Julius R Dewald

Conduct geospatial research on the relationship between urban vegetation and public health. Develop GIS datasets, perform spatial analyses, and contribute to scientific publications. Utilize remote sensing techniques, including Fmask and Google Earth Engine, to process satellite imagery. Collaborate with multidisciplinary research teams across universities to advance environmental health studies.

Led remote sensing analyses to study the environmental determinants of public health outcomes. Managed Landsat NDVI time series data for major U.S. cities, applying machine learning techniques to detect trends. Assisted in grant development focused on environmental health research. Designed and implemented two studies utilizing remotely sensed imagery to evaluate urban greenness.

Leads geospatial data processing and spatial analysis to assess urban vegetation and public health impacts. Develops spatial models in ArcGIS Pro, R, and Google Earth Engine to quantify environmental change. Publishes peer-reviewed research on geospatial health and conservation planning. Collaborates with multidisciplinary teams to integrate geospatial science into public health decision-making.

Designed and implemented automated NDVI analysis pipelines using R programming and ArcGIS Pro. Developed spatial data used to track environmental health trends in major U.S. cities. Assisted in grant proposal writing to secure funding for geospatial health research. Managed and optimized geospatial databases for multi-city longitudinal studies.

Designed a research project detecting tree cover changes in Zambia using machine learning and remote sensing. Analyzed spatial changes in fire regimes in response to growing human populations. Conducted focus groups and interviews with wildlife conservation stakeholders in Zambia. Presented findings to Zambian conservation agencies and local communities.

Designed and conducted a research project using machine learning to analyze tree cover changes in Zambia. Investigated spatial fire regime changes in response to human activity using large-scale Landsat datasets. Collected qualitative data through stakeholder interviews and focus groups on conservation efforts. Presented research findings to policymakers and conservation organizations in Zambia.

Created species distribution models to predict malaria vector habitats using ArcGIS and remote sensing tools. Designed high-resolution environmental risk maps using Dempster-Shafer models. Assisted in teaching GIS and remote sensing courses, providing technical training in spatial analysis.