CLASSIFICATION OF NONPHOTOGRAPHIC REMOTE SENSORS

Transcription

1 CLASSIFICATION OF NONPHOTOGRAPHIC REMOTE SENSORS PASSIVE ACTIVE DIGITAL CAMERA THERMAL (e.g. TIMS) VIDEO CAMERA MULTI- SPECTRAL SCANNERS VISIBLE & NIR MICROWAVE HYPERSPECTRAL (e.g. AVIRIS) SLAR Real Aperture Synthetic Aperture LIDAR ACROSS TRACK (sweep) e.g. Landsat, AVHRR ALONG TRACK (push) e.g. SPOT

2 Light Detection And Ranging LiDAR operates similar to Radar except that the wavelengths are much shorter (visible and near infrared ) 1064nm (or microns) is common for forestry applications. (near infrared) Why this range? Vegetation, Soil, Rock reflect (echo) strongly in these wavelengths Minimal loss of signal from atmospheric scattering

3 Light Detection And Ranging Airborne LiDAR uses a laser range finder mounted in a precisely navigated aircraft to scan the earth's surface at very high rates and collect very dense clouds of X-Y-Z coordinates. LIDAR data are useful for anyone wanting to know the shape of the land surface or height of the vegetation and buildings on the land.

4 Orthophoto (aerial photo) ) Bare earth shaded topography Relief map derived from LiDAR USGS topographic map (Oregon LiDAR Consortium)

5 Types of Airborne LiDAR Sensors Laser operating principles (Pulsed, Continuous Wave) Operating wavelengths (near--infrared, green) Laser system characteristics: Power, Pulse Repetition Frequency (PRF), Scanning Pattern, Footprint Size, etc. Number of returns: Single Return Multiple Return Waveform

6 Operating Wavelengths Near--Infrared wavelength Used by most airborne terrestrial LiDAR systems The most common laser is the solid--state Nd:YAG laser which produces radiation at an IR wavelength of 1064 nm Easily absorbed at the water surface (unreliable water surface reflections) Green Wavelength Used by airborne bathymetric and topo--bathy systems Nd:YAG IR laser output is frequency doubled to produce output at 532 nm (0.532 microns green) Can penetrate water

7 Laser Operating Principles Pulsed Lasers Most commonly used for ranging applications Consists of a pulsed laser transmitter, an optical telescope receiver that amplifies the backscatter, and photomultiplier tube to convert optical energy into electrical impulses. Distance to object is determined by recording the time taken by the transmitted pulse to the target and back (at the speed of light) Continuous Wave (CW) Lasers Transmits a continuous signal, and ranging is carried out by modulating the intensity of the laser light. Travel time is directly proportional to the phase difference between the received and transmitted sinusoidal signal.

8 Older, pulsed LIDAR profilers produced a nadir track transect, operated in the shorter wavelengths (e.g., green) and were first used in bathymetric (depth to underwater surface) studies and later for terrain profiling.

9 Early forest experiments produced a strip chart showing pulsed laser hits along the ground and off the top of the tree canopy. The difference between the height and ground modeled elevations allowed heights of objects, along the transect, to be calculated.

10 Airborne Lidar System (ALS) Consists of the following separate components that are basically operating independently: 1.Laser ranging device 2.GPS positioning device 3.Inertial System * Optional -Digital Camera (RGB or CIR)

11 LiDAR Acquisition Considerations Geodetic Control Very important to have accurate GPS control data associated with collection information Vendor will include report about accuracy information Aerial LiDAR Scanner Y Z X YAW ROLL PITCH

12 Point Cloud of Vegetation Returns

13 LiDAR Acquisition Considerations - Seasonality No snow cover (false ground returns) No Inclement weather (fog, wind, smoke, etc) Leaf-on or leaf-off? Leaf-off better ground returns Leaf-off tough on timing Leaf-on better for tree heights

14 LiDAR Acquisition Parameters Pulse Repetition Frequency (PRF) Number of Pulses/Sec (50,000 KHz = 50,000/sec) Relates to other project planning components Number of Returns Commonly 3-5 returns/pulse Pulse Density Horizontal density between laser footprints (.3 12 pulses/m 2 ) Sparser spacing allows for higher flying altitude (cheaper) 4 6 pulses/m 2 good balance for vegetation applications

15 LiDAR Acquisition Considerations Photos at the same time? Not typically compatible. Timing Flying heights Compromise both acquisitions Vendors don t have both systems mounted on the same aircraft either another constraint

16 LiDAR Applications Ground Surface Mapping Geology Habitat Assessment Timber Resource Planning Post Disturbance Assessment (Fire/fuels) Slope Stability Hydrology Fisheries Coastal Change

17 Forest Characteristics Canopy height Subcanopy topography Vertical distribution- understory Crown diameters Above ground biomass or volume Basal area Mean stem diameter LIDAR Derivation Direct retrieval Direct retrieval Direct retrieval Direct retrieval Modeled Indirect Modeled Indirect Modeled Indirect Adapted from Dubayah, R.; Drake, J LIDAR remote sensing for forestry. Journal of Forestry. 98:

18 LiDAR data visualization NAIP 2009 Rei Hayashi PEF LiDAR Research 18

19 (Rei Hayashi MS Project PEF) 0.5 laser pulse per m 2 ( ca. 0.5 laser pulse per 10 feet 2 ) Newer LiDAR sensors: about 4-8 laser pulse per m 2 1 st return 2 nd return 1 m 3.28 ft 1 m 3.28 ft 3 rd return Ground return # of laser pulse returns from 1 emitted laser pulse 1 laser pulse return from flat surface (e.g. roads) ~ 5 laser pulse returns from forests 19

20 Underestimating tree height (Rei Hayashi) Underestimating tree heights are common using discrete LiDAR sensors. DTM may not appropriately represent ground surface Laser pulse hit at the top of each tree? 20

21 Maximum Height in each subplot (Rei Hayashi) Field measured vs. LiDAR measured height LiDAR underestimating total height 21

22 Public LiDAR Derived DEMs 2-m DEM calculated for all publically available LiDAR data acquired for Maine. MEGIS Website

23 Remote Sensor Comparison Rating (0 = none 1 = low, 10 = High) Parameter Camera Thermal RaDAR LiDAR Infrared Day/night Haze/fog penetration Cloud penetration Smoke penetration Temperature discrimination Subsurface detection (shorter wavelength) Interpretability of imagery