'Spectral reflectance' diaporamas de présentation

Nicolas Ackermann Supervisor : Prof. Christiane Schmullius

Biomass retrieval in temperate forested areas with a synergic approach using SAR and Optical satellite imagery. Nicolas Ackermann Supervisor : Prof. Christiane Schmullius Co- supervisors : Dr. Christian Thiel , Dr. Maurice Borgeaud WSL Davos , 8th December 2011. Presentation outline.

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Understanding Multispectral Reflectance

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Hyperspectral remote sensing

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Remote Sensing Energy Interactions with Earth Systems

Remote Sensing Energy Interactions with Earth Systems. Interactions with the Atmosphere. Scattering, refraction, absorption. Interactions with the Atmosphere. Scattering Refraction Absorption. Scattering.

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307 views • 29 slides

Dario Papale Contributi: Vern Vanderbilt, TA- Quinn Hart, M. Meroni, CCRS

Remote sensing and modeling in forestry Lecture 9 Vegetation indexes. Dario Papale Contributi: Vern Vanderbilt, TA- Quinn Hart, M. Meroni, CCRS. What is affecting canopy reflectance.

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Introduction and Basic Concepts

Introduction and Basic Concepts. (v) Spectral Reflectance Curves. Objectives. Spectral reflectance curve of some of the important earth surface features Vegetation Bare soil Water. Spectral Reflectance Curve. Spectral Reflectance R ? Spectral Reflectance Curve

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Introduction and Basic Concepts

Introduction and Basic Concepts. (iv) Energy Interactions with Earth Surface Features. Objectives. Interactions of the electromagnetic radiation with the Earth surface features Reflection Absorption Transmission. Incident radiation. Reflection. Earth. Transmission. Absorption.

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Dario Papale Contributi: Vern Vanderbilt, TA- Quinn Hart, M. Meroni, CCRS

Remote sensing and modeling in forestry Lecture 11 Models. Dario Papale Contributi: Vern Vanderbilt, TA- Quinn Hart, M. Meroni, CCRS. What is affecting canopy reflectance.

328 views • 21 slides

Electromagnetic Radiation

Electromagnetic Radiation. Most remotely sensed data is derived from Electromagnetic Radiation (EMR). This includes: Visible light Infrared light (heat) X-Rays Radar Etc. To use RS data we need to review some information on EM. Electromagnetic Radiation. Electromagnetic Energy.

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October 20, 2003

Using Conceptual Models to Select Indicators for Monitoring Conditions on Rangelands Bob Breckenridge. October 20, 2003. Purpose.

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Digital Image Processing: A Remote Sensing Perspective FW5560 Lecture 7 Radiometric Correction

Digital Image Processing: A Remote Sensing Perspective FW5560 Lecture 7 Radiometric Correction. Radiometric correction

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Objective of Remote Sensing

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Objective of Remote Sensing

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MAPPING SNOW AND ICE FROM GEOSTATIONARY SATELLITES: GETTING READY FOR GOES-R

Yes. T 4 < 230 K. No. SI > SI T and R 1 > R 1T and R 2 < 5% and T 4 < 290K. Yes. No. GOES-9. Yes. T 4 <265K. Colorado. No. Snow. Cloud. Yes. T 4 >285K. Texas. No. Yes. R 1 >25% or R 2 >10%. No. New Mexico. Colorado. Texas. Land. New Mexico. Feb 25, 2004.

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Material and Method ?Tea plants ( camellia sinensis L. cv. Yabukita )

86. 83. Experiment field. Measurement area of spectral reflectance. 81. 93. 97. 100. 104. 105. Annual meeting on ASA (13th to 15th Nov. 2006 at Indianapolis). Development of Yield and Quality Estimation Methods for Tea-plant by Image Processing.

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The Spectral Reflectance of Ship Wakes between 400 and 900 nm

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Yield Estimation and Quality Evaluation of Sweet Potato Using Spectral Reflectance

Yield Estimation and Quality Evaluation of Sweet Potato Using Spectral Reflectance. SATO Muneharu, ISHIGURO Etsuji, ISHIKAWA Daitaro, and SEKIOKA Shin-ichi Faculty of Agriculture, Kagoshima University, Japan. Question : Can we estimate yield & quality of sweet potato before harvest remotely?

161 views • 1 slides