Your search found 17 records
1 Johnson, R. M.; Barson, M. M. 1990. An assessment of the use of remote sensing techniques in land degradation studies. Canberra, Australia: Department of Primary Industries and Energy. Bureau of Rural Resources. viii, 64p. (Bureau of Rural Resources bulletin no.5)
Remote sensing ; Techniques ; Sensors ; Land degradation ; Land cover ; Surveys ; Indicators ; Erosion ; Soils ; Mapping ; Salinity ; Vegetation / Australia
(Location: IWMI-HQ Call no: 333.73 G000 JOH Record No: H06460)
2 Melesse, A. M.; Weng, Q.; Thenkabail, Prasad S.; Senay, G. B. 2007. Remote sensing sensors and applications in environmental resources mapping and modelling. Sensors, 7:3209-3241.
Remote sensing ; Sensors ; Imagery ; Models ; Environmental effects ; Drought ; Soil water ; Mapping ; Hydrology ; Forecasting ; Early warning systems
(Location: IWMI HQ Call no: IWMI 621.3678 G000 MEL Record No: H040633)
The history of remote sensing and development of different sensors for environmental and natural resources mapping and data acquisition is reviewed and reported. Application examples in urban studies, hydrological modeling such as land- cover and floodplain mapping, fractional vegetation cover and impervious surface area mapping, surface energy flux and micro-topography correlation studies is discussed. The review also discusses the use of remotely sensed-based rainfall and potential evapotranspiration for estimating crop water requirement satisfaction index and hence provides early warning information for growers. The review is not an exhausted application of the remote sensing technique rather summary of some important applications in environmental studies and modeling.
3 Diyawadana, D. M. N.; Alahakoon, P. M. K. 2006. A locally constructed seismic wave detector for groundwater explorations. In Dayawansa, N. D. K. (Ed.). Water resources research in Sri Lanka: symposium proceedings of the Water Professional’s Day 2006, Postgraduate Institute of Agriculture, University of Peradeniya, Sri Lanka, 1 October 2006. Peradeniya, Sri Lanka: University of Peradeniya. Postgraduate Institute of Agriculture (PGIA). pp.25-39.
(Location: IWMI HQ Call no: 631.7 G744 DAY Record No: H040722)
4 Vuran, M. C. 2010. Wireless underground sensor networks: a new perspective for automated water management. In University of Nebraska, Lincoln Office of Research and Economic Development. Proceedings of the 2010 Water for Food Conference, Lincoln, Nebraska, 2-5 May 2010. Lincoln, NE, USA: University of Nebraska. pp.107-108.
(Location: IWMI HQ Call no: 631.7 G000 UNI Record No: H043823)
http://waterforfood.nebraska.edu/docs/wff2010_fullversion.pdf
https://vlibrary.iwmi.org/pdf/H043823.pdf
https://vlibrary.iwmi.org/pdf/H043823.pdf
(0.18 MB) (14.87MB)
5 Marsalek, J.; Stancalie, G.; Balint, G. (Eds.) 2006. Transboundary floods: reducing risks through flood management. Dordrecht, Netherlands: Springer. 336p. (NATO Science Series IV - Earth and Environmental Sciences, vol. 72)
Flood control ; Forecasting ; Disasters ; Risks ; International waters ; River basins ; Remote sensing ; GIS ; Discharges ; Hydrometeorology ; Hydrology ; Telemetry ; Sensors ; Land use mapping ; Models ; Weather forecasting ; Rainfall-runoff relationships ; Urban areas ; History ; Decision making ; Dykes ; Disaster preparedness ; Reservoirs ; International cooperation / Czech Republic / Azerbaijan / Romania / Hungary / Koros River Basin / Upper Tisza Region / Crisul Alb River Basin / Crisul Negru River Basin / Hron River Basin / Crisul Repede River Basin
(Location: IWMI HQ Call no: 551.489 G000 MAR Record No: H043960)
(0.13 MB)
6 Thenkabail, P. S.; Lyon, J. G.; Huete, A. (Eds.) 2012. Hyperspectral remote sensing of vegetation. Boca Raton, FL, USA: CRC Press. 705p.
