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Taper functions are important tools for forest description, modelling, assessment, and management. A large number of studies have been conducted to develop and improve taper functions; however, few review studies have been dedicated to addressing their development and parameters. This review summarises the development of taper functions by considering their parameterisation, geographic and species-specific limitations, and applications. This study showed that there has been an increase in the number of studies of taper function and contemporary methods have been developed for the establishment of these functions. The reviewed studies also show that taper functions have been developed from simple equations in the early 1900s to complex functions in modern times. Early taper functions included polynomial, sigmoid, principal component analysis (PCA), and linear mixed functions, while contemporary machine learning (ML) approaches include artificial neural network (ANN) and random forest (RF). Further analysis of the published literature also shows that most of the studies of taper functions have been carried out in Europe and the Americas, meaning most taper equations are not specifically applicable to tropical tree species. Developing well-conditioned taper functions requires reducing the variation due to species, measurement techniques, and climatic conditions, among other factors. The information presented in this study is important for understanding and developing taper functions. Future studies can focus on developing better taper functions by incorporating emerging remote sensing and geospatial datasets, and using contemporary statistical approaches such as ANN and RF.
Serajis Salekin; Cristian Catalán; Daniel Boczniewicz; Darius Phiri; Justin Morgenroth; Dean Meason; Euan Mason. Global Tree Taper Modelling: A Review of Applications, Methods, Functions, and Their Parameters. Forests 2021, 12, 913 .
AMA StyleSerajis Salekin, Cristian Catalán, Daniel Boczniewicz, Darius Phiri, Justin Morgenroth, Dean Meason, Euan Mason. Global Tree Taper Modelling: A Review of Applications, Methods, Functions, and Their Parameters. Forests. 2021; 12 (7):913.
Chicago/Turabian StyleSerajis Salekin; Cristian Catalán; Daniel Boczniewicz; Darius Phiri; Justin Morgenroth; Dean Meason; Euan Mason. 2021. "Global Tree Taper Modelling: A Review of Applications, Methods, Functions, and Their Parameters." Forests 12, no. 7: 913.
The global pandemic emergent from SARS-COV-2 (COVID-19) has continued to cause both health and socio-economic challenges worldwide. However, there is limited information on the factors affecting the dynamics of COVID-19, especially in developing countries, including African countries. In this study, we have focused on understanding the association of COVID-19 cases with environmental and socioeconomic factors in Zambia - a sub-Saharan African country. We used Zambia's district-level COVID-19 data, covering 18 March 2020 (i.e., from first reported cases) to 17 July 2020. Geospatial approaches were used to organize, extract and establish the dataset, while a classification tree (CT) technique was employed to analyze the factors associated with the COVID-19 cases. The analyses were conducted in two stages: (1) the binary analysis of occurrences of COVID-19 (i.e., COVID-19 or No COVID-19), and (2) a risk level analysis which grouped the number of cases into four risk levels (high, moderate, low and very low). The results showed that the distribution of COVID-19 cases in Zambia was significantly influenced by the socioeconomic factors compared to environmental factors. More specifically, the binary model showed that distance to the airport, population density and distance to the town centres were the most combination influential factors, while the risk level analysis indicated that areas with high rates of human immuno-deficient virus (HIV) infection had relatively high chances of having many COVID-19 cases compared to areas with low HIV rates. The districts that are far from major urban establishments and that experience higher temperatures have lower chances of having COVID-19 cases. This study makes two major contributions towards the understanding of COVID-19 dynamics: (1) the methodology presented here can be effectively applied in other areas to understand the association of environmental and socioeconomic factors with COVID-19 cases, and (2), the findings from this study present the empirical evidence of the relationship between COVID-19 cases and their associated environmental and socioeconomic factors. Further studies are needed to understand the relationship of this disease and the associated factors in different cultural settings, seasons and age groups, especially as the COVID-19 cases increase and spread in many countries.
Darius Phiri; Serajis Salekin; Vincent R. Nyirenda; Matamyo Simwanda; Manjula Ranagalage; Yuji Murayama. Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach. Scientific African 2021, 12, e00827 .
