Population Density Map Research Articles

Adding Measurement Error to Location Data to Protect Subject Confidentiality While Allowing for Consistent Estimation of Exposure Effects

Summary In public use data sets, it is desirable not to report a respondent's location precisely to protect subject confidentiality. However, the direct use of perturbed location data to construct explanatory exposure variables for regression models will generally make naive estimates of all parameters biased and inconsistent. We propose an approach where a perturbation vector, consisting of a random distance at a random angle, is added to a respondent's reported geographic co-ordinates. We show that, as long as the distribution of the perturbation is public and there is an underlying prior population density map, external researchers can construct unbiased and consistent estimates of location-dependent exposure effects by using numerical integration techniques over all possible actual locations, although coefficient confidence intervals are wider than if the true location data were known. We examine our method by using a Monte Carlo simulation exercise and apply it to a real world example using data on perceived and actual distance to a health facility in Tanzania.

Картографирование обеспеченности населения детскими дошкольными учреждениями Ленинского района города Саранска

The Russian system of pre-school education is unique both in its mass character and in the diversity of services; today it is the most intensively developing sector in the education system. The situation related to preschool education in Russia can be called a crisis. The main problem is the impeded accessibility of preschool education, which is currently not implemented in a proper way. The growth in the number of places in preschool institutions is catastrophically behind the growth in the number of children. Revealing the accessibility and differences in locating preschool institutions can be solved through using geoinformation technologies. As a result of our research, we specified the population coverage with the service of children’s preschool institutions in Leninsky district, Saransk, RF. The peculiar properties of preschool institutions placement are defined and the assessment of children’s preschool institutions’ service availability according to demographic structure of the population is carried out. As a result, a population density map of Leninsky district of Saransk was created. As part of the research, we developed a method of making a map of the preschool institutions accessibility. To value the provision of population with these institutions, several zones were identified taking the area of service into account. Using this technique, evaluation maps characterizing the provision of the population with children’s preschool institutions in the Leninsky district, Saransk, RF were made. The results of the research can be used by local authorities at assessing the state of the city’s infrastructure.

Satellite-derived leaf area index and roughness length information for surface–atmosphere exchange modelling: a case study for reactive nitrogen deposition in north-western Europe using LOTOS-EUROS v2.0

Abstract. The nitrogen cycle has been continuously disrupted by human activity over the past century, resulting in almost a tripling of the total reactive nitrogen fixation in Europe. Consequently, excessive amounts of reactive nitrogen (Nr) have manifested in the environment, leading to a cascade of adverse effects, such as acidification and eutrophication of terrestrial and aquatic ecosystems, and particulate matter formation. Chemistry transport models (CTMs) are frequently used as tools to simulate the complex chain of processes that determine atmospheric Nr flows. In these models, the parameterization of the atmosphere–biosphere exchange of Nr is largely based on few surface exchange measurement and is therefore known to be highly uncertain. In addition to this, the input parameters that are used here are often fixed values, only linked to specific land use classes. In an attempt to improve this, a combination of multiple satellite products is used to derive updated, time-variant leaf area index (LAI) and roughness length (z0) input maps. As LAI, we use the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD15A2H product. The monthly z0 input maps presented in this paper are a function of satellite-derived normalized difference vegetation index (NDVI) values (MYD13A3 product) for short vegetation types (such as grass and arable land) and a combination of satellite-derived forest canopy height and LAI for forests. The use of these growth-dependent satellite products allows us to represent the growing season more realistically. For urban areas, the z0 values are updated, too, and linked to a population density map. The approach to derive these dynamic z0 estimates can be linked to any land use map and is as such transferable to other models. We evaluated the sensitivity of the modelled Nr deposition fields in LOng Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS) v2.0 to the abovementioned changes in LAI and z0 inputs, focusing on Germany, the Netherlands and Belgium. We computed z0 values from FLUXNET sites and compared these to the default and updated z0 values in LOTOS-EUROS. The root mean square difference (RMSD) for both short vegetation and forest sites improved. Comparing all sites, the RMSD decreased from 0.76 (default z0) to 0.60 (updated z0). The implementation of these updated LAI and z0 input maps led to local changes in the total Nr deposition of up to ∼30 % and a general shift from wet to dry deposition. The most distinct changes are observed in land-use-specific deposition fluxes. These fluxes may show relatively large deviations, locally affecting estimated critical load exceedances for specific natural ecosystems.

