{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T16:36:09Z","timestamp":1774715769143,"version":"3.50.1"},"reference-count":89,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,3,9]],"date-time":"2021-03-09T00:00:00Z","timestamp":1615248000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Research Foundation South Africa","award":["118770"],"award-info":[{"award-number":["118770"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Forests contribute significantly to terrestrial biodiversity conservation. Monitoring of tree species diversity is vital due to climate change factors. Remote sensing imagery is a means of data collection for predicting diversity of tree species. Since various sensors have different spectral and spatial resolutions, it is worth comparing them to ascertain which could influence the accuracy of prediction of tree species diversity. Hence, this study evaluated the influence of the spectral and spatial resolutions of PlanetScope, RapidEye, Sentinel 2 and Landsat 8 images in diversity prediction based on the Shannon diversity index (H\u2032), Simpson diversity Index (D1) and Species richness (S). The Random Forest regression was applied for the prediction using the spectral bands of the sensors as variables. The Sentinel 2 was the best image, producing the highest coefficient of determination (R2) under both the Shannon Index (R2 = 0.926) and the Species richness (R2 = 0.923). Both the Sentinel and RapidEye produced comparable higher accuracy for the Simpson Index (R2 = 0.917 and R2 = 0.915, respectively). The PlanetScope was the second-accurate for the Species richness (R2 = 0.90), whiles the Landsat 8 was the least accurate for the three diversity indices. The outcomes of this study suggest that both the spectral and spatial resolutions influence prediction accuracies of satellite imagery.<\/jats:p>","DOI":"10.3390\/rs13051033","type":"journal-article","created":{"date-parts":[[2021,3,9]],"date-time":"2021-03-09T06:22:32Z","timestamp":1615270952000},"page":"1033","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["RETRACTED: Evaluating Multi-Sensors Spectral and Spatial Resolutions for Tree Species Diversity Prediction"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4274-4433","authenticated-orcid":false,"given":"Enoch","family":"Gyamfi-Ampadu","sequence":"first","affiliation":[{"name":"School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Westville Campus, Private Bag X54001, Durban 4000, South Africa"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4784-576X","authenticated-orcid":false,"given":"Michael","family":"Gebreslasie","sequence":"additional","affiliation":[{"name":"School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Westville Campus, Private Bag X54001, Durban 4000, South Africa"}]},{"given":"Alma","family":"Mendoza-Ponce","sequence":"additional","affiliation":[{"name":"Centro de Ciencias de la Atm\u00f3sfera, Ciudad Universitaria, Universidad Nacional Aut\u00f3noma de M\u00e9xico Investigaci\u00f3n Cient\u00edfica s\/n, C.U., Coyoac\u00e1n, Mexico City 04510, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.1038\/ncomms2328","article-title":"Higher levels of multiple ecosystem services are found in forests with more tree species","volume":"4","author":"Gamfeldt","year":"2013","journal-title":"Nat. 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