Your search found 12 records
1 Cai, Xueliang; Haile, Alemseged Tamiru; Magidi, J.; Mapedza, Everisto; Nhamo, Luxon. 2017. Living with floods – household perception and satellite observations in the Barotse floodplain, Zambia. Physics and Chemistry of the Earth, 100:278-286. [doi: https://doi.org/10.1016/j.pce.2016.10.011]
Natural disasters ; Floodplains ; Hydrology ; Indigenous knowledge ; Remote sensing ; Risk prevention ; Households ; Living standards ; Satellite observation ; Satellite imagery ; Farmland / Zambia / Barotseland
(Location: IWMI HQ Call no: e-copy only Record No: H047877)
The Barotse Floodplain, a designated Ramsar site, is home to thousands of indigenous people along with an extensive wetland ecosystem and food production system. Increasingly it is also a popular tourist destination with its annual Kuomboka festival which celebrates the relocation of the king and the Lozi people to higher ground before the onset of the ood season. This paper presents an integrated approach which cross validates and combines the oodplain residents' perceptions about recent oods with information on ood inundation levels derived from satellite observations. Local residents' surveys were conducted to assess farmers’ perception on the ooding patterns and the impact on their livelihoods. Further, a series of ood inundation maps from 1989 to 2014 generated from remotely sensed Landsat imagery were used to assess the recent patterns of oods. Results show that the oodplain has a population of 33 thousand living in 10,849 small permeant or temporary buildings with a total cropland area of 4976 ha. The oodplain hydrologyand ooding patterns have changed, con rmed by both surveys and satellite image analysis, due to catchment development and changing climate. The average annual inundated areas have increased from about 316 thousand ha in 1989e1998 to 488 thousand ha in 2005 e2014. As a result the inundated cropland and houses increased from 9% to 6% in 1989 to 73% and 47% in 2014, respectively. The timing of the oods has also changed with both delaying and early onset happening more frequently. These changes cause increasing dif culties in ood forecast and preparation using indigenous knowledge, therefore creating greater damages to crops, livestock, and houses. Current oodplain management system is inadequate and new interventions are needed to help manage the oods at a systematic manner.
2 Cai, Xueliang; Magidi, J.; Nhamo, Luxon; van Koppen, Barbara. 2017. Mapping irrigated areas in the Limpopo Province, South Africa. Colombo, Sri Lanka: International Water Management Institute (IWMI). 37p. (IWMI Working Paper 172) [doi: https://doi.org/10.5337/2017.205]
Irrigated land ; Agricultural land ; Cultivated land ; Agricultural development ; Rainfed farming ; Land cover ; Remote sensing ; Satellite imagery ; Mapping ; Sustainable development ; Water resources ; Water security ; Surface water ; Groundwater irrigation ; Seasonal cropping ; Winter crops ; Food production ; Developing countries ; Irrigation operation ; Smallholders ; Surveys ; Capacity building / South Africa / Limpopo Province
(Location: IWMI HQ Call no: IWMI Record No: H048084)
(2 MB)
This report summarizes the findings of a collaborative effort to map and assess irrigated areas in the Limpopo Province, South Africa. The study was conducted by the International Water Management Institute (IWMI) in collaboration with the Department of Agriculture, Forestry and Fisheries (DAFF) and the Limpopo Department of Agriculture and Rural Development (LDARD), as part of the DAFF-supported ‘Revitalization of irrigation in South Africa’ project. Based on a combination of Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, previous irrigated area mapping exercises carried out by DAFF and three-field ground truthing (GT) surveys, a total of 1.6 million hectares (Mha) of cropland were identified, with 262,000 ha actually irrigated in the 2015 winter season. The study also found that only 29% of all land equipped with center pivots was actually irrigated.