A literature-based review was made to assess the applications of GIS in veterinary epidemiology and its relevance in the prevention and control of animal diseases.

A literature-based review was made to assess the applications of GIS in veterinary epidemiology and its relevance in the prevention and control of animal diseases. GIS is “a powerful set of tools for collecting, retrieving, transforming, and displaying spatial data from the real world”. Overall, a GIS is a platform consisting of hardware, software, data, and people and encompasses a fundamental and universally applicable set of value-added tools for capturing, transforming, managing, analyzing, and presenting information that is geographically referenced. These data can be combined with population data and previous disease records for the prediction of diseases. Applications of GIS are very wide in all human activities. It is used for marketing studies, telecommunications, and the location of restaurants, museums, and hospitals; in tracking truck traffic; in establishing maps of animal population density by species or maps of changes in vegetation; in locating forests, rivers, and mountains and in determining soil compositions. The application of GIS to the veterinary field has been developed over the last decade. Specialized software is becoming more affordable and user friendly. GIS can be applied in veterinary epidemiology for investigation of complex disease problems, GIS is used for early warning systems, for recording and reporting disease information and for planning animal disease prevention and control program. One of the most useful functions of GIS in epidemiology is its utility in basic mapping. It is believed that GIS will play an important role in the control and eradication of epidemic Transboundary Animal Diseases (TADs). Thus training of veterinary staff on GIS, its tools, and applications are highly recommended.

Cartographic Methods of the Research of the Rural Settlement System in Volgograd Region

The article presents the methodology of cartographic support of economic and geographical research of rural territories in Volgograd region. The methodological basis of the article is the theoretical foundations of classical economic geography and applied directions of geoinformation mapping. The authors consider the stages of the study, including: identification of mapped indicators; formation of an information base; compilation of thematic maps for each indicator; compilation of an integrated assessment card for a set of indicators. The following are proposed as the main mapped indicators: the number of rural population in 2010, % by 1969; density of the rural population in 2010, people / km2; grouping of rural settlements by population, people; grouping of rural settlements by extrapolation tendency; conditions of the temporary transport accessibility of Volgograd; conditions of the temporary transport accessibility of the district center; natural fertility of agricultural lands in bonitet points. When constructing thematic maps, methods for classifying numerical fields are used, based on the calculation of the standard deviation: for maps of population dynamics, population density, and soil quality of agricultural land. Isoline mapping is used in the construction of maps of temporary transport accessibility, where the main methods of mapping are isochrones. To conduct a comprehensive assessment of the favorable resource potential of rural areas, the method of applying thematic maps is used, i.e. overlay operations. The methodology proposed by the authors as a whole allows the formation of an information database that includes information on the dynamics of the rural population in Volgograd region for individual villages, individual rural settlements, the density of the rural population in rural settlements, the conditions of transport accessibility of rural settlements, and the natural fertility of agricultural land in rural settlements, on the differences in resource potential in rural settlements.