Remote sensing ; Vegetation ; Indicators ; Multispectral imagery ; Satellite observation ; Satellite imagery ; Image analysis ; Data processing ; Data analysis ; Algorithms ; Models ; Sensors ; Water use ; Agriculture ; Crop management ; Cereal crops ; Cotton ; Botany ; Tissue analysis ; Nitrogen content ; Moisture content ; Plant diseases ; Pastures ; Indicator plants ; Species ; Canopy ; Forest management ; Tropical forests ; Wetlands ; Ecosystems ; Soil properties ; Land cover ; Reflectance
(Location: IWMI HQ Call no: 621.3678 G000 THE Record No: H044548)
(0.54 MB)
7 Ahmad, Z.; Asad, E. U.; Muhammad, A.; Ahmad, Waqas; Anwar, Arif. 2013. Development of a low-power smart water meter for discharges in Indus Basin irrigation networks. In Shaikh, F. K.; Chowdhry, B. S.; Ammari, H. M.; Uqaili, M. A.; Shah, A. (Eds.). Wireless sensor networks for developing countries. Revised selected papers of the 1st International Symposium on Wireless Sensor Networks for Developing Countries (WSN4DC) 2013, Jamshoro, Pakistan, 24-26 April 2013. New York, NY, USA: Springer. pp.1-6. (Communications in Computer and Information Science 366)
River basins ; Hydrometry ; Sensors ; Water management ; Irrigation development / Pakistan / Indus Basin
(Location: IWMI HQ Call no: e-copy only Record No: H046217)
(2.84 MB)
To improve the sampling frequency of water diversion to distributary canals and to improve equity of distribution and data handling we have developed a smart electronic water meter based on ultrasonic sensors and GPRS modem to frequently record and transmit the water diversion data to a centralized server. The server processes the data to extract useful information for example seasonal cumulative water deliveries and discharge time series. The Wireless Sensor Node (WSN) inspired design is extremely low-power, field deployable and scalable with respect to cost and numbers. This paper, reports the first steps towards practical realization of a smart water grid in the Indus river basin, conceptualized by the authors in previous theoretical studies.
8 Stirzaker, R.; Mbakwe, I.; Mziray, N. R. 2017. A soil water and solute learning system for small-scale irrigators in Africa. International Journal of Water Resources Development, 33(5):788-803. (Special issue: The Productivity and Profitability of Small Scale Communal Irrigation Systems in South-eastern Africa). [doi: https://doi.org/10.1080/07900627.2017.1320981]
Irrigation schemes ; Small scale systems ; Soil water ; Experiential learning ; Equipment ; Soil moisture ; Soil salinity ; Sensors ; Colour patterns ; Social participation ; Farmers ; Water conservation ; Irrigation scheduling ; Crops ; Constraints / Africa South of Sahara / Zimbabwe / Mozambique / Tanzania / Kiwere Irrigation Scheme / Silalatshani Irrigation Scheme / Mkoba Irrigation Scheme / Boane Irrigation Scheme / Khanimambo Irrigation Scheme
(Location: IWMI HQ Call no: e-copy only Record No: H048144)
http://www.tandfonline.com/doi/abs/10.1080/07900627.2017.1320981?needAccess=true#aHR0cDovL3d3dy50YW5kZm9ubGluZS5jb20vZG9pL3BkZi8xMC4xMDgwLzA3OTAwNjI3LjIwMTcuMTMyMDk4MT9uZWVkQWNjZXNzPXRydWVAQEAw
https://vlibrary.iwmi.org/pdf/H048144.pdf
https://vlibrary.iwmi.org/pdf/H048144.pdf
(1.65 MB) (1.65 MB)
Better yields of high-value crops are necessary for a profitable irrigation industry in sub-Saharan Africa. We introduced two simple tools, the Chameleon soil moisture sensor and the FullStop wetting front detector, which represent soil water, nitrate and salt levels in the soil by displaying different colours. These tools form the basis of an experiential learning system for small-scale irrigators. We found that farmers quickly learned from the tools and changed their management within a short time. The cost of implementing a learning system would be a small fraction of that of building or revitalizing irrigation schemes.