3 Nhamo, Luxon; Magidi, J.; Dickens, Chris. 2017. Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing. Water SA, 43(4):543-552. [doi: https://doi.org/10.4314/wsa.v43i4.02]
Wetlands ; Flooding ; Remote sensing ; GIS ; Spatial planning ; Multispectral imagery ; Satellite imagery ; Sustainable development ; Ecosystems ; Dam construction ; Catchment areas / South Africa / Mpumalanga Province / Witbank Dam
(Location: IWMI HQ Call no: e-copy only Record No: H048390)
https://www.ajol.info/index.php/wsa/article/download/162560/152061
https://vlibrary.iwmi.org/pdf/H048390.pdf
https://vlibrary.iwmi.org/pdf/H048390.pdf
(2.58 MB)
Wetlands can only be well managed if their spatial location and extent are accurately documented, which presents a problem as wetland type and morphology are highly variable. Current efforts to delineate wetland extent are varied, resulting in a host of inconsistent and incomparable inventories. This study, done in the Witbank Dam Catchment in Mpumalanga Province of South Africa, explores a remote-sensing technique to delineate wetland extent and assesses the seasonal variations of the inundated area. The objective was to monitor the spatio-temporal changes of wetlands over time through remote sensing and GIS for effective wetland management. Multispectral satellite images, together with a digital elevation model (DEM), were used to delineate wetland extent. The seasonal variations of the inundated area were assessed through an analysis of monthly water indices derived from the normalised difference water index (NDWI). Landsat images and DEM were used to delineate wetland extent and MODIS images were used to assess seasonal variation of the inundated area. A time-series trend analysis on the delineated wetlands shows a declining tendency from 2000 to 2015, which could worsen in the coming few years if no remedial action is taken. Wetland area declined by 19% in the study area over the period under review. An analysis of NDWI indices on the wetland area showed that wetland inundated area is highly variable, exhibiting an increasing variability over time. An overlay of wetland area on cultivated land showed that 21% of the wetland area is subjected to cultivation which is a major contributing factor to wetland degradation.
4 Nhamo, Luxon; van Dijk, R.; Magidi, J.; Wiberg, David; Tshikolomo, K. 2018. Improving the accuracy of remotely sensed irrigated areas using post-classification enhancement through UAV [Unmanned Aerial Vehicle] capability. Remote Sensing, 10(5):1-12. (Special issue: Remote Sensing for Crop Water Management). [doi: https://doi.org/10.3390/rs10050712]
Irrigated sites ; Remote sensing ; Unmanned aerial vehicles ; Land use mapping ; Land cover mapping ; Satellite imagery ; Landsat ; Farmland ; Vegetation index ; Crops / South Africa / Limpopo Province / Venda / Gazankulu
(Location: IWMI HQ Call no: e-copy only Record No: H048752)
(2.23 MB) (2.23 MB)
Although advances in remote sensing have enhanced mapping and monitoring of irrigated areas, producing accurate cropping information through satellite image classification remains elusive due to the complexity of landscapes, changes in reflectance of different land-covers, the remote sensing data selected, and image processing methods used, among others. This study extracted agricultural fields in the former homelands of Venda and Gazankulu in Limpopo Province, South Africa. Landsat 8 imageries for 2015 were used, applying the maximum likelihood supervised classifier to delineate the agricultural fields. The normalized difference vegetation index (NDVI) applied on Landsat imageries on the mapped fields during the dry season (July to August) was used to identify irrigated areas, because years of satellite data analysis suggest that healthy crop conditions during dry seasons are only possible with irrigation. Ground truth points totaling 137 were collected during fieldwork for pre-processing and accuracy assessment. An accuracy of 96% was achieved on the mapped agricultural fields, yet the irrigated area map produced an initial accuracy of only 71%. This study explains and improves the 29% error margin from the irrigated areas. Accuracy was enhanced through post-classification correction (PCC) using 74 post-classification points randomly selected from the 2015 irrigated area map. High resolution aerial photographs of the 74 sample fields were acquired by an unmanned aerial vehicle (UAV) to give a clearer picture of the irrigated fields. The analysis shows that mapped irrigated fields that presented anomalies included abandoned croplands that had green invasive alien species or abandoned fruit plantations that had high NDVI values. The PCC analysis improved irrigated area mapping accuracy from 71% to 95%.
