| FazBrowse GitHub Viewer | Trending | | Home |
| Tools: [Original HTTPS Page] |
🙋♀️ We are a research group of geographers, machine learning engineers, interdisciplinary ecologists, and environmental data scientists from Dr. Chang Zhao’s Ecosystem Services Geo-AI Lab at the Agronomy Department at the University of Florida.
Ecosystem services is a transdisciplinary field that examines both marketed and non-marketed goods and benefits within complex socio-ecological systems, encompassing biodiversity, human activities, and the abiotic environment. These include provisioning, regulating, supporting, and cultural services, for example, food and forage production, water quality regulation, carbon sequestration, microclimate moderation, pollination, and intangible cultural benefits such as wildlife viewing, landscape aesthetics, and outdoor recreation.
We apply a broad suite of geospatial, statistical, and artificial intelligence (AI) methods, alongside observational, modeling, and mixed approaches, to quantify, map, and value multiple ecosystem services and their interactions across heterogenous urban and rural landscapes, at local to global scales. As an interdisciplinary team, we actively collaborate with agronomists, ecologists, entomologists, engineers, economists, computer scientists, and social scientists to advance research on ecosystem services supply, demand and flows.
This is a repository for the weed segmentation model developed in the paper "Detection and mapping of Amaranthus spinosus L. in bermudagrass pastures using drone imagery and deep learning for a site‐specific weed management".
This is a repository for the botanical composition model developed in the paper "Estimating the Botanical Composition in Grass-Legume Mixed Pastures Using Aerial Multispectral Imagery and Deep Learning".
🌿This is a repository for mapping Cultural Ecosystem Service flows from social media imagery with the Vision–Language Model CLIP.
10‑m invasive Opuntia stricta mapping in Laikipia, Kenya with time‑series remote sensing and explainable Random Forest (RF-SHAP)
This organization has no public members. You must be a member to see who’s a part of this organization.
Loading…
Loading…
| Back | FazBrowse Home | New Git URL |