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Near surface spectral measurements of the land surface Heidi Steltzer email@example.com Plant and Ecosystem Ecologist Natural Resource Ecology Laboratory (NREL)
SpecNet – a spectral network http://specnet.info
Advantages of near surface spectral measurements Scaling –Spatial fine resolution imagery pure pixels –Temporal frequent observations
Spatial variability in plant cover Complex or brief growing season Short grass steppe Patterned ground in the Arctic
Multi-spectral digital camera to structure sampling NDVI is the Normalized Difference Vegetation Index Images are 20 cm x 20 cm plots in a polar desert ecosystem
New tool: non-destructive measurements of the leaf area index Steltzer and Welker (2006) Ecology
Experimental manipulations of climate and other global changes Alpine tundra Polar desert
Plant cover as a continuous variable
Phenological variation NDVI vs day of year Lines are different years, data was collected using a near surface multi-band radiation sensor Data from Barrow, AK; Huemmrich et al
Environmental sensor networks An LED pyranometer for $20 Can be converted to measure NDVI or other vegetation indexes
Needs Variables of interest –Vegetation and soils –Microbial communities, biological diversity –Direct and indirect assessment models Instrumentation –Sensors –Platforms –Sensor networks Data –Automated analysis of imagery –Bioinformatics/data management
Acknowledgements National Science Foundation –Office of Polar Programs Tetracam Inc. Joe DeCant Jeff Welker Rich Conant Fred Hummerich and other Specnetters Seth Munson NREL
Lab for Remote Sensing Hydrology and Spatial Modeling Dept. of Bioenvironmental Systems Engineering, NTU Satellite Remote Sensing for Land-Use/Land-Cover.
U.S. Department of the Interior U.S. Geological Survey USGS/EROS Data Center Global Land Cover Project – Experiences and Research Interests GLC2000-JRC.
Scaling Biomass Measurements for Examining MODIS Derived Vegetation Products Matthew C. Reeves and Maosheng Zhao Numerical Terradynamic Simulation Group.
Reducing Canada's vulnerability to climate change - ESS Variation of land surface albedo and its simulation Shusen Wang Andrew Davidson Canada Centre for.
Active Remote Sensing Systems March 2, 2005 Spectral Characteristics of Vegetation Temporal Characteristics of Agricultural Crops Vegetation Indices Biodiversity.
원격 지질학 발표수업 - vegetation 강예랑 김은진 박수진 신선용 이보미 지성인.
BIOL 585 – Fall Schedule: Week 1: Figure set activity (LAB) Week 2: Field sampling at Prophetstown State Park (FIELD) Week 3: Data analysis & interpretation.
Estimating forest structure in wetlands using multitemporal SAR by Philip A. Townsend Neal Simpson ES 5053 Final Project.
Floods and droughts are the most important hydrological disturbances in intermittent streams. The concept of hydrological disturbance is strongly.
Remote Sensing vs. Individual-Based Ecology. Goals of the Talk (Paper) Order my thoughts. Order my thoughts. Assemble/summarize/link some relevant 1°
Remote Sensing of Urban Landscapes and contributions of remote sensing to the Social Sciences.
Life: levels of organization – organism (individuals): any form of life – population: a group of interacting individuals of same species – community: populations.
Lunar Observations of Changes in the Earth’s Albedo (LOCEA) Alexander Ruzmaikin Jet Propulsion Laboratory, California Institute of Technology in collaboration.
DIFFERENCES IN SOIL RESPIRATION RATES BASED ON VEGETATION TYPE Maggie Vest Winter Ecology 2013 Mountain Research Station.
Use of Multispectral Imagery for Variable Rate “Application-zone” Identification in Cotton Production Tim Sharp Beltwide Cotton Conference January 6-10,
An Object-oriented Classification Approach for Analyzing and Characterizing Urban Landscape at the Parcel Level Weiqi Zhou, Austin Troy& Morgan Grove University.
Satellite Imagery and Remote Sensing NC Climate Fellows June 2012 DeeDee Whitaker SW Guilford High Earth/Environmental Science & Chemistry.
MODIS Subsetting and Visualization Tool: Bringing time-series satellite-based land data to the field scientist National Aeronautics and Space Administration.
Real-time integration of remote sensing, surface meteorology, and ecological models.
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