Dr Sofanit Girma Araya
Sofanit did her PhD in spatial information sciences at School of Biological Sciences, The University of Adelaide. Her PhD thesis is titled:
"Digital soil mapping for sustainable agricultural productivity"
The understanding of spatial and temporal yield variability is the key for better management of agricultural fields. The crop yield in the arid and semi-arid environment is highly dependent on the water availability. Vegetation condition is a good indicator of the soil and its interaction with the environmental factors such as rainfall. Time series analysis of MODIS imagery has been widely used for various agricultural related studies such as crop identification and yield estimation. However, it hasn't been widely used for the understanding of the soil conditions underneath.
The main focus of her PhD project was to study the soil condition (Water Holding Capacity) in terms of agricultural productivity using time series spatial information, which require extensive manipulation and analysis of multi-temporal vegetation index data. As part of the project a software package, "CropPhenology" has designed to extract crop's growth stage and condition from vegetation dynamics data in R computing environment.
The CropPhenology software package is desinged as a tool for analysing multi temporal remote sensing imagery. It is a , a free, easy to use package designed in the R environment that enables flexibility and interoperability that allows users to progress from downloading remote sensing images to crop phenology analysis and visualisation with only minor processing steps. It is an inovative research outcome for promoting multi temporal remote sensing application in agranomic and vegetation related resaerch works.
CropPhenology package is available at :https://github.com/SofanitAraya/CropPhenology, user manuals and other additional informationis available at http://cropphenology.wixsite.com/package.
Sofanit is currently a postdoctoral researcher at the school of Civil, Environmental and Mining Engineering.
|2018||University of Adelaide, Adelaide||Australia||PhD|
|2007||University of Twente, Enschede||Netherlands||MSc|
|1998||Addis Ababa University, Addis Ababa||Ethiopia||BSc|
|2018||Araya, S., Ostendorf, B., Lyle, G., & Lewis, M. (2018). CropPhenology: An R package for extracting crop phenology from time series remotely sensed vegetation index imagery. Ecological Informatics, 46, 45-56.
|2017||Araya, S., Ostendorf, B., Lyle, G., & Lewis, M. (2017). Remote Sensing Derived Phenological Metrics to Assess the Spatio-Temporal Growth Variability in Cropping Fields. Advances in Remote Sensing, 06(03), 212-228.
|2016||Araya, S., Lyle, G., Lewis, M., & Ostendorf, B. (2016). Phenologic metrics derived from MODIS NDVI as indicators for Plant Available Water-holding Capacity. Ecological Indicators, 60, 1263-1272.
DOI Scopus4 WoS2
The University of Adelaide Divisional Scholarship
Teaching Interest - Spatial information, GIS and remote sensing for environmental management
I have experience
- Demonstrating GIS for Agriculture and Environmental Management subjects at the University of Adelaide.
- Teaching GIS and map preparation and presentation courses at TAFESA