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9 Hazard Identification
near-visible frequencies. Visible pictures of the surface are available with resolutions
of a few centimeters and can provide instantaneous descriptions of a tailings dam
and its surroundings.
Optical satellites can be very powerful. The immediate recognition of objects from
the imagery helps the human brain to provide context and quickly exploit the image
information. Understanding change can be very quick from one image to the next
but understanding the difference between a persistent change or a particular type of
change can be more challenging.
Two techniques, PCM
® and Intermittent Water Analysis (IW), help with the automated understanding of the magnitude and persistence of infrastructure or land use
change and with the measurement of standing water cover and periodic surface water
changes.
Persistent Change Monitoring
Persistent Change Monitoring (PCM
® ) is an automated detection algorithm that
identifies multi-date change within a series of optical satellite imagery. Some of
the changes that PCM
® detected in real-life studies include: significant slumps or
block (earth) movement; new standing water; new encroaching infrastructure such
as roads, buildings, power lines or pipelines; de-vegetation and re-vegetation (from
barren). Based on a process patented by Maxar Technologies, the algorithm is highly
accurate and not affected by temporary features such as clouds, crop changes, or
data gaps. It is now being used by commercial companies, government agencies,
and organizations for a variety of applications, such as identifying areas of potential
encroachment risk/features and map updating.
PCM
® requires a stack of imagery to initially establish baseline conditions, followed by a series of observations over the evaluation period. Reporting includes an
indication of areas where change is verified (due to its persistence over time) and also
an indication where there has been potential change that has not yet been verified. It
requires imagery that is automatically tightly co-registered and, as a result, is limited
to medium-resolution imagery (5–30 m), such as LANDSAT or Sentinel satellites.
Pending suitable image availability, PCM
® provides information on historic change,
which is a useful input for predictive risk assessment.
PCM
® delivers data useful for quantitative risk analysis such as:
• When and where did historic change first or most recently occur?
• Which change is definite versus less likely based on the strength of the spectral
difference and other factors?
• What is the probable type of change?
That information can be directly used within a risk assessment procedure to update
the probabilities and consequences values.
Figure 9.5 displays an example of PCM
® outputs in the vicinity of the Jim Bridger
Power Plant in Wyoming. It shows two dates of imagery indicating change near the
dams. The containment areas behind some of these dams have been alternately filled
with water and sediment over time.
Figure 9.6 shows the PCM
® -confirmed change results over that region.
9 Hazard Identification
near-visible frequencies. Visible pictures of the surface are available with resolutions
of a few centimeters and can provide instantaneous descriptions of a tailings dam
and its surroundings.
Optical satellites can be very powerful. The immediate recognition of objects from
the imagery helps the human brain to provide context and quickly exploit the image
information. Understanding change can be very quick from one image to the next
but understanding the difference between a persistent change or a particular type of
change can be more challenging.
Two techniques, PCM
® and Intermittent Water Analysis (IW), help with the automated understanding of the magnitude and persistence of infrastructure or land use
change and with the measurement of standing water cover and periodic surface water
changes.
Persistent Change Monitoring
Persistent Change Monitoring (PCM
® ) is an automated detection algorithm that
identifies multi-date change within a series of optical satellite imagery. Some of
the changes that PCM
® detected in real-life studies include: significant slumps or
block (earth) movement; new standing water; new encroaching infrastructure such
as roads, buildings, power lines or pipelines; de-vegetation and re-vegetation (from
barren). Based on a process patented by Maxar Technologies, the algorithm is highly
accurate and not affected by temporary features such as clouds, crop changes, or
data gaps. It is now being used by commercial companies, government agencies,
and organizations for a variety of applications, such as identifying areas of potential
encroachment risk/features and map updating.
PCM
® requires a stack of imagery to initially establish baseline conditions, followed by a series of observations over the evaluation period. Reporting includes an
indication of areas where change is verified (due to its persistence over time) and also
an indication where there has been potential change that has not yet been verified. It
requires imagery that is automatically tightly co-registered and, as a result, is limited
to medium-resolution imagery (5–30 m), such as LANDSAT or Sentinel satellites.
Pending suitable image availability, PCM
® provides information on historic change,
which is a useful input for predictive risk assessment.
PCM
® delivers data useful for quantitative risk analysis such as:
• When and where did historic change first or most recently occur?
• Which change is definite versus less likely based on the strength of the spectral
difference and other factors?
• What is the probable type of change?
That information can be directly used within a risk assessment procedure to update
the probabilities and consequences values.
Figure 9.5 displays an example of PCM
® outputs in the vicinity of the Jim Bridger
Power Plant in Wyoming. It shows two dates of imagery indicating change near the
dams. The containment areas behind some of these dams have been alternately filled
with water and sediment over time.
Figure 9.6 shows the PCM
® -confirmed change results over that region.