共找到2條詞條名為彭漪的結果 展開
- 北京科技大學教授,碩士生導師
- 武漢大學遙感信息工程學院副教授
彭漪
武漢大學遙感信息工程學院副教授
彭漪,武漢大學遙感信息工程學院副教授。研究方向:定量環境遙感。
目錄
教育經歷
2002 – 2006,武漢大學,遙感信息工程學院,學士
2006 – 2008,武漢大學,遙感信息工程學院,碩士
2008 – 2012,美國內布拉斯加大學,自然資源環境學院,博士
工作經歷
2012 – 2013,美國馬里蘭大學,地理科學系,初級研究員(博士后)
2013 – 至今,武漢大學,遙感信息工程學院,副教授
研究方向
定量環境遙感:基於高光譜的近景及衛星遙感數據,反演植被及水環境生態系統的各類典型生化參數,以達到生態環境監測的目的。
主持及參與項目
美國NASA資助項目:農作物初級生產力的遙感估測模型研究,2008 - 2012
美國NASA資助項目:濕地森林生長變化的遙感監測模型研究,2012 – 2013
國家青年自然基金資助項目:適應光照環境變化的多種農作物的GPP遙感估測模型研究,2014 – 至今
發表主要論文
[1] Nguy-Robertson, A.L., Peng, Y., Gitelson, A.A.,Arkebauer, T.,Scoby, D., & Schepers, J. (2015). Using a simple leaf color chart to estimate leaf and canopy chlorophyll a content in maize (Zea mays).Communications in Soil Science and Plant Analysis, In press.
[2] Gitelson, A.A., Peng, Y., T.J. Arkebauer, A.E. Suyker. (2015). Productivity, absorbed photosynthetically active radiation, and light use efficiency in crops: Implications for remote sensing of crop primary production,Journal of Plant Physiology, 177, 100-109.
[3] Gitelson, A. A., Peng, Y., K. F. Huemmrich. (2014). Relationship between fraction of radiation absorbed by photosynthesizing maize and soybean canopies and NDVI from remotely sensed data taken at close range and from MODIS 250 m resolution data.Remote Sensing of Environment, 147: 108–120.
[4] Gitelson, A.A., Peng, Y., Schepers, J. & Arkebauer, T. (2014).Relationships between gross primary production, green LAI, and canopy chlorophyll content: Implications for remote sensing of primary production.Remote Sensing of Environment, 144, 65-72.
[5] Huang, C., Peng, Y., Lang, M. & Yeo, I.Y. (2014). Wetland inundation mapping and change monitoring using Landsat and airborne LiDAR data.Remote Sensing of Environment, 141, 231-242.
[6] Nguy-Robertson, A.L., Peng, Y., Gitelson, A.A., Arkebauer, T.J., Pimstein, A., Herrmann, I., Karnieli, A., Rundquist, D.C. & Bonfil, D.J. (2014). Estimating green LAI in four crops: Potential of determining optimal spectral bands for a universal algorithm.Agricultural and Forest Meteorology, 192-193: 140-148.
[7] Peng, Y. Sakamoto, T., & Gitelson, A.A. (2013). Remote estimation of gross primary productivity in crops using MODIS 250 m data.Remote Sensing of Environment,128, 186-196.
[8] Gitelson, A.A., Peng, Y., Masek, J., Verma, S.B., Suyer, A., Baker, J.M., Hatfield, J.L. & Meyers, T. (2013). Remote estimation of gross primary productivity in crops with Landsat data.Remote Sensing of Environment, 121, 404-414.
[9] Nguy-Robertson, A., Gitelson,A.A., Peng, Y., Walter-Shea, E., Leavitt, B., & T. Arkebauer. (2013). Continuous Monitoring of Crop Reflectance, Vegetation Fraction, and Identification of Developmental Stages Using a Four Band Radiometer,Agronomy Journal, 105: 1769–1779.
[10] Schlemmer, M., Gitelson, A.A., Schepers, J., Ferguson R., Peng Y., Shanahan, J., Rundquist, D.C. (2013). Remote estimation of nitrogen and chlorophyll contents in maize at leaf and canopy levels,International Journal of Applied Earth Observation and Geoinformation,25: 47–54.
[11] Peng, Y. & Gitelson, A.A. (2012). Remote estimation of gross primary productivity in soybean and maize based on total crop chlorophyll content. Remote Sensing of Environment, 117, 440-448.
[12] Nguy-Robertson, A.L., Gitelson, A.A., Peng, Y., Vina, A., Arkebauer, T. & Rundquist, D. (2012). Combining vegetation indices to increase their sensitivity to green leaf area index of crops along its entire dynamic range.Agronomy Journal, 104, 5, 1336 – 1347.
[13] Peng, Y. & Gitelson, A.A.(2011). Application of chlorophyll-related vegetation indices for remote estimation of maize productivity.Agricultural and Forest Meteorology,151, 1267 – 1276.
[14] Peng, Y., Gitelson, A.A., Keydan, G., Rundquist, D.C. & Moses, W. (2011). Remote estimation of gross primary production in maize and support for a new paradigm based on total crop chlorophyll content.Remote Sensing of Environment, 115, 978-989.
[15] Vina, A., Gitelson, A.A., Nguy-Robertson, A.L. & Peng, Y. (2011). Comparison of different vegetation indices for the remote assessment of green leaf area index of crops.Remote Sensing of Environment, 115, 3468 – 3478.