Use of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa

Rampheri, Mangana B.; Dube, Timothy; Dhau, Inos

doi:10.1080/10106049.2020.1723717

Cited by 9 publications

(6 citation statements)

References 41 publications

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“…The information depicted by Landsat images is critical for aquatic and wetland management and decision-making, especially in regions that have a restricted network system of field observation frameworks in place (Thamaga and Dube 2019). The findings of this study are consistent with previous investigations, and they underscore the precision and strength of using Landsat data for long-term mapping in wetland-related studies, LULC quantification, biomass estimation, crop and fire mapping, aquatic plant species and urban development (Dube et al 2018;Dube and Mutanga 2015;Rampheri et al 2022). Jin et al (2017) demonstrated the unique strength and superiority of Landsat missions, as well as their practical viability in accurately mapping, detecting and monitoring the spatio-temporal changes for wetland assessment over-time.…”

Section: Long-time Wetland Monitoring Using Landsat Datasupporting

confidence: 88%

Evaluating the impact of land use and land cover change on unprotected wetland ecosystems in the arid-tropical areas of South Africa using the Landsat dataset and support vector machine

Thamaga

Dube

Shoko

2022

Geocarto International

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The study explored the impact of Land Use and Land Cover (LULC) change dynamics in relation to the condition and status of an unprotected wetland located in the arid-tropical parts of the Limpopo Province, South Africa. The long-term Landsat archival data series was used to map and quantify the impacts of LULC change on the wetland over a period of 36 years . A multi-source satellite image analysis was performed, using the support vector machine (SVM) algorithm and advanced spatiallyexplicit geographic information system tools. Landsat data series covering the entire study area was used to assess, map and monitor LULC change that occurred over-time. Post-classification maps for the Maungani wetland area were analysed to provide a quantitative assessment and a detailed overview of the rate of change. The generated wetland detection maps for four temporal phases (i.e., 1983-1992, 1992-2001, 2002-2010) were analysed. This study found that the spatial extent of the wetland area declined severely during the period under study with 728 300 ha. The findings of this work provide critical insights and baseline information about the state of unprotected wetlands in the rural parts. This information is useful for the development of tailor-made wetland management strategies and a possible rehabilitation framework for unprotected wetland ecosystems.

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Section: Long-time Wetland Monitoring Using Landsat Datasupporting

confidence: 88%

Evaluating the impact of land use and land cover change on unprotected wetland ecosystems in the arid-tropical areas of South Africa using the Landsat dataset and support vector machine

Thamaga

Dube

Shoko

2022

Geocarto International

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“…According to Madonsela et al [44], the differences in sensitivity to vegetation characteristics could be explained by the different measurement scales of the VIs. For instance, in the study of Rampheri et al [71], the VIs that had a better relationship with H ′ (NDVI and SAVI) have a measurement scale that ranges from −1 to 1. Overall, the type of forest and complexity of forest stands in terms of multi-layers and species composition can affect the outcome of estimations.…”

Section: Discussionmentioning

confidence: 99%

Assessing Forest Species Diversity in Ghana’s Tropical Forest Using PlanetScope Data

Njomaba,

Ofori,

Guuroh

et al. 2024

Remote Sensing

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This study utilized a remotely sensed dataset with a high spatial resolution of 3 m to predict species diversity in the Bobiri Forest Reserve (BFR), a moist semi-deciduous tropical forest in Ghana. We conducted a field campaign of tree species measurements to achieve this objective for species diversity estimation. Thirty-five field plots of 50 m × 20 m were established, and the most dominant tree species within the forest were identified. Other measurements, such as diameter at breast height (DBH ≥ 5 cm), tree height, and each plot’s GPS coordinates, were recorded. The following species diversity indices were estimated from the field measurements: Shannon–Wiener (H′), Simpson diversity index (D2), species richness (S), and species evenness (J′). The PlanetScope surface reflectance data at 3 m spatial resolution was acquired and preprocessed for species diversity prediction. The spectral/pixel information of all bands, except the coastal band, was extracted for further processing. Vegetation indices (VIs) (NDVI—normalized difference vegetation index, EVI—enhanced vegetation index, SRI—simple ratio index, SAVI—soil adjusted vegetation index, and NDRE—normalized difference red edge index) were also calculated from the spectral bands and their pixel value extracted. A correlation analysis was then performed between the spectral bands and VIs with the species diversity index. The results showed that spectral bands 6 (red) and 2 (blue) significantly correlated with the two main species diversity indices (S and H′) due to their influence on vegetation properties, such as canopy biomass and leaf chlorophyll content. Furthermore, we conducted a stepwise regression analysis to investigate the most important spectral bands to consider when estimating species diversity from the PlanetScope satellite data. Like the correlation results, bands 6 (red) and 2 (blue) were the most important bands to be considered for predicting species diversity. The model equations from the stepwise regression were used to predict tree species diversity. Overall, the study’s findings emphasize the relevance of remotely sensed data in assessing the ecological condition of protected areas, a tool for decision-making in biodiversity conservation.

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“…This is important not only for the sustainability of the species but also for the provision of habitats for some fauna which live in and on some of these plant species. In their study, RAMPHERI et al [2022] also noted that tree species loss could threaten the stability of ecosystem services which sustain human wellbeing. They highlighted the major human threats to biodiversity loss as deforestation, bush encroachment, pollution, and poor management practices.…”

Section: Introductionmentioning

confidence: 99%

Journal of Water and Land Development

2022

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The 15 th of United Nations' Sustainable Development Goals (SDGs) aims to protect, restore, and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss. This paper investigates the approach adopted by indigenous peoples for conservation of woody plant species diversity in some selected spots in Abia State, Southeastern Nigeria.Relying on mixed method approach to research, data collection comprising field observation, ground truthing, plant species inventory, and key-informant interviews and analysis of data, two spots were purposively sampled, one from each of the two LGAs; Mbom in Bende LGA and Amangwu in Ohafia Local Government Area (LGA). A 50 × 20 m quadrat was sampled from each site, from where plant species inventory was undertaken. Shannon-Wiener diversity index (H') was used to analyse the data.The result of Shannon-Wiener diversity index, shows that the diversity indices of the plant species for the two sites were 3.20 (Mbom) and 3.95 (Amangwu) respectively. The people of Bende and Ohafia LGAs employ some traditional laws to ensure conservation of woody plant species so as to achieve goal 15 th of the SDGs. This paper advocates sustenance of those traditional laws that encourage conservation of woody plant species in the study area with enforceable sanctions to deter defaulters.

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Use of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa

Cited by 9 publications

References 41 publications

Evaluating the impact of land use and land cover change on unprotected wetland ecosystems in the arid-tropical areas of South Africa using the Landsat dataset and support vector machine

Evaluating the impact of land use and land cover change on unprotected wetland ecosystems in the arid-tropical areas of South Africa using the Landsat dataset and support vector machine

Assessing Forest Species Diversity in Ghana’s Tropical Forest Using PlanetScope Data

Journal of Water and Land Development

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