Showing papers by "Scott J. Goetz published in 2006"

Global Environmental Data for Mapping Infectious Disease Distribution

Abstract: This contribution documents the satellite data archives, data processing methods and temporal Fourier analysis (TFA) techniques used to create the remotely sensed datasets on the DVD distributed with this volume. The aim is to provide a detailed reference guide to the genesis of the data, rather than a standard review. These remotely sensed data cover the entire globe at either 1 x 1 or 8 x 8 km spatial resolution. We briefly evaluate the relationships between the 1 x 1 and 8 x 8 km global TFA products to explore their inter-compatibility. The 8 x 8 km TFA surfaces are used in the mapping procedures detailed in the subsequent disease mapping reviews, since the 1 x 1 km products have been validated less widely. Details are also provided on additional, current and planned sensors that should be able to provide continuity with these environmental variable surfaces, as well as other sources of global data that may be used for mapping infectious disease.

Trends in Satellite-Observed Circumpolar Photosynthetic Activity from 1982 to 2003: The Influence of Seasonality, Cover Type, and Vegetation Density

Abstract: Time series analyses of a 22-yr record of satellite observations across the northern circumpolar high latitudes were conducted, and trend si n vegetation photosynthetic activity were assessed using a series of statistical tests. The results indicate that most of the northern circumpolar high latitudes (>85%) showed no significant trend in vegetation activity despite systematic climate warming during the period of analysis. Of the areas that did change, many showed the expected trends in "greening" of vegetation activity. There were, however, significant differences in the magnitude and even in the direc- tion of trends when stratified by vegetation type and density. Tundra areas consistently and predominantly showed greening trends. Forested areas showed declines in activity ("browning") in many areas, and these were systematically higher in areas with denser tree cover—whether deciduous or evergreen, needle- or broad-leafed. The seasonality of the trends was also distinct between vegetation types, with a divergence in trends between late spring and early summer (positive) versus late summer (negative) portions of the growing sea-

Remote Sensing of Riparian Buffers: Past Progress and Future Prospects

Abstract: Riparian buffer zone management is an area of increasing relevance as human modification of the landscape continues unabated. Land and water resource managers are continually challenged to maintain stream ecosystem integrity and water quality in the context of rapidly changing land use, which often offsets management gains. Approaches are needed not only to map vegetation cover in riparian zones, but also to monitor the changes taking place, target restoration activities, and assess the success of previous management actions. To date, these objectives have been difficult to meet using traditional techniques based on aerial photos and field visits, particularly over large areas. Recent advances in remote sensing have the potential to substantially aid buffer zone management. Very high resolution imagery is now available that allows detailed mapping and monitoring of buffer zone vegetation and provides a basis for consistent assessments using moderately high resolution remote sensing (e.g., Landsat). Laser-based remote sensing is another advance that permits even more detailed information on buffer zone properties, such as refined topographic derivatives and multidimensional vegetation structure. These sources of image data and map information are reviewed in this paper, examples of their application to riparian buffer mapping and stream health assessment are provided, and future prospects for improved buffer monitoring are discussed.

Validation of MODIS F/sub PAR/ products in boreal forests of Alaska

Abstract: Moderate Resolution Imaging Spectroradiometer (MODIS) fraction of photosynthetically active radiation absorbed by vegetation (FPAR ) products covering the boreal forest of interior Alaska were analyzed and compared with field measurements of canopy light harvesting over a multiyear period (2001 to 2004), as well as to high-resolution F PAR maps derived from IKONOS and Landsat ETM+ imagery. The spatial variability of FPAR within the MODIS products was examined by incorporating the field measurements and aggregating the high-resolution FPAR maps to the MODIS scale. Characterization of the temporal accuracy of the MODIS FPAR products was conducted through comparisons with continuously operating canopy light interception measurements. The MODIS product tended to overestimate FPAR relative to both ground-based measurements and Landsat-derived estimates of FPAR, particularly in the more sparsely vegetated burn scars on which we focus related research, but adequately captured seasonal variability associated with vegetation phenology. A combination of canopy closure and ground cover vegetation was identified as the source of most of the discrepancies between the MODIS estimated and field measured FPAR values. Neither the field measurements nor the high resolution image FPAR maps based on the field measurements characterized the light environment of the ground cover vegetation (i.e., <10 cm height); thus, absolute validation of the MODIS products was incomplete - despite the extensive spatial and temporal characterization of FPAR dynamics in the study region. We discuss these results, explore some other possible sources for observed differences between the MODIS, field, and high-resolution FPAR maps, and consider possible ways to address these issues in future work

