TAILIEUCHUNG - REMOTE SENSING – APPLICATIONS_2

Nowadays it is hard to find areas of human activity and development that have not profited from or contributed to remote sensing. Natural, physical and social activities find in remote sensing a common ground for interaction and development. This book intends to show the reader how remote sensing impacts other areas of science, technology, and human activity, by displaying a selected number of high quality contributions dealing with different remote sensing applications. | Section 3 Oceans and Cryosphere 12 Remote Sensing of Submerged Aquatic Vegetation Hyun Jung Cho1 Deepak Mishra2 3 and John Wood4 department of Integrated Environmental Science Bethune-Cookman University Daytona Beach FL department of Geosciences Mississippi State University 3Northern Gulf Institute and Geosystems Research Institute Mississippi State University MS State MS Harte Research Institute for Gulf of Mexico Studies Texas A M University-Corpus Christi Corpus Christi TX USA 1. Introduction Remote sensing has significantly advanced spatial analyses of terrestrial vegetation for various fields of science. The plant pigments chlorophyll a and b strongly absorb the energy in the blue centered at 450 nm and the red centered at 670 nm regions of the electromagnetic spectrum to utilize the light energy for photosynthesis. In addition the internal spongy mesophyll structures of the healthy leaves highly reflect the energy in the near-infrared NIR 700- 1300 regions Jensen 2000 Lillesand et al. 2008 . The distinctive spectral characteristics of the green plants low reflectance in the visible light and high reflectance in NIR have have been used for mapping monitoring and resource management of plants and also have been used to develop spectral indices such as Simple Vegetation Index SVI NIR reflectance - red reflectance and Normalized Difference Vegetation Index NDVI NIR reflectance - red reflectance NIR reflectance red reflectance Giri et al. 2007 . The simplicity and flexibility of vegetation indices allow comparison of data obtained under varying light conditions Walters et al. 2008 . NDVI was first suggested by Ruose et al. 1973 and is one of the earliest and most popular vegetation index used to date. It is usually applied in an attempt to decrease the atmospheric and surface Bidirectional Reflectance Distribution Function BRDF effects by normalizing the difference between the red and NIR reflectance by total radiation. Index values have been associated with .

• Cơ khí - Chế tạo máy
• Remote Sensing
• human activity
• contributions dealing
• sensing applications
• interaction and development
• Journal of technology and science education
• Linking climate change education through the integration
• Kite borne remote sensing system
• Investgatng Climate Change and Remote Sensing
• Analyzing remote sensing data
• LiDAR Data
• Data Transmission
• Sensors and Platforms
• Radiometric Miscalibration
• Thematic Classification
• Remote Sensing Images
• High Performance
• Computer Architectures
• Data Analysis
• Case Study
• Land cover change
• Multi temporal remote sensing data
• Quantify forest cover change
• Dien Bien Dong district
• Groundwater potential
• Groundwater potential zones
• Middle catchment
• Remote sensing and GIS
• Morphometric parameters
• Baitarani basin
• Indicate high surface runoff
• Carbon absorption capacity
• Que Phong district
• Remote sensing – GIS combined
• GIS combined with quick measurement method
• Groundnut water stress
• Hyperspectral remote sensing
• Spectral index
• Hyperspectral remote sensing technique
• Water stress in groundnut
• Reduced photosynthesis
• Morphometric analysis of a drainage basin
• Morphometric analysis
• Drainage basin
• Geographical information system
• Sea surface temperature
• Southwest sea of Vietnam
• Remote sensing data and GIS
• Sea surface temperature trends
• Remote sensing in evaluating
• Application of remote sensing
• Evaluating the PM10 concentration
• Geometric correction
• The algorithm calculates AOD
• Simulated concentration
• Green tree
• Green space study
• Remote sensing data
• Planning of green plants
• Change detection
• Land cover/Land use
• Remote sensing and gis to analyze
• Land cover classification
• Application of remote sensing imagery
• Google Earth Engine
• Algorithms in Google Earth Engine platform
• Drought assessment
• Forecasting model
• Remote sensing as pest forecasting model
• Pest forecasting model in agriculture
• Indian economy contributing nearly
• Aerosols Concentration
• Microwave Radiometers
• Global Scale
• Image Information
• Mining Systems
• Low Res olution Images
• Seismic Profiling
• Image Sharpening
• High Resoluti on Infrared
• Sona r Rever beratio n
• earth sciences
• Research
• VNU Journal of Science
• scientific research
• scientific reports
• plant sciences
• hydrology
• land use analysis
• digital preprocessing
• Irrigation performance
• Relative water supply
• Water user associations
• Crop water deficit
• Depleted fraction
• Vietnam Journal of Science and Technology
• A review of seagrass studies
• Satellite remote sensing data
• The southeast Asia
• Status and potential
• The spectral clustering
• The spatial information
• The remote sensing image
• The fuzzy clustering
• The spectral method depends