国30个省级行政单位的建设用地碳排放量与灯光指数ANLI的关系进行实证,并基于城市化的视角对结果进行分析。研究发现:(1)城市化与建设用地碳排放在全国与西部存在双向因果关系,在东中部存在城市化对建设用地碳排放的单向因果关系,说明东中部的城市化质量高于全国整体以及西部;(2)全国以及东中西部的ANLI指数与建设用地碳排放都存在着倒U型曲线的关系,说明城市化对建设用地碳排放具有驱动与制动的双重作用;(3)城市化对建设用地碳排放的贡献具有区域性,按大小排序为:东部中部全国西部。研究结果可为夜间灯光数据估算碳排放提供一定的理论支持,未来应因地制宜地制定减排政策,积极构建环境友好型社会。     

A Reducing Saturation Method for DMSP/OLS Nighttime Light Image Combining Landsat Data

Defense Meteorological Satellite Program/Operational Linescan System(DMSP/OLS)is one of the data sources,which can effectively reflect human activities of earth surfaces.During the past decade,DMSP/OLS had been extensively applied in urban extraction and extension study.In the recent year,the Vegetation Adjusted NTL Urban Index(VANUI)has been proposed and had proven to be a simple,convenient and high precision desaturation index to extract urban area.In VANUI method,negative values of imagery were directly eliminated to remove water body,which not only removed the bridge over the river and building but also extracted the aquaculture areas along the coast,thus,this method reduced the extraction accuracy.This paper proposed a new index\|RwNTLI,combining DMSP/OLS nighttime light data and the vegetation index (NDVI)and water index (MNDWI)which were constructed by Landsat data.In this study,Guangzhou was taken as experimental area.By comparing the VANUI index with the ability to identify ground objects as well as the ability to alleviate saturation regions,the result showed RwNTLI index could effectively solve the problem of VANUI as well as eliminate saturation effect of nighttime light imagery.Among them,the correlation between RwNTLI index and RCNTL is better than that of VANUI index and RCNTL.Therefore,RwNTLI index is a simple and effective index of luminous desaturation,which has more advantages than VANUI index in describing the characteristics of night lights of urban areas and will have higher application value in urban built\|up areas in the future.     

Spatial improvement of human population distribution based on multi-sensor remote-sensing data: an input for exposure assessment

A spatial mismatch of hazard data and exposure data (e.g. population) exists in risk analysis. This article provides an integrated approach for a rapid and accurate estimation of population distribution on a per-pixel basis, through the combined use of medium and coarse spatial resolution remote-sensing data, namely the Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) night-time imagery, enhanced vegetation index (EVI), and digital elevation model (DEM) data. The DMSP/OLS night-time light data have been widely used for the estimation of population distribution because of their free availability, global coverage, and high temporal resolution. However, given its low-radiometric resolution as well as the overglow effects, population distribution cannot be estimated accurately. In the present study, the DMSP/OLS data were combined with EVI and DEM data to develop an elevation-adjusted human settlement index (EAHSI) image. The model for population density estimation, developed based on the significant linear correlation between population and EAHSI, was implemented in Zhejiang Province in southeast China, and a spatialized population density map was generated at a resolution of 250 m?×?250 m. Compared with the results from raw human settlement index (59.69%) and single night-time lights (35.89%), the mean relative error of estimated population by EAHSI has been greatly reduced (17.74%), mainly due to the incorporation of elevation information. The accurate estimation of population density can be used as an input for exposure assessment in risk analysis on a regional scale and on a per-pixel basis.     

VANUI指数监测京津冀城市群区域2001～2012年城市化过程

快速城市化改变了下垫面物理性质和地气相互作用,影响了气候及环境变化,如何通过合理的时空尺度对我国城市过程进行监测与认知是我国城市化发展战略的迫切需求。以京津冀城市群为研究区,利用改进的夜晚灯光指数(VANUI)对京津冀城市群2001~2012年的城市化发展过程进行了监测,对比了VANUI指数与传统夜间灯光指数对城市区域的监测能力差异及其优势所在,为京津冀地区未来城市化发展战略规划服务。结果表明,VANUI城市指数能很好地弥补夜晚灯光指数在城市区域饱和的缺陷,并能够较好地反映城市区域的空间格局及相应的细节信息。根据VANUI结果,2001~2012年间京津冀城市群扩张了约一倍,其中城市扩张速度最快的为河北省唐山市。从整个研究区域来看,在此10年间,VANUI以接近线性的发展趋势增加,从统计结果来看,2004~2007年及2009~2012年为研究区域VANUI普遍增长的时期。     