Products in Boreal Forests of Alaska

Abstract: Moderate Resolution Imaging Spectroradiometer (MODIS) fraction of photosynthetically active radiation absorbed by vegetation ( ) products covering the boreal forest of interior Alaska were analyzed and compared with field measure- ments of canopy light harvesting over a multiyear period (2001 to 2004), as well as to high-resolution maps derived from IKONOS and Landsat ETM+ imagery. The spatial variability of within the MODIS products was examined by incorpo- rating the field measurements and aggregating the high-resolution maps to the MODIS scale. Characterization of the tem- poral accuracy of the MODIS products was conducted through comparisons with continuously operating canopy light interception measurements. The MODIS product tended to over- estimate relative to both ground-based measurements and Landsat-derived estimates of , particularly in the more sparsely vegetated burn scars on which we focus related research, but adequately captured seasonal variability associated with veg- etation phenology. A combination of canopy closure and ground cover vegetation was identified as the source of most of the discrep- ancies between the MODIS estimated and field measured values. Neither the field measurements nor the high resolution image maps based on the field measurements characterized the light environment of the ground cover vegetation (i.e., 10 cm height); thus, absolute validation of the MODIS products was incomplete—despite the extensive spatial and temporal charac- terization of dynamics in the study region. We discuss these results, explore some other possible sources for observed differences between the MODIS, field, and high-resolution maps, and consider possible ways to address these issues in future work. Index Terms—Boreal, fraction of photosynthetically active radiation absorbed by vegetation ( ), Moderate Resolution Imaging Spectroradiometer (MODIS), satellite remote sensing, validation.

Land‐Cover Classification and Change Detection

Abstract: Various multispectral data sets and tools are available for mapping land cover and land-cover change for inputs to hydrologic applications. The best choice is often a function of the specific application. New sensors offer increased capability in mapping spatial detail and temporal variation of land-cover categories. Algorithms have advanced in robustness and include distribution-free methods that are superior to traditional approaches in terms of modeling the multispectral distributions of reference data. Advanced subpixel methods of mapping land cover offer greater thematic coherency and the possibility of using consecutive land-cover characterizations to map change. The success of deriving a meaningful result, such as deriving a relationship between aquatic biotic indices and land-cover change, relies on a high-quality land-cover reference map. By choosing the most appropriate data sources, constructing a defensible land-cover definition set, and employing robust algorithms, analysts allow for the meaningful incorporation of land-cover map information into hydrological studies. Keywords: multispectral remote sensing; land cover; mapping; classification; mixture modeling; change detection

Laser Remote Sensing of Canopy Habitat Heterogeneity as a Predictor of Bird Species Richness

Abstract: Habitat heterogeneity has long been recognized as a fundamental variable indicative of species diversity, in terms of both richness and abundance. Satellite remote sensing data sets can be useful for quantifying habitat heterogeneity across a range of spatial scales. Past remote sensing analyses of species diversity have largely been limited to correlative studies based on the use of vegetation indices or derived land cover maps. A relatively new form of laser remote sensing (lidar) provides another means to acquire information on habitat heterogeneity. Here we examine the efficacy of lidar metrics of canopy structural diversity as predictors of bird species richness in the temperate forests of Maryland, USA. Canopy height, topography and the vertical distribution of canopy elements were derived from lidar imagery of the Patuxent National Wildlife Refuge and compared to bird survey data collected at referenced grid locations. The canopy vertical distribution information was consistently found to be the strongest predictor of species richness, and this was predicted best when stratified into guilds dominated by forest, scrub, suburban and wetland species. Similar lidar variables were selected as primary predictors across guilds. Generalized linear and additive models, as well as binary hierarchical regression trees produced similar results. The lidar metrics were also consistently better predictors than traditional remotely sensed variables such as canopy cover, indicating that lidar provides a valuable resource for biodiversity research applications.

Satellite maps show Chesapeake Bay urban development

Abstract: The extent, density, and configuration of the built environment—such as buildings, roads, parking lots, and other materials constructed for human use—have an impact on a wide range of biogeochemical and hydrological processes. These built areas, which are impervious to water infiltration, modify hydrology through the combined influence of increased peak flows, reduced base flows, flashier stream hydrographs (decreased lag times between storm events and peak discharge), and changes in bank and streambed erosion [Nilsson et al., 2003]. Additionally, increasing impervious cover has long been known to amplify point source pollution discharges into streams, including chemical runoff from parking lots and roads [Schuelen 1994]. Two maps of the built environment, expressed in terms of impervious surface area, have been derived for areas that encompass the 168,000-square-kilometer Chesapeake Bay watershed (Figure l), a region that has been highly altered by human land use [Goetz et al., 2004; Jantz et al., 2005]. One map was developed for the region at fine (30-square-meter) spatial resolution, and the other covers the extent of the conterminous United States at one-square-kilometer resolution [Elvidge et al., 2004].A finer-resolution regional map was used to assess the quality of the national map, demonstrating the utility the latter map for a range of applications related to monitoring land transformation and assessing watershed impacts.