AMA StyleDarius Phiri, Serajis Salekin, Vincent R. Nyirenda, Matamyo Simwanda, Manjula Ranagalage, Yuji Murayama. Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach. Scientific African. 2021; 12 ():e00827.
Chicago/Turabian StyleDarius Phiri; Serajis Salekin; Vincent R. Nyirenda; Matamyo Simwanda; Manjula Ranagalage; Yuji Murayama. 2021. "Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach." Scientific African 12, no. : e00827.
Forecasting scenarios of future intra-urban land-use (intra-urban-LU) expansion can help to curb the historically unplanned urbanization in cities in sub-Saharan Africa (SSA) and promote urban sustainability. In this study, we applied the neural network–Markov model to simulate scenarios of future intra-urban-LU expansion in Lusaka city, Zambia. Data derived from remote sensing (RS) and geographic information system (GIS) techniques including urban-LU maps (from 2000, 2005, 2010, and 2015) and selected driver variables, were used to calibrate and validate the model. We then simulated urban-LU expansion for three scenarios (business as usual/status quo, environmental conservation and protection, and strategic urban planning) to explore alternatives for attaining urban sustainability by 2030. The results revealed that Lusaka had experienced rapid urban expansion dominated by informal settlements. Scenario analysis results suggest that a business-as-usual setup is perilous, as it signals an escalating problem of unplanned settlements. The environmental conservation and protection scenario is insufficient, as most of the green spaces and forests have been depleted. The strategic urban planning scenario has the potential for attaining urban sustainability, as it predicts sufficient control of unplanned settlement expansion and protection of green spaces and forests. The study proffers guidance for strategic policy directions and creating a planning vision.
Matamyo Simwanda; Yuji Murayama; Darius Phiri; Vincent Nyirenda; Manjula Ranagalage. Simulating Scenarios of Future Intra-Urban Land-Use Expansion Based on the Neural Network–Markov Model: A Case Study of Lusaka, Zambia. Remote Sensing 2021, 13, 942 .
AMA StyleMatamyo Simwanda, Yuji Murayama, Darius Phiri, Vincent Nyirenda, Manjula Ranagalage. Simulating Scenarios of Future Intra-Urban Land-Use Expansion Based on the Neural Network–Markov Model: A Case Study of Lusaka, Zambia. Remote Sensing. 2021; 13 (5):942.
Chicago/Turabian StyleMatamyo Simwanda; Yuji Murayama; Darius Phiri; Vincent Nyirenda; Manjula Ranagalage. 2021. "Simulating Scenarios of Future Intra-Urban Land-Use Expansion Based on the Neural Network–Markov Model: A Case Study of Lusaka, Zambia." Remote Sensing 13, no. 5: 942.
Rodent assemblages have ecological importance in ecosystem functioning and protected area management. Our study examines the patterns of assemblages of rodents across four habitat types (i.e., Miombo woodland, Acacia woodland, grasslands and farmlands) in the savanna environment. Capture-mark-recapture (CMR) methods were applied for data collection across the Chembe Bird Sanctuary (CBS) landscape. The Non-metric Multi-Dimensional Scaling (NMDS) was used for exploratory data analysis, followed by Analysis of Variance (ANOVA) and Tukey–Kramer’s Honestly Significant Difference (HSD) post-hoc tests. The rodent assemblages in CBS significantly differed between the non-farmlands (i.e., Miombo woodland, Acacia woodland and grasslands) and farmlands. There were: (1) zero rodent diversity in farmlands, dominated completely by a pest species, M. natalensis; and (2) different rodent assemblages in three non-farmland habitat types. We suggest that rodent assemblages should be mediated by conservation planning and multi-stakeholder collaboration beyond the protected area boundaries to contribute to a working CBS landscape positively.
Vincent R. Nyirenda; Ngawo Namukonde; Matamyo Simwanda; Darius Phiri; Yuji Murayama; Manjula Ranagalage; Kaula Milimo. Rodent Assemblages in the Mosaic of Habitat Types in the Zambezian Bioregion. Diversity 2020, 12, 365 .
