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Publications Citing Accelerated Canopy Chemistry Program (ACCP)

The following 17 publications cited the Accelerated Canopy Chemistry Program (ACCP) project.

YearCitationDataset or Project
2017Piatek, Kathryn B.;Fajvan, Mary Ann;Turcotte, Richard M.; (2017) Thinning effects on foliar elements in eastern hemlock: implications for managing the spread of the hemlock woolly adelgid1.Canadian Journal of Forest Research. 47(1): 81-88. https://doi.org/10.1139/cjfr-2016-0260
2016Oliveira, Rodolfo Assis de;Brunetto, Gustavo;Loss, Arcângelo;Gatiboni, Luciano Colpo;Kürtz, Claudinei;Müller Júnior, Vilmar;Lovato, Paulo Emílio;Oliveira, Bruno Salvador;Souza, Monique;Comin, Jucinei José; (2016) Cover Crops Effects on Soil Chemical Properties and Onion Yield.Revista Brasileira de Ciência do Solo. 40. https://doi.org/10.1590/18069657rbcs20150099
2015Feilhauer, Hannes; Asner, Gregory P.; Martin, Roberta E. (2015). Multi-method ensemble selection of spectral bands related to leaf biochemistry, Remote Sensing of Environment, 164. https://doi.org/10.1016/j.rse.2015.03.033
2013Gonsamo A., Chen, J. M.; (2013) Spectral Response Function Comparability Among 21 Satellite Sensors for Vegetation Monitoring. IEEE Transactions on Geoscience and Remote Sensing. 51 (3): 1319-1335. https://doi.org/10.1109/TGRS.2012.2198828
2012Crowley, K., McNeil, B., Lovett, G., Canham, C., & Driscoll, C.; (2012). Do Nutrient Limitation Patterns Shift from Nitrogen Toward Phosphorus with Increasing Nitrogen Deposition Across the Northeastern United States? Ecosystems. 15 (0): 940-957.https://doi.org/10.1007/s10021-012-9550-2
2012Romero, A., Aguado, I., & Yebra, M.; (2012). Estimation of dry matter content in leaves using normalized indexes and PROSPECT model inversion. International Journal of Remote Sensing. 33 (2): 396-414. https://doi.org/10.1080/01431161.2010.532819
2012Romero, A., Aguado, I., & Yebra, M.; (2012). Estimation of dry matter content in leaves using normalized indexes and PROSPECT model inversion. International Journal of Remote Sensing. 33 (2): 396-414. https://doi.org/10.1080/01431161.2010.532819
2012Romero, A., Aguado, I., & Yebra, M.; (2012). Estimation of dry matter content in leaves using normalized indexes and PROSPECT model inversion. International Journal of Remote Sensing. 33 (2): 396-414. https://doi.org/10.1080/01431161.2010.532819
2012Romero, A., Aguado, I., & Yebra, M.; (2012). Estimation of dry matter content in leaves using normalized indexes and PROSPECT model inversion. International Journal of Remote Sensing. 33 (2): 396-414. https://doi.org/10.1080/01431161.2010.532819
2012Romero, A., Aguado, I., & Yebra, M.; (2012). Estimation of dry matter content in leaves using normalized indexes and PROSPECT model inversion. International Journal of Remote Sensing. 33 (2): 396-414. https://doi.org/10.1080/01431161.2010.532819
2004Dash, J.; Curran, P. J.; (2004). The MERIS terrestrial chlorophyll index. International Journal of Remote Sensing. 25 (23): 5403-5413. https://doi.org/10.1080/0143116042000274015
2003Bortolot, Z. J.; Wynne, R. H.; (2003). A method for predicting fresh green leaf nitrogen concentrations from shortwave infrared reflectance spectra acquired at the canopy level that requires no in situ nitrogen data. International Journal of Remote Sensing. 24 (3): 619-624. https://doi.org/10.1080/01431160304993
2003Bortolot, Z. J.; Wynne, R. H.; (2003). A method for predicting fresh green leaf nitrogen concentrations from shortwave infrared reflectance spectra acquired at the canopy level that requires no in situ nitrogen data. International Journal of Remote Sensing. 24 (3): 619-624. https://doi.org/10.1080/01431160304993
2003Bortolot, Z. J.; Wynne, R. H.; (2003). A method for predicting fresh green leaf nitrogen concentrations from shortwave infrared reflectance spectra acquired at the canopy level that requires no in situ nitrogen data. International Journal of Remote Sensing. 24 (3): 619-624. https://doi.org/10.1080/01431160304993
2003Bortolot, Z. J.; Wynne, R. H.; (2003). A method for predicting fresh green leaf nitrogen concentrations from shortwave infrared reflectance spectra acquired at the canopy level that requires no in situ nitrogen data. International Journal of Remote Sensing. 24 (3): 619-624. https://doi.org/10.1080/01431160304993
2003Bortolot, Z. J.; Wynne, R. H.; (2003). A method for predicting fresh green leaf nitrogen concentrations from shortwave infrared reflectance spectra acquired at the canopy level that requires no in situ nitrogen data. International Journal of Remote Sensing. 24 (3): 619-624. https://doi.org/10.1080/01431160304993
2009Kokaly, R. F.,Asner, G. P.,Ollinger, S. V.,Martin, M. E.,Wessman, C. A.; (2009). Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies. Remote Sensing of Environment. 113 (0): S78-S91. https://doi.org/10.1016/j.rse.2008.10.018