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Amon Murwira
Researcher at University of Zimbabwe
Publications - 91
Citations - 1358
Amon Murwira is an academic researcher from University of Zimbabwe. The author has contributed to research in topics: Normalized Difference Vegetation Index & Vegetation. The author has an hindex of 18, co-authored 89 publications receiving 1120 citations.
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Potential of weight of evidence modelling for gully erosion hazard assessment in Mbire District – Zimbabwe
TL;DR: In this paper, the potential of gully erosion could be successfully modelled as a function of seven environmental factors (landcover, soil type, distance from river and distance from road, Sediment Transport Index (STI), Stream Power Index (SPI), and Wetness Index (WI)) using a GIS-based Weight of Evidence Modelling (WEM) in the Mbire District of Zimbabwe.
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The response of elephants to the spatial heterogeneity of vegetation in a Southern African agricultural landscape
Amon Murwira,Andrew K. Skidmore +1 more
TL;DR: In this paper, the authors investigated whether and how the African elephant (Loxodonta africana) responded to spatial heterogeneity of vegetation cover based on data of the early 1980s and early 1990s.
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Integration of mid-infrared spectroscopy and geostatistics in the assessment of soil spatial variability at landscape level
Juan Guillermo Cobo,Juan Guillermo Cobo,Gerd Dercon,Tsitsi Yekeye,Lazarus Chapungu,Chengetai Kadzere,Amon Murwira,Robert J. Delve,Georg Cadisch +8 more
TL;DR: In this paper, mid-infrared spectroscopy (MIRS) and geostatistics were integrated for evaluating soil spatial structures of three land settlement schemes in Zimbabwe (i.e. communal area, old resettlement and new resettlement; on loamy-sand, sandy-loam and clay soils, respectively).
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Predicting maize yield in Zimbabwe using dry dekads derived from remotely sensed Vegetation Condition Index
TL;DR: It is suggested that VCI-derived dry dekads could be used to predict maize yield before the end of the season thereby making it possible to plan strategies for dealing with food deficits or surpluses on time.
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Linking remotely sensed forage quality estimates from WorldView-2 multispectral data with cattle distribution in a savanna landscape
TL;DR: The results of this study suggest that new multispectral data with unique band settings such as WorldView-2 improves the estimation and mapping of forage quality in rangelands at landscape level and indicates that remotely sensed foragequality can be used to explain herbivore distribution, particularly cattle grazing patterns in rAngelands.