Limiting Factors Clause Samples

Limiting Factors. Developing the canopy height model and ITOs used in the abundance model is very time consuming, taking several weeks for the Mashel watershed. The methods used to develop these datasets are described in Appendix D - Individual Tree Segmentation.

Limiting Factors. Development of the canopy height model, and measuring the diameters of the individual tree objects is very time consuming. This processing took several weeks for the Mashel watershed. The inclusion of the Canopy Height Model (CHM) radius and diameter information as possible metrics for the model did increase the accuracy, but not by a substantial amount. The additional processing time may not be worth the accuracy improvement. This will need to be determined based on available project budget and goals.

Limiting Factors. Illumination angles, sensor viewing angles, species, stand density, and image quality can all affect the feasibility of identifying individual tree canopies for both automated and manual methods. Imagery must be of a high enough resolution for individual crowns to be visible. Differing image quality over an area can cause results to vary across a study site.

Limiting Factors. Fat Red 7B, as well as the Sudan black stains, has a much greater affinity for triglycerides and cholesterol esters than it has for free cholesterol and phospholipids. Bands seen after staining with these dyes do not reflect a true quantitation of the total plasma lipids.12 For this reason it is not recommended that relative percentages of lipoprotein bands be used to calculate the total lipid content in each fraction from a total plasma lipid value. Since most laboratories routinely offer total cholesterol and triglyceride levels, this information is unnecessary. Interfering Factors: Specimens collected in heparin should not be used since heparin alters the migration patterns of the lipoprotein fractions.

Limiting Factors. LIDAR is expensive per unit area. LIDAR data is not available statewide; it is only available in relatively small spatial extents where acquisitions have taken place. LIDAR point data requires a large amount of storage space and processing capability. All models presented in this report are specific to the LiDAR data and geographic location, thus the models cannot be and should not be extrapolated to other landscapes and watersheds without understanding that the errors and uncertainties will change and cannot be evaluated.

Limiting Factors. Exact, known locations of individual trees. Overlapping of tree crowns [which we found on several occasions, large alder trees with smaller red cedar or ▇▇▇▇▇▇▇ firs growing underneath.] Illumination angles, sensor viewing angles, species, stand density, and image quality can all affect the feasibility of identifying individual tree canopies for both automated and manual methods. Imagery must be of a high enough resolution for individual crowns to be visible. Differing image quality over an area can cause results to vary across a study site.

Limiting Factors. At this time, it is not known which DEM resolution, flow accumulation algorithm, or flow accumulation threshold produce the most accurate stream channel locations. Flow accumulation algorithms and digital culvert development can take a large amount of processing time, especially for large areas.

Limiting Factors. Illumination angles, sensor viewing angles, species, stand density, and image quality can all affect the feasibility of identifying individual tree canopies for both automated and manual methods. Imagery must be of a high enough resolution for individual crowns to be visible. Differing image quality over an area can cause results to vary across a study site. Field estimations of percent canopy cover may have subjective biases because of the methodology used. Moreover, it may be possible to only estimate upper levels of tree canopy coverage using aerial/satellite imagery because of its inability to offer some of the vertical information capable in LiDAR.

Limiting Factors. There are different ways to estimate canopy closure or canopy cover (which are not the same) in the field, but they can be time consuming and the estimates they produce don’t necessarily agree with one another or with LIDAR. None of these methods can be said to represent the precise field condition, thus while some are considered by researchers to have greater or lesser accuracy none can really serve as a check on the performance of the others.