Geography 411/611 Remote sensing: Principles and Applications Thomas Albright, Associate Professor Laboratory for Conservation Biogeography, Department of Geography & Program in Ecology, Evolution, & Conservation Biology Fall 2018, University of Nevada, Reno Remote sensing: Outline for today What Key concepts and tradeoffs Types and platforms RS for biogeochemical cycles 2 1
3 Why remote sensing? 4 2
Why study remote sensing? It s remote! 5 Why study remote sensing? It s remote! Synoptic perspective 6 3
Why study remote sensing? It s remote! Synoptic perspective Expand limits of human perception 7 Why study remote sensing? It s remote! Synoptic perspective Expand limits of human perception Often quantifiable and repeatable 8 4
Remote Sensing, Defined (Jensen) General definition: the acquiring of data about an object without touching it Detailed definition: the noncontact recording of information from the ultraviolet, visible, infrared, and microwave regions of the EM spectrum by means of instruments such as cameras, scanners, lasers, linear arrays, and/or area arrays located on platforms such as aircraft or spacecraft, and the analysis of acquired information by means of visual and digital image processing 9 GIS Remote Sensing is not: Just about taking pictures Just about computer processing Necessarily very precise A panacea that can someday allow us to detect everything of interest on the earth s surface (i.e. substitute for field investigations). 10 5
Remote Sensing is: A science An art A practice A set of tools A vehicle for education and communication A combination of all the above! 11 Physics Geography Bio-geophysical sciences Statistics Remote Sensing Computer Science Aviation, Rocket Science Mechanical, electrical, civil, Engineering Mathematics 12 6
Deciduous vs Coniferous Trees 0.4 0.7 μm 0.7 0.9 μm 13 Lillesand and Kiefer 1994 14 7
0.4 0.7 μm 0.7 0.9 μm 15 Why study remote sensing? Some of you will use remote sensing data in your professional career Some of you will become professional remote sensing specialists push the envelope and generate data for others We are all consumers of remote sensing data Google Earth/maps Nightly weather 16 8
Key concepts: Resolution 10 m 10 m B G R NIR Jan 16 Feb 16 ruler 8-bit (0-255) 10-bit (0-1023) Spatial - the size of the field-of-view, e.g. 10 10 m. Spectral - the number and size of spectral regions (or frequencies) the sensor records data in, e.g. blue, green, red, near-infrared, thermal infrared. Temporal - how often the sensor acquires data, e.g., every 30 days. Radiometric - sensitivity of detectors to small difference in electromagnetic energy. 17 Spatial Resolution Imagery of residential housing in Mechanicsville, New York, obtained on June 1, 1998, at a nominal spatial resolution of 0.3 x 0.3 m (approximately 1 x 1 ft.) using a digital camera. Jensen, 2007 18 9
Spectral Resolution Jensen, 2009 19 Airborne Visible Infrared Imaging Spectrometer (AVIRIS) Datacube of Sullivan s Island Obtained on October 26, 1998 Color-infrared color composite on top of the datacube was created using three of the 224 bands at 10 nm nominal bandwidth. Jensen, 2009 10
Radiometric Resolution 0 0 7-bit (0-127) 8-bit (0-255) 0 9-bit (0-511) 0 10-bit (0-1023) Jensen, 2009 21 Radiometric Resolution high low Lowest (binary) 1 x 1 m of Ronald Reagan International Airport in Washington, DC by Digital Globe, Inc. 22 Jensen, 2009 11
Temporal Resolution Remote Sensor Data Acquisition June 1, 2008 June 17, 2008 July 3, 2008 16 days Jensen, 2009 23 Time Series of 1984 and 1988 NDVI Measurements Derived from AVHRR Data for the Region around El Obeid, Sudan, in Sub-Saharan Africa Which year was probably wetter? Jensen, 2000 24 12
Discussion: Why not just use a system that is: - High spatial resolution - High spectral resolution - High temporal resolution - High radiometric resolution 26 13
Platforms: from drones to geostationary satellites 27 Basic principle of RS: measuring EMR radiation 28 14
Three models for remote sensing Passive - Reflected - Emitted Active 29 Three models for remote sensing Reflected Passive Optical Remote Sensing: Energy is radiated by atomic particles from the Sun Moves through space at the speed of light Interacts with atmosphere (refraction, scattering, absorption) Interacts with Earth surface features Again interacts with atmosphere Reaches sensor and interacts with optical system, filter, emulsion or detector 30 15
Three models for remote sensing Emitted Passive Remote Sensing: Energy is radiated (emitted) by the target of interest May be mixed with some reflected energy Moves through space at the speed of light Interacts with atmosphere (refraction, scattering, absorption) Reaches sensor and interacts with optical system, filter, emulsion or detector Mostly longer wavelengths (e.g. thermal, microwave) 31 Three models for remote sensing Active Remote Sensing case: Instruments generate their own energy, illuminating the target features Moves through space at the speed of light Interacts with atmosphere (refraction, scattering, absorption) Interacts with Earth surface features Again interacts with atmosphere Reaches sensor and interacts with optical system, filter, emulsion or detector 32 16
Electromagnetic Energy Energy Balance: Incident Energy = (Reflected or Scattered) + Absorbed + Transmitted Spectral Reflectance (%) = (Reflected / Incident) * 100 Sabins 1987 33 17
Water absorption bands: 0.97 mm, 1.19 mm, 1.45 mm, 1.94 mm, 2.70 mm Jensen 2004 18
Spectral Reflectance Characteristics of Sweetgum Leaves (Liquidambar styraciflua L.) Plant stress most apparent in 535-640 and 685 700 nm visible light wavelength ranges Jensen 2007 Jensen 2007 19
What can RS contribute to ecosystem science and biogeochemical cycling? Strategies Direct measurements Atmospheric Water column Vegetation & soil Indirect measurements Accounting (solving for missing stuff) 39 What can RS contribute to ecosystem science and biogeochemical cycling? Examples from different biogeochemical cycles Nitrogen Satellite lightning mapping Canopy N Nitrogen oxide in atmosphere Methane Carbon 40 20
NASA/JPL 41 Michigan Tech 42 21
RS and Carbon https://www.ted.com/talks/greg_asner_ecolo gy_from_the_air?language=en 43 22