Using Biophysical Geospatial and Remotely Sensed Data to Classify Ecological Sites and States

Monitoring and identifying the state of rangelands on a landscape scale can be a time consuming process. In this thesis, remote sensing imagery has been used to show how the process of classifying different ecological sites and states can be done on a per pixel basis for a large landscape. Twenty-seven years\u27 worth of remotely sensed imagery was collected, atmospherically corrected, and radiometrically normalized. Several vegetation indices were extracted from the imagery along with derivatives from a digital elevation model. Dominant vegetation components from five major ecological sites in Rich County, Utah, were chosen for study. The vegetation components were Aspen, Douglas-fir, Utah juniper, mountain big sagebrush, and Wyoming big sagebrush. Training sites were extracted from within map units with a majority of one of the five ecological sites. A Random Forests decision tree model was developed using an attribute table populated with spectral biophysical variables derived from the training sites. The overall out-of-bag accuracy for the Random Forests model was 97.2%. The model was then applied to the predictor spectral and biophysical variables to spatially map the five major vegetation components for all of Rich County. Each vegetation class had greater than 90% accuracies except for Utah juniper at 81%. This process is further explained in chapter 2. As a follow-on effort, we attempted to classify vegetation ecological states within a single ecological site (Wyoming big sagebrush). This was done using field data collected by previous studies as training data for all five ecological states documented for our chosen ecological site. A Maximum Likelihood classifier was applied to four years of Landsat 5 Thematic Mapper imagery to map each ecological state to pixels coincident to the map units correlated to the Wyoming big sagebrush ecological site. We used the Mahalanobis distance metric as an indicator of pixel membership to the Wyoming big sagebrush ecological site. Overall classification accuracy for the different ecological states was 64.7% for pixels with low Mahalanobis distance and less than 25% for higher distances

Characterization, Mapping, and Monitoring of Rangelands: Methods and Approaches

While there are many definitions of rangeland, the central theme of all these is that it is land on which the dominating vegetation is mainly grasses, grass-like plants, forbs, shrubs, and isolated trees. Rangelands include shrublands, natural grasslands, woodlands, savannahs, tundra, and many desert regions. A distinguishing factor of rangelands from pasture lands is that they grow primarily native vegetation, rather than plants established by humans. Rangelands are also managed mainly through extensive practices such as managed livestock grazing and prescribed fire rather than more intensive agricultural practices and the use of fertilizers. Rangelands worldwide are known to provide a wide range of desirable goods and services, including but not limited to livestock forage, wildlife habitat, wood products, mineral resources, water, and recreation space. Large populations depend on rangelands for their livelihoods, hence effective monitoring and management is crucial for sustainable production, health, and biodiversity of these systems

The B-Star Exoplanet Abundance Study: a co-moving 16–25 M Jup companion to the young binary system HIP 79098

9 pages, 6 figures, accepted for publication in A&AInternational audienceWide low-mass substellar companions are known to be very rare among low-mass stars, but appear to become increasingly common with increasing stellar mass. However, B-type stars, which are the most massive stars within ~150 pc of the Sun, have not yet been examined to the same extent as AFGKM-type stars in that regard. In order to address this issue, we launched the ongoing B-star Exoplanet Abundance Study (BEAST) to examine the frequency and properties of planets, brown dwarfs, and disks around B-type stars in the Scorpius-Centaurus (Sco-Cen) association; we also analyzed archival data of B-type stars in Sco-Cen. During this process, we identified a candidate substellar companion to the B9-type spectroscopic binary HIP 79098 AB, which we refer to as HIP 79098 (AB)b. The candidate had been previously reported in the literature, but was classified as a background contaminant on the basis of its peculiar colors. Here we demonstrate that the colors of HIP 79098 (AB)b are consistent with several recently discovered young and low-mass brown dwarfs, including other companions to stars in Sco-Cen. Furthermore, we show unambiguous common proper motion over a 15-year baseline, robustly identifying HIP 79098 (AB)b as a bona fide substellar circumbinary companion at a 345+/-6 AU projected separation to the B9-type stellar pair. With a model-dependent mass of 16-25 Mjup yielding a mass ratio of <1%, HIP 79098 (AB)b joins a growing number of substellar companions with planet-like mass ratios around massive stars. Our observations underline the importance of common proper motion analysis in the identification of physical companionship, and imply that additional companions could potentially remain hidden in the archives of purely photometric surveys