Remote Sensing of Soils andGeomorphology
19 May 2003
Outline
• Soils– Properties that are detectable from remote
sensing using optical and radar sensors
• Geomorphology– Patterns as an indication of processes
Factors Influencing Soil Reflectance
• mineral composition
• soil moisture
• organic matter content
• texture and roughness
• salinity
Soils: Mineral Composition
• Affects the visible, NIR, and thermal portions of thereflectance spectrum
• Increasing reflectance from visible to NIR
• Iron and clays are detectable– oxidized iron appear red
– reduced iron appear green-blue
– clays affect water and OH+ absorption features
Basic Dry Soil Spectrum
20
60
100Pe
rcen
t Ref
lect
ance
0.5 0.7 1.1 1.30
Wavelength (mm)
80
40
0.9 1.5 1.7 1.9 2.1 2.3 2.5
Silt
Sand
10
30
50
70
90
Key characteristic of soil spectrum: increasing reflectance with increasingwavelength through the visible, near and mid infrared portions of the spectrum
Iron Oxide
• Iron oxide causes absorption in the UV, blue and green wavelengths as well as absorptionin the NIR (850 to 900 nm). Also, scattering in the red is higher for soils with iron oxide,leading to a red color.
Iron Oxide
• Iron content in the Santa Monica mountains mapped using AVIRIS(Palacios-Orueta et al. 1999)
Soils: Organic Matter Content
• OM affects soil color, heat capacity, waterholding capacity, nutrient exchange, structure,and erodability
• Dark color generally associated with high OM
• Landsat TM bands 5 and 6 have negativecorrelation with OM
Soil Organic Matter
• Organic matter is a strong absorber of EMR, so more organic matterleads to darker soils (lower reflectance curves)
Soil Organic Matter
• Organic matter content in the Santa Monica mountains mappedusing AVIRIS (Palacios-Orueta et al. 1999)
Soils: Texture
• Texture– %sand, %silt, %clay (these are size classes)
0.002 0.05 0.1 0.25 0.5 1 2 mm
Particle size relative to a grain of sand 0.15 mm in diameter
Sand
SiltClay
Clay Silt Sandv. fine fine medium coarse v. coarse Gravel
0.002 0.06 0.2 2 mm
Clay Silt SandGravel Stones
fine medium coarse
0.006 0.02 0.6
0.15 mm
fine medium coarse
76.2
0.002 0.2 2 mm
Clay Silt SandGravel
0.02fine coarse
a. Soil Science Society of America and U.S. Department of Agriculture Soil Particle Size Scale
b. MIT and British Standards Institute
c. International Society of Soil Science
Soil Texture• Proportion of sand, silt and clay
in a soil (or horizon), usuallycalculated as % weight for eachtype of particle
• These percentages are divideddifferent soil texture classes
100
90
80
70
60
50
40
30
20
10
100100 90 80 70 60 50 40 30 20 10
90
80
70
60
50
40
30
20
10
Clay
(%)
Sand (%)
Silt (%)
read
read
read
Clay
SiltSand
loamysand
sandy loam
Loam
sandy clayloam
silty clay
silty clayloam
clay loam
sandy clay
silt loam
Basic Dry Soil Spectrum
20
60
100Pe
rcen
t Ref
lect
ance
0.5 0.7 1.1 1.30
Wavelength (mm)
80
40
0.9 1.5 1.7 1.9 2.1 2.3 2.5
Silt
Sand
10
30
50
70
90
Key characteristic of soil spectrum: increasing reflectance with increasingwavelength through the visible, near and mid infrared portions of the spectrum
Soil Moisture
• Water is a strong absorber, sosoils with more moisture will bedarker over most of the VNIRand SWIR portions of thespectrum than drier soils.
• The depths of the waterabsorption bands at 1.4, 1.9and 2.7 mm can be used toestimate soil moisture.
specularreflectance
incident energy
interstitialair space
specularreflectance
soil water
a.
b.
dry soil
wet soil
volume reflectancespecular reflectance
incident energy
Soil Moisture and Texture
• Since clayey soil holdswater more tightly thansandy soil, the waterabsorption features willbe more prominent inclayey soils given thesame amount of timesince the lastprecipitation orwatering.