5 Mpandeli, S.; Nhamo, Luxon; Moeletsi, M.; Masupha, T.; Magidi, J.; Tshikolomo, K.; Liphadzi, S.; Naidoo, D.; Mabhaudhi, T. 2019. Assessing climate change and adaptive capacity at local scale using observed and remotely sensed data. Weather and Climate Extremes, 26:100240. [doi: https://doi.org/10.1016/j.wace.2019.100240]
Climate change adaptation ; Assessment ; Remote sensing ; Drought ; Rain ; Temperature ; Water stress ; Resilience ; Risk reduction ; Strategies ; Smallholders ; Farmers ; Agricultural production ; Heat stress ; Vegetation index / South Africa / Limpopo / Capricorn
(Location: IWMI HQ Call no: e-copy only Record No: H049413)
https://www.sciencedirect.com/science/article/pii/S2212094719301380/pdfft?md5=07c6303aa103fe96c44be00ac162f087&pid=1-s2.0-S2212094719301380-main.pdf
https://vlibrary.iwmi.org/pdf/H049413.pdf
https://vlibrary.iwmi.org/pdf/H049413.pdf
(4.02 MB) (4.02 MB)
Climate variability and change impacts are manifesting through declining rainfall totals and increasing frequency and intensity of droughts, floods and heatwaves. These environmental changes are affecting mostly rural populations in developing countries due to low adaptive capacity and high reliance on natural systems for their livelihoods. While broad adaptation strategies exist, there is need to contextualise them to local scale. This paper assessed rainfall, temperature and water stress trends over time in Capricorn District, South Africa, using Standardized Precipitation Index, Thermal Heat Index, and Normalised Difference Vegetation Index (NDVI) as a proxy of water stress. Observed rainfall and temperature data from 1960 to 2015 was used to assess climatic variations, and NDVI was used to assess water stress from 2000 to 2019. Results show a marked increase in drought frequency and intensity, decreasing rainfall totals accompanied by increasing temperatures, and increasing water stress during the summer season. Long-term climatic changes are a basis to develop tailor-made adaptation strategies. Eighty-one percent of the cropped area in Capricorn District is rainfed and under smallholder farming, exposing the district to climate change risks. As the intensity of climate change varies both in space and time, adaptation strategies also vary depending on exposure and intensity. A combination of observed and remotely sensed climatic data is vital in developing tailor-made adaptation strategies.
6 Nhamo, Luxon; Ebrahim, Girma Yimer; Mabhaudhi, T.; Mpandeli, S.; Magombeyi, Manuel; Chitakira, M.; Magidi, J.; Sibanda, M. 2020. An assessment of groundwater use in irrigated agriculture using multi-spectral remote sensing. Physics and Chemistry of the Earth, 115:102810. [doi: https://doi.org/10.1016/j.pce.2019.102810]
Groundwater assessment ; Crop water use ; Irrigated farming ; Remote sensing ; Climate change ; Resilience ; Water management ; Water productivity ; Evapotranspiration ; Estimation ; Irrigated land ; Satellite imagery ; Dry season / South Africa / Limpopo / Venda-Gazankulu
(Location: IWMI HQ Call no: e-copy only Record No: H049420)
(2.23 MB)
Declining water resources in dry regions requires sustainable groundwater management as trends indicate increasing groundwater use, but without accountability. The sustainability of groundwater is uncertain, as little is known about its extent and availability, a challenge that requires a quantitative assessment of its current use. This study assessed groundwater use for irrigated agriculture in the Venda-Gazankulu area of Limpopo Province in South Africa using crop evapotranspiration and irrigated crop area derived from the normalised difference vegetation index (NDVI). Evapotranspiration data was derived from the Water Productivity through Open access of Remotely sensed Actual Evapotranspiration and Interception (WaPOR) dataset (250 m resolution), and irrigated areas were characterised using dry season NDVI data derived from Landsat 8. Field surveys were conducted for four years to assess accuracy and for post-classification correction. Daily ET for the dry season (May to September) was developed from the actual ET for the irrigated areas. The irrigated areas were overlaid on the ET map to calculate ET for only irrigated land parcels. Groundwater use during the 2015 dry period was 3627.49 billion m3 and the irrigated area during the same period was 26% of cultivated land. About 82 435 ha of cultivated area was irrigated using 44 million m3 /ha of water, compared to 186.93 million m3 /ha on a rainfed area of 237 847 ha. Groundwater management is essential for enhancing resilience in arid regions in the advent of water scarcity.
