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.     

基于多源遥感数据的陕西2000～2015年城市扩展研究北大核心CSCD

夜间灯光数据已成为监测城市发展进程及空间格局演变的重要依据。利用覆盖陕西省的2000、2005、2010年3期DMSP/OLS数据及2015年无云复合NPP/VIIRS数据,结合MODIS等多源遥感数据构建VANUI、EANTLI两种指数模型,识别并提取陕西省城市建成区面积,经过对比分析后,选取较为精确的EANTLI指数重建陕西省2000～2015年城市扩展进程,并对西安市城市扩展的细节特征进行探究。结果表明:EANTLI指数在城市建成区识别与提取方面较VANUI指数稳定;2000～2015年陕西省城市扩展的不均衡性较为突出,关中各地市城市建成区面积增长速率最快,陕北次之,陕南地区较为缓慢。陕西省城市扩展的主要特征是以各地市中心城市为核心,呈同心圆或扇形模式向外蔓延;西安市城市扩展具有明显的外延性特征,城市重心逐渐向西移动,城市建成区向西北、西南方向持续扩展。     

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。     

Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data

Urban areas concentrate people, economic activity, and the built environment. As such, urbanization is simultaneously a demographic, economic, and land-use change phenomenon. Historically, the remote sensing community has used optical remote sensing data to map urban areas and the expansion of urban land-cover for individual cities, with little research focused on regional and global scale patterns of urban change. However, recent research indicates that urbanization at regional scales is growing in importance for economics, policy, land use planning, and conservation. Therefore, there is an urgent need to understand and monitor urbanization dynamics at regional and global scales. Here, we illustrate the use of multi-temporal nighttime light (NTL) data from the U.S Air Force Defense Meteorological Satellites Program/Operational Linescan System (DMSP/OLS) to monitor urban change at regional and global scales. We use independently derived data on population, land use and land cover to test the ability of multi-temporal NTL data to measure regional and global urban growth over time. We apply an iterative unsupervised classification method on multi-temporal NTL data from 1992 to 2008 to map urbanization dynamics in India, China, Japan, and the United States. For two-year intervals between 1992 and 2000, India consistently experienced higher rates of urban growth than China, and both countries exceeded the urban growth rates of the United States and Japan. This is not surprising given that the populations of India and China were growing faster than those of the U.S. and Japan during those periods. For two-year intervals between 2000 and 2008, China experienced higher rates of urban growth than India. Results show that the multi-temporal NTL provides a regional and potentially global measure of the spatial and temporal changes in urbanization dynamics for countries at certain levels of GDP and population-driven growth.     

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.     

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。     

A comparison of NDVI and EVI in the DisTrad model for thermal sub-pixel mapping in densely vegetated areas: a case study in Southern China

The DisTrad (Disaggregation Procedure for Radiometric Surface Temperature) model shows limited applicability for sub-pixel mapping of thermal remote-sensing images in densely vegetated areas due to the phenomenon of normalized difference vegetation index (NDVI) saturation. In this article, we compared the effect of NDVI and enhanced vegetation index (EVI) in the DisTrad model for thermal sub-pixel mapping in densely vegetated areas due to their different sensitivity in densely vegetated areas. Taking Ganzhou in Southern China as an example, we produced 250-m thermal remote-sensing images from a 1000-m image using 250-m NDVI and EVI data. After comparing with the synchronous 90-m thermal image from advanced spaceborne thermal emission and reflection radiometer, we found that the EVI can achieve a better result than NDVI in densely vegetated areas.     

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。     

Study of Urban Expansion and Driving Factors in Xi’an City based on Nighttime Light Data

The dynamic monitoring of urban expansion information is of great significance to understand the social and economic activities of cities and the implementation and feedback of urban planning.Using DMSP / OLS night-time light image as data source,the urban expansion data were corrected and extracted by using rational function model and threshold dichotomy.By using the light index,urban spatial expansion rate and intensity index and the index of center of gravity migration,The results show that the urban built-up area in Xi’an has expanded 2.2 times from 148 km² in 1993 to 473 km² in 2013.The direction of urban expansion expands from southwest to south and north,and the spatial expansion mode also increases from the early stage The single-core concentric expansion mode gradually transformed into a multi-level nuclear growth expansion mode;thus using gray relational analysis to analyze the socio-economic indicators of the suburbs in Xi’an in 2008~2013 (Weiyang district,Yanta district,Baqiao district and Chang’an district) It is confirmed that secondary industry,population density,tertiary industry and fixed assets of the whole society are the main driving factors of urban expansion in four districts respectively.     

