I have been involved in the remote sensing community for nearly two decades and performed field work around the world -- Monterey County, CA (2008 - 2012), Australia (2009), Tinian and Guam (2010), and San Diego County, CA (2019 - 2022). One common theme of my work of which I'm most proud is that my research results can be used to benefit emergency and first responders.

My recent research was focused on using moderate spatial resolution satellite imagery to locate and quantify non-native herbaceous growth forms in Southern California coastal shrubland ecoregions. My previous research objectives were mainly focused on using multispectral data to learn about shallow water bathymetry.

Ph.D. Research

Performing field work in Southern California grasslands (2020 - 2021)
SATELLITE-DERIVED ESTIMATES OF HERBACEOUS FRACTIONAL COVER AND ITS INFLUENCE ON FIRE REGIME IN SOUTHERN CALIFORNIA, USA

Abstract: Expanding invasive herbaceous vegetation (non-native grasses and forbs or herbs) is replacing portions of native shrublands in San Diego County, California, USA through a grass-fire cycle, which contributes to an increased risk of wildfire ignition and spread as well as a changing fire regime. Despite the association between herbaceous abundance and wildfire risk, remote sensing and image processing approaches for quantification of fractional herbaceous cover in shrublands are not well established, nor is the association between herbaceous fraction and proportion of ignitions. In this research, I comparatively assess the accuracy of herbaceous cover estimation and mapping based on three spectral unmixing models applied to Landsat-derived spectral reflectance and spectral vegetation index data from multiple 2020 dates. Based on the model and methods that most accurately and reliably represent herbaceous cover, I then reconstruct the spatial-temporal distribution of herbaceous growth using Landsat images from 1988, 1997, and 2011 and assess the extent to which herbaceous cover has expanded and replaced woody vegetation cover (1988 to 2020). Finally, I combine the herbaceous cover maps with historical ignition points to evaluate the spatial association between herbaceous fractions and locations where fires initially ignited and spread (1992 to 2020). When compared to generated reference data, results demonstrate the parsimonious spectral unmixing approach applied to a fall date estimates herbaceous cover at the 10% accuracy level and more accurately than the more sophisticated unmixing models. Absolute change estimates derived from the earliest and most recent herbaceous cover maps show approximately 25% of the study area exhibited an increase in herbaceous cover > 20%, and roughly 5% experienced a decrease in herbaceous < -20%, with the greatest concentration of change occurring in wildland-urban interface areas. Factors most strongly associated with substantial increase in herbaceous cover include fire return interval, drought, proximity to development, and elevation. The results of evaluating historical ignitions in herbaceous vegetation show the largest proportion of ignitions occurred in areas with > 20% herbaceous fractional cover. Results from this study will enable improved detection of sensitive habitats by satellite for wildfire-prone communities and help identify target areas for mitigating and combating the grass-fire cycle.

​Research Questions:
  1. How well can remote sensing and image processing approaches be used to identify and quantify herbaceous vegetation cover in San Diego County?
  2. When spectral unmixing models are applied to imagery covering a multi-decadal time period in the San Diego County study area, how reliable and accurate are maps of herbaceous cover change?
  3. Where within the study area did substantial change in herbaceous fractional cover occur and do areas of substantial change appear to coincide with wildfire frequency or drought effects occurring within the study period?
  4. Are differences in the spatial distribution of wildfire ignitions associated with differences in herbaceous fractional cover in San Diego County shrublands for 1992 to 2020?

​
West, K. R. L. (2023). Satellite-derived estimates of herbaceous fractional cover and its influence on fire regime in San Diego County, California, USA shrublands. Unpublished Ph.D. Dissertation, San Diego State University/University of California, Santa Barbara.

M.S. research

USING MULTI-ANGLE WORLDVIEW-2 (WV-2) IMAGERY TO DETERMINE OCEAN DEPTH NEAR OAHU, HAWAII

Abstract: Multispectral imaging (MSI) data collected at multiple angles over shallow water provide analysts with a unique perspective of bathymetry in coastal areas. Observations taken by DigitalGlobe’s (now Maxar's) WorldView-2 (WV-2) sensor acquired at 39 different view angles on 30 July 2011 were used to determine the effect of acquisition angle on derived depth. The site used for this study was on the island of Oahu, focused on Kailua Bay (on the windward side of the island). Satellite azimuth and elevation for these data ranged from 18.8 to 185.8 degrees and 24.9 (forward-looking) to 24.5 (backward-looking) degrees (respectively) with 90 degrees representing a nadir view. Bathymetry were derived directly from the WV-2 radiance data using a band ratio approach. Comparison of results to LiDAR-derived bathymetry showed that varying view angle impact the quality of the inferred bathymetry. Derived and reference bathymetry have a higher correlation as images are acquired closer to nadir. The band combination utilized for depth derivation also has an effect on derived bathymetry. Four band combinations were compared, and the Blue & Green combination provided the best results.

Specific Objectives: The objective of this study was to test the potential of bathymetric derivation using WV-2 imagery acquired at multiple angles, and then report upon the role that image acquisition angle plays in depth determination. The motivation for this work originated from the need to determine bathymetry from only a single spectral image of the coastal region in question. There is no guarantee that this image will have been acquired at optimal viewing geometry, e.g., nadir. Without sufficient time to task a satellite and acquire data at a particular viewing angle before a site visit, results from this research strive to provide a better understanding of how to manipulate image data in order to obtain a better understanding of bathymetry. Analysis of multi-angle MSI data was used to quantify the effects of varying satellite acquisition angle on accurate determination of bathymetry.

​
Lee, K. R. (2012). Using Multi-Angle WorldView-2 Imagery to Determine Ocean Depth near Oahu, Hawaii. Unpublished M.S. Thesis, Naval Postgraduate School.
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Five examples out of the 39 WV-2 image acquisitions (labels are actual Image IDs)
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After registration, each image (top) was chipped to the 995 x 999 pixel scene shown (bottom)
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Derived depths for each band combination for Image 1010 (most forward-looking)
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Derived depths for each band combination for Image 2100 (most nadir)
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Derived depths for each band combination for Image 4100 (most backward-looking)

Other Qualifications & Skills

Spatial Thinking, GIS Competency, & Data Visualization
  • Certificate: Satellite Observations and Tools for Fire Risk (NASA Applied Remote Sensing Training (ARSET)) (Aug 2021)
  • Certificate: Understanding Phenology with Remote Sensing (NASA ARSET) (Jul 2020)
  • Certificate: Advanced Webinar: Techniques for Wildfire Detection & Monitoring (NASA ARSET (Sep 2018)
  • Professional Training: Foundations of Geographic Information and Spatial Analysis (Booz Allen Hamilton) (Jul 2015)
  • GEOINT Professional Certification (National Geospatial-Intelligence Agency (NGA)) (Mar 2015 – Apr 2018)

Software
  • ​Esri ArcGIS Pro, Online, StoryMaps, and Desktop
  • Google Earth Engine (GEE) and the web-based integrated development environment (IDE) for the EarthEngine JavaScript API
  • ENVI+IDL
  • ERDAS IMAGINE
  • Microsoft Office Suite (Word, PowerPoint, Excel, SharePoint, and Visio)
Updated 7 April 2026