Recent improvements in mapping of global population distribution makes it possible to estimate the number and distribution of people near coasts with greater accuracy than previously possible, and hence consider the potential exposure of these populations to coastal hazards. In this paper, we combine the updated Gridded Population of the World (GPW2) population distribution estimate for 1990 and lighted settlement imagery with a global digital elevation model (DEM) and a high resolution vector coastline. This produces bivariate distributions of population, lighted settlements and land area as functions of elevation and coastal proximity. The near-coastal population within 100 km of a shoreline and 100 m of sea level was estimated as 1.2 X 10(9) people with average densities nearly 3 times higher than the global average density. Within the near coastal-zone, the average population density diminishes more rapidly with elevation than with distance, while the opposite is true of lighted settlements. Lighted settlements are concentrated within 5 km of coastlines worldwide, whereas average population densities are higher at elevations below 20 m throughout the 100 km width of the near-coastal zone. Presently most of the near-coastal population live in relatively densely-populated rural areas and small to medium cities, rather than in large cities. A range of improvements are required to define a better baseline and scenarios for policy analysis. Improving the resolution of the underlying population data is a priority.

A global analysis of human settlement in coastal zones

Biomass burning — a review of organic tracers for smoke from incomplete combustion

統計年鑑 = Statistical yearbook

The implications of current and future urbanization for global protected areas and biodiversity conservation

The third edition of Gordon Bonan's comprehensive textbook introduces an interdisciplinary framework to understand the interaction between terrestrial ecosystems and climate change. Ideal for advanced undergraduate and graduate students studying ecology, environmental science, atmospheric science, and geography, it reviews basic meteorological, hydrological, and ecological concepts to examine the physical, chemical, and biological processes by which terrestrial ecosystems affect and are affected by climate. This new edition has been thoroughly updated with new science and references. The scope has been expanded beyond its initial focus on energy, water, and carbon to include reactive gases and aerosols in the atmosphere. The new edition emphasizes the Earth as a system, recognizing interconnections among the planet's physical, chemical, biological, and socioeconomic components, and emphasizing global environmental sustainability. Each chapter contains chapter summaries and review questions, and with over 400 illustrations, including many in color, this textbook will once again be an essential student guide.

Ecological Climatology: Concepts and Applications

Night-time satellite imagery provided by the Defense Meteorological Satellite Program' s Operational Linescan System (DMSP OLS) is evaluated as a means of estimating the population of all the cities of the world based on their areal extent in the image. A global night-time image product was registered to a dataset of 2000 known city locations with known populations. A relationship between areal extent and city population discovered by Tobler and Nordbeck is identie ed on a nation by nation basis to estimate the population of the 22920 urban clusters that exist in the night-time satellite image. The relationship between city population and city areal extent was derived from 1597 city point locations with known population that landed in a ' lit' area of the image. Due to conurbation, these 1597 cities resulted in only 1383 points of analysis for performing regression. When several cities fell into one ' lit' area their populations were summed. The results of this analysis allow for an estimate of the urban population of every nation of the world. By using the known percent of population in urban areas for every nation a total national population was also estimated. The sum of these estimates is a total estimate of the global human population, which in this case was 6.3 billion. This is fairly close to the generally accepted contemporaneous (1997) estimate of the global population which stood at approximately 5.9 billion.

Census from Heaven: An estimate of the global human population using night-time satellite imagery

Time series data from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) have been used to derive georeferenced inventories of human settlements for Europe, North and South America, and Asia The visible band of the OLS is intensified at night, permitting detection of nocturnal visible-near infrared emissions from cities, towns, and villages The time series analysis makes it possible to eliminate ephemeral VNIR emission sources such as fire and to normalize for differences in the number of cloud-free observations An examination of the area lit (km2) for 52 countries indicates the OLS derived products may be used to perform the spatial apportionment of population and energy related greenhouse gas emissions

Satellite inventory of human settlements using nocturnal radiation emissions: a contribution for the global toolchest

The potential use of satellite observed nighttime lights for estimating carbon-dioxide (CO2) emissions has been demonstrated in several previous studies. However, the procedures for a moderate resolution (1 km2 grid cells) global map of fossil fuel CO2 emissions based on nighttime lights are still in the developmental phase. We report on the development of a method for mapping distributed fossil fuel CO2 emissions (excluding electric power utilities) at 30 arc-seconds or approximately 1 km2 resolution using nighttime lights data collected by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS). A regression model, Model 1, was initially developed based on carbon emissions from five sectors of the Vulcan data produced by the Purdue University and a nighttime satellite image of the U.S. The coefficient derived through Model 1 was applied to the global nighttime image but it resulted in underestimation of CO2 emissions for most of the world’s countries, and the states of the U.S. Thus, a second model, Model 2 was developed by allocating the distributed CO2 emissions (excluding emissions from utilities) using a combination of DMSP-OLS nighttime image and population count data from the U.S. Department of Energy's (DOE) LandScan grid. The CO2 emissions were distributed in proportion to the brightness of the DMSP nighttime lights in areas where lighting was detected. In areas with no DMSP detected lighting, the CO2 emissions were distributed based on population count, with the assumption that people who live in these areas emit half as much CO2 as people who live in the areas with DMSP detected lighting. The results indicate that the relationship between satellite observed nighttime lights and CO2 emissions is complex, with differences between sectors and variations in lighting practices between countries. As a result it is not possible to make independent estimates of CO2 emissions with currently available coarse resolution panchromatic satellite observed nighttime lights. However, the nighttime lights image in conjunction with the population grid can help in more accurate disaggregation of national CO2 emissions to a moderate resolution spatial grid.

https://www.mdpi.com/1996-1073/3/12/1895/pdf

Creating a Global Grid of Distributed Fossil Fuel CO2 Emissions from Nighttime Satellite Imagery

A procedure has been developed to locate and estimate the area of heavy forest burning based on the frequency of DMSP-OLS (US Air Force Defense Meteorological Satellite Program Operational Linescan System) fire detection from time series of observations across the fire season. A calibration was developed for Roraima, Brazil, using Landsat Thematic Mapper (TM) data acquired near the end of the 1998 burn season and analysed to identify unburnt, partially burnt and heavily burnt forest areas. A fire detection frequency threshold of five nights was used to map heavily burnt forest using the 3 months of DMSP-OLS observations. The threshold of five fire detections, which could occur anytime during the 3-month time period, was selected to constrain errors of commission involving unburnt forest to 10% of the total area for unburnt forest in the calibration area. At this threshold setting the DMSP-OLS estimate of heavily burnt forest area covered 79% of the Landsat measured area. It was found that 77% of the 1998 ...

Kimberly E. Baugh

Papers

Census from Heaven: An estimate of the global human population using night-time satellite imagery

Satellite inventory of human settlements using nocturnal radiation emissions: a contribution for the global toolchest

Creating a Global Grid of Distributed Fossil Fuel CO2 Emissions from Nighttime Satellite Imagery

DMSP-OLS estimation of tropical forest area impacted by surface fires in Roraima, Brazil: 1995 versus 1998

National Trends in Satellite Observed Lighting: 1992-2009