TB
Timothy Brown
Lead for Digital Innovation, Australian Plant Phenomics Facility, Australian National University (Biological sciences; Earth sciences; Environmental sciences; Engineering; Plant biology not elsewhere classified; Ecology not elsewhere classified; Carbon sequestration science; Climatology; Ecosystem function; Ecological impacts of climate change and ecological adaptation; Environmental biotechnology diagnostics (incl. biosensors); Environmental biotechnology not elsewhere classified; Communications engineering not elsewhere classified)
Canberra, Australia
Publications
- https://scholar.google.com/citations?user=nUQw2aIAAAAJ
- Regional scale impacts of Tamarix leaf beetles (Diorhabda carinulata) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods
- High-resolution, time-lapse imaging for ecosystem-scale phenotyping in the field
- Variation in Leaf Respiration Rates at Night Correlates with Carbohydrate and Amino Acid Supply
- Monitoring impacts of Tamarix leaf beetles (Diorhabda elongata) on the leaf phenology and water use of Tamarix spp. using ground and remote sensing methods
- WK 4-1: The landscape of climate change
- TraitCapture: genomic and environment modelling of plant phenomic data
- Regional scale impacts of Tamarix leaf beetles (Diorhabda carinulata) on the water availability of western US rivers as determined by multi-scale remote sensing methods
- Modeling Behavioral Rules and Self-organization in New World Army Ant Swarms
- Using phenocams to monitor our changing Earth: toward a global phenocam network
- Using Phenomic Analysis of Photosynthetic Function for Abiotic Stress Response Gene Discovery
- Interaction rules, information and foraging--a two-dimensional lattice model of self-organized swarming behavior in the army ant Eciton burchelli.
- Using Webcam Technology for Measuring and Scaling Phenology of Tamarisk (Tamarix ramosissima) Infested with the Biocontrol Beetle (Diorhabda carinulata) on the Dolores River, Utah
- Phenocamera: automated phenology monitoring
- Rapid dispersal of saltcedar (Tamarix spp.) biocontrol beetles (Diorhabda carinulata) on a desert river detected by phenocams, MODIS imagery and ground observations
- Gigavision-A weatherproof, multibillion pixel resolution time-lapse camera system for recording and tracking phenology in every plant in a landscape
- Using simple rules to solve complex problems--Measurements and modeling of army ant swarms
- Deep Phenotyping: Deep Learning For Temporal Phenotype/Genotype Classification
- Assimilating phenology datasets automatically across ICOS ecosystem stations
- Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe’s terrestrial ecosystems: a review
- Reviews and syntheses: Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography
- Biology and Modeling of Self-organization in the New World Army Ant Eciton Burchellii
- Dissertation, Ph. D., The University of Utah, Salt Lake City, UT (USA). Biology and modeling of self-organization in the New World army ant Eciton burchellii.
- 1. Brown, T. B. & Adler, F. Biology and Modeling of Self-organization in the New World Army Ant Exciton burchellii
- Deep phenotyping: deep learning for temporal phenotype/genotype classification
- Rapid dispersal of saltcedar (Tamarix spp.) biocontrol beetles (Diorhabda carinulata) on a desert river detected by phenocams, MODIS imagery and ground observations
- Using phenocams to monitor our changing earth: Toward a global phenocam network
- TraitCapture: Genomic and environment modelling of plant phenomic data
- High-resolution, time-lapse imaging for ecosystem-scale phenotyping in the field