9 Thomas, E.; Andres, L. A.; Borja-Vega, C.; Sturzenegger, G. (Eds.) 2018. Innovations in WASH [Water, Sanitation and Hygiene] impact measures: water and sanitation measurement technologies and practices to inform the sustainable development goals. Washington, DC, USA: World Bank. 123p. (Directions in Development - Infrastructure) [doi: https://doi.org/10.1596/978-1-4648-1197-5]
Water quality ; Sanitation ; Technological changes ; Innovation ; Sustainable Development Goals ; Drinking water ; Quality assurance ; Measurement ; Sensors ; Guidelines ; Water supply ; Wastewater treatment ; Water use ; Hygiene ; Monitoring ; Indicators ; Public health ; Health programmes ; Households ; Behaviour ; Hand washing ; Satellite observation ; Remote sensing ; Unmanned aerial vehicles
(Location: IWMI HQ Call no: e-copy only Record No: H048488)
https://openknowledge.worldbank.org/bitstream/handle/10986/29099/9781464811975.pdf?sequence=4&isAllowed=y
https://vlibrary.iwmi.org/pdf/H048488.pdf
https://vlibrary.iwmi.org/pdf/H048488.pdf
(1.58 MB) (1.58 MB)
10 Khachatryan, H.; Suh, D. H.; Xu, W.; Useche, P.; Dukes, M. D. 2019. Towards sustainable water management: preferences and willingness to pay for smart landscape irrigation technologies. Land Use Policy, 85:33-41. [doi: https://doi.org/10.1016/j.landusepol.2019.03.014]
Water management ; Sustainability ; Irrigation systems ; Irrigation practices ; Technology ; Willingness to pay ; Water conservation ; Soil moisture ; Evapotranspiration ; Sensors ; Models / USA / California / Florida / Texas
(Location: IWMI HQ Call no: e-copy only Record No: H049282)
(1.10 MB)
Urbanization trends, leading to growing irrigated residential landscapes continue to escalate concerns on surface, ground, and drinking water quantity and quality among environmental groups and regulatory agencies. While automated lawn irrigation systems established in urban areas are critical factors affecting water quantity and quality, homeowners’ water use may vary with their preferences for lawn irrigation systems. The choice of an irrigation system is not determined only by local restrictions or policies but also by homeowners’ preferences. Further, individuals’ preferences can be influenced by the availability of product-specific attributes such as evapotranspiration or soil-moisture based controllers (known as smart irrigation controllers). With a focus on single-family home residents in California, Florida, and Texas, the present study uses the discrete choice analysis framework to link smart irrigation attributes (e.g., sensor types, wireless operation, remote control, alert notification) and monetary incentives (e.g., annual water bill savings, rebates) to preferences and willingness-to-pay. Results indicate that homeowners prefer smart irrigation controllers to conventional automated systems, and that savings on annual water bills could be one of the most important features determining adoption of smart irrigation controllers. Controller features such as the type of operation (i.e., wireless/on-site weather station) and system malfunction alert/notification also impacted homeowners’ preferences. The findings provide practical insights into the promotion of smart irrigation controllers that can be integrated with educational campaigns, or advertisements highlighting benefits of smart irrigation technologies. Clearer understanding about homeowners’ preferences could serve as a feedback loop for policy makers and improve water policies at state and local levels.
11 Bhatti, Muhammad Tousif; Anwar, Arif A.; Ali Shah, Muhammad Azeem. 2019. Revisiting telemetry in Pakistan’s Indus Basin Irrigation System. Water, 11(11):1-20. [doi: https://doi.org/10.3390/w11112315]
Irrigation systems ; Telemetry ; Flow discharge ; Estimation ; Sensors ; Irrigation canals ; Rivers ; Data collection ; Quality assurance ; Measuring instruments / Pakistan / Indus Basin Irrigation System
(Location: IWMI HQ Call no: e-copy only Record No: H049422)
(1.82 MB) (1.82 MB)
The Indus Basin Irrigation System (IBIS) lacks a system for measuring canal inflows, storages, and outflows that is trusted by all parties, transparent, and accessible. An earlier attempt for telemetering flows in the IBIS did not deliver. There is now renewed interest in revisiting telemetry in Pakistan’s IBIS at both national and provincial scales. These investments are typically approached with an emphasis on hardware procurement contracts. This paper describes the experience from field installations of flow measurement instruments and communication technology to make the case that canal flows can be measured at high frequency and displayed remotely to the stakeholders with minimal loss of data and lag time between measurement and display. The authors advocate rolling out the telemetry system across IBIS as a data as a service (DaaS) contract rather than as a hardware procurement contract. This research addresses a key issue of how such a DaaS contract can assure data quality, which is often a concern with such contracts. The research findings inform future telemetry investment decisions in large-scale irrigation systems, particularly the IBIS.
