The most widely used classification method for statistical mapping is Jenks’s natural breaks. However, it has been found that natural breaks is not good at classifying data which have scaling property. Scaling property is ubiquitous in many societal and natural phenomena. It can be explained as there are far more smaller things than larger ones. For example, there are far more shorter streets than longer ones, far more smaller street blocks than bigger ones, and far more smaller cities than larger ones. Head/tail breaks is a new classification scheme that is designed for values that exhibit scaling property. In Digital Elevation Models (DEMs), there are far more lower elevation points than higher elevation points. This study performs both head/tail breaks and natural breaks for values from five resolutions of DEMs. The aim of this study is to examine advantages and disadvantages of head/tail breaks classification scheme compared with natural breaks. One of the five resolutions of DEMs is given as an example to illustrate the principle behind the head/tail breaks in the case study.The results of head/tail breaks for five resolutions are slightly different from each other in number of classes or level of details. The similar results of comparisons support the previous finding that head/tail breaks is advantaged over natural breaks in reflecting the hierarchy of data. But the number of classes could be reduced for better statistical mapping. Otherwise the top values, which are very little, would be nearly invisible in the map.A main conclusion to be drawn from this study is that head/tail breaks classification scheme is advantaged over natural breaks in presenting hierarchy or scaling of elevation data, with the top classes gathered into one. Another conclusion is when the resolution gets higher; the scaling property gets more striking.

Light Detection and Ranging (Lidar) is a remote sensing technique that provides high resolution range measurements between the laser scanner and Earth’s topography. These range measurements are mapped as 3D point cloud with high accuracy (< 0.1 meters). Depending on the geometry of the illuminated surfaces on earth one or more backscattered echoes are recorded for every pulse emitted by the laser scanner. Lidar has the advantage of being able to create elevation surfaces in 3D, while also having information about the intensity of the returned pulse at each point, thus it can be treated as a spatial and as a spectral data system. The 3D elevation attributes of Lidar data are used in this study to identify possible water surface points quickly and efficiently. The approach incorporates the use of Laplacian curvature computed via wavelets where the wavelets are the first and second order derivatives of a Gaussian kernel. In computer science, a kd-tree is a space-partitioning data structure used for organizing points in a k dimensional space. The 3D point cloud is segmented by using a kd-tree and following this segmentation the neighborhood of each point is identified and Laplacian curvature is computed at each point record. A combination of positive curvature values and elevation measures is used to determine the threshold for identifying possible water surface points in the point cloud. The efficiency and accurate localization of the extracted water surface points are demonstrated by using the Lidar data for Williamson County in Texas. Six different test sites are identified and the results are compared against high resolution imagery. The resulting point features mapped accurately on streams and other water surfaces in the test sites. The combination of curvature and elevation filtering allowed the procedure to omit roads and bridges in the test sites and only identify points that belonged to streams, small ponds and floodplains. This procedure shows the capability of Lidar data for water surface mapping thus providing valuable datasets for a number of applications in geomorphology, hydrology and hydraulics. / text

Complex interactions between topographic heterogeneity and steep gradients in climate and environmental conditions are commonly assumed to promote biotic diversification. Using tropical frogs as a model, I investigate the nature of these interactions that disrupt migration between populations, causing genetic divergence and speciation. I determine the role of several putative factors that affect gene flow (Euclidean distances, Least Cost Path (LCP) distances, topographic complexity, and elevation difference) and promote genetic structure (FST) between populations of three tropical Andean frog species. Moreover, I investigate, from an intraspecific perspective, whether montane frog species display on average larger genetic distances per kilometer relative to lowland species. Finally, I test if recent genetic divergence caused by topographic barriers to gene flow is paralleled by independent character systems such as acoustics and morphological traits in the high Andean frog Dendropsophus labialis. Even though the effect of geographic features on migration (and conversely, FST) was species-specific, LCP and Euclidean distances had the strongest effect on migration rate. Topographic complexity also reduced migration rate whereas elevation difference did not have an effect. I found that indeed highland species show larger genetic distances per kilometer between haplotypes than do lowland species. Also, genetic divergence is strongly associated with topographic heterogeneity, which is an intrinsic characteristic of montane regions. Finally, I found that acoustic variation in D. labialis diverges according to genealogical history, but external morphology does not follow this relationship. Stochastic processes due to genetic drift appear to be a better explanatory mechanism for the divergence in calls than adaptive variation. The strong and congruent divergence observed in acoustic and genetic characters indicates that these two groups correspond to morphologically cryptic parapatric species. Overall, the results of this study suggest some of the mechanisms that allow tropical mountains to promote intraspecific genetic divergence. The combined effect of ridges (promoting allopatric differentiation) and environmental gradients across elevation (promoting parapatric differentiation) are effective forces that are present mostly in highland biomes. Unfortunately, such biomes are critically threatened by habitat destruction and climate change, possibly more than any other biome on earth. / text

