A collection of Jon’s current and completed research projects.

Current Projects

Optimizing the Planning and Management of Los Angeles County’s Urban Forest
Los Angeles County Department of Public Health
Winter 2021 - Present

DIY Remote Sensing Drones: Finding an affordable option for university students and early career researchers
Graduate Student Collaboration with Morgan L. Rogers, Ph.D. Student, UCLA Luskin School of Public Affairs & the UCLA MakerSpace
Winter 2021 - Present

Alternate project title: An Open-source Autonomous Remote Sensing Drone for Microscale Socio-ecological Systems.

Both Jon and Morgan have an interest in interdisciplinary, microscale research in socio-ecological systems and are seeking to implement fine resolution remote sensing analysis to questions of socio-morphologies and their impact on biodiversity presence and movement. Although fine resolution remote sensing data already exists, cost and or availability at the preferred spatial and spectral resolutions are difficult to obtain for graduate students and early career researchers. We intend to design, program, and build a low-cost, fine resolution, and autonomous remote sensing drone to not only provide an instrument of observation for our own research interests, but to also provide a blueprint for other students and researchers to easily deploy and collect their own data for a fraction of the cost of off-the-shelf drones.

Dron kit

Completed Work

Picking Up Traces: An interdisciplinary approach to multispecies storytelling
Nature, Art & Habitat Residency (NAHR)- 2021 California Fellow
Spring 2021

Jon was selected as the first Fellow for NAHR_California. The Nature Art & Habitat Residency is an eco-laboratory of multidisciplinary practice and is typically hosted in the Taleggio Valley, Bergamo, Italy. He spent two weeks in March, 2021 in the Santa Ynez Valley studying the residency’s theme, Interdependence Between Species.

The artifact created during the residency, “Picking Up Traces: An interdisciplinary approach to multispecies storytelling” is a white paper that documents Jon’s time in the Santa Ynez Valley. He shares details of his pursuit for a cohesive research framework that brings together embedded, environmental histories with more empirical approaches such as remote sensing and species distribution modelling. Jon also spent time capturing images of the local landscape, some of which are included in the white paper.

2021 NAHR_CA Announcement Photo

Mitigating Thermal Exposure in Hyper-Local Land Systems
Civano, Tucson, AZ - UCLA Luskin Center for Innovation
Fall 2019 - Summer 2020

Abstract: Regional land surface temperature (LST) maps derived from remote sensing data are most available to cities to assess and respond to heat. Yet, LST only captures one dimension of urban climate. This study investigates the extent to which remote sensing derived estimates of LST are a proxy for multiple climate variables at hyper-local scales (<10s of meters). We compare remotely sensed estimates of LST (RS-LST) to field and simulated LST, MRT, and air temperature (AT), in a neighborhood in Tucson, Arizona, USA. We find that LST, MRT, and ST follow different diurnal trends masked by RS-LST. We also find that three-dimensional urban design is a better predictor of MRT than two-dimensional land cover and albedo—a known determinant of RS-LST. Shade is a better predictor of both simulated LST and MRT than RS-LST. We conclude that RS-LST is not adequate for guiding heat mitigation at hyper-local scales in cities.

Civano Interactive Map: Interactive map of 25 field measurements from sample sites located in the Civano neighborhood of Tucson, AZ. Interact with the map to see figures with air temperature, surface temperature, and mean radiant temperature readings overlaid on each site.

Figure: (a) Map of Civano I and II neighborhoods in relation to the comparison community; (b) Land Cover map of 8 classified land cover types; (c) Soil adjusted vegetation index indicating the largest prevalence of greenery in all neighborhoods;, (d) Albedo with brightness summaries by neighborhood; (e) Land surface temperature with temperature summaries by neighborhood; and (f) Visualization of the Local Indicators of Spatial Association (LISA) analysis showing the level of confidence for the locations of the coolest and hottest spots across all study areas.

Map of the Civano neighborhood along with visualizations of several remote sensing metrics.

Global tropical dry forest extent and cover: A comparative study of bioclimatic definitions using two climatic data sets
Master’s Thesis - UCLA Department of Geography
Fall 2018 - Spring 2020

Abstract: There is a debate concerning the definition and extent of tropical dry forest biome and vegetation type at a global spatial scale. We identify the potential extent of the tropical dry forest biome based on bioclimatic definitions and climatic data sets to improve global estimates of distribution, cover, and change. We compared four bioclimatic definitions of the tropical dry forest biome–Murphy and Lugo, Food and Agriculture Organization (FAO), DryFlor, aridity index–using two climatic data sets: WorldClim and Climatologies at High-resolution for the Earth’s Land Surface Areas (CHELSA). We then compared each of the eight unique combinations of bioclimatic definitions and climatic data sets using 540 field plots identified as tropical dry forest from a literature search and evaluated the accuracy of World Wildlife Fund tropical and subtropical dry broadleaf forest ecoregions. We used the definition and climate data that most closely matched field data to calculate forest cover in 2000 and change from 2001 to 2020. Globally, there was low agreement (< 58%) between bioclimatic definitions and WWF ecoregions and only 40% of field plots fell within these ecoregions. FAO using CHELSA had the highest agreement with field plots (81%) and was not correlated with the biome extent. Using the FAO definition with CHELSA climatic data set, we estimate 4,931,414 km2 of closed canopy (≥ 40% forest cover) tropical dry forest in 2000 and 4,369,695 km2 in 2020 with a gross loss of 561,719 km2 (11.4%) from 2001 to 2020. Tropical dry forest biome extent varies significantly based on bioclimatic definition used, with nearly half of all tropical dry forest vegetation missed when using ecoregion boundaries alone, especially in Africa. Using site-specific field validation, we find that the FAO definition using CHELSA provides an accurate, standard, and repeatable way to assess tropical dry forest cover and change at a global scale.

Code: Complete set of programming scripts used in this analysis.

Figure: Forest cover and change from FAO bioclimatic definition, CHELSA climate data set, and closed canopy cover. (a) Global, (b) Africa, (c) North and Central America, (d) South America, (e) South Asia, and (f) Southeast Asia & Asia Pacific.

Global Tropical Dry Forest Extent & Cover

Garden Apartments & Superblock Planning: Historical Housing Development versus Housing Design in Los Angeles
Student Undergraduate Research Experience (SURE) - USC Sol Price School of Public Policy
Fall 2012 - Spring 2013

By-Right, By-Design

Alongside his undergraduate mentor Liz Falletta, Jon helped ascertain historical records and tenant data on three multi-unit, architecturally significant housing projects in Los Angeles to highlight the importance of well-designed, multi-unit housing for future development. His research is featured in Liz’s book By-Right, By-Design: Housing Development versus Housing Design in Los Angeles (Routledge, 2020)