{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:11:56Z","timestamp":1760127116946,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,5,6]],"date-time":"2023-05-06T00:00:00Z","timestamp":1683331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000203","name":"USGS EROS","doi-asserted-by":"publisher","award":["USGS SA2000371"],"award-info":[{"award-number":["USGS SA2000371"]}],"id":[{"id":"10.13039\/100000203","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper evaluates the Arable Mark 2 sensor, an automated and low-cost radiometer, for its potential to retrieve surface reflectance data and validate orbital sensors such as the Landsat-8 (L8) Operational Land Imager (OLI) Level 2 product. While orbital sensors are widely used for monitoring solar radiation changes, managing natural resources, and understanding climatic trends, atmospheric effects can make it challenging to obtain accurate measurements. Equipped with multiple sensors, including long-wave and short-wave radiometers, the Arable Mark 2 sensor can measure upwelling and downwelling irradiance to calculate surface reflectance. To assess the accuracy and consistency of the Arable Mark 2 sensor, the study performed a cross-calibration using a ground truth measurement collected with the Analytical Spectral Device (ASD) as the reference point. Additionally, a spectral band adjustment factor (SBAF) was applied across the calibrated Arable surface reflectance to compare it against the orbital sensor. An automated library aided in calculating SBAF for the days with unavailable hyperspectral data. The study found that the Arable Mark 2 sensor can provide accurate surface reflectance data that can be used for orbital sensor validation. The Arable sensor was successfully calibrated against the ASD FieldSpec with an average difference of less than 1\/10 reflectance unit (reflectance unit = 0.01) for the blue, green, yellow, and red bands. The red-edge and NIR-1 bands showed an average difference of less than 1\/2 reflectance units, while the NIR-2 band had an average difference of less than 1\/10 reflectance unit of calibration accuracy. The calibrated Arable surface reflectance data was then compared against orbital sensor surface reflectance data, and the results showed good agreement between the two datasets. The study concludes that the low-cost and automated nature of the Arable Mark 2 sensor makes it a promising tool for surface reflectance retrieval and orbital sensor validation.<\/jats:p>","DOI":"10.3390\/rs15092444","type":"journal-article","created":{"date-parts":[[2023,5,8]],"date-time":"2023-05-08T02:03:31Z","timestamp":1683511411000},"page":"2444","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Evaluation of Low-Cost Radiometer for Surface Reflectance Retrieval and Orbital Sensor\u2019s Validation"],"prefix":"10.3390","volume":"15","author":[{"given":"Dinithi Siriwardana","family":"Pathiranage","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, South Dakota State University (SDSU), Brookings, SD 57007, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0836-4768","authenticated-orcid":false,"given":"Larry","family":"Leigh","sequence":"additional","affiliation":[{"name":"Imaging Center, Image Processing Laboratory, Department of Electrical Engineering and Computer Science, South Dakota State University (SDSU), Brookings, SD 57007, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2895-8697","authenticated-orcid":false,"given":"Cibele Teixeira","family":"Pinto","sequence":"additional","affiliation":[{"name":"Imaging Center, Image Processing Laboratory, Department of Electrical Engineering and Computer Science, South Dakota State University (SDSU), Brookings, SD 57007, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(95)00137-P","article-title":"Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data","volume":"54","author":"Hall","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.rse.2011.06.026","article-title":"Forty-year calibrated record of earth-reflected radiance from Landsat: A review","volume":"122","author":"Markham","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.rse.2014.02.001","article-title":"Landsat-8: Science and product vision for terrestrial global change research","volume":"145","author":"Roy","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Teixeira Pinto, C., Jing, X., and Leigh, L. (2020). Evaluation analysis of Landsat level-1 and level-2 data products using in situ measurements. Remote Sens., 12.","DOI":"10.3390\/rs12162597"},{"key":"ref_5","unstructured":"(2023, March 14). Arable Mark 2 Core Measurements. Available online: https:\/\/www.arable.com\/wp-content\/uploads\/2021\/10\/Arable-Mark-2-Core-Measurements-Accuracy-Whitepaper-21_01.pdf."