Monitoring intra and inter annual dynamics of forest degradation from charcoal production in Southern Africa with Sentinel – 2 imagery

Sedano, Fernando; Lisboa, Sá Nogueira; Duncanson, Laura; Ribeiro, Natasha; Sitoe, Almeida; Sahajpal, Ritvik; Hurtt, George C.; Tucker, Compton J.

doi:10.1016/j.jag.2020.102184

Cited by 21 publications

(21 citation statements)

References 39 publications

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“…Here we showed that while pole cutting may partly be driven by local demand, activities such as tree cutting and charcoal production correlated almost entirely with distances to major cities such as Dar es Salaam. Degradation thus appeared to be mainly driven by energy and timber demand emanating from larger cities and international markets, as opposed to mainly local demand (Ahrends et al., 2010)—a pattern that has been observed throughout southern Africa (McNicol et al., 2018; Sedano et al., 2020). Deforestation on the other hand is thought to be mainly driven by agriculture, highlighting the need for coordinated policy responses (Doggart et al., 2020; Hamunyela et al., 2020).…”

Section: Discussionmentioning

confidence: 97%

“…This echoes findings from other studies which show that small-scale deforestation tends to be underestimated by GFW, particularly in areas with low and/or seasonally dry woody cover (Bos et al, 2019;McNicol et al, 2018) where time-series analyses (Verbesselt et al 2010(Verbesselt et al , 2012) may perform better (Bos et al, 2019); but also in moist forest in Tanzania (Hamunyela et al, 2020) and elsewhere (Bos et al, 2019;Milodowski et al, 2017). This is not a critique of the data generated by GFW, but it serves as a reminder that in areas where smaller scale deforestation and degradation are a significant cause of carbon emission and biodiversity loss, such as southern and eastern Africa (Baccini et al, 2017;McNicol et al, 2018;Pearson et al, 2017;Sedano et al, 2020), it is necessary to go beyond easily accessible deforestation data and to use a combination of approaches to detect these changes.…”

Section: Discussionmentioning

confidence: 99%

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Detecting and predicting forest degradation: A comparison of ground surveys and remote sensing in Tanzanian forests

Ahrends

Bulling

Platts

et al. 2021

Plants People Planet

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Detecting and predicting forest degradation: A comparison of ground surveys and remote sensing in Tanzanian forests

Ahrends

Bulling

Platts

et al. 2021

Plants People Planet

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“…The methodology developed herein offers a new opportunity that would improve efficient forest management as well as land-use planning. The studies focus on large plot sizes, demonstrating the great potential of using medium resolution temporal imagery [78]. However, there is no literature analyzing small plot sizes and their significance.…”

Section: Discussionmentioning

confidence: 99%

Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut Control

López-Amoedo¹,

Álvarez

Lorenzo

et al. 2021

Remote Sensing

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Land fragmentation and small plots are the main features of the rural environment of Galicia (NW Spain). Smallholding limits land use management, representing a drawback in local forest planning. This study analyzes the potential use of multitemporal Sentinel-2 images to detect and control forest cuts in very small pine and eucalyptus plots located in southern Galicia. The proposed approach is based on the analysis of Sentinel-2 NDVI time series in 4231 plots smaller than 3 ha (average 0.46 ha). The methodology allowed us to detect cuts, allocate cut dates and quantify plot areas due to different cutting cycles in an uneven-aged stand. An accuracy of approximately 95% was achieved when the whole plot was cut, with an 81% accuracy for partial cuts. The main difficulty in detecting and dating cuts was related to cloud cover, which affected the multitemporal analysis. In conclusion, the proposed methodology provides an accurate estimation of cutting date and area, helping to improve the monitoring system in sustainable forest certifications to ensure compliance with forest management plans.

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“…As population growth and anthropogenic developments have escalated over time, many studies have focused on identifying ecological changes, such as within climate and vegetation, that occur with the expansion of urban LC classes (Kleemann et al, 2017b;Asabere et al, 2020;Nyamekye et al, 2020). The large amounts of natural resources required by rapid industrial growth has placed significant demands on the environment that advances LCC beyond natural shifts (Yiran et al, 2012;Kuenzer et al, 2014;Mensah et al, 2019;Sedano et al, 2020). The methods used to acquire these materials also create disturbances within LC dynamics (Alo and Pontius, 2008;Kusimi, 2008;Tutu Benefoh et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

A Structural Equation Modeling Approach to Disentangling Regional-Scale Landscape Dynamics in Ghana

Peeling

Singh

Judge

2022

Front. Environ. Sci.

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Land cover (LC) change is an integrative indicator of changes in ecosystems due to anthropogenic or natural forcings. There is a significant interest in the investigation of spatio-temporal patterns of LC transitions, and the causes and consequences thereof. While the advent of satellite remote sensing techniques have enhanced our ability to track and measure LC changes across the globe, significant gaps remain in disentangling specific factors that influence, or in certain cases, are influenced by, LC change. This study aims to investigate the relative influence of regional-scale bioclimatology and local-scale anthropogenic factors in driving LC and environmental change in Ghana. This analysis builds upon previous research in the region that has highlighted multiple drivers of LC change in the region, especially via drivers such as deforestation, urbanization, and agricultural expansion. It used regional-scale remotely sensed, demographic, and environmental data for Ghana across 20 years and developed path models on causal factors influencing LC transitions in Ghana. A two-step process is utilized wherein causal linkages from an exploratory factor analysis (EFA) are constrained with literature-based theoretical constructs to implement a regional-scale partial least squares path model (PLSPM). The PLSPM reveals complex interrelationships among drivers of LC change that vary across the geography of Ghana. The model suggests strong effects of local urban expansion on deforestation and vegetation losses in urban and peri-urban areas. Losses of vegetation are in turn related to increases in local heating patterns indicative of urban heat island effects. Direct effects of heat islands are however masked by strong latitudinal gradients in climatological factors. The models confirm that decreases in vegetation cover results in increased land surface albedo that is indirectly related to urban and population expansion. These empirically-estimated causal linkages provide insights into complex spatio-temporal variations in potential drivers of LC change. We expect these models and spatial data products to form the basis for detailed investigations into the mechanistic underpinnings of land cover dynamics across Ghana. These analyses are aimed at building a template for methods that can be utilized to holistically design spatially-disaggregated strategies for sustainable development across Ghana.

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Monitoring intra and inter annual dynamics of forest degradation from charcoal production in Southern Africa with Sentinel – 2 imagery

Cited by 21 publications

References 39 publications

Detecting and predicting forest degradation: A comparison of ground surveys and remote sensing in Tanzanian forests

Detecting and predicting forest degradation: A comparison of ground surveys and remote sensing in Tanzanian forests

Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut Control

A Structural Equation Modeling Approach to Disentangling Regional-Scale Landscape Dynamics in Ghana

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