AMA StyleVincent R. Nyirenda, Ngawo Namukonde, Matamyo Simwanda, Darius Phiri, Yuji Murayama, Manjula Ranagalage, Kaula Milimo. Rodent Assemblages in the Mosaic of Habitat Types in the Zambezian Bioregion. Diversity. 2020; 12 (10):365.
Chicago/Turabian StyleVincent R. Nyirenda; Ngawo Namukonde; Matamyo Simwanda; Darius Phiri; Yuji Murayama; Manjula Ranagalage; Kaula Milimo. 2020. "Rodent Assemblages in the Mosaic of Habitat Types in the Zambezian Bioregion." Diversity 12, no. 10: 365.
Forest-cover change has become an important topic in global biodiversity conservation in recent decades because of the high rates of forest loss in different parts of the world, especially in the tropical region. While human interventions are the major cause, natural disasters also contribute to forest cover changes. During the past decades, several studies have been conducted to address different aspects of forest cover changes (e.g., drivers of deforestation, degradation, interventions) in different parts of the world. In Sri Lanka, increasing rates of forest loss have been recorded during the last 100 years on a regional basis, especially in the dry zone. However, Sri Lanka needs detailed studies that employ contemporary data and robust analytical tools to understand the patterns of forest cover changes and their drivers. The dry zone of Sri Lanka encompasses 59% of the total land area of the country, ergo, the most extensive forest cover. Our study analyzed forest cover dynamics and its drivers between 1992 and 2019. Our specific objectives included (i) producing a forest cover map for 2019, (ii) analyzing the spatiotemporal patterns of forest cover changes from 1992 to 2019, and (iii) determining the main driving forces. Landsat 8 images were used to develop forest-cover maps for 2019, and the rest of the forest cover maps (1992, 1999, and 2010) were obtained from the Forest Department of Sri Lanka. In this study, we found that the dry zone had undergone rapid forest loss (246,958.4 ha) during the past 27 years, which accounts for 8.0% of the net forest cover changes. From 2010 to 2019, the rates of forest loss were high, and this can be associated with the rapid infrastructure development of the country. The findings of this study can be used as a proxy to reform current forest policies and enhance the forest sustainability of the study area.
Manjula Ranagalage; M. H. J. P. Gunarathna; Thilina D. Surasinghe; Dmslb Dissanayake; Matamyo Simwanda; Yuji Murayama; Takehiro Morimoto; Darius Phiri; Vincent R. Nyirenda; K. T. Premakantha; Anura Sathurusinghe. Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka. Forests 2020, 11, 836 .
AMA StyleManjula Ranagalage, M. H. J. P. Gunarathna, Thilina D. Surasinghe, Dmslb Dissanayake, Matamyo Simwanda, Yuji Murayama, Takehiro Morimoto, Darius Phiri, Vincent R. Nyirenda, K. T. Premakantha, Anura Sathurusinghe. Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka. Forests. 2020; 11 (8):836.
Chicago/Turabian StyleManjula Ranagalage; M. H. J. P. Gunarathna; Thilina D. Surasinghe; Dmslb Dissanayake; Matamyo Simwanda; Yuji Murayama; Takehiro Morimoto; Darius Phiri; Vincent R. Nyirenda; K. T. Premakantha; Anura Sathurusinghe. 2020. "Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka." Forests 11, no. 8: 836.
