The future adequacy of freshwater resources is difficult to assess, owing to a complex and rapidly changing geography of water supply and use. Numerical experiments combining climate model outputs, water budgets, and socioeconomic information along digitized river networks demonstrate that (i) a large proportion of the world's population is currently experiencing water stress and (ii) rising water demands greatly outweigh greenhouse warming in defining the state of global water systems to 2025. Consideration of direct human impacts on global water supply remains a poorly articulated but potentially important facet of the larger global change question.

https://science.sciencemag.org/content/sci/289/5477/284.full.pdf

Global Water Resources: Vulnerability from Climate Change and Population Growth

Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised ...

Development of a global land cover characteristics database and igbp discover from 1 km avhrr data

I Genesis, God blesses human beings and bids us to take dominion over the fish in the sea, the birds in the air, and every other living thing. We are entreated to be fruitful and multiply, to fill the earth, and subdue it (Gen. 1:28). The bad news, and the good news, is that we have almost succeeded. There is little debate in scientific circles about the importance of human influence on ecosystems. According to scientists’ reports, we appropriate over 40% of the net primary productivity (the green material) produced on Earth each year (Vitousek et al. 1986, Rojstaczer et al. 2001). We consume 35% of the productivity of the oceanic shelf (Pauly and Christensen 1995), and we use 60% of freshwater run-off (Postel et al. 1996). The unprecedented escalation in both human population and consumption in the 20th century has resulted in environmental crises never before encountered in the history of humankind and the world (McNeill 2000). E. O. Wilson (2002) claims it would now take four Earths to meet the consumption demands of the current human population, if every human consumed at the level of the average US inhabitant. The influence of human beings on the planet has become so pervasive that it is hard to find adults in any country who have not seen the environment around them reduced in natural values during their lifetimes—woodlots converted to agriculture, agricultural lands converted to suburban development, suburban development converted to urban areas. The cumulative effect of these many local changes is the global phenomenon of human influence on nature, a new geological epoch some call the “anthropocene” (Steffen and Tyson 2001). Human influence is arguably the most important factor affecting life of all kinds in today’s world (Lande 1998, Terborgh 1999, Pimm 2001, UNEP 2001). Yet despite the broad consensus among biologists about the importance of human influence on nature, this phenomenon and its implications are not fully appreciated by the larger human community, which does not recognize them in its economic systems (Hall et al. 2001) or in most of its political decisions (Soulé and Terborgh 1999, Chapin et al. 2000). In part, this lack of appreciation may be due to scientists’ propensity to express themselves in terms like “appropriation of net primary productivity” or “exponential population growth,” abstractions that require some training to understand. It may be due to historical assumptions about and habits inherited from times when human beings, as a group, had dramatically less influence on the biosphere. Now the individual deci-

/pdf/the-human-footprint-and-the-last-of-the-wild-1vhji89mdz.pdf

The Human Footprint and the Last of the Wild

A major benefit of multitemporal, remotely sensed images is their applicability to change detection over time. Because of concerns about global and environmental change, these data are becoming increasingly more important. However, to maximize the usefulness of the data from a multitemporal point of view, an easy-to-use, cost-effective, and accurate radiometric calibration and correction procedure is needed. The atmosphere effects the radiance received at the satellite by scattering, absorbing, and refracting light; corrections for these effects, as well as for sensor gains and offsets, solar irradiance, and solar zenith angles, must be included in radiometric correction procedures that are used to convert satellite-recorded digital counts to ground reflectances. To generate acceptable radiometric correction results, a model is required that typically uses in-situ atmospheric measurements and radiative transfer code (RTC) to correct for atmospheric effects. The main disadvantage of this type of correction procedure is that it requires in-situ field measurements during each satellite overflight. This is unacceptable for many applications and is often impossible, as when using historical data or when working in very remote locations. The optimum radiometric correction procedure is one based solely on the digital image and requiring no in-situ field measurements during the satellite overflight. The darkobject subtraction (DOS) method, a strictly image-based technique, is an attempt to achieve this ideal procedure. However, the accuracy is not acceptable for many applications, mostly because it corrects only for the additive scattering effect and not for the multiplicative transmittance effect. This paper presents an entirely image-based procedure that expands on the ~10s model by including a simple multiplicative correction for the effect of atmospheric transmittance. Two straightforward methods to derive the multiplicative transmittance-correction coefficient are presented. The COSITZ) or COST method uses the cosine of the solar zenith angle, which, to a first order, is a good approximation of the atmospheric transmittance for the dates und sites used in this study. The default TAUS method uses the average of the transmittance values computed by using in-situ atmospheric field measurements made during seven different satellite overflights. Published and unpublished data made available for this study by Moran et al. (1992) are used, and my model results are compared with their results. The corrections generated by the entirely image-based COST model are as accurate as those generated by the models that used in-situ atmospheric field measurements and RTC software.