12 Jabro, J. D.; Stevens, W. B.; Iversen, W. M.; Allen, B. L.; Sainju, U. M. 2020. Irrigation scheduling based on wireless sensors output and soil-water characteristic curve in two soils. Sensors, 20(5):1336. (Special issue: Soil Moisture Sensors for Irrigation Management) [doi: https://doi.org/10.3390/s20051336]
Irrigation Scheduling ; Soil water characteristics ; Soil water content ; Soil water potential ; Wilting point ; Water availability ; Sandy loam soils ; Clay loam soils ; Monitoring ; Rain ; Sensors / USA / North Dakota / Montana
(Location: IWMI HQ Call no: e-copy only Record No: H049690)
(1.53 MB) (1.53 MB)
Data-driven irrigation planning can optimize crop yield and reduce adverse impacts on surface and ground water quality. We evaluated an irrigation scheduling strategy based on soil matric potentials recorded by wireless Watermark (WM) sensors installed in sandy loam and clay loam soils and soil-water characteristic curve data. Five wireless WM nodes (IRROmesh) were installed at each location, where each node consisted of three WM sensors that were installed at 15, 30, and 60 cm depths in the crop rows. Soil moisture contents, at field capacity and permanent wilting points, were determined from soil-water characteristic curves and were approximately 23% and 11% for a sandy loam, and 35% and 17% for a clay loam, respectively. The field capacity level which occurs shortly after an irrigation event was considered the upper point of soil moisture content, and the lower point was the maximum soil water depletion level at 50% of plant available water capacity in the root zone, depending on crop type, root depth, growth stage and soil type. The lower thresholds of soil moisture content to trigger an irrigation event were 17% and 26% in the sandy loam and clay loam soils, respectively. The corresponding soil water potential readings from the WM sensors to initiate irrigation events were approximately 60 kPa and 105 kPa for sandy loam, and clay loam soils, respectively. Watermark sensors can be successfully used for irrigation scheduling by simply setting two levels of moisture content using soil-water characteristic curve data. Further, the wireless system can help farmers and irrigators monitor real-time moisture content in the soil root zone of their crops and determine irrigation scheduling remotely without time consuming, manual data logging and frequent visits to the field
13 Torres, A. B. B.; da Rocha, A. R.; Coelho da Silva, T. L.; de Souza, J. N.; Gondim, R. S. 2020. Multilevel data fusion for the internet of things in smart agriculture. Computers and Electronics in Agriculture, 171:105309. [doi: https://doi.org/10.1016/j.compag.2020.105309]
Decision support systems ; Internet ; Agriculture ; Irrigation ; Soil moisture ; Evapotranspiration ; Energy consumption ; Linear models ; Sensors ; Crops ; Cashews ; Coconuts / Brazil / Paraipaba
(Location: IWMI HQ Call no: e-copy only Record No: H049724)
(7.91 MB)
The Internet of Things (IoT) aims to enable objects to sense, identify, and analyze the world, but to achieve such goal cost-effectively, it should involve low-cost solutions. That implies a series of limitations, such as small battery life, limited storage capabilities, low accuracy, and imprecise sensors. Data fusion is one of the most widely used methods for improving sensor accuracy and providing a more precise decision. Therefore, we propose Hydra, a multilevel data fusion architecture, to improve sensor accuracy, identify application target events, and make more accurate decisions. Hydra is composed of three layers: low-level (sensor data fusion), medium-level (events and decision making), and high-level (decision fusion based on multiple applications). In partnership with Embrapa (Brazilian Agricultural Research Corporation), we instantiated Hydra for the smart agriculture domain, and we also developed two applications aiming smart water management. The first application goal was to determine the need for irrigation based on soil moisture levels, and the second ascertained the adequate irrigation time by estimating the crop’s evapotranspiration (rate of water evaporation by the soil and transpiration by plants). We performed a set of experiments to assess Hydra: (i) evaluation of methods to detect and remove outliers; (ii) analyze data resulting from the applications; (iii) the use of machine learning to create a new accurate evapotranspiration model based on the sensors data. The results indicate that a combination of the ESD method (Extreme Studentized Deviate) and WRKF filter (Weighted Outlier-Robust Kalman Filter) was the best method to identify and remove outliers. Moreover, we generated an evapotranspiration model using the SVM (Support Machine Vector) quadratic machine-learning model that produced values close to the evapotranspiration reference model (Penman-Monteith).