Changes in the urban landscape resulting from rapid urbanisation and climate change have the potential to increase land surface temperature (LST) and the incidence of the urban heat island (UHI). An increase in urban heat directly affects urban livelihoods and systems. This study investigated the spatiotemporal variation of the UHI in the Kurunegala urban area (KUA) of North-Western Province, Sri Lanka. The KUA is one of the most intensively developing economic and administrative capitals in Sri Lanka with an urban system that is facing climate vulnerabilities and challenges of extreme heat conditions. We examined the UHI formation for the period 1996–2019 and its impact on the urban-systems by exploring nature-based solutions (NBS). This study used annual median temperatures based on Landsat data from 1996 to 2019 using the Google Earth Engine (GEE). Various geospatial approaches, including spectral index-based land use/cover mapping (1996, 2009 and 2019), urban-rural gradient zones, UHI profile, statistics and grid-based analysis, were used to analyse the data. The results revealed that the mean LST increased by 5.5 °C between 1996 and 2019 mainly associated with the expansion pattern of impervious surfaces. The mean LST had a positive correlation with impervious surfaces and a negative correlation with the green spaces in all the three time-points. Impacts due to climate change, including positive temperature and negative rainfall anomalies, contributed to the increase in LST. The study recommends interactively applying NBS to addressing the UHI impacts with effective mitigation and adaptation measures for urban sustainability.
Manjula Ranagalage; Sujith S. Ratnayake; Dmslb Dissanayake; Lalit Kumar; Hasula Wickremasinghe; Jagathdeva Vidanagama; Hanna Cho; Susantha Udagedara; Keshav Kumar Jha; Matamyo Simwanda; Darius Phiri; Enc Perera; Priyantha Muthunayake. Spatiotemporal Variation of Urban Heat Islands for Implementing Nature-Based Solutions: A Case Study of Kurunegala, Sri Lanka. ISPRS International Journal of Geo-Information 2020, 9, 461 .
AMA StyleManjula Ranagalage, Sujith S. Ratnayake, Dmslb Dissanayake, Lalit Kumar, Hasula Wickremasinghe, Jagathdeva Vidanagama, Hanna Cho, Susantha Udagedara, Keshav Kumar Jha, Matamyo Simwanda, Darius Phiri, Enc Perera, Priyantha Muthunayake. Spatiotemporal Variation of Urban Heat Islands for Implementing Nature-Based Solutions: A Case Study of Kurunegala, Sri Lanka. ISPRS International Journal of Geo-Information. 2020; 9 (7):461.
Chicago/Turabian StyleManjula Ranagalage; Sujith S. Ratnayake; Dmslb Dissanayake; Lalit Kumar; Hasula Wickremasinghe; Jagathdeva Vidanagama; Hanna Cho; Susantha Udagedara; Keshav Kumar Jha; Matamyo Simwanda; Darius Phiri; Enc Perera; Priyantha Muthunayake. 2020. "Spatiotemporal Variation of Urban Heat Islands for Implementing Nature-Based Solutions: A Case Study of Kurunegala, Sri Lanka." ISPRS International Journal of Geo-Information 9, no. 7: 461.
The advancement in satellite remote sensing technology has revolutionised the approaches to monitoring the Earth’s surface. The development of the Copernicus Programme by the European Space Agency (ESA) and the European Union (EU) has contributed to the effective monitoring of the Earth’s surface by producing the Sentinel-2 multispectral products. Sentinel-2 satellites are the second constellation of the ESA Sentinel missions and carry onboard multispectral scanners. The primary objective of the Sentinel-2 mission is to provide high resolution satellite data for land cover/use monitoring, climate change and disaster monitoring, as well as complementing the other satellite missions such as Landsat. Since the launch of Sentinel-2 multispectral instruments in 2015, there have been many studies on land cover/use classification which use Sentinel-2 images. However, no review studies have been dedicated to the application of ESA Sentinel-2 land cover/use monitoring. Therefore, this review focuses on two aspects: (1) assessing the contribution of ESA Sentinel-2 to land cover/use classification, and (2) exploring the performance of Sentinel-2 data in different applications (e.g., forest, urban area and natural hazard monitoring). The present review shows that Sentinel-2 has a positive impact on land cover/use monitoring, specifically in monitoring of crop, forests, urban areas, and water resources. The contemporary high adoption and application of Sentinel-2 can be attributed to the higher spatial resolution (10 m) than other medium spatial resolution images, the high temporal resolution of 5 days and the availability of the red-edge bands with multiple applications. The ability to integrate Sentinel-2 data with other remotely sensed data, as part of data analysis, improves the overall accuracy (OA) when working with Sentinel-2 images. The free access policy drives the increasing use of Sentinel-2 data, especially in developing countries where financial resources for the acquisition of remotely sensed data are limited. The literature also shows that the use of Sentinel-2 data produces high accuracies (>80%) with machine-learning classifiers such as support vector machine (SVM) and Random forest (RF). However, other classifiers such as maximum likelihood analysis are also common. Although Sentinel-2 offers many opportunities for land cover/use classification, there are challenges which include mismatching with Landsat OLI-8 data, a lack of thermal bands, and the differences in spatial resolution among the bands of Sentinel-2. Sentinel-2 data show promise and have the potential to contribute significantly towards land cover/use monitoring.