},{"key":"ref_6","unstructured":"(2023, March 14). Decision Agriculture. Available online: https:\/\/www.arable.com\/."},{"key":"ref_7","unstructured":"(2023, March 15). Arable. Available online: https:\/\/www.arable.com\/company\/."},{"key":"ref_8","unstructured":"Pinto, C.T. (2016). Uncertainty Evaluation for in-Flight Radiometric Calibration of Earth Observation Sensors. [Ph.D. Thesis, Instituto Nacional de Pesquisas Espaciais]."},{"key":"ref_9","unstructured":"(2023, March 30). ARABLE MARK 2 MEASUREMENTS. Available online: https:\/\/www.arable.com\/wp-content\/uploads\/2021\/10\/Arable-Mark-2-Measurements-21_05.pdf."},{"key":"ref_10","unstructured":"(2023, March 15). Arable Developer. Available online: https:\/\/developer.arable.com\/guide\/data.html."},{"key":"ref_11","unstructured":"(2023, March 30). Arable Mark Agricultural Sensor. Available online: https:\/\/byronclee.com\/arable-mark."},{"key":"ref_12","unstructured":"(2023, March 15). Arable Mark Installation Guide. Available online: https:\/\/assets.ctfassets.net\/uzs63p7awoht\/q7nR9cf80Seea2wm8uwq6\/6de68cb66a8f529a757b70f36186a906\/Arable_Mark_Installation_Guide.pdf."},{"key":"ref_13","unstructured":"(2023, March 15). Arable Mark 2 Product Specifications. Available online: https:\/\/www.arable.com\/wp-content\/uploads\/2021\/10\/Arable-Mark-2-w_-Solar-Product-Specifications-20_10.pdf."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Pinto, C., Ponzoni, F., Castro, R., Leigh, L., Mishra, N., Aaron, D., and Helder, D. (2016). First in-flight radiometric calibration of MUX and WFI on-board CBERS-4. Remote Sens., 8.","DOI":"10.3390\/rs8050405"},{"key":"ref_15","unstructured":"Anderson, N., Biggar, S.F., Burkhart, C.J., Thome, K.J., and Mavko, M. (2002). Proceedings of the Earth Observing Systems VII, Society of Photo Optical."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"S21","DOI":"10.1088\/0026-1394\/49\/2\/S21","article-title":"Recent surface reflectance measurement campaigns with emphasis on best practices, SI traceability and uncertainty estimation","volume":"49","author":"Helder","year":"2012","journal-title":"Metrologia"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0034-4257(87)90032-0","article-title":"Field calibration of reference reflectance panels","volume":"22","author":"Jackson","year":"1987","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1174","DOI":"10.1109\/TGRS.2003.813211","article-title":"Vicarious radiometric calibration of EO-1 sensors by reference to high-reflectance ground targets","volume":"41","author":"Biggar","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/S0034-4257(01)00247-4","article-title":"Absolute radiometric calibration of Landsat 7 ETM+ using the reflectance-based method","volume":"78","author":"Thome","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_20","unstructured":"U.S. Geological Survey (2023, March 15). Landsat 8, Available online: https:\/\/www.usgs.gov\/landsat-missions\/landsat-8."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.rse.2016.04.008","article-title":"Preliminary analysis of the performance of the Landsat 8\/OLI land surface reflectance product","volume":"185","author":"Vermote","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1109\/36.581987","article-title":"Second simulation of the satellite signal in the solar spectrum, 6S: An overview","volume":"35","author":"Vermote","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/LGRS.2005.857030","article-title":"A Landsat surface reflectance dataset for North America, 1990\u20132000","volume":"3","author":"Masek","year":"2006","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_24","unstructured":"Masek, J., Vermote, E., Saleous, N., Wolfe, R., Hall, F., Huemmrich, K., Gao, F., Kutler, J., and Lim, T. (2012). LEDAPS Landsat Calibration, Reflectance, Atmospheric Correction Preprocessing Code, ORNL DAAC."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Vermote, E., Roger, J.