Paul C. Sutton

The value of the world's ecosystem services and natural capital

The services of ecological systems and the natural capital stocks that produce them are critical to the functioning of the Earths life-support system. They contribute to human welfare, both directly and indirectly, and therefore represent part of the total economic value of the planet. We have estimated the current economic value of 17 ecosystem services for 16 biomes, based on published studies and a few original calculations. For the entire biosphere, the value (most of which is outside the market) is estimated to be in the range of US

The Value of Coastal Wetlands for Hurricane Protection

16-54 trillion (1012) per year, with an average of US

Radiance calibration of DMSP-OLS low-light imaging data of human settlements

33 trillion per year. Because of the nature of the uncertainties, this must be considered a minimum estimate. Global gross national product total is around US

Global estimates of market and non-market values derived from nighttime satellite imagery, land cover, and ecosystem service valuation

18 trillion per year.

A scale-adjusted measure of “Urban sprawl” using nighttime satellite imagery

Abstract Coastal wetlands reduce the damaging effects of hurricanes on coastal communities. A regression model using 34 major US hurricanes since 1980 with the natural log of damage per unit gross domestic product in the hurricane swath as the dependent variable and the natural logs of wind speed and wetland area in the swath as the independent variables was highly significant and explained 60% of the variation in relative damages. A loss of 1 ha of wetland in the model corresponded to an average USD 33 000 (median = USD 5000) increase in storm damage from specific storms. Using this relationship, and taking into account the annual probability of hits by hurricanes of varying intensities, we mapped the annual value of coastal wetlands by 1km × 1km pixel and by state. The annual value ranged from USD 250 to USD 51 000 ha−1 yr−1, with a mean of USD 8240 ha−1 yr−1 (median = USD 3230 ha−1 yr−1) significantly larger than previous estimates. Coastal wetlands in the US were estimated to currently provide USD 23.2 billion yr−1 in storm protection services. Coastal wetlands function as valuable, selfmaintaining “horizontal levees” for storm protection, and also provide a host of other ecosystem services that vertical levees do not. Their restoration and preservation is an extremely cost-effective strategy for society.

The Nightsat mission concept

Abstract Nocturnal lighting is a primary method for enabling human activity. Outdoor lighting is used extensively worldwide in residential, commercial, industrial, public facilities, and roadways. A radiance calibrated nighttime lights image of the United States has been assembled from Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). The satellite observation of the location and intensity of nocturnal lighting provide a unique view of humanities presence and can be used as a spatial indicator for other variables that are more difficult to observe at a global scale. Examples include the modeling of population density and energy related greenhouse gas emissions.

Modeling population density with night-time satellite imagery and GIS

We estimated global marketed and non-marketed economic value from two classified satellite images with global coverage at 1 km 2 resolution. GDP (a measure of marketed economic output) is correlated with the amount of light energy (LE) emitted by that nation as measured by nighttime satellite images. LE emitted is more spatially explicit than whole country GDP, may (for some nations or regions) be a more accurate indicator of economic activity than GDP itself, can be directly observed, and can be easily updated on an annual basis. As far as we know, this is the first global map of estimated economic activity produced at this high spatial resolution (1 km 2 ). Ecosystem services product (ESP) is an important type of non-marketed value. ESP at 1 km 2 resolution was estimated using the IGBP land-cover dataset and unit ecosystem service values estimated by Costanza et al. [Valuing Ecosystem Services with Efficiency, Fairness and Sustainability as Goals. Nature’ sS erices, Island Press, Washington DC, pp. 49–70]. The sum of these two (GDP+ESP)=SEP is a measure of the subtotal ecological–economic product (marketed plus a significant portion of the non-marketed). The ratio: (ESP/SEP)× 100= %ESP is a measure of proportion of the SEP from ecosystem services. Both SEP and %ESP were calculated and mapped for each 1 km 2 pixel on the earth’s surface, and aggregated by country. Results show the detailed spatial patterns of GDP, ESP, and SEP (also available at: http://www.du.edu/psutton/esiindexisee/EcolEconESI.htm). Globally, while GDP is concentrated in the northern industrialized countries, ESP is concentrated in tropical regions and in wetlands and other coastal systems. %ESP ranges from 1% for Belgium and Luxembourg to 3% for the Netherlands, 18% for India, 22% for the United States, 49% for Costa Rica, 57% for Chile, 73% for Brazil, and 92% for Russia. While GDP per capita has the usual northern industrialized countries at the top of the list, SEP per capita shows a quite different picture, with a mixture of countries with either high GDP/capita, high ESP/capita, or a combination near the top of the list. Finally, we compare our results with two other indices: (1) The 2001 Enironmental Sustainability Index (ESI) derived as an

