DMSP/OLS 与 NPP/VIIRS 中国大陆地区相互校正研究

DMSP/OLS与NPP/VIIRS两种夜间灯光数据来源于不同传感器,单一数据内及两种数据间无法直接比较.文章研究了中国大陆地区(不包括香港特别行政区和澳门特别行政区)DMSP/OLS之间、DMSP/OLS和NPP/VIIRS的不连续问题,对两种数据进行相互校正,最终形成一致的、可比的长时间序列研究数据.首先,通过逐步...     

NPP/VIIRS和DMSP/OLS夜光数据模拟社会经济参量对比

鉴于新一代夜间灯光数据NPP/VIIRS比传统DMSP/OLS数据具有更高空间分辨率和更宽的辐射范围,提出对比两种夜间灯光模拟社会经济参量的潜力。以环渤海区域为研究区,选取全市年平均人口、市辖区年平均人口、全市生产总值、市辖区生产总值、客运总量、全社会用电总量、工业用电、城乡居民用电、建设用地、居住用地、城市道路共11个社会参量指标,分别构建基于NPP/VIIRS和DMSP/OLS两种夜光数据夜光总值参量与11个社会经济参量的回归模型。结果表明:相比DMSP/OLS数据,NPP/VIIRS数据与除全市年平均人口外的10个社会经济指标相关性更高,模拟残差也小于DMSP/OLS数据,表明NPP/VIIRS在模拟社会经济参量上具有优势。     

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。     

基于DMSP/OLS数据的夜间低云大雾监测技术研究

在分析现有低云大雾识别方法的基础上,提出了利用夜间微光云图和红外云图识别低云大雾的双通道阈值法,并用美国国防气象卫星DMSP/OLS实测数据进行了验证。实验结果表明了基于DMSP/OLS数据的双通道阈值法进行夜间低云大雾监测的可行性。     

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。     

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。     

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...     

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。     

基于DMSP/OLS影像的城市化水平遥感估算方法

提出了一种利用DMSP/OLS夜间稳定灯光影像定量估算区域城市化水平的方法。首先,从美国国防气象卫星计划的线性扫描业务系统(Defense Meteorological Satellite Program/Operational Linescan System,DM-SP/OLS)获取的夜间稳定灯光数据中提取了夜间灯光综合指数(Night Light Compositive Index,NLCI)。然后建立了基于社会经济统计数据的城市化水平指数(Urbanization Level Index,ULI)与NLCI间的统计学模型,并据此对中国大陆地区级尺度的城市化水平进行了估算。结果表明,ULI与NLCI间存在明显的线性关系,NLCI能较好地反映城市化水平,根据该模型得到的其他年份ULI估算值与基于统计数据的ULI实际值具有较强的一致性,故模型具有一定的可靠性和普适性。本文的创新之处在于对前人提出的NLCI公式进行了改进,并提出了公式中最优参数的搜寻算法。     

基于城镇居民用地再分类的人口数据空间化方法研究——以长江中游4省为例

基于土地利用数据的人口统计数据空间化方法,在处理过程中会出现同一土地利用类型下人口难以细分的情况,从而影响人口空间数据精度。引入夜间灯光信息并提出了一种基于夜间灯光强度对城镇居民地再分类的人口空间化方法,以改善人口空间数据精度。基于DMSP/OLS夜间灯光及土地利用数据,以长江中游4省为研究区进行方法试验。研究结果显示:利用夜间灯光数据对城镇居民地再分类后,各分区模型的调整R2都提高到了0.8以上,人口空间数据总体平均相对误差较重分类前降低了12.32%。说明该方法在提高传统人口数据空间化模型精度的基础上能够细化城镇居民地人口空间分布。     

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.     

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.     

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.     

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.     

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.     

双拼组合宽角相机低空航测实验研究

介绍无人机载双拼组合相机低空航测的实验过程,包括双拼组合相机组成结构、原理以及利用该系统进行大比例尺测图的生产流程,对此过程中出现的误差进行了重点分析,并提出消除误差的方法。理论和实践证明,无人机载双拼相机低空航测可以满足1∶1000测图精度标准,比装备普通单相机工作效率有明显提高。     

DMSP/OLS night-time light intensity as an innovative indicator of regional sustainable development

This study proposes the use of DMSP/OLS night-time light data as a surrogate measure for comprehensive indicators to evaluate regional sustainable development. First, Sustainable Development Indicators (SDIs) were selected from annual multiple scores of sustainable development based on Principal Component Analysis (PCA), and annual Sum of Lights (SOL) of the study region were extracted for each year. Next, three time-series-based regression models were applied to the multiple score and SOL to verify their correlation. Lastly, based on time series, DMSP/OLS data is used to estimate regional sustainable development. Experiments using Shandong, Hubei, Henan, Anhui, Jiangxi, and Hunan Provinces, China as test datasets demonstrate that SOL is strongly related to multiple scores (R² ≥ 0.8). Moreover, the PCA results of sustainable development agree with the actual regional development conditions. In theory, night-time light can explain the key factors of SDIs. Hence, it is feasible to study regional sustainable development using SOL instead of SDIs.     

Population spatialization in China based on night-time imagery and land use data

Population is a key indicator of socioeconomic development, urban planning and environmental protection, particularly for developing countries like China. But, census data for any given area are neither always available nor adequately reflect the internal differences of population. The authors tried to overcome this problem by spatializing the population across China through utilizing integer night-time imagery (Defense Meteorological Satellite Program/Operational Linescan System, DMSP/OLS) and land-use data. In creating the population linear regression model, night-time light intensity and lit areas, under different types of land use, were employed as predictor variables, and census data as dependent variables. To improve model performance, eight zones were created using night-time imagery clustering and shortest path algorithm. The population model is observed to have a coefficient of determination (R ²) ranging from 0.80 to 0.95 in the research area, which remained the same in different years. A comparison of the results of this study with those of other researchers shows that the spatialized population density map, prepared on the basis of night-time imagery, reflects the population distribution character more explicitly and in greater detail.     

基于夜间灯光数据的城市建成区提取方法评价与应用

DMSP/OLS夜间灯光数据已被广泛应用于城市建成区的提取。目前主要存在4类提取方法:经验阈值法、突变检测法、统计数据法和较高分辨率影像数据空间比较法。以上海为例,在2000年、2003年、2006年夜间灯光数据的基础上,利用4种方法完成了城市建成区的提取。通过对不同年份数据提取结果的比较,证明了相同的灰度分割阈值对不同年份的夜间灯光数据中不存在通用性;在对2003年夜间灯光数据的提取中,4类方法所得结果精确度从高到低依次为统计数据法、突变检测法、经验阈值法和较高分辨率影像数据空间比较法,相对误差分别为1.3%、2.1%、5.1%和11.2%,在对4种方法的便捷性和可实现性进行分析与评价后,使用突变检测法完成了上海市2000~2006年城市建成区的提取。