7 Nhamo, Luxon; Magidi, J.; Nyamugama, A.; Clulow, A. D.; Sibanda, M.; Chimonyo, V. G. P.; Mabhaudhi, T. 2020. Prospects of improving agricultural and water productivity through unmanned aerial vehicles. Agriculture, 10(7):256. [doi: https://doi.org/10.3390/agriculture10070256]
Agricultural productivity ; Water productivity ; Unmanned aerial vehicles ; Water management ; Plant health ; Crop yield ; Monitoring ; Vegetation index ; Remote sensing ; Evapotranspiration ; Water stress ; Irrigation scheduling ; Mapping ; Smallholders ; Farmers ; Models ; Disaster risk reduction ; Resilience ; Satellite imagery ; Cost benefit analysis
(Location: IWMI HQ Call no: e-copy only Record No: H049892)
(1.05 MB) (1.05 MB)
Unmanned Aerial Vehicles (UAVs) are an alternative to costly and time-consuming traditional methods to improve agricultural water management and crop productivity through the acquisition, processing, and analyses of high-resolution spatial and temporal crop data at field scale. UAVs mounted with multispectral and thermal cameras facilitate the monitoring of crops throughout the crop growing cycle, allowing for timely detection and intervention in case of any anomalies. The use of UAVs in smallholder agriculture is poised to ensure food security at household level and improve agricultural water management in developing countries. This review synthesises the use of UAVs in smallholder agriculture in the smallholder agriculture sector in developing countries. The review highlights the role of UAV derived normalised difference vegetation index (NDVI) in assessing crop health, evapotranspiration, water stress and disaster risk reduction. The focus is to provide more accurate statistics on irrigated areas, crop water requirements and to improve water productivity and crop yield. UAVs facilitate access to agro-meteorological information at field scale and in near real-time, important information for irrigation scheduling and other on-field decision-making. The technology improves smallholder agriculture by facilitating access to information on crop biophysical parameters in near real-time for improved preparedness and operational decision-making. Coupled with accurate meteorological data, the technology allows for precise estimations of crop water requirements and crop evapotranspiration at high spatial resolution. Timely access to crop health information helps inform operational decisions at the farm level, and thus, enhancing rural livelihoods and wellbeing.
8 Magidi, J.; van Koppen, Barbara; Nhamo, L.; Mpandeli, S.; Slotow, R.; Mabhaudhi, Tafadzwanashe. 2021. Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems. Water, 13(24):3627. [doi: https://doi.org/10.3390/w13243627]
Smallholders ; Farming systems ; Irrigated farming ; Water policies ; Food policies ; Food security ; Water security ; Spatial distribution ; Rainfed farming ; Irrigated land ; Cultivated land ; Catchment areas ; Crop production ; Farmers ; Sustainable development ; Datasets ; Normalized difference vegetation index / South Africa / Usuthu Sub-Catchment / Crocodile Sub-Catchment / Sabie Sub-Catchment / Komati Sub-Catchment
(Location: IWMI HQ Call no: e-copy only Record No: H050853)
(5.03 MB) (5.03 MB)
Accurate information on irrigated areas’ spatial distribution and extent are crucial in enhancing agricultural water productivity, water resources management, and formulating strategic policies that enhance water and food security and ecologically sustainable development. However, data are typically limited for smallholder irrigated areas, which is key to achieving social equity and equal distribution of financial resources. This study addressed this gap by delineating disaggregated smallholder and commercial irrigated areas through the random forest algorithm, a non-parametric machine learning classifier. Location within or outside former apartheid “homelands” was taken as a proxy for smallholder, and commercial irrigation. Being in a medium rainfall area, the huge irrigation potential of the Inkomati-Usuthu Water Management Area (UWMA) is already well developed for commercial crop production outside former homelands. However, information about the spatial distribution and extent of irrigated areas within former homelands, which is largely informal, was missing. Therefore, we first classified cultivated lands in 2019 and 2020 as a baseline, from where the Normalised Difference Vegetation Index (NDVI) was used to distinguish irrigated from rainfed, focusing on the dry winter period when crops are predominately irrigated. The mapping accuracy of 84.9% improved the efficacy in defining the actual spatial extent of current irrigated areas at both smallholder and commercial spatial scales. The proportion of irrigated areas was high for both commercial (92.5%) and smallholder (96.2%) irrigation. Moreover, smallholder irrigation increased by over 19% between 2019 and 2020, compared to slightly over 7% in the commercial sector. Such information is critical for policy formulation regarding equitable and inclusive water allocation, irrigation expansion, land reform, and food and water security in smallholder farming systems.