The Critical Zone (CZ) is the surficial layer of the planet that sustains life on Earth and extends from the base of the weathered bedrock to the top of the vegetation canopy. Its structure influences water fluxes, biogeochemistry and vegetation. In this dissertation, I explore the relationships between climate, water fluxes, vegetation dynamics, biogeochemistry, and effective energy and mass transfer fluxes (EEMT) in a semi-arid critical zone. This research was carried out in the upper Jemez River Basin in northern New Mexico across gradients of climate and elevation. The main research objectives were to (i) quantify relations among inputs of mass and energy (EEMT), hydrological and biogeochemical processes within the CZ, (ii) determine water fluxes and vegetation dynamics in high elevation mountain catchments with different terrain aspect and solar radiation, and (iii) study temporal variability of climate and its influence on the CZ water availability, forest productivity and energy and mass fluxes. The key findings of this study include (i) significant correlations between EEMT, water transit times (WTT) and mineral weathering products around Redondo Peak. Significant correlations were observed between dissolved weathering products (Na⁺ and DIC) and maximum EEMT. Similarly, ³H concentrations measured at the springs were significantly correlated with maximum EEMT; (ii) terrain aspect strongly controls energy, water distribution, and vegetation productivity in high elevation ecosystems in catchments draining different aspects of Redondo Peak. The predominantly north facing catchment, when compared to the other two eastern catchments, receives less solar radiation, exhibits less forest cover and smaller biomass, has more surface runoff and smaller vegetation water consumption. Furthermore, the north facing catchment showed smaller NDVI values and shorter growing season length as a consequence of energy limitation, and (iii) from 1984 to 2012 a decreasing trend in water availability, increased vegetation water use, a reduction in both forest productivity and EEMT was observed at the upper Jemez River Basin. These changes point towards a hotter, drier and less productive ecosystem which may alter critical zone processes in high elevation semi-arid systems.

Closed depressions, low elevation features in a landscape with no outlet point, play an important role in both surface and subsurface hydrology. These depressions, which are common in hummocky morainal landscapes, pool incoming surface flow, promoting infiltration and facilitating leaching of surface pollutants into vital groundwater resources. Due to the cost of ground based identification in large areas and difficulties with the identification of irregular depressions, remote identification using digital elevation models (DEMs) stands as a practical and effective tool for the mapping of these closed depressions. A modified stochastic depression identification algorithm was used in this study to characterize depressions in the Waterloo and Paris-Galt-Guelph moraines of Southwestern Ontario. The simulation output was a map of depressions in the study area. Depressions were corroborated using GRCA Wetlands data, Google Street View imagery, SWOOP 2006 orthophotos and field validation. Depression corroboration showed that the algorithm was able to accurately identify the location of closed depressions containing wetlands and closed depressions that are dry (largely due to wetland draining) in the hummocky topography of the study site. This research has implications for depression mapping in the field of digital terrain analysis as it enables the identification of real depressions in large study areas with a moderate resolution DEM. Providing a means of efficiently mapping closed depressions is important because of the role closed depressions play in the recharge of important groundwater stores. / Natural Resources Canada

The Lower Keys marsh rabbit (Sylvilagus palustris hefneri, LKMR), 1 of 3 subspecies of Sylvilagus palustris, is endemic to the Lower Florida Keys. The LKMR is listed as an endangered species due to predation by feral and free roaming domestic cats (Felis catus) and raccoons (Procyon lotor), road mortality, effects of storm surges, sea level rise, the small declining metapopulation size, and possible habitat loss from hardwood encroachment. The purpose of this study was to determine the current LKMR density on lands managed by the United States Navy, Naval Air Station Key West and evaluate how vegetation structure and patch elevation effect LKMR population density. I conducted fecal pellet counts to determine LKMR density, collected vegetation data using percent composition of ground cover, Robel range pole, and point-centered quarter methods, and obtained data on patch area and elevation. I used simple linear regression to assess the relationship between LKMR density and 9 measured vegetation characteristics, patch area, and patch elevation to determine which variables have an influence on LKMR density and the relationship between them. In my examination of the simple regression models, 6 out of the 11 variables appeared to influence LKMR population density. The average per patch percent composition of nonliving material and grasses, maximum height of vegetation at the range pole, distance to nearest woody vegetation, patch elevation, and visual obstruction readings (VOR) individually accounted for 26.4%, 30.4% , 18.1%, 8.5%, 6.8%, and 1.4% of the variability in LKMR density, respectively. According to the regression models, LKMR density increased in patches with greater amounts of grasses and with greater distance to woody vegetation. Habitat management is vital to the recovery of the LKMR and needs to focus on providing greater amounts of grasses and reducing the amount of woody vegetation encroachment to enhance LKMR population density.

