1. Week Fourteen Remote sensing of vegetation Remote sensing of water
Significance
Spectral characteristics of veg.
Temporal characteristics of veg.
Veg. indices
Landscape ecology metrics
Biodiversity and GAP analysis
Remote sensing of water
Spectral properties of water
Spectral properties of suspended minerals
Bathymetry – optical, sonar, lidar
Precipitation

2. Significance Different types of veg. distinguished by:
Leaf shape, size, density
Plant shape
Planting density / spacing
Water content
Soil type
Crop monitoring for productivity:
Crop type
Crop health
Stage of growth
Predicted yields

3. Spectral characteristics of veg.

4. Spectral characteristics of veg.
From 400 to 700 nm, veg. is dark in visible: high absorption of pigments (chlorophyll)
Plants absorb blue and red better than green (550 nm).
From 700 to 1200 nm (near IR), veg. is bright:
Scattered & reflected in spongy mesophyll (cell wall / air contact)
E.g., 76% reflected at 900 nm
If plants absorbed 700 to 1200 nm, they would sizzle
From 1300 to 2500 nm, veg. is dark: water absorbs these wavelengths

5. Spectral characteristics of veg.
Natural color on left, color near infrared on right. Source: Your book.

6. Spectral characteristics of veg.
Less chlorophyll means less reflectance (600 – 700 nm). Source: Your book.

7. Temporal characteristics of veg.
Phenological cycles viewed as pixels in attribute space – Near IR vs. red
Dancing pixels: Near IR vs. red.
Image source: Your book.

8. Vegetation indices TM band 4 is near-IR; 1 blue, 2 green, 3 red
Reflectance curves for the upper leaf surface of the seven selected weed and crop species; the wavelengths within the Landsat Thematic Mapper satellite sensor wavebands 1, 2, 3, 4, 5, and 7 are indicated by the shaded areas. Figure from: ANNE M. SMITH, ROBERT E. BLACKSHAW, Weed–Crop Discrimination Using Remote Sensing: A Detached Leaf Experiment, Weed Technology (4),

9. Vegetation indices
Normalized Difference Vegetation Index (NDVI) of AZ 3/14/2002. [NDVI = (NIR – Red) / (NIR + Red)]
Source:

10. Landscape ecology metrics
The study of structure, function, and changes in heterogeneous land areas composed of interacting organisms (pg. 393).
Landscape ‘integrity’ can be monitored through indicators:
Land cover composition and pattern
Riparian extent and composition
Ground water
Greenness pattern
Degree of biophysical contraints
Erosion potential
Managing ecosystems, communities, landscapes. Mixes scales.

11. Landscape ecology metrics

12. Biodiversity and gap analysis
Looks at multiple species
Looks for ‘gaps’ between habitats
GIS based:
Veg. cover layer
Land ownership layer
Land management status layer
Distribution of terrestrial vertebrates as predicted from RS imagery and from in situ veg. mapping

13. A few applications of veg. RS
Discriminating vegetative, crop and timber types
Measuring crop and timber acreage
Precision farming land management
Monitoring crop and forest harvests
Determining range readiness, biomass and health
Determining soil conditions and associations
Monitoring desert blooms
Assessing wildlife habitat
Characterizing forest range vegetation
Monitoring and mapping insect infestations
Monitoring irrigation practices
Bison management
Crop production estimates
Quantifying burn severity
Fighting crop insurance fraud
Better Estimate of Boreal Forest Loss
Crop water stress
Crop water demand
Rice production monitoring
Forest damage caused by Hurricane Katrina

14. Remote sensing of water
From

15. Significance 74% of Earth is water covered
Meteorologists, climatologists, oceanographers, geographers, hydrologists, soil scientists, snow scientists, and you measure, monitor, and predict water….
In situ works sometimes; not too well for:
Surface area measures
Water constituents
Water depth
Water surface temperature
SWE

16. Spectral properties of water
Violet to light blue ( nm) transmits best/deepest (not absorbed or scattered well) in water
740 – 2500 nm (middle infrared) used to discriminate water from land
Water absorbs here; veg./land reflect here
Caution: sediment and organics reflect near infrared

17. Spectral properties of suspended minerals
Suspended mineral concentrations
Calibrated in-situ using Secchi disk
E.g., clays and silts have different spectral properties for different concentrations

18. Bathymetry - optical Optical (aerial photography)
Optical film: 0.44 to 0.54 um
Landsat blue band: 0.45 to 0.54 um
80 cm depth at 0.80 um
For best results, calibrate using in-situ depth measurements

19. Bathymetry - SONAR Sound navigation and ranging (SONAR)
Can penetrate to 36,000 ft.
Resolution of a few cm
Main types:
> Single-beam for transects
> Multiple beam for continuous coverage and feature mapping
> Side-scanning for searching for objects (not for mapping; large overlap)

21. Bathymetry - lidar Lidar 532 nm (green) for bottom
1064 nm (near IR) for surface
Can detect down to about 60 m
Fly m above water at about 130 mph
Good for shallow water mapping (object detection)

22. Precipitation Precipitation
Measured directly with NEXRAD radar (11.1 cm microwave energy)
Precipitation rate measured indirectly with
Cloud top temperature
Cloud reflectance
Frozen precip. detection
Tropical rainfall Measuring Mission (TRMM)
5 instruments for measuring precip.

23. Unsupervised classification
Helper image from pg. 184

24. Supervised classification
Make sure to manually set the “ID or value” field for each class to 1.