Year after year, their crops, livestock, equipment, barns, out buildings and fences went up in smoke. With nothing left to sell, they reinvested what money they did have (and borrowed) to replace it all. What they could not do—at any cost—was restore fragile habitats and native grasses, which had been groomed and guarded over for generations.
The most recent wildfire was the worst so far. Most of the livestock, birds and game were carbonized. Those that did survive had no food or shelter, and trees don't grow back for decades. Hunting lease revenue, a cushion in times of natural hardships, was gone completely.
The landowners had to litigate. The wildfires were getting worse and the number of them increased every year. The fire origin in this case was not in dispute: the local fire brigade was there, they noted the location and declared it was extinguished. Therefore, said the railroad, there must've been two wildfires, and they would assume liability for only the smaller one.
When fires are in remote spaces, they get a head start before alarms are sounded and actual firefighters are sent in to take away the fire's fuel, heat or air.
The fire brigade fought the initial flareup, said the fire was out and went home. Even so, a second fire was extremely unlikely: there had been no lightening in the area, no downed power lines, no plane crashes, it wasn't deer season, and no public roads that a cigarette butt could be thrown from. Wind speeds had not changed direction. The second fire idea was wrong.Remote sensing provided the proof: staring down persistently, day and night, it documented an uninterrupted plume of smoke:
2. Inventory the extent of destruction:
"Burn Severity" is a method of describing how badly land is damaged by a wildfire, a function of fire intensity and how long it was in place. This is separate from determining the exact crop, habitat, or improvements that were affected. For instance, some forest fires burn only the tops of trees and leave the understory to grow. Not this fire: the soil heating was extreme...it destroyed the organic layers beneath the trees and shrubs and virtually sterilized the buried-in-the-soil plant parts necessary to grow back. The trees were gone too, which is regrettable enough, but it also meant that creeks and ponds had no shelter from the sun and wind, so precious water evaporated. Soil erosion was exacerbated because no plants—not even their roots—remained to hold essential topsoil in place. Ponds filled with eroded sediment.
Shown here in yellow and red, 75% of the ranch land was severely burned:
3. Establish the value of the losses:
Crops and vegetation types were classified with USDA air-photos and imaging satellites (I was not tasked with this) in support of value assessments conducted by other experts, e.g. agronomists, real estate appraisers, building contractors, fence companies, fish and game, soil scientists, etc.
4. Show where fires had happened in previous years:
Accurate records about wildfire locations, how big they were, and what got burned up (let alone who was responsible) is vague. Many fires are not large enough to alert local VFDs.
The map below shows the number and location of wildfires over the ranches during the four years previous to the subject fire. The railroad tracks go along the bottom and lower left corner of the map. Each of these wildfire locations have to be at least 11.32 acres—almost 12 football fields—in size before the satellites can record them.
++++ = railroad tracks in the subject area.
Pink = fires during the year just previous to the subject fire.
Red = the year before that.
Green = the year before that.
Blue = the year before that.
Totals: 17 wildfires in the ranches during the previous four years.
Over the entire length of the railroad (not shown here), 139 wildfires.
The dots are locations only, but they are approximately the minimum size for a fire to be detected from the satellite. Probably none of them remained this small. Different satellites would, if necessary, give us the measure of how large each of these fires became.
5. Establish that wildfires were caused by the railroad's shoddy practices:
Most wildfires were to the northeast of the tracks. This is not a coincidence, as 1) winds prevail mostly out of the southwest and 2) the nearly 90º curve in the tracks caused more strain and therefore sparks to emanate from the wheels there.
When railroad right of way is poorly maintained, weeds and grasses grow tall, get dry and become flammable. Weeds and brush were neither sprayed nor mowed, spark suppression mechanisms on the wheels were absent, and so wildfires erupted with increasing frequency.
Success in this case came in the form of an augmented reality created from different satellite data platforms. Remote sensing—multi-spatial, multi-spectral, and multi-temporal—allowed us to affordably and repeatably:
The case settled quickly out of court. The railroad also agreed to install spark suppressors on the wheels of the trains, insure that the wheels were well maintained and lubricated, and to keep the weeds mowed in their ROW.
David G. Koger is a Remote Sensing Image Analysis expert with over 40 years of experience in the field. A Vietnam Era Marine Corps veteran, he configured and operates a state-of-the-art remote sensing image analysis and geographic information system and consults on various remote sensing applications. Mr. Koger offers Forensic Digital Image Analysis of remotely sensed, aerial photo (digital or film), and underwater video. His services include forensics, time-series studies, and documentation of surface damages, wildfires, material movements. Expert witness strategies and research methodologies are available to attorneys representing plaintiff and defendant.
©Copyright - All Rights Reserved
DO NOT REPRODUCE WITHOUT WRITTEN PERMISSION BY AUTHOR.