Darius Phiri; Matamyo Simwanda; Serajis Salekin; Vincent Nyirenda; Yuji Murayama; Manjula Ranagalage. Sentinel-2 Data for Land Cover/Use Mapping: A Review. Remote Sensing 2020, 12, 2291 .
AMA StyleDarius Phiri, Matamyo Simwanda, Serajis Salekin, Vincent Nyirenda, Yuji Murayama, Manjula Ranagalage. Sentinel-2 Data for Land Cover/Use Mapping: A Review. Remote Sensing. 2020; 12 (14):2291.
Chicago/Turabian StyleDarius Phiri; Matamyo Simwanda; Serajis Salekin; Vincent Nyirenda; Yuji Murayama; Manjula Ranagalage. 2020. "Sentinel-2 Data for Land Cover/Use Mapping: A Review." Remote Sensing 12, no. 14: 2291.
Decision tree (DT) algorithms are important non-parametric tools used for land cover classification. While different DTs have been applied to Landsat land cover classification, their individual classification accuracies and performance have not been compared, especially on their effectiveness to produce accurate thresholds for developing rulesets for object-based land cover classification. Here, the focus was on comparing the performance of five DT algorithms: Tree, C5.0, Rpart, Ipred, and Party. These DT algorithms were used to classify ten land cover classes using Landsat 8 images on the Copperbelt Province of Zambia. Classification was done using object-based image analysis (OBIA) through the development of rulesets with thresholds defined by the DTs. The performance of the DT algorithms was assessed based on: (1) DT accuracy through cross-validation; (2) land cover classification accuracy of thematic maps; and (3) other structure properties such as the sizes of the tree diagrams and variable selection abilities. The results indicate that only the rulesets developed from DT algorithms with simple structures and a minimum number of variables produced high land cover classification accuracies (overall accuracy > 88%). Thus, algorithms such as Tree and Rpart produced higher classification results as compared to C5.0 and Party DT algorithms, which involve many variables in classification. This high accuracy has been attributed to the ability to minimize overfitting and the capacity to handle noise in the data during training by the Tree and Rpart DTs. The study produced new insights on the formal selection of DT algorithms for OBIA ruleset development. Therefore, the Tree and Rpart algorithms could be used for developing rulesets because they produce high land cover classification accuracies and have simple structures. As an avenue of future studies, the performance of DT algorithms can be compared with contemporary machine-learning classifiers (e.g., Random Forest and Support Vector Machine).
Darius Phiri; Matamyo Simwanda; Vincent Nyirenda; Yuji Murayama; Manjula Ranagalage. Decision Tree Algorithms for Developing Rulesets for Object-Based Land Cover Classification. ISPRS International Journal of Geo-Information 2020, 9, 329 .
AMA StyleDarius Phiri, Matamyo Simwanda, Vincent Nyirenda, Yuji Murayama, Manjula Ranagalage. Decision Tree Algorithms for Developing Rulesets for Object-Based Land Cover Classification. ISPRS International Journal of Geo-Information. 2020; 9 (5):329.
Chicago/Turabian StyleDarius Phiri; Matamyo Simwanda; Vincent Nyirenda; Yuji Murayama; Manjula Ranagalage. 2020. "Decision Tree Algorithms for Developing Rulesets for Object-Based Land Cover Classification." ISPRS International Journal of Geo-Information 9, no. 5: 329.
