Thursday, February 19, 2009
The example above shows the lines from the Lake Mead 100k map (USGS open-file data) in Google Earth. It works very well when zoomed into specific areas (down to 1:6000, for example), but the overall heterogeneity of the base imagery is a bit distracting. From this image (and the next) you can see that the detail in the bedrock is somewhat to considerably greater than that in the 'dirt'.
The image below is from ArcGIS and the lines from the Lake Mead 100k sheet are overlain on NAIP imagery. This imagery is also great when zoomed in and is homogeneous with respect to overall color balance, tone, etc. It is also from a much smaller window of time.
Our team has recently set up an image service at the UNR Geospatial Lab (Geography Dept.) that allows each investigator on the project to access the same high-resolution imagery remotely. Thus, we do not have multiple copies of giant .tiff files on all of our various computers. This is extremely helpful for collaboration and ensuring that everyone has equal access to the base imagery.
Friday, February 13, 2009
The same area from the 100k Mesquite Lake map shows considerably less detail, but relies on composite / combined units to account for this in most cases:
The Mesquite Lake snip above is from a map in which Ivanpah Valley is only a moderately small part. The map I developed (with help) was focused entirely on Ivanpah. As mentioned in a previous post, we are leaning toward some point between these two renditions. The NBMG map (published at 50k but mapped at ~12k) is excessively detailed and the USGS 100k map is a bit too general for what we would like to develop with the ND2MP. For example, we hope to map fewer composite units.
We suspect that we will ultimately end up closer to the USGS characterization of Ivanpah than to the NBMG characterization....not sure yet. We are actively applying generalization routines of various sorts to the NBMG data set. I will post a few examples next week.
I made the contacts red to be obvious. Most of the tonal variations that you see in the image represent distinct surficial piedmont units. Many that have been lumped together are quite large and also span a huge range of time as far as surficial deposits go. Also it is not clear why some large active washes were mapped individually and other, larger ones weren't. This approach to mapping is covered in the unit descriptions from this map for the most part, but for our purposes, additional mapping is certainly required.
Tuesday, February 3, 2009
ND2MP is supported in part by the Ecosystem Indicators (EIP), funded by the Clark County Multiple Species Habitat Conservation Program (MSHCP). The EIP has three main research objectives, ND2MP being a portion of one of those objectives. Objective one is to establish a robust GIS-based characterization of the geomorphology and surficial geology of Clark County, Nevada (i.e. ND2MP). Although the term ‘habitat’ is often used loosely as equivalent to ‘native vegetation’, this is not always the case. Nonetheless, scientist and managers continue to use vegetation as a means for defining habitat. Geologic materials provide an alternative and at times more appropriate means of defining species habitat and extent of vegetation communities, especially in arid environments (Miller and Franklin 2002, Heaton et al. 2006).
Objective two is to map the ecosystems in Clark County. The MSHCP uses an ecosystem-based approach to conservation planning and management for plant and animal species. We will update and refine the current vegetation based ecosystem model for Clark County. This includes the identification and spatial modeling of various NatureServe based Ecological Systems, Alliances and possible Associations. Our goal is to capture important ecosystems that include such broadly defined vegetation classes as blackbrush, sagebrush, pinion-juniper, saltbrush, creosote bush, Joshua Trees, etc. Additionally, we will for the first time develop spatial models for non-vegetation based MSHCP ecosystems such as dunes and dry lakes.
Objective three is to develop an enhanced vegetation based ecosystem classification model in three pilot areas using more intensive sampling, advanced spatial statistical methods and object-oriented classification and the newly developed geomorphology and surfical geology datasets. Current pilot areas under consideration include Piute-Eldorado Valleys, Ivanpah Valley, Gold-Butte and Kyle Canyon area across to the Sheep Range.