-C., Franch, B., and Skakun, S. (2018, January 22\u201327). LaSRC (Land Surface Reflectance Code): Overview, application and validation using MODIS, VIIRS, LANDSAT and Sentinel 2 data\u2019s. Proceedings of the IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517622"},{"key":"ref_26","unstructured":"U.S. Geological Survey (2023, March 15). March 6, 2017\u2014Landsat 8 Collection 1 Data Available, Available online: https:\/\/www.usgs.gov\/landsat-missions\/march-6-2017-landsat-8-collection-1-data-available."},{"key":"ref_27","unstructured":"U.S. Geological Survey (2023, March 15). Landsat Collection 2 Level-2 Science Products, Available online: https:\/\/www.usgs.gov\/land-resources\/nli\/landsat\/landsat-collection-2-level-2-science-products."},{"key":"ref_28","unstructured":"(2023, March 15). Landsat Collection 1 vs. Collection 2 Summary. Available online: https:\/\/d9-wret.s3.us-west-2.amazonaws.com\/assets\/palladium\/production\/s3fs-public\/atoms\/files\/Landsat-C1vsC2-2021-0430-LMWS.pdf."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1267","DOI":"10.1109\/TGRS.2012.2228007","article-title":"Applications of spectral band adjustment factors (SBAF) for cross-calibration","volume":"51","author":"Chander","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Chander, G., Mishra, N., Helder, D.L., Aaron, D., Choi, T., Angal, A., and Xiong, X. (2010, January 25\u201330). Use of EO-1 Hyperion data to calculate spectral band adjustment factors (SBAF) between the L7 ETM+ and Terra MODIS sensors. Proceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, HI, USA.","DOI":"10.1109\/IGARSS.2010.5652746"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/j.isprsjprs.2017.07.002","article-title":"Radiometric inter-sensor cross-calibration uncertainty using a traceable high accuracy reference hyperspectral imager","volume":"130","author":"Banks","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Habte, A.M., Andreas, A.M., Sengupta, M., Narasappa, R., Hoke, A.F., Gotseff, P., Thiagarajan, R., Wolf, A., Carranza, L., and Watts, D. (2019). Low-Cost Multiparameter Device for Solar Resource Applications, National Renewable Energy Lab. (NREL).","DOI":"10.2172\/1505549"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1016\/j.solener.2003.12.003","article-title":"Solar position algorithm for solar radiation applications","volume":"76","author":"Reda","year":"2004","journal-title":"Sol. Energy"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1175\/1520-0426(2000)017<1171:SSP>2.0.CO;2","article-title":"Spectroradiometric sun photometry","volume":"17","author":"Osterwald","year":"2000","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_35","unstructured":"(2023, March 15). Aerosol Robotic Network (AERONET), Available online: https:\/\/aeronet.gsfc.nasa.gov\/."},{"key":"ref_36","unstructured":"Berk, A., Anderson, G.P., Acharya, P.K., and Shettle, E.P. (2023, March 15). MODTRAN\u00ae 5.2.1 User\u2019s Manual. Available online: https:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.458.1743&rep=rep1&type=pdf."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Hanslmeier, A. (2010). The Sun and Space Weather, Springer.","DOI":"10.1007\/978-3-642-11341-3_14"},{"key":"ref_38","unstructured":"Landsat, U. (2021). Landsat 8\u20139 Calibration and Validation (Cal\/Val) Algorithm Description Document (ADD), United States Geological Society."},{"key":"ref_39","unstructured":"USGS (2020). Landsat 8\u20139 Operational Land Imager (OLI)-Thermal Infrared Sensor (TIRS) Collection 2 Level 2 (L2) Data Format Control Book (DFCB), U.S. Geological Survey."},{"key":"ref_40","unstructured":"Teixeira Pinto, C. (2018). Vicarious Calibration Reflectance-Based Approach Cross-Calibration Method Evaluation of Uncertainties. [Ph.D. Thesis, Utah Sate University]."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Helder, D., Doelling, D., Bhatt, R., Choi, T., and Barsi, J. (2020). Calibrating geosynchronous and polar orbiting satellites: Sharing best practices. Remote Sens., 12.","DOI":"10.3390\/rs12172786"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/9\/2444\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:30:31Z","timestamp":1760124631000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/9\/2444"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,6]]},"references-count":41,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2023,5]]}},"alternative-id":["rs15092444"],"URL":"https:\/\/doi.org\/10.3390\/rs15092444","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,5,6]]}}}