Historical Changes and Future Trajectories of Deforestation in the Ituri-Epulu-Aru Landscape (Democratic Republic of the Congo)

Kabuanga, Joël Masimo; Kankonda, Onésime Mubenga; Saqalli, Mehdi; Maestripieri, Nicolas; Bilintoh, Thomas Mumuni; Mweru, Jean-Pierre Mate; Liama, Aimé Balimbaki; Nishuli, Radar; Mané, Landing

doi:10.3390/land10101042

Cited by 7 publications

(4 citation statements)

References 47 publications

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“…However, in 2017, people mentioned that they were still being bitten by blackflies around the Kakoi river at lower altitude and during the cold season or in rainy and foggy weather [ 42 ]. A similar level of deforestation (up to 6.8% between 2000 and 2020) has also been noted in many other parts of the DRC [ 43 , 44 ]. Another explanation of the low O. volvulus transmission in the Logo health zone in DRC could be the restrictions of movements to crop fields far from houses due to the conflicts and insecurity that have increased since 2017 [ 45 ].…”

Section: Discussionsupporting

confidence: 67%

Surveillance for Onchocerciasis-Associated Epilepsy and OV16 IgG4 Testing of Children 6–10 Years Old Should Be Used to Identify Areas Where Onchocerciasis Elimination Programs Need Strengthening

Dusabimana

Fodjo

Ndahura³

et al. 2022

Pathogens

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To eliminate onchocerciasis-associated morbidity, it is important to identify areas where there is still high ongoing Onchocerca volvulus transmission. Between 2015 and 2021, door-to-door surveys were conducted in onchocerciasis-endemic villages in Cameroon, the Democratic Republic of Congo (DRC), Nigeria, South Sudan, and Tanzania to determine epilepsy prevalence and incidence, type of epilepsy and ivermectin therapeutic coverage. Moreover, children aged between six and 10 years were tested for anti-Onchocerca antibodies using the Ov16 IgG4 rapid diagnostic test (RDT). A mixed-effect binary logistic regression analysis was used to assess significantly associated variables of Ov16 antibody seroprevalence. A high prevalence and incidence of epilepsy was found to be associated with a high Ov16 antibody seroprevalence among 6–10-year-old children, except in the Logo health zone, DRC. The low Ov16 antibody seroprevalence among young children in the Logo health zone, despite a high prevalence of epilepsy, may be explained by a recent decrease in O. volvulus transmission because of a decline in the Simulium vector population as a result of deforestation. In the Central African Republic, a new focus of O. volvulus transmission was detected based on the high Ov16 IgG4 seropositivity among children and the detecting of nodding syndrome cases, a phenotypic form of onchocerciasis-associated epilepsy (OAE). In conclusion, Ov16 IgG4 RDT testing of 6–10-year-old children is a cheap and rapid method to determine the level of ongoing O. volvulus transmission and to assess, together with surveillance for OAE, the performance of onchocerciasis elimination programs.

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Section: Discussionsupporting

confidence: 67%

Surveillance for Onchocerciasis-Associated Epilepsy and OV16 IgG4 Testing of Children 6–10 Years Old Should Be Used to Identify Areas Where Onchocerciasis Elimination Programs Need Strengthening

Dusabimana

Fodjo

Ndahura³

et al. 2022

Pathogens

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“…Deforestation in the São Francisco River Basin (SFRB) in South America resulted in a total loss of 133. 19 Tg of carbon [17], while LULC carbon storage in coastal Bangladesh showed an increasing trend as the area of planted forests increased [18]. In order to increase the income of farmers or the government, deforestation has occurred in the Amazon [19], Central Africa [20], and Southeast Asia [21] to expand the planting area, which has changed the original LULC composition and reduced the regional carbon storage.…”

Section: Introductionmentioning

confidence: 99%

“…19 Tg of carbon [17], while LULC carbon storage in coastal Bangladesh showed an increasing trend as the area of planted forests increased [18]. In order to increase the income of farmers or the government, deforestation has occurred in the Amazon [19], Central Africa [20], and Southeast Asia [21] to expand the planting area, which has changed the original LULC composition and reduced the regional carbon storage. The above studies help to understand how LULC changes in the near equatorial region and how it affects carbon storage, and can provide a clear conclusion that changes in forest area are a vital factor [22].…”

Section: Introductionmentioning

confidence: 99%

Assessment and Prediction of Carbon Storage Based on Land Use/Land Cover Dynamics in the Tropics: A Case Study of Hainan Island, China