14 Masenyama, A.; Mutanga, O.; Dube, T.; Bangira, T.; Sibanda, M.; Mabhaudhi, T. 2022. A systematic review on the use of remote sensing technologies in quantifying grasslands ecosystem services. GIScience and Remote Sensing, 59(1):1000-1025. [doi: https://doi.org/10.1080/15481603.2022.2088652]
Grasslands ; Ecosystem services ; Remote sensing ; Technology ; Earth observation satellites ; Hydrological modelling ; Systematic reviews ; Biomass ; Leaf area index ; Canopy ; Vegetation index ; Sensors ; Water management ; Monitoring ; Machine learning ; Forecasting
(Location: IWMI HQ Call no: e-copy only Record No: H051246)
https://www.tandfonline.com/doi/pdf/10.1080/15481603.2022.2088652
https://vlibrary.iwmi.org/pdf/H051246.pdf
https://vlibrary.iwmi.org/pdf/H051246.pdf
(3.82 MB) (3.82 MB)
The last decade has seen considerable progress in scientific research on vegetation ecosystem services. While much research has focused on forests and wetlands, grasslands also provide a variety of different provisioning, supporting, cultural, and regulating services. With recent advances in remote sensing technology, there is a possibility that Earth observation data could contribute extensively to research on grassland ecosystem services. This study conducted a systematic review on progress, emerging gaps, and opportunities on the application of remote sensing technologies in quantifying all grassland ecosystem services including those that are related to water. The contribution of biomass, Leaf Area Index (LAI), and Canopy Storage Capacity (CSC) as water-related ecosystem services derived from grasslands was explored. Two hundred and twenty-two peer-reviewed articles from Web of Science, Scopus, and Institute of Electrical and Electronics Engineers were analyzed. About 39% of the studies were conducted in Asia with most of the contributions coming from China while a few studies were from the global south regions such as Southern Africa. Overall, forage provision, climate regulation, and primary production were the most researched grassland ecosystem services in the context of Earth observation data applications. About 39 Earth observation sensors were used in the literature to map grassland ecosystem services and MODIS had the highest utilization frequency. The most widely used vegetation indices for mapping general grassland ecosystem services in literature included the red and near-infrared sections of the electromagnetic spectrum. Remote sensing algorithms used within the retrieved literature include process-based models, machine learning algorithms, and multivariate techniques. For water-related grassland ecosystem services, biomass, CSC, and LAI were the most prominent proxies characterized by remotely sensed data for understanding evapotranspiration, infiltration, run-off, soil water availability, groundwater restoration and surface water balance. An understanding of such hydrological processes is crucial in providing insights on water redistribution and balance within grassland ecosystems which is important for water management.
15 Oke, A.; Traore, K.; Nati-Bama, A. D.; Igbadun, H.; Ahmed, B.; Ahmed, F.; Zwart, Sander. 2022. Small-scale irrigation and water management technologies for African agricultural transformation. Colombo, Sri Lanka: International Water Management Institute (IWMI). 166p. (Also in French) [doi: https://doi.org/10.5337/2022.212]
Small-scale irrigation ; Water management ; Technology ; Agricultural transformation ; Smallholders ; Farmer-led irrigation ; Land resources ; Water resources ; Water supply ; Pumping ; Shallow water ; Groundwater ; Tube wells ; Runoff water ; Water harvesting ; Ponds ; Embankments ; Dams ; Conveyance structures ; Pipes ; Irrigation methods ; Surface irrigation ; Basin irrigation ; Border irrigation ; Furrow irrigation ; Sprinkler irrigation ; Drip irrigation ; Irrigation systems ; Irrigation scheduling ; Wetting front ; Soil water content ; Sensors ; Contour cultivation ; Tillage ; Land levelling ; Soil moisture ; Moisture conservation ; Water conservation ; Techniques ; Crop production ; Water requirements ; Water use efficiency ; Irrigation equipment ; Maintenance ; Irrigation efficiency ; Solar energy ; Cost analysis ; Investment ; Business models ; Capacity development ; Training materials ; Learning activities / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H051446)
(7.73 MB)