Earth Observation for the Implementation of Sustainable Development Goal 11 Indicators at Local Scale: Monitoring of the Migrant Population Distribution

This study focused on implementation of the Sustainable Development Goal (SDG) 11 indicators, at local scale, useful in monitoring urban social resilience. For this purpose, the study focused on updating the distribution map of the migrant population regularly residing in Bari and a neighboring town in Southern Italy. The area is exposed to increasing migration fluxes. The method implemented was based on the integration of Sentinel-2 imagery and updated census information dated 1 January 2019. The study explored a vector-based variant of the dasymetric mapping approach previously used by the Joint Research Center (JRC) within the Data for Integration initiative (D4I). The dasymetric variant implemented can disaggregate data from census areas into a uniform spatial grid by preserving the information complexity of each output grid cell and ensure lower computational costs. The spatial distribution map of regular migrant population obtained, along with other updated ancillary data, were used to quantify, at local level, SDG 11 indicators. In particular, the map of regular migrant population living in inadequate housing (SDG 11.1.1) and the ratio of land consumption rate to regular migrant population growth rate (SDG 11.3.1) were implemented as specific categories of SDG 11 in 2018. At the local level, the regular migrant population density map and the SDG 11 indicator values were provided for each 100 × 100 m cell of an output grid. Obtained for 2018, the spatial distribution map revealed in Bari a high increase of regular migrant population in the same two zones of the city already evidenced in 2011. These zones are located in central parts of the city characterized by urban decay and abandoned buildings. In all remaining city zones, only a slight generalized increase was evidenced. Thus, these findings stress the need for adequate policies to reduce the ongoing process of residential urban segregation. The total of disaggregated values of migrant population evidenced an increase of 44.5% in regular migrant population. The indicators obtained could support urban planners and decision makers not only in the increasing migration pressure management, but also in the local level monitoring of Agenda 2030 progress related to SDG 11.

A geographically weighted random forest approach for evaluate forest change drivers in the Northern Ecuadorian Amazon.

The Tropical Andes region includes biodiversity hotspots of high conservation priority whose management strategies depend on the analysis of forest dynamics drivers (FDDs). These depend on complex social and ecological interactions that manifest on different space-time scales and are commonly evaluated through regression analysis of multivariate datasets. However, processing such datasets is challenging, especially when time series are used and inconsistencies in data collection complicate their integration. Moreover, regression analysis in FDD characterization has been criticized for failing to capture spatial variability; therefore, alternatives such as geographically weighted regression (GWR) have been proposed, but their sensitivity to multicollinearity has not yet been solved. In this scenario, we present an innovative methodology that combines techniques to: 1) derive remote sensing time series products; 2) improve census processing with dasymetric mapping; 3) combine GWR and random forest (RF) to derive local variables importance; and 4) report results based in a clustering and hypothesis testing. We applied this methodology in the northwestern Ecuadorian Amazon, a highly heterogeneous region characterized by different active fronts of deforestation and reforestation, within the time period 2000-2010. Our objective was to identify linkages between these processes and validate the potential of the proposed methodology. Our findings indicate that land-use intensity proxies can be extracted from remote sensing time series, while intercensal analysis can be facilitated by calculating population density maps. Moreover, our implementation of GWR with RF achieved accurate predictions above the 74% using the out-of-bag samples, demonstrating that derived RF features can be used to construct hypothesis and discuss forest change drivers with more detailed information. In the other hand, our analysis revealed contrasting effects between deforestation and reforestation for variables related to suitability to agriculture and accessibility to its facilities, which is also reflected according patch size, land cover and population dynamics patterns. This approach demonstrates the benefits of integrating remote sensing-derived products and socioeconomic data to understand coupled socioecological systems more from a local than a global scale.

Condition of mule deer during winter: stress and spatial overlap with North American elk