Liu

Yang

Cao

et al. 2022

Land

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Land use and land cover (LULC) change in tropical regions can cause huge amounts of carbon loss and storage, thus significantly affecting the global climate. Due to the differences in natural and social conditions between regions, it is necessary to explore the correlation mechanism between LULC and carbon storage changes in tropical regions from a broader geographical perspective. This paper takes Hainan Island as the research object, through the integration of the CA-Markov and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models, based on multi-source data, analyses the dynamics of LULC and carbon storage from 1992 to 2019 and the relationship between the two, and predicts future LULC and carbon storage under different scenarios. The results show that (1) the built-up land area of Hainan Island expanded from 103.59 km2 to 574.83 km2 from 1992 to 2019, an increase of 454.91%; the area of cropland and shrubland decreased; and the area of forest increased. (2) Carbon storage showed an upward trend during 1992–2000, and a downward trend during 2000–2019. Overall, LULC changes during 1992–2019 reduced carbon storage by about 1.50 Tg. (3) The encroachment of cropland in built-up land areas is the main reason for the reduction of carbon storage. The conversion of shrubland to forest is the main driving force for increasing carbon storage. The increase and decrease of carbon storage have obvious spatial clustering characteristics. (4) In the simulation prediction, the natural trend scenario (NT), built-up land priority scenario (BP) and ecological priority scenario (EP) reduce the carbon storage of Hainan Island, and the rate of decrease is BP> NT > EP. The cropland priority scenario (CP) can increase the LULC carbon storage, and the maximum increase in 2050 can reach 0.79 Tg. This paper supplements and improves the understanding of the correlation between LULC and carbon storage changes in tropical regions, and can provide guidance for the optimization of LULC structure in tropical regions with high economic development from a low-carbon perspective.

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“…At the same time, deforestation and the unbalanced functioning of forest ecosystems have wider effects and environmental consequences including land degradation, desertification, the loss of wildlife habitat and soil erosion [34]. Analysis of deforestation is possible by comparing forest areas on older maps with those detected on the remote sensing data [35][36][37] or landscape dynamics evaluated by time series of images [38]. Other approaches include continuous metrics to measure the degree of forest degradation [39] While the techniques of the remote sensing data acquisition and image processing by Geographic Information System (GIS) have demonstrated advances over recent decades [40,41], the algorithms of geospatial data modelling are not as straightforward regarding handling the data automatically.…”

Section: Introductionmentioning

confidence: 99%

R Libraries for Remote Sensing Data Classification by K-Means Clustering and NDVI Computation in Congo River Basin, DRC

Lemenkova

Debeir

2022

Applied Sciences

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In this paper, an image analysis framework is formulated for Landsat-8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) scenes using the R programming language. The libraries of R are shown to be effective in remote sensing data processing tasks, such as classification using k-means clustering and computing the Normalized Difference Vegetation Index (NDVI). The data are processed using an integration of the RStoolbox, terra, raster, rgdal and auxiliary packages of R. The proposed approach to image processing using R is designed to exploit the parameters of image bands as cues to detect land cover types and vegetation parameters corresponding to the spectral reflectance of the objects represented on the Earth’s surface. Our method is effective at processing the time series of the images taken at various periods to monitor the landscape dynamics in the middle part of the Congo River basin, Democratic Republic of the Congo (DRC). Whereas previous approaches primarily used Geographic Information System (GIS) software, we proposed to explicitly use the scripting methods for satellite image analysis by applying the extended functionality of R. The application of scripts for geospatial data is an effective and robust method compared with the traditional approaches due to its high automation and machine-based graphical processing. The algorithms of the R libraries are adjusted to spatial operations, such as projections and transformations, object topology, classification and map algebra. The data include Landsat-8 OLI-TIRS covering the three regions along the Congo river, Bumba, Basoko and Kisangani, for the years 2013, 2015 and 2022. We also validate the performance of graphical data handling for cartographic visualization using R libraries for visualising changes in land cover types by k-means clustering and calculation of the NDVI for vegetation analysis.

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Historical Changes and Future Trajectories of Deforestation in the Ituri-Epulu-Aru Landscape (Democratic Republic of the Congo)

Cited by 7 publications

References 47 publications

Surveillance for Onchocerciasis-Associated Epilepsy and OV16 IgG4 Testing of Children 6–10 Years Old Should Be Used to Identify Areas Where Onchocerciasis Elimination Programs Need Strengthening

Surveillance for Onchocerciasis-Associated Epilepsy and OV16 IgG4 Testing of Children 6–10 Years Old Should Be Used to Identify Areas Where Onchocerciasis Elimination Programs Need Strengthening

Assessment and Prediction of Carbon Storage Based on Land Use/Land Cover Dynamics in the Tropics: A Case Study of Hainan Island, China

R Libraries for Remote Sensing Data Classification by K-Means Clustering and NDVI Computation in Congo River Basin, DRC

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