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Remote-sensing Data (remote-sensing + data)
Selected AbstractsTracking Fragmentation of Natural Communities and Changes in Land Cover: Applications of Landsat Data for Conservation in an Urban Landscape (Chicago Wilderness)CONSERVATION BIOLOGY, Issue 4 2001Yeqiao Wang Within the metropolis survive some of the world's best remaining examples of eastern tallgrass prairie, oak savanna, open oak woodland, and prairie wetland. Chicago Wilderness is more than 81,000 ha of protected areas in the urban and suburban matrix. It also is the name of the coalition of more than 110 organizations committed to the survival of these natural lands. The long-term health of these imperiled communities depends on proper management of the more extensive, restorable lands that surround and connect the patches of high-quality habitat. Information critical to the success of conservation efforts in the region includes (1) a current vegetation map of Chicago Wilderness in sufficient detail to allow quantitative goal setting for the region's biodiversity recovery plan; (2) quantified fragmentation status of the natural communities; and (3) patterns of land-cover change and their effects on the vitality of communities under threat. We used multispectral data from the Landsat thematic mapper (October 1997) and associated ground truthing to produce a current vegetation map. With multitemporal remote-sensing data (acquired in 1972, 1985, and 1997), we derived land-cover maps of the region at roughly equivalent intervals over the past 25 years. Analyses with geographic information system models reveal rapid acceleration of urban and suburban sprawl over the past 12 years. Satellite images provide striking visual comparisons of land use and health. They also provide banks of geographically referenced data that make quantitative tracking of trends possible. The data on habitat degradation and fragmentation are the biological foundation of quantitative goals for regional restoration. Resumen: En Chicago hay una concentración de comunidades naturales globalmente significativas sorprendentemente alta. En la metrópolis sobreviven algunos de los mejores ejemplos mundiales remanentes de praderas de pastos orientales, sabanas de roble, bosques abiertos de roble y humedales de pradera. Chicago Wilderness es más de 81,000 ha de áreas protegidas en la matriz urbana y suburbana. También es el nombre de una coalición de más de 110 organizaciones dedicadas a la supervivencia de esas tierras naturales. La salud a largo plazo de estas comunidades amenazadas depende del manejo adecuado de las tierras, más extensas y restaurables, que rodean y conectan a los fragmentos de hábitat de alta calidad. La información crítica para el éxito de los esfuerzos de conservación en la región incluye: (1) un mapa actualizado de la vegetación de Chicago Wilderness con suficiente detalle para que la definición de metas cuantitativas para el plan de recuperación de la región sea posible; (2) cuantificación de la fragmentación de las comunidades naturales y (3) patrones de cambio de cobertura de suelo y sus efectos sobre la vitalidad de las comunidades amenazadas. Utilizamos datos multiespectrales del mapeador temático Landsat (octubre 1997) y verificaciones de campo asociadas para producir el mapa actualizado de vegetación. Con datos de percepción remota multitemporales (obtenidos en 1972, 1985 y 1997), derivamos los mapas de cobertura de suelo en la región en intervalos equivalentes en los últimos 25 años. El análisis de los modelos SIG revela una rápida aceleramiento del crecimiento urbano y suburbano en los últimos 12 años. Las imágenes de satélite proporcionan comparaciones visuales notables del uso y condición del suelo. También proporcionan bancos de datos referenciados geográficamente que hacen posible el rastreo de tendencias cuantitativas. Los datos de degradación y fragmentación del hábitat son la base biológica de metas cuantitativas para la restauración regional. [source] Use of multi-platform, multi-temporal remote-sensing data for calibration of a distributed hydrological model: an application in the Arno basin, ItalyHYDROLOGICAL PROCESSES, Issue 13 2006Lorenzo Campo Abstract Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS-2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring,summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat-ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd. [source] Predicting time-specific changes in demographic processes using remote-sensing dataJOURNAL OF APPLIED ECOLOGY, Issue 2 2006HENRIK B. RASMUSSEN Summary 1Models of wildlife population dynamics are crucial for sustainable utilization and management strategies. Fluctuating ecological conditions are often key factors influencing both carrying capacity, mortality and reproductive rates in ungulates. To be reliable, demographic models should preferably rely on easily obtainable variables that are directly linked to the ecological processes regulating a population. 2We compared the explanatory power of rainfall, a commonly used proxy for variability in ecological conditions, with normalized differential vegetation index (NDVI), a remote-sensing index value that is a more direct measure of vegetation productivity, to predict time-specific conception rates of an elephant population in northern Kenya. Season-specific conception rates were correlated with both quality measures. However, generalized linear logistic models compared using Akaike's information criteria showed that a model based on the NDVI measure outperformed models based on rainfall measures. 3A predictive model based on coarse demographic data and the maximum seasonal NDVI value was able to trace the large variation in observed season-specific conception rates (Range 0,0·4), with a low median deviation from observed values of 0·07. 4By combining the model of season-specific conception rates with the average seasonal distribution of conception dates, the monthly number of conceptions (range 0,22) could be predicted within ±3 with 80% confidence. 5Synthesis and applications. The strong predictive power of the normalized differential vegetation index on time-specific variation in a demographic variable is likely to be generally applicable to resource-limited ungulate species occurring in ecologically variable ecosystems, and could potentially be a powerful factor in demographic population modelling. [source] Multiyear ground-based and satellite observations of aerosol properties over a tropical urban area in IndiaATMOSPHERIC SCIENCE LETTERS, Issue 1 2007K. V. S. Badarinath Abstract Aerosol particle size distributions along with their spatial and temporal variability are important for describing both direct and indirect radiative forcing. In this study, the variation of black carbon (BC) aerosols, total aerosol mass loading and aerosol optical depth (AOD) over an urban region of Hyderabad, south India, was analyzed for 3 consecutive years from 2003 to 2005. The AOD was measured using a handheld multichannel sun-photometer at six wavelengths centered on 380, 440, 500, 675, 870 and 1020 nm and aerosol mass,size distribution was made using a quartz crystal microbalance (QCM) cascade impactor. In addition, satellite remote-sensing data from nighttime DMSP-OLS images were analyzed for inferring ancillary sources of aerosols. Results from temporal analysis (2004,2006) suggest that aerosol mass loading and BC mass concentration increased considerably over the 3-year time-period mainly due to increasing vehicular traffic from urban population growth. DMSP-OLS nighttime images for different years suggested higher forest fire occurrences in the year 2004 compared to other years. The annual mean AOD at 550 nm from moderate resolution imaging spectroradiometer (MODIS) showed relatively high values during 2004. Copyright © 2007 Royal Meteorological Society [source] | ||||||||||