We assessed body condition, diet quality (indexed by fecal nitrogen), and stress levels (using fecal glucocorticoid metabolites) in mule deer Odocoileus hemionus in southeastern Idaho, USA, during a mild (2007) and a harsh winter (2008) to evaluate spatial overlap and potential competition with North American elk Cervus elaphus. We used data from GPS telemetry to construct spatially explicit maps of local population density of elk for January–April. Loss of body condition over winter in yearling and adult female mule deer was not related to elk density but to winter severity. Fecal nitrogen increased as winter progressed in both winters, was significantly lower during 2008 than in 2007, but was not related to local population density of elk. In the mild winter of 2007, a significant positive relationship existed between local population density of elk and fecal glucocorticoid metabolite levels of mule deer, indicating increased physiological stress among mule deer wintering in close proximity to elk. Fecal glucocorticoid metabolite levels in deer were lower in 2008 than in 2007 and exhibited no significant relationship with elk density. Declining fecal glucocorticoid levels through winter may be typical of northern cervids. No difference existed in levels of fecal glucocorticoids between sexes of deer. A reduction in elk populations may not improve diet quality, physiological stress levels, or body condition of mule deer on winter range, especially during severe winters. Consequently, management and conservation of winter habitat are more likely to benefit mule deer than would altering density of elk.

U.S. Census Bureau Area Measurements for Sub-County Areas and Clarence Batschelet’s U.S. Population Density Map of 1942

ABSTRACTDuring the Second World War, the U.S. Bureau of the Census published a novel population density map for the U.S. that used minor civil divisions as its areal basis. Prior to that time, the national-level area measurements required to calculate densities for such sub-county units were unavailable. The data that enabled the production of the map published in 1942 were collected by clerical workers who were employed as part of a joint project between the Census Bureau and the Works Progress Administration. The area measurements, made using planimeters, were used with 1940 Census of Population data to compute densities that are represented on the map using a choropleth technique.

A Task Assignment Method for Sweep Coverage Optimization Based on Crowdsensing

One of the keys for the success of sweep coverage is to organize the participants to patrol effectively in large-scale target areas in order to satisfy the quality requirements of the sweep tasks. In this article, we first analyze the possibility of applying crowdsensing technology for sweep coverage and propose a framework to solve the problem of arranging participants to sweep large-scale target areas when the quality requirements change dynamically over time. First, this problem is formulated as a task assignment problem with the goal of maximizing social welfare. Then, we establish a sweep coverage quality model for the area, which is a different approach from conventional methods that focus on the point of interest (PoI), and we propose a participant incentive model that considers the sustainability of the crowdsensing platform. Since determining the optimal assignment solution is an NP-hard problem, we design two approximate algorithms to arrange participants with the goal of maximizing social welfare; these are the participant-task oriented search (PTOS) algorithm based on a two-stage greed search and the bipartite graph-based participant search (BGPS) algorithm. We evaluate our methods using a population density map dataset from real-world cities as the large-scale target area and create dynamic task requirements for the sweep coverage. The experimental results show that the performance of our two algorithms is significantly better than the performance of the baseline algorithm.

A harmony‐based approach to generating sequential color schemes for maps

AbstractGenerating high‐quality sequential color schemes for maps is challenging for most mapmakers. This article presents a harmony‐based approach for automatically generating sequential color schemes for maps. The proposed approach consists of two steps: (a) color harmony quantification for sequential color schemes on maps and (b) color scheme generation using quantified color harmony factors. The approach was tested using three experimental maps, including the Chinese water body density index map, Chinese vegetation cover index map, and Chinese population density map. Effectiveness was evaluated by comparing color schemes generated by the proposed approach with those created by the probability‐based method and ColorBrewer. Twenty‐six participants were invited to rate each map color scheme using a 5‐point scale. A t test was also used to examine the significance of the difference. The results show that the mean points of color schemes using the proposed approach are higher than those using the probability‐based method, and the corresponding P‐values are far lower than .05, which suggests that the proposed approach is better than the probability‐based method and can improve the sequential color scheme quality in automatic ways. The mean points of color schemes created using the proposed approach are also slightly higher than or similar to those of ColorBrewer, which are well‐known map color schemes manually designed by an experienced cartographer. This result further suggests that the proposed approach can meet the requirement of automatic generation for high‐quality sequential color schemes on maps.