• AVIRIS can be usefulfor quantifying theseabsorption features.
20
60
Perc
ent R
efle
ctan
ce
0.5 0.7 1.1 1.30
40
0.9 1.5 1.7 1.9 2.1 2.3 2.5
22 – 32%
10
30
50Sand
20
60
0.5 0.7 1.1 1.30
Wavelength (mm)
40
0.9 1.5 1.7 1.9 2.1 2.3 2.5
35 – 40% 10
30
50 2 – 6%
0 – 4% moisture content
5 – 12%
Clay
a.
b.
Perc
ent R
efle
ctan
ce
SandSandSand
ClayClayClay
Soils: Moisture Content
• Theoretically, soil moisture is directly relatedto surface soil moisture content
• SAR estimates of soil moisture are alsoinfluenced by:– roughness– topography– vegetation density
Soil Moisture from RADAR
• Higher dielectricconstants (moremoisture) yields higherRADAR backscatter.
Melfort, Saskatchewan, Canada,ERS-1: Rainfall was incident on thelower half of the image but not on theupper half.
Surface Soil Moisture from Synthetic Aperture Radar
Soil Moisture from Thermal Sensors
• Water has a higherthermal capacity thansoil and rock.
• Moist soils will changein temperature moreslowly than dry soils
• Apparent thermal inertiacan be used todistinguish dry frommoist soils
Soil Moisture from Thermal Sensors
Daedalus thermal image(night time). If we had adaytime image tocompare it to, we couldsee the amount ofchange in temperatureand make inferences onthe soil moisturecontent (less change =more moisture).
Soils: Salinity
• Saline soils are a major limiting factor forvegetation growth– drawdown of coastal aquifers allows saltwater
intrusion into groundwater
– increase in irrigation in regions of salt-bearingminerals will activate salts into the groundwater
– evaporation of salt-bearing irrigation water willincrease soil salinity over time
Application: Remote Sensing of SwellingClay Soils
• Smectite clays (e.g. bentonite) can absorb more than theirweight in water, have >100% increases in volume
• Responsible for massive damage to structures throughout U.S.
Colorado Front RangeGeologic Map
Pierre shale containshigh concentrations ofbentonite clays
AVIRIS data acquiredto try to usehyperspectral imageryfor mapping bentonite(Chabrillat and Goetz,1999)
Bentonite clay exposurenear Denver, CO
increasingswellingpotential
Geomorphology
• Landforms: patterns and processes– eolian
– igneous
– tectonic
– karstic
– fluvial
– shoreline
– glacial
Landforms
• Typically identified by shape, not spectralproperties
• Use shadowing to identify features– optical (VIS/NIR imagery)
– synthetic aperture radar• useful in regions frequent cloud cover
Eolian landforms
crescentic dunes from SAR crescentic dunes from ASTER
longitudinal dunes from ASTER(w/clays between dunes)
star dunes from Landsat TM
Igneous landforms
Mount Rainier, Washington
stratovolcano
Western Australia granite-greenstone complex: Pilbara Block
granite batholiths intruded into metamorphosed basalt
Tectonic Landforms
Landsat TMimage ofNevada basinand rangeregion
Colorado Rocky Mountainsfrom Landsat TM (band 4)
Canadian Rocky Mountainsfrom Radarsat
Karstic Landforms
• Karst topography develops by chemical dissolution of limestonerocks
• Creates caves, sinkholes, solution valleys, towers, pittedlandscapes
Landsat TM image of Guangxiprovince, China (karst areas are dark)
photo of karstic towers in Guangxi,province China
Fluvial Landforms
• dendritic networks are easily recognized
Radar image of dendritic river network in east-central Colombia
Flat floodplains haveshifting river channelsproducing meanders andoxbows
Edge of floodplain ismarked by bluffs onwhich is maturevegetation
Lower Mississippi River Floodplain
Shoreline Landforms
MISR image of Mississippi Delta (birdsfoot delta)multi-angle composite false color composite
true color composite
Quickbird imageof Bora Boraisland (atoll)
Landsat image offjords on Iceland
Glacial Landforms
ASTER image of receding glaciers in Bhutan(note lakes forming at glacier termini)
Landsat TM image of “fluting” causedby massive glacial erosion of bedrock onthe Canadian shield during the last iceage