Evaluating scale dependence of ecosystem service valuation: a comparison of NOAA-AVHRR and Landsat TM datasets

Abstract “Urban Sprawl” is a growing concern of citizens, environmental organizations, and governments. Negative impacts often attributed to urban sprawl are traffic congestion, loss of open space, and increased pollutant runoff into natural waterways. Definitions of “Urban Sprawl” range from local patterns of land use and development to aggregate measures of per capita land consumption for given contiguous urban areas (UA). This research creates a measure of per capita land use consumption as an aggregate index for the spatially contiguous urban areas of the conterminous United States with population of 50,000 or greater. Nighttime satellite imagery obtained by the Defense Meteorological Satellite Programs Operational Linescan System (DMSP OLS) is used as a proxy measure of urban extent. The corresponding population of these urban areas is derived from a grid of the block group level data from the 1990 U.S. Census. These numbers are used to develop a regression equation between Ln(Urban Area) and Ln(Urban Population). The ‘scale-adjustment’ mentioned in the title characterizes the “Urban Sprawl” of each of the urban areas by how far above or below they are on the “Sprawl Line” determined by this regression. This “Sprawl Line” allows for a more fair comparison of “Urban Sprawl” between larger and smaller metropolitan areas because a simple measure of per capita land consumption or population density does not account for the natural increase in aggregate population density that occurs as cities grow in population. Cities that have more “Urban Sprawl” by this measure tended to be inland and Midwestern cities such as Minneapolis–St. Paul, Atlanta, Dallas–Ft. Worth, St. Louis, and Kansas City. Surprisingly, west coast cities including Los Angeles had some of the lowest levels of “Urban Sprawl” by this measure. There were many low light levels seen in the nighttime imagery around these major urban areas that were not included in either of the two definitions of urban extent used in this study. These areas may represent a growing commuter-shed of urban workers who do not live in the urban core but nonetheless contribute to many of the impacts typically attributed to “Urban Sprawl”. “Urban Sprawl” is difficult to define precisely partly because public perception of sprawl is likely derived from local land use planning decisions, spatio-demographic change in growing urban areas, and changing values and social mores resulting from differential rates of international migration to the urban areas of the United States. Nonetheless, the aggregate measures derived here are somewhat different than similar previously used measures in that they are ‘scale-adjusted’; also, the spatial patterns of “Urban Sprawl” shown here shed some insight and raise interesting questions about how the dynamics of “Urban Sprawl” are changing.

U.S. constructed area approaches the size of Ohio

Nightsat is a concept for a satellite system capable of global observation of the location, extent and brightness of night‐time lights at a spatial resolution suitable for the delineation of primary features within human settlements. Based on requirements from several fields of scientific inquiry, Nightsat should be capable of producing a complete cloud‐free global map of lights on an annual basis. We have used a combination of high‐resolution field spectra of outdoor lighting, moderate resolution colour photography of cities at night from the International Space Station, and high‐resolution airborne camera imagery acquired at night to define a range of spatial, spectral, and detection limit options for a future Nightsat mission. The primary findings of our study are that Nightsat should collect data from a near‐synchronous orbit in the early evening with 50 to 100 m spatial resolution and have detection limits of 2.5E−8 Watts cm−2sr−1µm−1 or better. Although panchromatic low‐light imaging data would be useful, multispectral low‐light imaging data would provide valuable information on the type or character of lighting; potentially stronger predictors of variables such as ambient population density and economic activity; and valuable information to predict response of other species to artificial night lighting. The Nightsat mission concept is unique in its focus on observing a human activity, in contrast to traditional Earth observing systems that focus on natural systems.

Estimation of Mexico’s Informal Economy and Remittances Using Nighttime Imagery

Abstract Night-time satellite imagery, as provided by the Defense Meteorological Satellite Programs Operational Linescan System (DMSP OLS), shows promise as a proxy measurement of urban extent. Earlier efforts have shown that the areas of contiguous saturated DMSP OLS images show strong correlations with the total population living in those areas. This paper describes efforts at modeling the population density within the urban areas identified within the continental United States. These efforts build upon the previous efforts of Clark, Berry, Nordbeck, Tobler and others to describe the variation of population density within cities. The method described herein differs from the aforementioned theories because it operates from the edges of the urban areas rather than attempting to identify a “center” of the urban cluster. By measuring distance from the edge rather than the distance from the center this method allows for the “multiple nuclei” of urban clustering that have clearly manifested as a result of the conurbation of urban centers within the U.S.A. This paper describes the methods used to allocate population to one, two, three, five, and ten square kilometer pixels for the continental U.S.A. Several urban population decay functions are applied and evaluated. In addition, an empirical urban population density decay function is derived for all the urban clusters defined by the DMSP imagery.