Mapping of Waste Water Sources in the City of Manado and Alternative Solutions

The problem of wastewater is a serious problem to overcome. Pollution of rivers, waterways, wells, and the sea is increasing due to the increase in community activities. This condition is a serious challenge in the context of developing Manado as a world tourism city. This study aims to identify the location of waste water accumulation, by tracing the source of waste. This information is traced through the RTRW map and the Manado City masterplan. The study of wastewater management in the city of Manado is based on population density maps. The results of the mapping show the level of waste sources starting from a density level of less than 100 people / ha (Model A), a density level of 100-300 People / Ha (Model B), and a density level of more than 300 People / Ha (Model C). The alternative conclusions for solving the problem of Area A wastewater treatment are in place while the waste from the bathroom, kitchen and washing water may be disposed of without treatment. Area B of other household wastes must be processed by processing on-site to a certain degree of processing, which is to reach a BOD concentration of 60 mg / liter. Area C of all household wastewater will be processed in a centralized manner, namely the riolization system to a certain degree of processing so that the BOD concentration that exits is maximum of 30 mg / liter

The mapping population density in a sparsely populated region: a case study the Irkutsk Region

Adequate assessment of population density is becoming an increasingly pressing issue on both state and regional levels. It is due to the heterogeneity of population distribution patterns. We have developed the principles and methods of mapping the population density in a sparsely populated area on the example of the Irkutsk Region. Most of the region is rather characterized by the linear and local settlements with an extremely sparse network of permanent settlements except for the south of the Trans-Siberian Railway than the total areal population settlements. Applying a spot mapping method to define the borders of a populated territory, we use a buffer area radius of 3 km. Settlement lines formed by the single or double settlement chains located along the communication lines are adjacent to the areal populated territory. We have constructed the quantiareal map of the entire population density (rural-urban population areas), which adequately reflects the peculiarities of the population distribution. The map allows visualizing the quantitative differentiation of the populated territories based on the population density and separating them from the unpopulated areas. The map of population distribution areas can serve as the basis for mapping demographic, ethnographic, ecological, and socioeconomic characteristics of a population.

Spatial Quantification of the Population Exposed to Cryptococcus neoformans and Cryptococcus gattii Species Complexes in Europe: Estimating the Immunocompetent and HIV/AIDS Patients Under Risk.

Cryptococcus is an important fungal pathogen worldwide, causing serious clinical manifestations that can affect immunocompetent patients and can be particularly severe for immunocompromised patients. The Cryptococcus gattii s.s. (AFLP4/VGI), Cryptococcus tetragattii (AFLP/VGIV), Cryptococcus neoformans, and Cryptococcus deneoformans have been isolated from both clinical and environmental sources in Europe. We aim to quantify the people in Europe and the entire Mediterranean area who are under risk associated with each of the three fungal pathogens in a spatially explicit way, generating a series of maps and population statistics per country. Niche modeling was applied to estimate the potential distribution of each fungal pathogen, then these models were overlapped with a map of population density to estimate risk levels. The potential number of people per risk level and per country was quantified using a map of population count per pixel. Prevalence of HIV per country was also included in the analysis to quantify the HIV-infected population under potential risk. People under risk associated with exposure to C. gattii species (C. gattii s.s. and C. tetragattii) reached 137.65 million, whereas those exposed to C. neoformans and C. deneoformans were 268.58 and 360.78 million people, respectively. More than a half million HIV-infected patients are exposed to each of the two species of the C. neoformans species complex, and more than 200,000 to the C. gattii species complex. The present results can be useful for public health planning by European governments, focusing on the provision of inputs for a "screen-and-treat" approach, availability of medical resources, and continuous monitoring programs in risk zones.

