J
Juliana Useya
Researcher at Jilin University
Publications - 9
Citations - 127
Juliana Useya is an academic researcher from Jilin University. The author has contributed to research in topics: Support vector machine & Speckle pattern. The author has an hindex of 5, co-authored 8 publications receiving 56 citations. Previous affiliations of Juliana Useya include University of Zimbabwe.
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Journal ArticleDOI
Exploring the Potential of Mapping Cropping Patterns on Smallholder Scale Croplands Using Sentinel-1 SAR Data
Juliana Useya,Chen Shengbo +1 more
TL;DR: In this paper, the authors explored the potential of mapping cropping patterns occurring on different field parcels on small-scale farmlands in Zimbabwe using the Sentinel-1 synthetic aperture radar (SAR) time series.
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Decision-level fusion of Sentinel-1 SAR and Landsat 8 OLI texture features for crop discrimination and classification: case of Masvingo, Zimbabwe
TL;DR: It is concluded that integration of Landsat 8 and Sentinel-1, either speckle filtered or unfiltered, improves crop classification and speckles do not have statistically significant effects.
Journal ArticleDOI
Comparative Performance Evaluation of Pixel-Level and Decision-Level Data Fusion of Landsat 8 OLI, Landsat 7 ETM+ and Sentinel-2 MSI for Crop Ensemble Classification
Juliana Useya,Shengbo Chen +1 more
TL;DR: The conclusion is that both decision-level and pixel-level fusion approaches produced comparable classification results, and either of the procedures can be adopted in areas with inescapable cloud problems for updating crop inventories and acreage estimation at regional scales.
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Cropland Mapping and Change Detection: Toward Zimbabwean Cropland Inventory
TL;DR: To map cropland utilizing automatic classification; multi-classifier system (MCS); and normalized difference vegetation index and bare-soil index (NDVI-BSI) thresholding and determine the spatiotemporalCropland changes, change detection shows a general increase in the croplands area due to human activities despite the prolonged drought.
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Agent-based modelling of cholera diffusion
TL;DR: The proposed model is simple in its setup but can be extended by adding additional elements such as human movement and change of behaviour of individuals based on disease awareness, which will open opportunities to explore policy related research questions related to interventions to influence the diffusion process.