Analyzing Regional Inequality of Socioeconomic Development in China with Nighttime Light

Satellite\|derived nighttime light (NTL)data have been extensively used as an efficient proxy measure for monitoring urbanization dynamics and socioeconomic activity.This is because remotely sensed NTL signals can be quantitatively connected to demographic and socioeconomic variables.The recently composited cloud\|free NTL imagery derived from the Visible Infrared Imaging Radiometer Suite (VIIRS)provides spatially detailed observations of human settlements.We quantitatively estimated socioeconomic development inequalities across 30 provinces andmunicipalities in mainland China using VIIRS NTL data associated with both regional gross domestic product (GDP)and population census data.We quantitatively investigated relations between NTL,GDP,and population using a linear regression model.Our results suggest that NTL have significant positive correlations with GDP and population at different levels.Several inequality coefficients were derived from VIIRS data and statistical data at multiple spatial scales.NTL\|derived inequality coefficients enabled us to elicit more detailed information on differences in regional development at multiple levels.Our study of provinces and municipalities revealed that county\|level inequality was more significant than city\|level.The results of population\|weighted NTL inequality indicate an obvious regional disparity with NTL distribution being more unequal in China’s undeveloped western regions compared with eastern regions.Our findings suggest that given the timely and spatially explicit advantages of VIIRS,NTL data are capable of providing comprehensive information regarding inequality at multiple levels,which is not possible through the use of traditional statistical sources.     

Development of a two-band enhanced vegetation index without a blue band

The enhanced vegetation index (EVI) was developed as a standard satellite vegetation product for the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS). EVI provides improved sensitivity in high biomass regions while minimizing soil and atmosphere influences, however, is limited to sensor systems designed with a blue band, in addition to the red and near-infrared bands, making it difficult to generate long-term EVI time series as the normalized difference vegetation index (NDVI) counterpart. The purpose of this study is to develop and evaluate a 2-band EVI (EVI2), without a blue band, which has the best similarity with the 3-band EVI, particularly when atmospheric effects are insignificant and data quality is good. A linearity-adjustment factor β is proposed and coupled with the soil-adjustment factor L used in the soil-adjusted vegetation index (SAVI) to develop EVI2. A global land cover dataset of Terra MODIS data extracted over land community validation and FLUXNET test sites is used to develop the optimal parameter (L, β and G) values in EVI2 equation and achieve the best similarity between EVI and EVI2. The similarity between the two indices is evaluated and demonstrated with temporal profiles of vegetation dynamics at local and global scales. Our results demonstrate that the differences between EVI and EVI2 are insignificant (within ± 0.02) over a very large sample of snow/ice-free land cover types, phenologies, and scales when atmospheric influences are insignificant, enabling EVI2 as an acceptable and accurate substitute of EVI. EVI2 can be used for sensors without a blue band, such as the Advanced Very High Resolution Radiometer (AVHRR), and may reveal different vegetation dynamics in comparison with the current AVHRR NDVI dataset. However, cross-sensor continuity relationships for EVI2 remain to be studied.     

MODIS NDVI与MODIS EVI的比较分析

MODIS NDVI与MODIS EVI是目前应用比较广泛的植被指数,MODIS EVI是对NDVI的发展和延续,从植被指数计算公式和合成方法两方面做了改进。具体表现在:避免了MODIS NDVI在植被高覆盖区易饱和的问题,考虑了土壤背景对植被指数的影响,对气溶胶等残留做了进一步校正,采用BRDF/CV-MVC合成方法保证了合成采用最佳像元。EVI时间序列相较于NDVI时间序列季节性更明显,能够更好地反映高植被覆盖区的季节性变化特征,并且很少有突降现象,时间序列曲线较平滑。EVI的这些优势为高覆盖植被物候特征的季节性变化监测提供了新的思路。     

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.     

A dynamic model for population mapping: a methodology integrating a Monte Carlo simulation with vegetation-adjusted night-time light images

Population is attracting increasing attention as a driver of resource overexploitation, environmental degradation, loss of biodiversity, and other environmental challenges. Timely and accurately updating maps of population distribution are thus urgently needed. Images of night-time lights from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) have been used for years in population mapping as an alternative to human settlement distribution. The capacity of night-time light images for gridding populations, however, is compromised by the dual effects of saturation and overglow. Static models of the human settlement index (HSI), elevation-adjusted human settlement index (EAHSI), and vegetation-adjusted night-time light urban index (VANUI) have been developed to counteract these negative effects by using constant coefficients. The static models, however, retain disadvantages due to the negative effects of the high variation of socio-economic backgrounds in different study areas. In this study, we integrate Monte Carlo simulation with the above three static indices and propose the dynamic model VANUI Supported by Monte Carlo Simulation (VANUIMCS) for mapping the population of Liaoning Province, China. We assess the accuracy of the simulation using data for 60 counties and 1251 townships. The VANUIMCS improve the accuracy of population mapping, with the mean percentage errors of 19.43% at the county level and 43.19% at the township level.     