EFFECTIVENESS OF CLASSIFICATION METHOD AND COLOR SYMBOL SCHEME ON CHOROPLETH MAP OF POPULATION DENSITY IN SPECIAL REGION OF YOGYAKARTA

Abstract. The need for presenting information in maps is increasingly high in various scientific fields. All scientific fields need to present effective data for decision making. Good decision making based on maps requires good understanding but not all scientific fields are familiar with using maps. Supporting factors for easy maps to understand are classification method and color symbol scheme. The purpose of this study was to select and test the classification method and the most effective color symbol scheme for mapping population density in the Special Region of Yogyakarta. The classification methods used in this study are constant interval, arithmetic progression, geometric progression, quantile, standard deviation and dispersal graph. The effectiveness test method for the most effective classification method is the proportion assessment. The color symbol scheme used in this study is a sequential color scheme, diverging color schemes, Corel Draw color schemes and color symbol schemes provided in ArcMap 10.3 software. The effectiveness test method for the most effective color symbol scheme is conventional eye tracking. The results showed that according to the proportion test the most effective classification method was the arithmetic interval classification method with results of 0.26. The most effective color symbol scheme in accordance with the effectiveness test using the conventional eye tracking method shows that the most effective color symbol scheme is a diverging color scheme. The important aspects to consider are average answering duration of 8.15 seconds, the accuracy of the answer is 98.9%, and easiness level of symbolization readings is 341. This research can be one of the references on the most effective classification method and reference regarding the selection of the most effective color symbol scheme on Choropleth Map of Population Density in Special Region of Yogyakarta, so that further research can continue the analysis of appropriate classification methods for demographic data. The method discussed in this study is also expected to be applicable to other data.

Effects of Co dopant on the mechanical and magnetic properties of Cr23C6 by using first principles calculation

(Co, Cr)23C6 type carbide is a typical metallic compound in many cobalt bearing alloys, and it acts as the strengthening phase in the form of bulk eutectic carbides or precipitated carbides. In this work, first-principles calculations were carried out to investigate the electronic structure, phase stability, mechanical and magnetic properties of (Co, Cr)23C6 with different cobalt occupation. Some of the calculated values are compared with previous studies and, they are found to be in a good agreement. The method considering curvature radius is firstly used to describe the degree of anisotropy. The hardness calculated through elastic constants presents an approximate downtrend with the cobalt concentration. Analysis of the density of states (DOS), overlapped population and electron density maps, indicates that the bonds in (Co, Cr)23C6 are the mixture of covalent, ionic and metallic bonds, the interactions of d-d orbits between metallic atoms contribute most to the hybridization mode. According to the population analysis, the reduction in hardness can attribute to the increase of metallicity and iconicity of the interacted metallic atoms. In addition, the formation of a large quantity of antibonding also plays a negative role in intrinsic hardness of (Co, Cr)23C6 when massive substitution of cobalt atom.

Location Mapping And Tsunami Disaster Evacuation Pathway Using Dijkstra Algorithm In Kota Sigli District, Pidie District

Sigli City Sub District is one of the Sub Districts affected by the 2004 tsunami. At that time, the community did not understand the danger of the tsunami and did not understand how to save themselves. The purpose of this study was to identify and to map out effective tsunami evacuation locations and routes in Sigli City Sub District using Dijkstra algorithm. Primary data (tsunami inundation) for this study were obtained from interviews with community representatives involving 32 people in 16 villages. Administrative map, topographic map, population density map, contour map and land use map (secondary data) were obtained from relevant institutions. The results of the study indicate that horizontal evacuation can be done through available paved road living the coastal area towads 4 recommended locations based on the physical feasibility of the land. For vertical evacuation, 24 buildings available in 7 villages can be recommended, on the condition that their structural feasibility and access standard are met.

The Comparison of Crowd Counting Algorithms based on Computer Vision

This paper aims to compare the three mainstream solutions for today’s crowd counting and analyze the highlights of each model. In MCNN, they proposed a multi-column parallel convolutional neural network structure that generates population density maps by adapting crowd changes caused by camera view-points and resolution using filters with different size receptive fields. In Switch-CNN, they added a density classifier to the MCNN to enable the use of local density changes in the crowd. In CSRNet, they abandoned the structure of a multi-column convolutional neural network, using the first ten layers of VGG-16 as the front part and the convolutional neural network as the latter part. From the analysis results, CSRNet shows advanced performance. In addition, we analyzed the comparison results of three convolutional neural networks, and derived the trend of convolutional neural network structure.