9 Chitakira, M.; Nhamo, L.; Torquebiau, E.; Magidi, J.; Ferguson, W.; Mpandeli, S.; Mearns, K.; Mabhaudhi, Tafadzwanashe. 2022. Opportunities to improve eco-agriculture through transboundary governance in transfrontier conservation areas. Diversity, 14(6):461. (Special issue: The Human Dimension of Biodiversity Protection) [doi: https://doi.org/10.3390/d14060461]
Eco-agriculture ; Conservation areas ; Governance ; Biodiversity conservation ; Ecosystems ; Sustainable Development Goals ; Resource conservation ; Poverty alleviation ; Sustainable livelihoods ; Policies ; Legislation ; Landscape approaches ; Local communities / Mozambique / Eswatini / South Africa / Lubombo Transfrontier Conservation Area / Usuthu-Tembe-Futi Transfrontier Conservation Area
(Location: IWMI HQ Call no: e-copy only Record No: H051227)
https://www.mdpi.com/1424-2818/14/6/461/pdf?version=1654685762
https://vlibrary.iwmi.org/pdf/H051227.pdf
https://vlibrary.iwmi.org/pdf/H051227.pdf
(0.89 MB) (906 KB)
Transfrontier Conservation Areas (TFCAs) are critical biodiversity areas for the conservation and sustainable use of biological and cultural resources while promoting regional peace, cooperation, and socio-economic development. Sustainable management of TFCAs is dependent on the availability of an eco-agriculture framework that promotes integrated management of conservation mosaics in terms of food production, environmental protection or the conservation of natural resources, and improved human livelihoods. As a developmental framework, eco-agriculture is significantly influenced by existing legal and governance structures at all levels; this study assessed the impact of existing legal and governance frameworks on eco-agriculture implementation in the Lubombo TFCA that cuts across the borders between Mozambique, Eswatini, and South Africa. The assessment used a mixed research method, including a document review, key informant interviews, and focus group discussions. Although the three countries have no eco-agriculture policies, biodiversity practices are directly or indirectly affected by some policies related to environmental protection, agriculture improvement, and rural development. The assessment found that South Africa has the most comprehensive policies related to eco-agriculture; Mozambican policies mainly focus on equity and involvement of disadvantaged social groups, while Eswatini is conspicuous for explicitly making it the responsibility of each citizen to protect and safeguard the environment. The protection of conservation areas is critical to preserving natural habitats and ensuring the continued provision of ecosystem services. The lack of transboundary governance structures results in the Lubombo TFCA existing as a treaty on paper, as there are no clear processes for transboundary cooperation and collaboration.
10 Mabhaudhi, Tafadzwanashe; Haileslassie, Amare; Magidi, J.; Nhamo, L. 2022. Irrigation suitability mapping examples from Zimbabwe, Zambia, Malawi and Kenya. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Diversification in East and Southern Africa. 52p.
Irrigation management ; Land suitability ; Mapping ; Planning ; Soil texture ; Land use ; Land cover ; Rain ; Surface water ; Groundwater ; Slope ; Diversification ; Socioeconomic aspects / Zimbabwe / Zambia / Malawi / Kenya / Balaka / Nkhotakota / Monze / Chipata / Nakuru / Makueni / Masvingo / Makonde / Murehwa
(Location: IWMI HQ Call no: e-copy only Record No: H051676)
(3.07 MB)
The irrigation suitability classification was achieved by using physical factors that include slope, rainfall, landuse, closeness to waterbodies (surface and groundwater) and soil characteristics for selected districts in Zimbabwe, Zambia, Malawi, and Kenya, some of the UU target countries. As cereals form the main food basket of the selected countries, and cereals are not tolerant to saline conditions, the report also provides maps showing high soil salinity areas of Makueni and Nakuru of Kenya, where soils are highly saline. However, soil salinity is insignificant in the other study districts and therefore not mapped. This report provides (a) a conceptual framework and detailed methodology for irrigation suitability mapping, including details of identified boundary maps and geospatial data, and (b) a synthesis model and maps on irrigation suitability mapping for the selected districts in the four target countries.