16 Oke, A.; Traore, K.; Nati-Bama, A. D.; Igbadun, H.; Ahmed, B.; Ahmed, F.; Zwart, Sander. 2022. Technologies d’irrigation à petite échelle et de gestion de l’eau pour la transformation agricole Africaine. In French. [Small-scale irrigation and water management technologies for African agricultural transformation]. Colombo, Sri Lanka: International Water Management Institute (IWMI). 179p. (Also in English) [doi: https://doi.org/10.5337/2022.213]
Small-scale irrigation ; Water management ; Technology ; Agricultural transformation ; Smallholders ; Farmer-led irrigation ; Land resources ; Water resources ; Water supply ; Pumping ; Shallow water ; Groundwater ; Tube wells ; Runoff water ; Water harvesting ; Ponds ; Embankments ; Dams ; Conveyance structures ; Pipes ; Irrigation methods ; Surface irrigation ; Basin irrigation ; Border irrigation ; Furrow irrigation ; Sprinkler irrigation ; Drip irrigation ; Irrigation systems ; Irrigation scheduling ; Wetting front ; Soil water content ; Sensors ; Contour cultivation ; Tillage ; Land levelling ; Soil moisture ; Moisture conservation ; Water conservation ; Techniques ; Crop production ; Water requirements ; Water use efficiency ; Irrigation equipment ; Maintenance ; Irrigation efficiency ; Solar energy ; Cost analysis ; Investment ; Business models ; Capacity development ; Training materials ; Learning activities / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H051447)
(7.50 MB)
17 Pattinson, N. B.; Taylor, J.; Dickens, Chris W. S.; Graham, P. M. 2023. Digital innovation in citizen science to enhance water quality monitoring in developing countries. Colombo, Sri Lanka: International Water Management Institute (IWMI). 37p. (IWMI Working Paper 210) [doi: https://doi.org/10.5337/2024.201]
Digital innovation ; Citizen science ; Water quality ; Monitoring ; Developing countries ; Freshwater ecosystems ; Water resources ; Water management ; Decision support ; Community involvement ; Data collection ; Digital technology ; Sensors ; Databases ; Smartphones ; Mobile applications ; Innovation adoption ; Big data ; Sustainable Development Goals ; Goal 6 Clean water and sanitation ; Parameters ; Mitigation
(Location: IWMI HQ Call no: IWMI Record No: H052509)
(1.02 MB)
Freshwater systems are disproportionately adversely affected by the ongoing, global environmental crisis. The effective and efficient water resource conservation and management necessary to mitigate the crisis requires monitoring data, especially on water quality. This is recognized by Sustainable Development Goal (SDG) 6, particularly indicator 6.3.2., which requires all UN member states to measure and report the ‘proportion of water bodies with good ambient water quality’. However, gathering sufficient data on water quality is reliant on data collection at spatial and temporal scales that are generally outside the capacity of institutions using conventional methods. Digital technologies, such as wireless sensor networks and remote sensing, have come to the fore as promising avenues to increase the scope of data collection and reporting. Citizen science (which goes by many names, e.g., participatory science or community-based monitoring) has also been earmarked as a powerful mechanism to improve monitoring. However, both avenues have drawbacks and limitations. The synergy between the strengths of modern technologies and citizen science presents an opportunity to use the best features of each to mitigate the shortcomings of the other. This paper briefly synthesizes recent research illustrating how smartphones, sometimes in conjunction with other sensors, present a nexus point method for citizen scientists to engage with and use sophisticated modern technology for water quality monitoring. This paper also presents a brief, non-exhaustive research synthesis of some examples of current technological upgrades or innovations regarding smartphones in citizen science water quality monitoring in developing countries and how these can assist in objective, comprehensive, and improved data collection, management and reporting. While digital innovations are being rapidly developed worldwide, there remains a paucity of scientific and socioeconomic validation of their suitability and usefulness within citizen science. This perhaps contributes to the fact that the uptake and upscaling of smartphone-assisted citizen science continues to underperform compared to its potential within water resource management and SDG reporting. Ultimately, we recommend that more rigorous scientific research efforts be dedicated to exploring the suitability of digital innovations in citizen science in the context of developing countries and SDG reporting.
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