{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T10:38:51Z","timestamp":1770287931041,"version":"3.49.0"},"reference-count":45,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T00:00:00Z","timestamp":1668038400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001321","name":"South African Research Chair Initiative (SARChI) in Land Use Planning and Management","doi-asserted-by":"publisher","award":["84157"],"award-info":[{"award-number":["84157"]}],"id":[{"id":"10.13039\/501100001321","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study sought to establish the performance of Spatially Varying Coefficient (SVC) Bayesian Hierarchical models using Landsat-8, and Sentinel-2 derived auxiliary information in predicting plantation forest carbon (C) stock in the eastern highlands of Zimbabwe. The development and implementation of Zimbabwe\u2019s land reform program undertaken in the year 2000 and the subsequent redistribution and resizing of large-scale land holdings are hypothesized to have created heterogeneity in aboveground forest biomass in plantation ecosystems. The Bayesian hierarchical framework, accommodating residual spatial dependence and non-stationarity of model predictors, was evaluated. Firstly, SVC models utilizing Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Enhanced Vegetation Index (EVI), derived from Landsat-8 and Sentinel-2 data and 191 sampled C stock observations were constructed. The SVC models built for each of the two multispectral remote sensing data sets were assessed based on the goodness of fit criterion as well as the predictive performance using a 10-fold cross-validation technique. The introduction of spatial random effects in the form of Landsat-8 and Sentinel-2 derived covariates to the model intercept improved the model fit and predictive performance where residual spatial dependence was dominant. For the Landsat-8 C stock predictive model, the RMSPE for the non-spatial, Spatially Varying Intercept (SVI) and SVC models were 8 MgCha\u22121, 7.77 MgCha\u22121, and 6.42 MgCha\u22121 whilst it was 7.85 MgCha\u22121, 7.69 MgCha\u22121 and 6.23 MgCha\u22121 for the Sentinel-2 C stock predictive models, respectively. Overall, the Sentinel-2-based SVC model was preferred for predicting C stock in plantation forest ecosystems as its model provided marginally tighter credible intervals, [1.17\u20131.60] MgCha\u22121 when compared to the Landsat-8 based SVC model with 95% credible intervals of [1.13\u20131.62] Mg Cha\u22121. The built SVC models provided an understanding of the performance of the multispectral remote sensing derived predictors for modeling C stock and thus provided an essential foundation required for updating the current carbon forest plantation databases.<\/jats:p>","DOI":"10.3390\/rs14225676","type":"journal-article","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T21:33:02Z","timestamp":1668115982000},"page":"5676","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Landsat-8 and Sentinel-2 Based Prediction of Forest Plantation C Stock Using Spatially Varying Coefficient Bayesian Hierarchical Models"],"prefix":"10.3390","volume":"14","author":[{"given":"Tsikai Solomon","family":"Chinembiri","sequence":"first","affiliation":[{"name":"College of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7358-8111","authenticated-orcid":false,"given":"Onisimo","family":"Mutanga","sequence":"additional","affiliation":[{"name":"College of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3456-8991","authenticated-orcid":false,"given":"Timothy","family":"Dube","sequence":"additional","affiliation":[{"name":"Institute of Water Studies, Department of Earth Sciences, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,10]]},"reference":[{"key":"ref_1","first-page":"373","article-title":"Trends in forest ownership, institutional arrangements and the impact on forest management and poverty reduction","volume":"13","author":"Matose","year":"2008","journal-title":"Cbneih"},{"key":"ref_2","unstructured":"Newsday Forestry Commision decentralise issuance of timber movement, Newsday, 24 July 2017."},{"key":"ref_3","first-page":"100166","article-title":"Satellite based integrated approaches to modelling spatial carbon stock and carbon sequestration potential of different land uses of Northeast India","volume":"13","author":"Bordoloi","year":"2022","journal-title":"Environ. 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