11 Sibanda, M.; Buthelezi, S.; Mutanga, O.; Odindi, J.; Clulow, A. D.; Chimonyo, V. G. P.; Gokool, S.; Naiken, V.; Magidi, J.; Mabhaudhi, Tafadzwanashe. 2023. Exploring the prospects of UAV-remotely sensed data in estimating productivity of maize crops in typical smallholder farms of Southern Africa. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, X-1/W1-2023:1143-1150. (ISPRS Geospatial Week 2023, Cairo, Egypt, 2-7 September 2023) [doi: https://doi.org/10.5194/isprs-annals-X-1-W1-2023-1143-2023]
Agricultural productivity ; Small farms ; Smallholders ; Maize ; Yield forecasting ; Models ; Remote sensing ; Unmanned aerial vehicles ; Vegetation index / Southern Africa / South Africa / KwaZulu-Natal
(Location: IWMI HQ Call no: e-copy only Record No: H052490)
https://isprs-annals.copernicus.org/articles/X-1-W1-2023/1143/2023/isprs-annals-X-1-W1-2023-1143-2023.pdf
https://vlibrary.iwmi.org/pdf/H052490.pdf
https://vlibrary.iwmi.org/pdf/H052490.pdf
(1.59 MB) (1.59 MB)
This study estimated maize grain biomass, and grain biomass as a proportion of the absolute maize plant biomass using UAV-derived multispectral data. Results showed that UAV-derived data could accurately predict yield with R2 ranging from 0.80 - 0.95, RMSE ranging from 0.03 - 0.94 kg/m2 and RRMSE ranging from 2.21% - 39.91% based on the spectral datasets combined. Results of this study further revealed that the VT-R1 (56-63 days after emergence) vegetative growth stage was the most optimal stage for the early prediction of maize grain yield (R2 = 0.85, RMSE = 0.1, RRMSE = 5.08%) and proportional yield (R2 = 0.92, RMSE = 0.06, RRMSE = 17.56%), with the Normalized Difference Vegetation Index (NDVI), Enhanced Normalized Difference Vegetation Index (ENDVI), Soil Adjusted Vegetation Index (SAVI) and the red edge band being the most optimal prediction variables. The grain yield models produced more accurate results in estimating maize yield when compared to the biomass and proportional yield models. The results demonstrate the value of UAV-derived data in predicting maize yield on smallholder farms – a previously challenging task with coarse spatial resolution satellite sensors.
12 Magidi, J.; Nhamo, L.; Kurwakumire, E.; Gumindoga, W.; Mpandeli, S.; Liphadzi, S.; Mabhaudhi, Tafadzwanashe. 2024. Catalysing cleaner production systems: benchmarking with the COVID-19 lockdowns in South Africa. In Nhamo, L.; Mpandeli, S.; Liphadzi, S.; Mabhaudhi, Tafadzwanashe. (Eds.). Circular and transformative economy: advances towards sustainable socio-economic transformation. Boca Raton, FL, USA: CRC Press. pp.242-259. (Africa Circular Economy Series) [doi: https://doi.org/10.1201/9781003327615-13]
(Location: IWMI HQ Call no: e-copy only Record No: H052580)
https://www.taylorfrancis.com/chapters/oa-edit/10.1201/9781003327615-13/catalysing-cleaner-production-systems-james-magidi-luxon-nhamo-edward-kurwakumire-webster-gumindoga-sylvester-mpandeli-stanley-liphadzi-tafadzwanashe-mabhaudhi
https://vlibrary.iwmi.org/pdf/H052580.pdf
https://vlibrary.iwmi.org/pdf/H052580.pdf
(1.45 MB) (1.45 MB)
Industrial and vehicular emissions are among the major contributors to greenhouse gas (GHG) atmospheric concentration, causing ozone depletion, climate change, and health risks. Reducing air pollution to permissible levels fosters human and environmental health through reduced radiation, stabilised temperatures, and improved air quality. This chapter quantifies the spatio-temporal atmospheric pollution in South Africa using remotely sensed satellite data acquired between April 2019 and April 2020, just before and during the coronavirus disease 2019 (COVID-19) pandemic lockdown. Remotely sensed data are essential for quantifying and monitoring air quality over time by assessing the change in pollution indicators such as fine particulate matter (PM2.5) and nitrogen dioxide (NO2) content. An analysis of results reveals that NO2 levels in South Africa reduced by 20.5% during the COVID-19 lockdown period compared to normal economic activity. The findings were used to develop a framework to guide policy and support decision-making to formulate coherent strategies for reducing pollution and alignment towards a low-carbon economy. Developing controlling and monitoring systems that capture episodic pollution events and enhance cleaner production mechanisms is critical for ensuring low carbon emissions and reducing environmental and human health risks. Although most NO2 emissions are generated in urban environments, the effects are felt far beyond, with detrimental effects on the environment and human health.
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