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Image-Based Atmospheric Corrections - Revisited and Improved

GDP growth is often measured poorly for countries and rarely measured at all for cities or subnational regions. We propose a readily available proxy: satellite data on lights at night. We develop a statistical framework that uses lights growth to augment existing income growth measures, under the assumption that measurement error in using observed light as an indicator of income is uncorrelated with measurement error in national income accounts. For countries with good national income accounts data, information on growth of lights is of marginal value in estimating the true growth rate of income, while for countries with the worst national income accounts, the optimal estimate of true income growth is a composite with roughly equal weights. Among poor-data countries, our new estimate of average annual growth differs by as much as 3 percentage points from official data. Lights data also allow for measurement of income growth in sub- and supranational regions. As an application, we examine growth in Sub Saharan African regions over the last 17 years. We find that real incomes in non-coastal areas have grown faster by 1/3 of an annual percentage point than coastal areas; non-malarial areas have grown faster than malarial ones by 1/3 to 2/3 annual percent points; and primate city regions have grown no faster than hinterland areas. Such applications point toward a research program in which "empirical growth" need no longer be synonymous with "national income accounts."

https://papers.ssrn.com/sol3/Delivery.cfm/nber_w15199.pdf?abstractid=1442664&mirid=1

Measuring Economic Growth from Outer Space

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.

Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption

The Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) has a unique capability to detect low levels of visible and near-infrared (VNIR) radiance at night. With the OLS "VIS" band data, it is possible to detect clouds illuminated by moonlight, plus lights from cities, towns, industrial sites, gas pares, and ephemeral events such as fires and lightning illuminated clouds. This paper presents methods which have been developed for detecting and geolocating VNIR emission sources with nighttime DMSP-OLS data and the analysis of image time series to identify spatially stable emissions from cities, towns, and industrial sites. Results are presented for the United States.

Mapping City Lights With Nighttime Data from the DMSP Operational Linescan System

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

: In reviewing the literature, the earliest report we were able to find describing the observation of fire using a satellite sensor acquiring daily-global earth observations occurred when Croft (1973) described observing fires at night in Africa using "photographs" generated from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) visible band data. Croft (1978) was later able to use digital OLS data to observe fires, city lights and gas flares. The first systematic inventory of fires with OLS data was accomplished by Cahoon et al. (1992) who manually digitized fire points from film produced from nighttime OLS orbits over Africa. Since 1972, the U.S. Department of Defense has maintained at least two DMSP platforms carrying OLS sensors in earth orbit. Because of the large data volume and restrictions on access to the data, a digital archive for DMSP-OLS data was not established until 1992. A film archive established in 1974 at the NOAA National Geophysical Data Center holds analog data from approximately 1.7 million OLS orbits acquired in the twenty years prior to 1992.

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Ethan R. Davis

Papers

Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption

Mapping City Lights With Nighttime Data from the DMSP Operational Linescan System

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

Algorithm for the Retrieval of Fire Pixels from DMSP Operational Linescan System Data