High-resolution population distribution data are critical for successfully addressing important issues ranging from socio-environmental research to public health to homeland security, since scientific analyses, operational activities, and policy decisions are significantly influenced by the number of impacted people. Dasymetric modeling has been a well-recognized approach for spatial decomposition of census data to increase the spatial resolution of population distribution. However, enhancing the temporal resolution of population distribution poses a greater challenge. In this paper, we discuss the development of LandScan USA, a multi-dimensional dasymetric modeling approach, which has allowed the creation of a very high-resolution population distribution data both over space and time. At a spatial resolution of 3 arc seconds (*90 m), the initial LandScan USA database contains both a nighttime residential as well as a baseline daytime population distribution that incorporates movement of workers and students. Challenging research issues of disparate and misaligned spatial data and modeling to develop a database at a national scale, as well as model verification and validation approaches are illustrated and discussed. Initial analyses indicate a high degree of locational accuracy for LandScan USA distribution model and data. High-resolution population data such as LandScan USA, which describes both distribution and dynamics of human population, clearly has the potential to profoundly impact multiple domain applications of national and global priority.

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We present the first global inventory of the spatial distribution and density of constructed impervious surface area (ISA). Examples of ISA include roads, parking lots, buildings, driveways, sidewalks and other manmade surfaces. While high spatial resolution is required to observe these features, the new product reports the estimated density of ISA on a one-km2 grid based on two coarse resolution indicators of ISA – the brightness of satellite observed nighttime lights and population count. The model was calibrated using 30-meter resolution ISA of the USA from the U.S. Geological Survey. Nominally the product is for the years 2000-01 since both the nighttime lights and reference data are from those two years. We found that 1.05% of the United States land area is impervious surface (83,337 km2) and 0.43 % of the world's land surface (579,703 km2) is constructed impervious surface. China has more ISA than any other country (87,182 km2), but has only 67 m2 of ISA per person, compared to 297 m2 per person in the USA. The distribution of ISA in the world's primary drainage basins indicates that watersheds damaged by ISA are primarily concentrated in the USA, Europe, Japan, China and India. The authors believe the next step for improving the product is to include reference ISA data from many more areas around the world.

Land-use change, dominated by an increase in urban/impervious areas, has a significant impact on water resources. This includes impacts on nonpoint source (NPS) pollution, which is the leading cause of degraded water quality in the United States. Traditional hydrologic models focus on estimating peak discharges and NPS pollution from high-magnitude, episodic storms and successfully address short-term, local-scale surface water management issues. However, runoff from small, low-frequency storms dominates long-term hydrologic impacts, and existing hydrologic models are usually of limited use in assessing the long-term impacts of land-use change. A long-term hydrologic impact assessment (L-THIA) model has been developed using the curve number (CN) method. Long-term climatic records are used in combination with soils and land-use information to calculate average annual runoff and NPS pollution at a watershed scale. The model is linked to a geographic information system (GIS) for convenient generation and management of model input and output data, and advanced visualization of model results.The L-THIA/NPS GIS model was applied to the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana, USA. Historical land-use scenarios for 1973, 1984, and 1991 were analyzed to track land-use change in the watershed and to assess impacts on annual average runoff and NPS pollution from the watershed and its five subbasins. For the entire watershed between 1973 and 1991, an 18% increase in urban or impervious areas resulted in an estimated 80% increase in annual average runoff volume and estimated increases of more than 50% in annual average loads for lead, copper, and zinc. Estimated nutrient (nitrogen and phosphorus) loads decreased by 15% mainly because of loss of agricultural areas. The L-THIA/NPS GIS model is a powerful tool for identifying environmentally sensitive areas in terms of NPS pollution potential and for evaluating alternative land use scenarios for NPS pollution management.

Although remote sensing has long been used to aid in the estimation of population, it has usually been in the context of spatial disaggregation of national census data, with the census counts serving both as observational data for specifying models and as constraints on model outputs. Here we present a framework for estimating populations from the bottom up, entirely independently of national census data, a critical need in areas without recent and reliable census data. To make observations of population density, we replace national census data with a microcensus, in which we enumerate population for a sample of small areas within the states of Kano and Kaduna in northern Nigeria. Using supervised texture-based classifiers with very high resolution satellite imagery, we produce a binary map of human settlement at 8-meter resolution across the two states and then a more refined classification consisting of 7 residential types and 1 non-residential type. Using the residential types and a model linking them to the population density observations, we produce population estimates across the two states in a gridded raster format, at approximately 90-meter resolution. We also demonstrate a simulation framework for capturing uncertainty and presenting estimates as prediction intervals for any region of interest of any size and composition within the study region. Used in concert with previously published demographic estimates, our population estimates allowed for predictions of the population under 5 in ten administrative wards that fit strongly with reference data collected during polio vaccination campaigns.

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