<p>Global climate change can cause shifts in species distributions, and increases in some of their competitors, predators, and diseases that might even cause their extinction. Species may respond to a warming climate by moving to higher latitudes or elevations. Shifts in geographic ranges are common responses in temperate regions. For the tropics, latitudinal temperature gradients are shallow: the only escape for species may be to move to higher elevations. There are few data to suggest that they do, and our understanding of the process is still very limited. Yet, the greatest loss of species from climate disruption may be for tropical montane species. To better understand the potential process of elevational range shifts in the tropics and their implications we have to: 1) Build theoretical models for the process of range shifting, 2) Evaluate potential constraints that species could face while moving to higher elevations, 3) Obtain empirical evidence confirming the uphill shift of species ranges, 4) Determine the number of extinctions that could arise from elevational range shifts (mountain top extinctions) and 5) Identify vulnerable species and areas, and determine their representation by the Protected Areas Network. The purpose of this dissertation is to address these issues, by applying novel methods and collecting empirical evidence. </p><p>In the second chapter I incorporated temperature gradients and land-cover data from the current ranges of species in a model of range shifts in response to climate change. I tested 4 possible scenarios of amphibian movement on a tropical mountain and estimated the constraints to range shifts imposed by each scenario. Confirming the occurrence of elevational range shifts with empirical data is also essential, but requires historical data as a baseline for comparison. I repeated a historical transect in Peru, sampling birds at the same locations they were sampled 40 years ago, and compared their elevational ranges between sampling occasions to evaluate if they were moving uphill as a response to warming temperatures. Finally, based on the results from this comparison, I estimated the potential extinctions derived from elevational range shifts, using information on the species distribution, the topography and land cover within the ranges and surrounding areas. I evaluated the extent of mountain top extinctions for 172 bird species with restricted ranges in the northern Andes. I also considered how Colombia's protected Area Network represents species and sites that are vulnerable in the face of climate change.</p><p>More than 30% of the range of 21 of 46 amphibian species in the tropical Sierra Nevada de Santa Marta is likely to become isolated as climate changes. More than 30% of the range of 13 amphibian species would shift to areas that currently are unlikely to sustain survival and reproduction. Combined, over 70% of the current range of 7 species would become thermally isolated or shift to areas that currently are unlikely to support survival and reproduction. The constraints on species' movements to higher elevations in response to climate change can increase considerably the number of species threatened by climate change in tropical mountains.</p><p>In the comparison of bird distributions in the Cerrros del Sira, in Peru, I found an average upward shift of 49 m for 55 bird species over a 41 year interval. This shift is significantly upward, but also significantly smaller than the 152 m one expects from warming in the region. The range shifts in elevation were similar across different trophic guilds. Endothermy may provide birds with some flexibility to temperature changes and allow them to move less than expected. Instead of being directly dependent on temperature, birds may be responding to gradual changes in the nature of the habitat or availability of food resources, and presence of competitors. If so, this has important implications for estimates of mountaintop extinctions from climate change. </p><p>The estimated number of mountain top extinctions from climate disruption in the northern Andes is low, both the absolute number (5 species) and the relative number (less than 0.5% of Colombian land birds). According to future climate predictions these extinctions will not likely occur in this century. The extent of species loss in the Andes is not predicted by absolute mountaintop extinctions modeled by the kind of processes most other studies use. Rather, it is highly contingent -- the species will survive or not depending on how well we protect their much reduced ranges from the variety of other threats.</p> / Dissertation

