Assessing wetland health using a newly developed land cover citizen science tool for use by local people who are not wetland specialists

Dumakude, Nondumiso; Graham, Mark

doi:10.4314/sajee.v.33i1.6

Cited by 6 publications

(1 citation statement)

References 18 publications

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“…In general, CS has been used in hydrological observations and/or in the monitoring of surface water quality in all different continents of the globe. This is the case of Europe [13], North America [14], Central America [15], South America [11], Oceania [16], Asia [17], and Africa [18], demonstrating that CS is a low-cost and crucial tool in raising awareness on the importance of good water quality [13], and important in decision-making instances [19]. When educators are involved in CS, the benefits for school environmental education are multiple [20,21].…”

Section: Introductionmentioning

confidence: 99%

Development of a Metric of Aquatic Invertebrates for Volunteers (MAIV): A Simple and Friendly Biotic Metric to Assess Ecological Quality of Streams

Pinto

Oliveira

Leitão

et al. 2020

Water

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Citizen science activities, involving local people in volunteer-supported and sustainable monitoring programs, are common. In this context, the objective of the present work was to develop a simple Metric of Aquatic Invertebrates for Volunteers (MAIV), including a user-friendly tool that can be easily accessed by volunteers, and to evaluate the efficiency of a volunteer monitoring program following an audit procedure. To obtain MAIV values, macroinvertebrate communities were reduced to 18 surrogate taxa, which represented an acceptable compromise between simplicity, efficiency, and reproducibility of the data, compared to the regular Water Framework Directive monitoring. When compared to results obtained with the National Classification System of Portugal, MAIV accurately detected moderate, poor, and bad ecological status. Thus, MAIV can be used by volunteers as a complement to the official monitoring program, as well as a prospective early warning tool for local problems related to ecological quality. Volunteers were students supervised by their teachers. Results obtained by volunteers were compared to results obtained by experts on macroinvertebrate identification to measure the efficiency of the procedure, by counting gains and losses on sorting, and identification. Characteristics of groups of volunteers (age and school level) did not influence significantly the efficiency of the procedure, and generally results of volunteers and experts matched.

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Section: Introductionmentioning

confidence: 99%

Development of a Metric of Aquatic Invertebrates for Volunteers (MAIV): A Simple and Friendly Biotic Metric to Assess Ecological Quality of Streams

Pinto

Oliveira

Leitão

et al. 2020

Water

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Urban Aquatic Insects

2019

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Using UAV multispectral photography to discriminate plant species in a seep wetland of the Fynbos Biome

Musungu,

Dube,

Smit

et al. 2024

Wetlands Ecol Manage

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Wetlands harbour a wide range of vital ecosystems. Hence, mapping wetlands is essential to conserving the ecosystems that depend on them. However, the physical nature of wetlands makes fieldwork difficult and potentially erroneous. This study used multispectral UAV aerial photography to map ten wetland plant species in the Fynbos Biome in the Steenbras Nature Reserve. We developed a methodology that used K-Nearest Neighbour (KNN), Support Vector Machine (SVM), and Random Forest (RF) machine learning algorithms to classify ten wetland plant species using the preselected bands and spectral indices. The study identified Normalized green red difference index (NGRDI), Red Green (RG) index, Green, Log Red Edge (LogRE), Normalized Difference Red-Edge (NDRE), Chlorophyll Index Red-Edge (CIRE), Green Ratio Vegetation Index (GRVI), Normalized Difference Water Index (NDWI), Green Normalized Difference Vegetation Index (GNDVI) and Red as pertinent bands and indices for classifying wetland plant species in the Proteaceae, Iridaceae, Restionaceae, Ericaceae, Asteraceae and Cyperaceae families. The classification had an overall accuracy of 87.4% and kappa accuracy of 0.85. Thus, the findings are pertinent to understanding the spectral characteristics of these endemic species. The study demonstrates the potential for UAV-based remote sensing of these endemic species.

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Assessing wetland health using a newly developed land cover citizen science tool for use by local people who are not wetland specialists

Abstract: More than half of the wetlands in South Africa

Cited by 6 publications

References 18 publications

Development of a Metric of Aquatic Invertebrates for Volunteers (MAIV): A Simple and Friendly Biotic Metric to Assess Ecological Quality of Streams

Development of a Metric of Aquatic Invertebrates for Volunteers (MAIV): A Simple and Friendly Biotic Metric to Assess Ecological Quality of Streams

Urban Aquatic Insects

Using UAV multispectral photography to discriminate plant species in a seep wetland of the Fynbos Biome

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