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。      

VIIRS constant spatial-resolution advantages

The Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imager Radiometer Suite (VIIRS) was launched on 28 October 2011, nearly 20 years after the conceptual definition began at the Hughes Aircraft Company's Santa Barbara Research Center. Constrained off-nadir pixel growth, producing constant or near-constant VIIRS spatial resolution over the entire scan swath, is a patented design feature that dramatically improves imaging radiometry compared to VIIRS predecessors. VIIRS ground-projected east–west (across the orbit track) and north–south (along the orbit track) pixel dimensions are constrained to within a factor of two from nadir to ±1500 km off-nadir (edge of scan) in all 22 VIIRS spectral bands. The capability is a valuable improvement to previous systems' six-fold across-track pixel growth over narrower swaths, while improving signal-to-noise ratio (SNR) without larger optics. The technique allows the VIIRS day/night band (DNB) to offer nearly 9- to over 50-fold finer and truly constant area spatial resolution with enhanced sensitivity and dynamic range compared with the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). This article reviews constant resolution from concept to VIIRS implementation and compares several VIIRS applications to similar applications of systems VIIRS replaces to demonstrate advantages of the new capability.     

An estimation of housing vacancy rate using NPP-VIIRS night-time light data and OpenStreetMap data

ABSTRACT

As an informative proxy measure for a range of socio-economic variables, satellite-derived night-time light (NTL) data have been widely used to investigate the diverse anthropogenic activities and reveal urbanization development. Due to the rapid increase of Chinese urbanization rate, from 25.3% in 1987 to 58.5% in 2017, and ‘crazy expansion’ of city space, the sick phenomenon – ‘Ghost Town’ – has been brought out, generally defined as places with high housing vacancy rate (HVR), which will cause the huge waste of the limited land source in China. To investigate the HVR of urban areas in China, this study attempts to establish a hybrid model combining data derived from National Polar-Orbiting Partnership–Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL sensors with OpenStreetMap (OSM) data. By distinguishing non-residential areas and introducing detailed residential building information, we proposed a novel HVR estimation model, thus realizing the estimation of HVR in 31 Chinese provincial cities with different development levels (Tier 1–Tier 3). The results showed the average HVR of Tier 2 cities (0.204) was higher than that of Tier 1 cities (0.189) and Tier 3 cities (0.233). The model was proven more accurate (root mean square error of approximation (RMSE) = 0.022) when compared with previous models. To explore the reasons causing different HVRs in these provincial cities, the relationship between HVR and typical socio-economic factors – gross domestic product (GDP), population, and housing price – was also revealed. Through correlation verification and built of a regression model, HVR was found positively correlated with housing price (0.409), however, negatively correlated with population (?0.829) and GDP (?0.356). The research is an indication of the applicability of using data derived from NPP-VIIRS NTL sensors in reflecting HVR and an exploration to distinguish socio-economic factors influencing HVR in different cities. The model we proposed can potentially provide guidance for urban planners to formulate better land-use plan and rental measures.     

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。     

Vegetation Cover Change and Urban Expansion in Beijing-Tianjin-Hebei during 2001~2015 based on Google Earth Engine

At present,the main mode of remote sensing image analysis is to download the data,preprocess and extract the thematic information by using the algorithm model.The model has disadvantages of huge amount of data and low efficiency in large scale area.Based on the massive remote sensing image data and powerful computing and storage capabilities of Google Earth Engine platform,we use a linear regression trend analysis method programming to process MOD13Q1-NDVI data,and then analyze the change of vegetation coverage from 2001 to 2015 in beijing\|tianjin\|hebei.We use threshold method of processing DMSP/OLS data to extract urban land,and analysis of 2001 and 2013 urban expansion and degradation by using change detection method.The results show that:(1)The trend of vegetation change was mainly improved,and the area proportion of improvement was 63%,which was far greater than the proportion of degradation 22%.The region of vegetation improvement is mainly in the northwestern part of the study area,and the region with obvious degraded vegetation is the mainly in the Middle East(Beijing,Tianjin and other megacities).(2)From 2001 to 2010,the area of Beijing,Tianjin and Hebei changed little,with a ratio of 60%.[JP2]In 2013,the area decreased by 13 thousand Km2 compared with 2010,with a decrease of 5.97%.(3)90.45% of the urban areas remained unchanged,and the proportion of urban degradation areas(7.2%) was significantly higher than that of the expansion areas(2.3%).This paper makes full use of GEE platform to realize data processing quickly and efficiently,and solve Geosciences problems,so as to provide reference for related research.[JP]     

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.