{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T04:01:26Z","timestamp":1773374486329,"version":"3.50.1"},"reference-count":75,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T00:00:00Z","timestamp":1667174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Natural Science Foundation of China","award":["41971306"],"award-info":[{"award-number":["41971306"]}]},{"name":"the National Natural Science Foundation of China","award":["42090013"],"award-info":[{"award-number":["42090013"]}]},{"name":"the National Natural Science Foundation of China","award":["41971288"],"award-info":[{"award-number":["41971288"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Multi-angle optical reflectance measurements such as those from the NASA moderate resolution imaging spectroradiometer (MODIS) are sensitive to forest 3D structures, potentially serving as a useful proxy to estimate forest structural variables such as aboveground biomass (AGB)\u2014a potential theoretically recognized but rarely explored. In this paper, we examined the effectiveness of the reconstructed MODIS typical-angle reflectances\u2014reflectances observed from the hotspot, darkspot, and nadir directions\u2014for estimating forest AGB from both theoretical and practical perspectives. To gain theoretical insights, we first tested the sensitivities of typical-angle reflectances to forest AGB through simulations using the 4-scale bidirectional reflectance distribution function (BRDF) model. We then built statistical models to fit the relationship between MODIS multi-angle observations and field-measured deciduous-broadleaf\/mixed-temperate forest AGB at five sites in the eastern USA, assisted by a semivariogram analysis to determine the effect of pixel heterogeneity on the MODIS\u2013AGB relationship. We also determined the effects of terrain and season on the predictive relationships. Our results indicated that multi-angle reflectances with fewer visible shadows yielded better AGB estimates (hotspot: R2 = 0.63, RMSE = 54.28 Mg\/ha; nadir: R2 = 0.55, RMSE = 59.95 Mg\/ha; darkspot: R2 = 0.46, RMSE = 65.66 Mg\/ha) after filtering out the effects of complex terrain and pixel heterogeneity; the MODIS typical-angle reflectances in the NIR band were the most sensitive to forest AGB. We also found strong sensitivities of estimated accuracies to MODIS image acquisition dates or season. Overall, our results suggest that the current practice of leveraging only single-angle MODIS data can be a suboptimal strategy for AGB estimation. We advocate the use of MODIS multi-angle reflectances for optical remote sensing of forest AGB or potentially other ecological applications requiring forest structure information.<\/jats:p>","DOI":"10.3390\/rs14215475","type":"journal-article","created":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T06:01:28Z","timestamp":1667282488000},"page":"5475","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Effectiveness of the Reconstructed MODIS Typical-Angle Reflectances on Forest Biomass Estimation"],"prefix":"10.3390","volume":"14","author":[{"given":"Lei","family":"Cui","sequence":"first","affiliation":[{"name":"College of Urban and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mei","family":"Sun","sequence":"additional","affiliation":[{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3701-0830","authenticated-orcid":false,"given":"Ziti","family":"Jiao","sequence":"additional","affiliation":[{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jongmin","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Environmental Engineering, Korea National University of Transportation, Chungju 27469, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muge","family":"Agca","sequence":"additional","affiliation":[{"name":"Department of Geomatics Engineering, Izmir Katip Celebi University, Izmir 35620, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2768-7960","authenticated-orcid":false,"given":"Hu","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Urban and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"He","sequence":"additional","affiliation":[{"name":"College of Urban and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiqun","family":"Dai","sequence":"additional","affiliation":[{"name":"College of Urban and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yadong","family":"Dong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute of Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1352-5143","authenticated-orcid":false,"given":"Xiaoning","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Lian","sequence":"additional","affiliation":[{"name":"College of Urban and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Urban and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaiguang","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Environment and Natural Resources, The Ohio State University, Wooster, OH 43210, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1016\/j.rse.2017.09.007","article-title":"Utility of Multi Temporal Lidar for Forest and Carbon Monitoring: Tree Growth, Biomass Dynamics, and Carbon Flux","volume":"204","author":"Zhao","year":"2018","journal-title":"Remote Sens. 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