Strategy for studying nocturnal aerosol optical depth using artificial lights

In this concept study, we develop a strategy for the monitoring of nighttime aerosol particle optical properties over land using artificial lights on the earth's surface. We demonstrate the possibility of detecting significant aerosol events and deriving variations in aerosol optical depth using the operational linescan system (OLS) on defence meteorological satellite program (DMSP) platforms. Since the OLS instruments have no on‐board calibration, only a qualitative study of the potential to estimate aerosol and cloud properties using city lights at night is shown in this paper. The technique is demonstrated using China and India as test regions. With the launch of the visible/infrared imager/radiometer suite (VIIRS) instrument on the national polar‐orbiting operational environmental satellite system (NPOESS) in the coming decade, fully quantitative retrieval of nighttime aerosol particle optical properties from space observations using such methods will become possible. Such work will benefit aerosol forecasting, safety of navigation, aerosol data assimilation and climate studies.     

Relation between satellite observed visible-near infrared emissions,population, economic activity and electric power consumption

The area lit by anthropogenic visible-near infrared emissions (i.e., lights) has been estimated for 21 countries using night-time data from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). The area lit is highly correlated to gross domestic product and electric power consumption. Significant outliers exist in the relation between area lit and population. The results indicate that the local level of economic development must be factored into the apportionment of population across the land surface based on DMSP-OLS observed lights.     

An improved method of night-time light saturation reduction based on EVI

Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) night-time light (NTL) data have been widely applied to studies on anthropogenic activities and their interactions with the environment. Due to limitations of the OLS sensor, DMSP NTL data suffer from a saturation problem in central urban areas, which further affects studies based on nocturnal lights. Recently, the vegetation-adjusted NTL urban index (VANUI) has been developed based on the inverse correlation of vegetation and urban surfaces. Despite its simple implementation and ability to effectively increase variations in NTL data, VANUI does not perform well in certain rapidly growing cities. In this study, we propose a new index, denoted enhanced vegetation index (EVI)-adjusted NTL index (EANTLI), that was developed by reforming the VANUI algorithm and utilizing the EVI. Comparisons with radiance-calibrated NTL (RCNTL) and the new Visible Infrared Imager Radiometer Suite (VIIRS) data for 15 cities worldwide show that EANTLI reduces saturation in urban cores and mitigates the blooming effect in suburban areas. EANTLI’s similarity to RCNTL and VIIRS is consistently higher than VANUI’s similarity to RCNTL and VIIRS in both spatial distribution and latitudinal transects. EANTLI also yields better results in the estimation of electric power consumption of 166 Chinese prefecture-level cities. In conclusion, EANTLI can effectively reduce NTL saturation in urban centres, thus presenting great potential for wide-range applications.     

Estimating energy consumption from night-time DMPS/OLS imagery after correcting for saturation effects

A methodology is presented to accurately estimate electric power consumption from saturated night-time Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) imagery using a stable light correction. An area correction for the stable light image of DMSP/OLS for the year 1999 was performed and the build-up area rate data were used to clarify the intensity distribution characteristics of the stable light. Based on the spatial distribution characteristics of the stable light, the saturation light of the electric power supply area of Japan was corrected using a cubic regression equation. The regression between the correction calculations by the cubic regression equation and the statistical electric power consumption data was applied in Japan and also in China, India and 10 other Asian countries. The correction method was then evaluated. This study confirms that electric power consumption can be estimated with high precision from the stable light.     

Quantifying urban land use and impact on soils in Egypt using diurnal satellite imagery of the Earth surface

Conversion of agricultural land to urban use represents a potential loss of agricultural productivity, especially in areas where arable land is in short supply. Using derived products from both daytime (Landsat sensor data) and night-time imaging systems (U.S. Air Force Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS)) we examined the impacts of urbanization on soils in Egypt; a country with very limited agricultural land. We concluded that urban land cover types to occupy 3.7% of the total area of Egypt and that over 30% of the soils most suitable for agriculture are under urban land cover. Analysis of multiyear historical DMSP/OLS data sets (digitized from paper images) proved unreliable for long-term urban growth estimates.