In this study, DEMs and orthoimages were generated from ASTER imagery and their accuracies were assessed. The study site covers an area of approximately 60 x 60 km and encloses the city of Ankara. First, DEMs were generated from stereo ASTER images. In order to find the best GCP combination, different number of GCPs (8, 16, 24, and 32) was used. The accuracies of the generated DEMs were then assessed based on the check points (CP), slopes and land cover types. It was found that 16 GCPs were good compromise to produce the most accurate DEM. The post processing and blunder removal increased the overall accuracy up to 38%. It was also found that there is a strong linear relationship between the accuracies of DEMs and the slopes of the terrain. The accuracies computed for water, urban, forest, mountainous, and other areas were found to be 5.01 m, 8.03 m, 12.69 m, 17.14 m, and 10.21 m, respectively. The overall accuracy was computed as 10.92 m. The orthorectification of the ASTER image was carried out using 12 different mathematical models. Based on the results, the models First Order 2D Polynomial, Direct Linear Transformation and First Order Polynomial with Relief have produced the worst results. On the other hand, the model Second Order Rational Function appears to be the best model to orthorectify the ASTER images. However, the developed model Second Order Polynomial with Relief provides simplicity, consistency and requires less number of GCPs when compared to the model Second Order Rational Function.

The Darwin-Hatherton glacial system is an outlet glacial system in the Transantarctic Mountains, Antarctica, which drains ice from the East Antarctic Ice Sheet into the Ross Ice Shelf. This research provides remotely sensed data that can be used in modeling research for the Darwin-Hatherton glacial system, which in turn can be used in mass balance research for the West Antarctic Ice Sheet. Two improved digital elevation models (DEM) are produced to cover the lower Darwin Glacier and to cover the upper Darwin and Hatherton Glaciers. The new improved DEMs are generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data, with a resolution of 45 m. To produce the two final DEMs, multiple DEMs are firstly adjusted to remove systematic errors and are then stacked and averaged to increase the accuracy and produce the final two DEMs. For the lower Darwin Glacier, 5 DEMs were averaged and in the upper Darwin and Hatherton Glaciers, 6 DEMs were averaged. The accuracy is quantified by a remaining error of + 9 m for the lower Darwin Glacier DEM and + 37 m for the upper Darwin and Hatherton Glaciers DEM. This is a significant improvement from the existing 200 m resolution Radarsat Antarctic mapping project (RAMPv2) DEM which has a remaining error of + 138 m over the lower Darwin Glacier and + 152 m over the upper Darwin and Hatherton Glaciers. The accuracy is assessed by comparing the ASTER and RAMPv2 DEMs to highly accurate ice, cloud and land elevation satellite (ICESat) laser altimetry data. A 15 m resolution, true colour, orthorectified image is provided for the entire Darwin-Hatherton glacial system from ASTER satellite imagery. The DEMs used to orthorectify the ASTER satellite imagery are the two new 45 m resolution ASTER DEMs. Lastly feature tracking was explored as a method for measuring surface ice velocity. This research shows that feature tracking is unsuitable for the Darwin-Hatherton glacial system if using 15 m resolution satellite imagery over a 1 to 4 year time period.

Mountain glaciers are expected to be the greatest contributor to sea level rise over the next century. Glaciers provide a good indicator of global climate and how to monitor their change is an increasingly important issue for climate science and for sea level rise forecasts. However, there has been little direct measurement of glacier volume change in New Zealand. This study explores the use of remotely sensed data for measuring glacier volume change from 1965 to 2006. Digital photogrammetric methods were used to extract topographic data of the Tasman Glacier from aerial photography and ASTER imagery for the years 1965, 1986, 2002 and 2006. SRTM C band data from 2000 were also analysed. Data were compared to an existing digital elvation model produced from the New Zealand Digital Topographic Database to test for their reliability. Using regression analysis, the data were filtered and points representing rock were used to correct points on the glacier ice for vertical bias. The quality of the data extracted from the aerial photography was good on rock and debris covered ice, but poor on snow. The data extracted from ASTER was much more reliable on snow in the upper glacier than the aerial photography, but was very poor in the lower debris covered region of the glacier. While the quality of the SRTM data is very high, there is a second order distortion present in the data that is evident over elevation differences. However, the overall mean difference of the SRTM rock from TOPODATA is close to zero. An overall trend could be seen in the data between dates. However, the 2006 ASTER data proved unreliable on the debris covered section of the glacier. Total volume change is therefore calculated for the period between 1965 and 2002. The data show a loss of 3:4km³ or 0:092km³ per year, an estimated 6% of the total ice in New Zealand. This is compared to estimates using the annual end of summer snowline survey between 1977 and 2005 of 1:78 km³, or 0:064km³ per year. The spatial resolution of ASTER makes high temporal resolution monitoring of volume change unlikely for the New Zealand glaciers. The infrequency of aerial photography, the high cost and vast time involved in extracting good quality elevation data from aerial photography makes it impractical for monitoring glacier volume change remotely. However, SRTM and other radar sensors may provide a better solution, as the data do not rely heavily on user processing.