Cargando…
Detecting functional field units from satellite images in smallholder farming systems using a deep learning based computer vision approach: A case study from Bangladesh
Improving agricultural productivity of smallholder farms (which are typically less than 2 ha) is key to food security for millions of people in developing nations. Knowledge of the size and location of crop fields forms the basis for crop statistics, yield forecasting, resource allocation, economic...
Autores principales: | Yang, Ruoyu, Ahmed, Zia U., Schulthess, Urs C., Kamal, Mustafa, Rai, Rahul |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7678380/ https://www.ncbi.nlm.nih.gov/pubmed/33251327 http://dx.doi.org/10.1016/j.rsase.2020.100413 |
Ejemplares similares
-
Delineation of agricultural fields in smallholder farms from satellite images using fully convolutional networks and combinatorial grouping
por: Persello, C., et al.
Publicado: (2019) -
Farming on the fringe: Shallow groundwater dynamics and irrigation scheduling for maize and wheat in Bangladesh’s coastal delta
por: Schulthess, Urs, et al.
Publicado: (2019) -
Smallholder Farms and the Potential for Sustainable Intensification
por: Mungai, Leah M., et al.
Publicado: (2016) -
Enhancing Smallholder Access to Agricultural Machinery Services: Lessons from Bangladesh
por: Mottaleb, Khondoker A., et al.
Publicado: (2016) -
Deep Convolutional Neural Network for Mapping Smallholder Agriculture Using High Spatial Resolution Satellite Image
por: Xie, Bin, et al.
Publicado: (2019)