Episcopic imaging using techniques such as High Resolution Episcopic Microscopy (HREM) and its variants, allows biological samples to be visualized in three dimensions over a large field of view. Quantitative analysis of episcopic image data is undertaken using a range of methods. In this systematic review, we look at trends in quantitative analysis of episcopic images and discuss avenues for further research. Papers published between 2011 and 2022 were analyzed for details about quantitative analysis approaches, methods of image annotation and choice of image processing software. It is shown that quantitative processing is becoming more common in episcopic microscopy and that manual annotation is the predominant method of image analysis. Our meta-analysis highlights where tools and methods require further development in this field, and we discuss what this means for the future of quantitative episcopic imaging, as well as how annotation and quantification may be automated and standardized across the field.

Spatiotemporal climate variability is a leading environmental constraint to the rain-fed agricultural productivity and food security of communities in the Abbay basin and elsewhere in Ethiopia. The previous one-size-fits-all approach to soil and water management technology targeting did not effectively address climate-induced risks to rain-fed agriculture. This study, therefore, delineates homogenous climatic regions and identifies climate-induced risks to rain-fed agriculture that are important to guide decisions and selection of site-specific technologies for green water management in the Abbay basin. The k-means spatial clustering method was employed to identify homogenous climatic regions in the study area, while the Elbow method was used to determine an optimum number of the climate clusters. The k-mean clustering used the Enhancing National Climate Services (ENACTS) daily rainfall, minimum and maximum temperatures, and other derived climate variables that include daily rainfall amount, length of growing period (LGP), rainfall onset and cessation dates, and rainfall intensity, temperature, potential evapotranspiration (PET), soil moisture and AsterDEM to define climate regions. Accordingly, 12 climate clusters or regions were identified and mapped for the basin. Clustering a given geographic region into homogenous climate classes is useful to accurately identify and target locally relevant green water management technologies to effectively address local-scale climate-induced risks. The study has also provides a methodological framework that can be used in the other river basins of Ethiopia and indeed elsewhere.