Wednesday, September 3, 2014

Slipshod and Irrational:Federal Basecamp


At least once a the the Clark County captures aerial imagery that it uses for Assessment purposes and other mapping related functions. One of its primary uses is in a mapping application called OpenWeb where you can view the assessor records and other GIS data along with all the aerial imagery that the county has collected. This normally occurs every spring.


This year it just so happens that the aerial acquisition occurred during the build up for the BLM's Bundy Flop.



It beautifully captures the exaggerated, hysterical and theatrical show of force parade for the Federal Cattle Arrest.






















You can zoom around and see the base camp and surrounding area on April 7th 2014


To view the imagery you can click the following links:


PC version:

Mobile capable version: search by parcel number 00229000002







Sunday, August 24, 2014

Out and About


See if you can spot the deer in this picture. At the bottom of the post I have the same picture with the deer pointed out:



The boys and I loaded up this weekend for one last big ride before school got started and did we ever have a great trip. 



Be careful as you head out as the recent rains has torn the roads up to as about as bad as I have ever seen them. The road from Riverside Bridge to Whitney Pockets has been inundated with sand a gravel being carried down from the Virgin Mountains and all the washes along the road between Whitney Pockets  and Devils Throat are eroded some kind of fierce. None the less we are thankful for the rain. There is even a second wave of wildflowers coming up and the cheatgrass is coming on strong again.  



We unloaded a Whitney Pockets and headed for Horse Springs. Along the way we found a desert tortoise who seemed to be enjoying the green grass that is sprouting up after the recent rains.



After catching poly-wogs at Horse Springs  we headed for the graves at Gold Butte Headquarters. After saying hello to Mr Coleman and Garrett we headed on over to Cedar Basin.



I always enjoy the beautiful country and cedar trees in and around Cedar Basin. The recent rains hit the Virgin Mountain area pretty hard by by the time you got to Gold Butte Headquarters and Cedar Basin it was obvious the rains didn't drop quite as much there.




At Cedar Basin we found and old box spring and drug it under a cedar tree for a beautiful picnic spot. It was a lovely 82 degrees with a light breeze and it couldn't have been more beautiful.



After leaving Cedar Basin we headed for Azure Ridge and the windmill through Pierson's Gap back behind Mica Peak. While traveling down this canyon we kicked up four Mule Deer bucks that were bedded down under a Cedar tree. 






I love the Gold Butte country. There is such variety in both scenery and wildlife. You can about see it all in Gold Butte.





Friday, July 25, 2014

Comparing Elevation and Temperature - Virgin Mountain Trip




This graph charts the percent change in temperature in relation to elevation as my boys and I headed for our picnic spot on the Virgin Mountain. The data collection process is explained below...




The boys and I had a great trip up the Virgin Mountain last week as we searched for cooler temperatures. As we went up the mountain we logged the elevation, temperature and location.  My Arduino sensors haven’t come yet which will help me with capturing and logging data so for now they boys help me with the process. They are the best data loggers a dad could as for.






The raw data is interesting because it shows the change in temperature as you climb in elevation. One little side note to explain part of the data is the dramatic drop in the temperature after we initially peak in elevation, and then drop back down. This is because we dropped down the back side of the mountain in the shade of the sun.





Here I just overlaid the two graphs to show the comparison




I also wanted to normalize the data a little bit so it would make the comparisons and analysis a little bit easier. To do this I calculated the percent in change of both the elevation and temperature. 




We also tested the temperature of the water coming out of the spring.



Out data collection rig



Sure had a great trip with my boys up on the mountain.



Saturday, July 19, 2014

Fire Risk Map

This is Part IV in a series of articles on Wildfires in the desert region of Gold Butte in North Eastern Clark County, NV. 

To read Part I click the following link: Defining the Study Area:
To read Part II click the following link: Defining the Study Area:
To read Part III click the following link: Defining the Study Area:
To read Part IV click the following link: Defining the Study Area:

Fire Risk Indicator
The goal of this research was to assess the Gold Butte region for risk of fire. To create this model, I used geospatial data available on the internet from various government agencies, to create a model to calculate risk. I used the fire perimeter data available from the BLM’s website to create my sample area. I used Soil, Geology, Landform, and two different vegetation datasets to analyze the area within Gold Butte that has already experienced a wild fire event to look for clues as to why the fire burned where it did.  



After analyzing the data, I found there were strong colorations between the data and sample area that helped determine why did the fire burn where it did. After these indicators had been determined I developed model to classify the entire study area (Gold Butte region). The results of this model are as follows:
I created a ranking hierarchy that ranged from 1 to 15 with 1 being the lowest risk and 15 being the highest risk of fire.

Classification by Acreage:
1: 73,997.69
2: 48,133.22
3: 28,132.37
4: 31,386.28
5: 13,055.05
6: 16,103.41
7: 12,518.14
8: 38,121.84
9: 24,185.72
10: 14,517.97
11: 18,885.54
12: 37,333.26
13: 16,801.13
14: 36,380.47
15: 24,161.95

Acreage Statistics:
Count:  15
Minimum:           12518.147206
Maximum:          73997.693831
Sum:      433714.117105
Mean:   28914.274474
Standard Deviation:        15924.771133






With this information a person could then more easily determine which area were most at risk for a fire event and determine how to mitigate or better manage those risks. I plan to document the areas that are at most risk which haven’t burned yet so in case of a fire event the pre-fire landscape will be adequately documented.
  

