The recent global urban expansion has seen a massive decline and loss in the connectivity of urban vegetation. In urban areas, some vegetation patches have increasingly become isolated and less connected by a matrix composed of impervious surfaces and transportation networks like roads. Vegetation fragmentation is a global threat to the remaining urban green spaces and has an impact on biodiversity conservation, environmental quality and urban microclimates. So far, a lot of work has been done on mapping and monitoring urban green spaces, some using conventional methods and of late using remotely sensed data. However, not much is known or well documented on the new developments in the remote sensing of vegetation fragmentation in urban areas over the last two decades. Thus, the objective of this research work is to present a detailed and comprehensive synthesis of the progress of remote sensing in assessing and monitoring landscape structure of urban green spaces and vegetation fragmentation. Specifically, scientific literature from the year 2000 to 2020 was reviewed to provide a state-of-the-art progress on the remote sensing of vegetation fragmentation in urban areas. Results indicate that between 2000 and 2020, there was a considerable increase in the number of scientific publications on vegetation fragmentation in urban landscapes. The discrete landscape pattern indices are the most widely used method. Comparatively, Land Remote Sensing Satellite System (Landsat) data was widely used due to its suitable spatial and temporal resolution, free availability and the presence of historical archival data that spans over a period of 40 years. The most commonly used scale was local (a city and/or municipality) followed by regional (more than one municipality in one continent) and then global (several selected cities and urban areas across continents). Only two studies were conducted at the global level. Further, geographic bias was observed in most of the accessed vegetation fragmentation studies. The review showed that vegetation fragmentation studies were done mostly for cities in China, North America and Europe while cities in most parts of Africa, Asia, Eurasia, Oceania and South America have not been comprehensively studied. The study also showed that the majority of cities across the globe have experienced severe vegetation fragmentation over the years. This review underscores the relevance of scientific findings in urban and spatial planning to minimize the loss of urban green spaces and to conserve and restore affected areas.

The spatial configuration of vegetation patches in the landscape has implications for the provision of ecosystem services, human adaptation to climate change, enhancement, or mitigation of urban heat island. Until recently, the effect of spatial configuration of vegetation to enhance or mitigate urban heat island has received little consideration in urban thermal assessments. This study examines the impact of spatial configuration of vegetation patches on urban thermal warming and cooling in Harare metropolitan city, Zimbabwe. The study used Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat and Sentinel 2 data acquired between 1994 and 2017 to derive detailed information on vegetation patches, landscape metrics, and land surface temperature LST(°C). The spatial configuration of urban vegetation patterns was analyzed using landscape metrics in Fragstats program. Getis Ord Gi* as a Local Indicator of Spatial Association (LISA) was used to characterize the spatial clustering and dispersion of urban vegetation patches. Results of the Getis Ord Gi* showed that clustered vegetation lowers surface temperatures more effectively than dispersed and fragmented patterns of vegetation. The size, density, shape complexity, and cohesion of vegetation patches conferred different levels of cooling but Patch Cohesion Index had the strongest negative relationship with LST(°C) at three spatial resolutions of 10 m (Sentinel 2), 15 m (ASTER) and 30 m (Landsat 8). The Spatial Lag Regression model performed better than the Ordinary Least Squares regression analysis in exploring the relationship between LST(°C) and landscape metrics. Specifically, the Spatial Lag Regression model showed higher R² values and log likelihood, lower Schwarz criteria, and Akaike information criterion, and reduced spatial autocorrelations. The overall information provides important insights into the provision of larger, connected, and less fragmented urban vegetation patches to derive maximum and higher cooling effects which is critical for urban planning and design approaches for mitigating increasing surface temperatures in cities.

<!-- *** Custom HTML *** -->The spatial heterogeneity of urban vegetation obtained from discrete land cover classes is sensitive to classification errors and can result in a substantial loss of information, due to the degradation of continuous quantitative information. Although there is an increasing ecological need to use continuous methods to understand spatial heterogeneity and vegetation fragmentation, they remain unexplored. Since local indicators of spatial association (LISA) can capture important spatial patterns of clustering and dispersion at a local scale, it can capture important ecological patterns and process of vegetation fragmentation. This work examines the utility of LISA which allows exploration of local patterns in spatial data in identifying high (hot spots) and low (cold spots) spatial clusters of vegetation patches and fragmentation patterns in Harare metropolitan city in Zimbabwe. The LISA indices of Getis-Ord Gi* and local Moran’s I are computed both on continuous normalized difference vegetation index and discrete land cover data of vegetation and nonvegetation of Sentinel 2016 and 2018. Local spatial clustering patterns are identified with Z-score values that indicate the significance of each statistic. High positive Z-scores are located in the large core, undisturbed, and homogeneous vegetation. Negative Z-scores are located in more dispersed and highly fragmented vegetation. The results suggest that there is a strong tendency for large core, undisturbed, and homogeneous vegetation patches to be spatially clustered and for small, isolated and sparse vegetation patches to be dispersed. The highly fragmented vegetation patches are located in the heavily urbanized part of the city. Overall, findings of this study underscore the relevance of the spatially explicit method of LISA as a valuable source of spatial information for the assessment of local spatial clustering and dispersion of urban vegetation patches. This can be used to develop policies that support effective conservation and restoration strategies.

Occupational health and safety management (OHSMS) systems are recognised internationally as highly flexible and can be tailored to all sizes and types of businesses to manage accidents, injuries, fatalities and health risks at workplaces. This study evaluated the effectiveness of OHSMS audits to occupational accidents mitigation in food and beverage industries at Delta Sparkling Beverages, Harare, Zimbabwe. The study was based on an analytical research using a combination of qualitative and quantitative techniques. In particular in-depth interviews, non-participatory observations and documentary records data search were utilised. 84 questionnaires were self-administered to Delta Sparkling Beverages, employees from different departments using a stratified random technique in 2020. The effectiveness of OHS audits were analysed in which purposive interviews were employed to solicit vital information from key experts in the field of study. The study also sought to highlight challenges faced in the operationalisation of OHSMS audits and the implementation of safety systems. Statistical Package for Social Sciences (SPSS) was used for quantitative data analysis. The results of chi-square (p > 0.05) indicated that there was no association between occurrence of accidents at Delta Sparkling Beverages to OHSMS audits. The research findings further revealed that non-adherence to safe operating procedures (unsafe acts) by employees is the major cause of accidents at the company. The study recommended intervention towards employee behaviour, safety proceduresand ways to improve safety culture within the company.

Understanding how the spatial configuration of land cover patterns of built-up areas and urban vegetation affect urban surface temperatures is crucial for improving the sustainability of cities as well as optimizing urban design and landscape planning. Because of their capability to detect distinct surface thermal features, satellite data have proved useful in exploring the impacts of spatial configuration of land cover on land surface temperature (LST). In this study, we examine how the spatial configuration of built-up and urban vegetation affects the LST in the Harare metropolitan city, Zimbabwe. In order to achieve this objective, we combined the LST, local spatial statistics of Getis-Ord Gi* and local Moran’s I statistic, Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-Up Index (NDBI) derived from multi-date Landsat satellite data (1994, 2001 and 2017). The results of local Moran’s I statistic showed moderate and negative correlations between LST and Landsat derived NDVI. Overall, these results of local Moran’s I statistic demonstrate that clustered vegetation tend to lower LST, providing thermal comfort conditions. In contrast, clustered spatial arrangements of NDBI based on the Getis-Ord Gi* elevate LST, implying that continued clustered built-up expansion has the potential to increase urban surface temperatures.