Topographical relief characteristics and its impact on population and economy: A case study of the mountainous area in western Henan, China

Topographical relief is a key factor that limits population distribution and economic development in mountainous areas. The limitation is especially apparent in the mountain- plain transition zone. Taking the transition zone between the Qinling Mountains and the North China Plain (i.e. the mountainous area in western Henan Province) as an example and based on the 200-m resolution DEM data, we used the mean change-point analysis to determine the optimal statistical unit for topographical relief, and thereafter extracted the relief degree. Taking the 1:100,000 land use data, township population and county-level industrial data, population and economic spatial models were constructed, and 200-m resolution grid population and economic density maps were generated. Afterwards, statistical analysis was carried out to quantitatively reveal the impact of topographical relief on population and economy. In addition, the impacts of other topographical factors were discussed. The results showed the following. (1) The relief degree in western Henan is generally low, where 58.6% of the regional topography does not exceed half the height of a reference mountain (relative elevation ⩽250 m). Spatially, the relief degree is high in the west while low in the east, and high in the middle while low in the north and south. There is a positive correlation between relief degree and elevation, and a much stronger correlation between relief degree and slope. (2) The linear fitting degree between the population and economic validation data and the corresponding simulation data are 0.943 and 0.909, respectively, indicating that the spatialized results can reflect the actual population and economic distribution. (3) The impact of topographical relief on population and economy was stronger than that of other topographical factors. The relief degree showed a good logarithmic fit relationship with population density (0.911) and economic density (0.874). Specifically, 88.65% of the population lives in areas where the topographical relief is ⩽0.5 and 88.03% of the gross regional product was from areas where the relief is ⩽0.3. Compared with the population distribution, the economic development showed an obvious agglomeration trend towards low relief areas.

Evacuation Priority Method in Tsunami Hazard Based on DMSP/OLS Population Mapping in the Pearl River Estuary, China

Evacuation plans are critical in case of natural disaster to save people’s lives. The priority of population evacuation on coastal areas could be useful to reduce the death toll in case of tsunami hazard. In this study, the population density remote sensing mapping approach was developed using population records in 2013 and Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) night-time light (NTL) image of the same year for defining the coastal densest resident areas in Pearl River Estuary (PRE), China. Two pixel-based saturation correction methods were evaluated for application of population density mapping to enhance DMSP/OLS NTL image. The Vegetation Adjusted NTL Urban Index (VANUI) correction method (R2 (original/corrected): 0.504, Std. error: 0.0069) was found to be the better-fit correction method of NTL image saturation for the study area compared to Human Settlement Index (HSI) correction method (R2 (original/corrected): 0.219, Std. error: 0.1676). The study also gained a better dynamic range of HSI correction (0~25 vs. 0.1~5.07) compared to the previous one [27]. The town-level’s population NTL simulation model is built (R2 = 0.43, N = 47) for the first time in PRE with mean relative error (MSE) of 32% (N = 24, town level), On the other side, the tsunami hazard map was produced based on numerical modeling of potential tsunami wave height and velocity, combining with the river net system, elevation, slope, and vegetation cover factors. Both results were combined to produce an evacuation map in PRE. The simulation of tsunami exposure on density of population showed that the highest evacuation priority was found to be in most of Zhuhai city area and the coastal area of Shenzhen City under wave height of nine meters, while lowest evacuation priority was defined in Panyu and Nansha Districts of Guangzhou City, eastern and western parts of Zhongshan City, and northeast and northwest parts of Dongguan City. The method of tsunami risk simulation and the result of mapped tsunami exposure are of significance for direction to tsunami disaster-risk reduction or evacuation traffic arrangement in PRE or other coastal areas in the world.