This is not the end of this project but just another stepping stone to more research and better understanding of wild fires in a desert ecosystem. One interesting byproduct of this study has been to look more closely at the areas that are marked high risk and within close proximity to the fire boundary but yet didn’t burn. In many instances it is plainly clear the role that roads play as natural fire breaks to prevent the fire from spreading even farther within the desert ecosystem. I will continue to post data and information about my findings in researching the Gold Butte region…








Monday, July 14, 2014

Details Depicted - Doing the Analysis


This is Part IV in a series of articles on Wildfires in the desert region of Gold Butte in North Eastern Clark County, NV. 

To read Part II click the following link: Defining the Study Area:

To read Part II click the following link: Defining the Study Area:

To read Part III click the following link: Defining the Study Area:


In this step of the research, I am delving into the details. With the following graphics I try to depict how I performed the analysis to create the risk index. In the previous step (Step III) I calculated the specific value for each type we are researching. In this step I am applying those values to a grid that I created within the area of interest. The following is how I apply those values:











The next step is to create the map that depicts all these values which represent the potential risk an area has to fire.

Friday, July 4, 2014

Spatial Analysis - Sifting Statistics


This is Part III in a series of articles on Wildfires in the desert region of Gold Butte in North Eastern Clark County, NV. To read Part II click the following link: Defining the Study Area:


In the field of Spatial Analysis and Statistics you use geographic data, which is data that has a fixed location within the real world, to find trends and correlations between the data. The goal of my fire analysis project is to find try and find correlations between the fire area and the rest of the gold butte region to create a risk index to identify the most at risk areas in Gold Butte that haven’t yet burned but are likely to burn. Once this is complete I will then document those areas current habitat for future restoration plans. I will also look for ways to protect these desert ecosystems from the devastating consequences of a wildfire event.



In step 1 I defined the sampling area as the boundary of the Forks and Tramp fire within the Gold Butte Region and presented the summary five different datasets including soil, geology, vegetation types and landforms or slope classifications within the burned area (sample).

 In step 2 I defined the study area to which I would scale my analysis to. I then presented the summary results of the same datasets that I presented for the sample area in step 1.

In Step 3 I am looking for recurring patterns and relationships between the burned area and the total study area. In this step I am looking for scale invariance or the lack of scale invariance to try and see if I can determine why the fire burned where it did through analyzing the results of both step 1 and step 2.



For example, if all of the data from the sample area scaled perfectly to the study area, all that it would tell me is that this fire burned consistent with the statistical distribution across the total study area.  If 30 percent of the study area was made up of creosote and 30 percent of the burn area was also creosote the only inference that could be made is that the fire burned consistent with the overall makeup of the study area. However if 30 percent of the study area was made up of creosote but 5 percent of the burn area consisted of creosote then we could deduce that the creosote vegetation is not as susceptible to fire.  The following is the breakdown of the previously defined data:

Landform (Slope Classifications)
Looking at the total Landform distribution across the entire study area you can see that the gently sloping ridges and hills make up the majority of the study area. However that same classification only makes up 20% of the burn area meaning that this landform classification is not as susceptible to fire as other types.  The landform types that have the smallest percent of the total study area but the largest percentage of the burn area are the indicators of the most susceptible landform types:
·         very dry steep slopes
·         very moist steep slopes
·         hot aspect scarps, cliffs, canyons
·         cool aspect scarps, cliffs, canyons





Geologic Types
Again here I am looking for the geologic types that have the smallest percent of the total study area but the largest percentage of the burn area.  The most susceptible geologic types:
·         very dry steep slopes
·         very moist steep slopes
·         hot aspect scarps, cliffs, canyons
·         cool aspect scarps, cliffs, canyons





Soil Types
After analyzing the soil types the indicators are not as significant as other data is at showing correlation however there are still relationships that exist that will help add to the modeling. Again I am looking for the types that have the smallest percent of the total study area but the largest percentage of the burn area.  The most susceptible soil types are:
·         Water (this is the land that has been exposed by the drop in lake water levels)
·         lithic torriorthents-rock outcrop-lithic and deep calciorthids
·         deep and shallow paleorthids-calciorthids-haplargids






Vegetation Types
Again I am looking for the types that have the smallest percent of the total study area but the largest percentage of the burn area.  The most susceptible Vegetation types are:
·         Artemisia tridentata ssp. (tridentata, wyomingensis) – This type was only found in burn area
·         Inter-Mountain Basins Montane Sagebrush Steppe
·         Great Basin Pinyon-Juniper Woodland
·         Inter-Mountain Basins Big Sagebrush Shrubland
·         Agriculture-Cultivated Crops and Irrigated Agriculture
·         Mojave Mid-Elevation Mixed Desert Scrub







Vegetation 2
Again I am looking for the types that have the smallest percent of the total study area but the largest percentage of the burn area.  The most susceptible Vegetation types are:
·         Juniper II
·         Mountain shrub

·         Blackbrush