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Since 2016, Planet Labs has launched hundreds of nanosatellites, known as Doves. Despite the advantages of their high spatial and temporal resolution, these nanosatellites\u2019 images still present inconsistencies in radiometric resolution, limiting their broader usability. To address this issue, a model for radiometric normalization of PlanetScope (PS) images was developed using Multispectral Instrument\/Sentinel-2 (MSI\/S2) sensor images as a reference. An extensive database was compiled, including images from all available versions of the PS sensor (e.g., PS2, PSB.SD, and PS2.SD) from 2017 to 2022, along with data from various weather stations. The sampling process was carried out for each band using two methods: Conditioned Latin Hypercube Sampling (cLHS) and statistical visualization. Five machine learning algorithms were then applied, incorporating both linear and nonlinear models based on rules and decision trees: Multiple Linear Regression (MLR), Model Averaged Neural Network (avNNet), Random Forest (RF), k-Nearest Neighbors (KKNN), and Support Vector Machine with Radial Basis Function (SVM-RBF). A rigorous covariate selection process was performed for model application, and the models\u2019 performance was evaluated using the following statistical indices: Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Lin\u2019s Concordance Correlation Coefficient (CCC), and Coefficient of Determination (R2). Additionally, Kruskal\u2013Wallis and Dunn tests were applied during model selection to identify the best-performing model. The results indicated that the RF model provided the best fit across all PS sensor bands, with more accurate results in the longer wavelength bands (Band 3 and Band 4). The models achieved RMSE reflectance values of approximately 0.02 and 0.03 in these bands, with R2 and CCC ranging from 0.77 to 0.90 and 0.87 to 0.94, respectively. In summary, this study makes a significant contribution to optimizing the use of PS sensor images for various applications by offering a detailed and robust approach to radiometric normalization. These findings have important implications for the efficient monitoring of surface changes on Earth, potentially enhancing the practical and scientific use of these datasets.<\/jats:p>","DOI":"10.3390\/rs16214047","type":"journal-article","created":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T09:57:36Z","timestamp":1730368656000},"page":"4047","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Relative Radiometric Normalization for the PlanetScope Nanosatellite Constellation Based on Sentinel-2 Images"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1153-3147","authenticated-orcid":false,"given":"Rafael Lu\u00eds Silva","family":"Dias","sequence":"first","affiliation":[{"name":"Department of Agricultural Engineering, Universidade Federal de Vi\u00e7osa, Vi\u00e7osa, Minas Gerais 36570-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4570-1770","authenticated-orcid":false,"given":"Ricardo Santos Silva","family":"Amorim","sequence":"additional","affiliation":[{"name":"Department of Agricultural Engineering, Universidade Federal de Vi\u00e7osa, Vi\u00e7osa, Minas Gerais 36570-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9666-7421","authenticated-orcid":false,"given":"Demetrius David","family":"da Silva","sequence":"additional","affiliation":[{"name":"Department of Agricultural Engineering, Universidade Federal de Vi\u00e7osa, Vi\u00e7osa, Minas Gerais 36570-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9484-1411","authenticated-orcid":false,"given":"Elp\u00eddio In\u00e1cio","family":"Fernandes-Filho","sequence":"additional","affiliation":[{"name":"Department of Soil and Plant Nutrition, Universidade Federal de Vi\u00e7osa, Vi\u00e7osa, Minas Gerais 36570-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9451-2714","authenticated-orcid":false,"given":"Gustavo Vieira","family":"Veloso","sequence":"additional","affiliation":[{"name":"Department of Soil and Plant Nutrition, Universidade Federal de Vi\u00e7osa, Vi\u00e7osa, Minas Gerais 36570-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4675-1104","authenticated-orcid":false,"given":"Ronam Henrique Fonseca","family":"Macedo","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Universidade Federal de Vi\u00e7osa, Vi\u00e7osa, Minas Gerais 36570-900, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1058","DOI":"10.1093\/advances\/nmab003","article-title":"Perspective: The Importance of Water Security for Ensuring Food Security, Good Nutrition, and Well-Being","volume":"12","author":"Young","year":"2021","journal-title":"Adv. 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