Cyclones are some of the most devastating natural disasters that cause major losses of life and property. A few months after Cyclone Idai swept through Beira, Mozambique between 4 and 20 March 2019. An analysis is presented on the impacts of this disaster by assessing the extent of the floods. This study employed Sentinel-2 imagery and remote sensing techniques including a threshold analysis and an object‑based image analysis (OBIA) approach. Water and non-water land covers were established by using a Modified Normalized Difference Water Index (MNDWI), while the classification approach assessed three land covers. These assessments were done on four dates: (1) 31 January (before), (2) 25 February 20 (before), (3) 12 March (during) and (4) 16 April (after). Accuracies ranging from 74% to 90% were attained. The OBIA approach showed that 61% of the study area was affected by floods, while the threshold approach showed that 55% of the area was flooded. Areas with low elevation and close to the coast were more effected by the floods. After the cyclone, the area under water reduced by more than 20%. The results here could be useful for developing early warning systems, risk assessment, establishing damage and developing natural hazard policies.
Darius Phiri; Matamyo Simwanda; Vincent Nyirenda. Mapping the impacts of cyclone Idai in Mozambique using Sentinel-2 and OBIA approach. South African Geographical Journal 2020, 103, 237 -258.
AMA StyleDarius Phiri, Matamyo Simwanda, Vincent Nyirenda. Mapping the impacts of cyclone Idai in Mozambique using Sentinel-2 and OBIA approach. South African Geographical Journal. 2020; 103 (2):237-258.
Chicago/Turabian StyleDarius Phiri; Matamyo Simwanda; Vincent Nyirenda. 2020. "Mapping the impacts of cyclone Idai in Mozambique using Sentinel-2 and OBIA approach." South African Geographical Journal 103, no. 2: 237-258.
Forest products, wood and non-wood, remain vital among smallholder households in Zambia with charcoal being the most sought after product. This has led to increased exploitation of forest trees to meet the needs for fuel wood, among others. However, Jatropha curcas plant has been identified as a potential fuel source. In the early 2000s, profit-making organizations encouraged smallholder households to grow Jatropha for use as an alternative fuel source. This paper reports on a study conducted in Solwezi between 2011 and 2014 to evaluate the impact of Jatropha cultivation for biofuel production. A sample of 100 small-scale farmers involved in Jatropha cultivation and key informants were interviewed to evaluate the impact of growing Jatropha at the small-scale level. Results show that farmers lost out on time; income from sale of edible non-wood forest products; and experienced reduction in maize (Zea mays) and bean (Phaseolus vulgaris) production, worsening household economic conditions. Farmers attributed this loss to unclear policy alignment on biofuel production by government. We therefore recommend that project implementation should involve interactions of all legislative bodies and any other concerned stakeholders. There is also a need to promote the value chain, from production to marketing, which focuses on minimizing detrimental effects on the livelihood of small-scale farmers.
Chester Kalinda; Ziyaye Moses; Chama Lackson; Lwali A. Chisala; Zulu Donald; Phiri Darius; Chisha-Kasumu Exildah. Economic Impact and Challenges of Jatropha curcas L. Projects in North-Western Province, Zambia: A Case of Solwezi District. Sustainability 2015, 7, 9907 -9923.
AMA StyleChester Kalinda, Ziyaye Moses, Chama Lackson, Lwali A. Chisala, Zulu Donald, Phiri Darius, Chisha-Kasumu Exildah. Economic Impact and Challenges of Jatropha curcas L. Projects in North-Western Province, Zambia: A Case of Solwezi District. Sustainability. 2015; 7 (8):9907-9923.
Chicago/Turabian StyleChester Kalinda; Ziyaye Moses; Chama Lackson; Lwali A. Chisala; Zulu Donald; Phiri Darius; Chisha-Kasumu Exildah. 2015. "Economic Impact and Challenges of Jatropha curcas L. Projects in North-Western Province, Zambia: A Case of Solwezi District." Sustainability 7, no. 8: 9907-9923.