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1-1. About vegetation
1-2. General Principles For
Recognizing Vegetation
1-3. Remote sensing
1. About Vegetation
Vegetation can be distinguished using remote sensing data from most other (mainly
inorganic) materials by virtue of its notable absorption in the red and blue segments of the
visible spectrum, its higher green reflectance and, especially, its very strong reflectance in
the near-IR. Different types of vegetation show often distinctive variability from one another
owing to such parameters as leaf shape and size, overall plant shape, water content, and
associated background (e.g., soil types and spacing of the plants (density of vegetative cover
within the scene)).,Even marine/lake vegetation can be detected. Use of remote sensing to
monitor crops, in terms of their identity, stage of growth, predicted yields (productivity) and
health is a major endeavor. This is an excellent example of the value of multitemporal
observations, as several looks during the growing season allows better crop type
determination and estimates of output. Vegetation distribution and characteristics in forests
and grasslands also are readily determinable.
2. General Principles For Recognizing Vegetation
Absorption centered at about 0.65 µm (visible red) by chlorophyll
pigment in green-leaf chloroplasts that reside in the outer or
Palisade leaf, and to a similar extent in the blue, removes these
colors from white light, leaving the predominant but diminished
reflectance for visible wavelengths concentrated in the green.
Thus, most vegetation has a green-leafy color. There is also
strong reflectance between 0.7 and 1.0 µm (near IR) in the
spongy mesophyll cells located in the interior or back of a leaf,
within which light reflects mainly at cell wall/air space interfaces,
much of which emerges as strong reflection rays. The intensity of
this reflectance is commonly greater (higher percentage) than
from most inorganic materials, so vegetation appears bright in
the near-IR wavelengths.
3. Remote Sensing
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Landsat TM
SPOT HRV
Topographic variables obtained through fieldwork
DEMs(digital elevation model)
• Traditional methods are still demanded and used, and include airphoto
interpretation, fieldwork, literature reviews, map interpretation, and
collateral and ancillary data. With improvements in remote sensing, there
are certain advantages in its' use.
•For example, preparing and upgrading vegetation inventories for large regi
ons in a short period of time, and monitoring and detecting changes in veg
etation will be more easily obtainable with satellite sensing and thematic
mapper techniques.
2-2.
For natural or anthropogenic disasters, rapid assessment is
critical for an appropriate and effective emergency response.
Remote sensing has served a vital function in disaster
damage-assessment activities. This includes disaster-mapping
of natural and agricultural ecosystems and human settlements,
which may involve assessments of structural damage,
contamination, and affected populations. Single- and multidate (change detection) analyses can be employed, and a
need to exploit both spectral and spatial information in order
to delineate damage regions from remote sensor imagery is
identified. Specific attention is given to remote sensing-based
detection of vegetation damage and soil contamination,
including a discussion of the remote-sensing implications of
artificial radionuclide contamination, as well as damage to
urbanized areas and other human settlements.
 The use of many parts of
electromagnetic spectrum
 The saving of time, money, and
manpower
 Visual observation techniques
(sketch mapping and strip recording)
 Color and color infrared (CIR)
photography (both large and very
small scale) when properly matched
 The use of successive remote sensing
with damage symptom
surveys to follow damage trends.
 Multistage sampling
Vegetation has been identified as a vital component of
healthy urban environments and the benefits of urban
vegetation range widely, influencing both the physical
conditions of the city as well as the social well-being
of urban residents. These links form the foundation for
studies examining social-ecological systems (SES),
which suggest that many human and ecological
systems are tightly and inextricably linked (Alessa et al.,
2008). In a review of societal needs in urban areas,
Matsuka and Kaplan (2008) suggest that human
actions and attitudes are directly connected to the
physical features of the environmental setting, of
which trees are a major component.
Mapping the location and spatial extent of trees, vegetated ground cover, and high level
vegetation detail provides a valuable addition to vegetation land cover mapping using high
spatial resolution imagery. Image classification techniques developed to date extract a basic
vegetation class which encompasses a broad range of features whose structural and spectral
diversity have a variety of impacts on urban processes. Small and Lu (2006) explain that high
spatial resolution image vegetation fractions provide more informative vegetation estimates
than moderate resolution imagery due to the reduction of possible distinct mixtures and add
that Quickbird pixels can resolve many of the individual components representing vegetation.
1. Agriculture
2. Forestry
1. Agriculture
1. Agriculture
2. Forestry
2. Forestry
2. Forestry
Forest health
A. Insect disturbance
a. Damage affects morphological/physiological chars
b. Defoliation
B. Fire
a. Real-time
• Firefighter GPS
• AVHRR, SPOT & MODIS – hot spot information
b. Post-processing
• Change detection
• Prediction for future hot spots
C. Other natural disasters
2. Forestry
MODIS-detected real-time fire hot-spot image
2. Forestry
3. Geology
• Geological Structures
– Exposed structures
• Fault lines
• Identifying rocks
– Response to weathering
& erosion
– Texture, pattern & tone
– Hyperspectral
– Obscured structures
• Indirect effects
• Subsurface instrumentation
• Detection of hydrocarbons
– Oil & Gas
3. Geology
Normalized magnitude of 0.75
Hz electric fields at the seafloor
for a range bin of 3000-3600m,
plotted as a function of source
-receiver midpoint across the survey
area. Plotted for reference
is the approximate outline of
the known hydrocarbon resevoir.
 The use of many parts of electromagnetic spectrum
 The saving of time, money, and manpower
 The use of successive remote sensing surveys to follow damage trends.
 Visual observation techniques (sketch mapping and strip recording)
 Color and color infrared (CIR) photography (both large and very small scale)
when properly matched with damage symptom
 Multistage sampling