Office：Xifulou 311

Research Interest：Smart Agriculture; Forest Health; Remote Sensing and Data-Model Fusion

website：https://www.researchgate.net/profile/Ran-Meng-12

Education background

Professional appointment

2018.08 — Present Professor, Huazhong Agricultural University

2015.06 — 2018.07 Postdoc Research Associate, Brookhaven National Laboratory

2010.08 — 2015.05 Research Assistant, University of Utah

2007.09 — 2010.07 Research Assistant, IGSNRR, Chinese Academy of Sciences

Publications（*Corresponding，$equal contribution; Please check the latest updates on Research Gate: https://www.researchgate.net/profile/Ran-Meng-12）

Peer reviewed papers After 2018

[J27] Zhou L, Meng R, Tan Y, Lv Z, Zhao Y, Xu B, Zhao F. Comparison of UAV-based LiDAR and digital aerial photogrammetry for measuring crown-level canopy height in the urban environment. Urban Forestry Urban Greening, 69: 127489(2022).

[J26] Xu, L., Zhou, L.F., Meng, R. *, Zhao, F., Lv, Z., Xu, B., Zeng, L., Yu, X., & Peng, S. An Improved Approach to Estimate Ratoon Rice Aboveground Biomass by Integrating UAV-based Spectral, Textural and Structural Features. Precision Agriculture, (2022).

[J25] Zhao, F., Sun, R., Zhong, L., Meng, R. *, Huang, C., Zeng, X., Wang, M., Li, Y., & Wang, Z. Monthly Mapping of Forest Harvesting using Dense Time Series Sentinel-1 SAR Imagery and Deep Learning. Remote Sensing of Environment, 269, 112822(2022).

[J24] Meng, R. *, Gao, R., Zhao, F., Huang, C., Sun, R., Lv, Z., & Huang, Z. Landsat-based Monitoring of Southern Pine Beetle Infestation Severity and Severity Change in a Temperate Mixed Forest. Remote Sensing of Environment, 269, 112847(2022).

[J23]. Zeng, L.L., Peng, G.Z., Meng, R. *, Man, J.G., Li, W.B., Xu, B.Y., Lv, Z.G., & Sun, R. Wheat Yield Prediction Based on Unmanned Aerial Vehicles-Collected Red-Green-Blue Imagery. Remote Sensing, 13, 2937(2021).

[J22]. Lv, Z., Meng, R. $*, Man, J. $*, Zeng, L., Wang, M., Xu, B., Gao, R., Sun, R., & Zhao, F. Modeling of winter wheat fAPAR by integrating Unmanned Aircraft Vehicle-based optical, structural and thermal measurement. International Journal of Applied Earth Observation and Geoinformation, 102, 102407(2021).

[J21]. Zeng, L.L., Wardlow, B.D., Hu, S., Zhang, X., Zhou, G.Q., Peng, G.Z., Xiang, D.X., Wang, R., Meng, R., & Wu, W.X. A Novel Strategy to Reconstruct NDVI Time-Series with High Temporal Resolution from MODIS Multi-Temporal Composite Products. Remote Sensing, 13, 1397(2021).

[J20]. Zeng, L.L., Hu, Y.C., Wang, R., Zhang, X., Peng, G.Z., Huang, Z.Y., Zhou, G.Q., Xiang, D.X., Meng, R., Wu, W.X., & Hu, S. 8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale. Remote Sensing, 13, 2355(2021).

[J19].Xu, Y., Yu, L. *, Peng, D., Zhao, J., Cheng, Y., Liu, X., Li, W., Meng, R., Xu, X. and Gong, P., Annual 30-m land use/land cover maps of China for 1980–2015 from the integration of AVHRR, MODIS and Landsat data using the BFAST algorithm. Science China Earth Sciences, 63, pp.1390-1407 (2020).

[J18]. Meng, R. $*, Lv, Z. $, Yan, J., Chen, G., Zhao, F., Zeng, L., & Xu, B. Development of Spectral Disease Indices for Southern Corn Rust Detection and Severity Classification. Remote Sensing, 12, 3233(2020).

[J17]. Yang, D. *, Meng, R. $, Morrison, B. D., McMahon, A., Hantson, W., Hayes, D. J., ... & Serbin, S. P. A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra. Remote Sensing, 12(16), 2638(2020).

[J16]. Guo, L. *, Fu, P., Shi, T., Chen, Y., Zhang, H., Meng, R. and Wang, S., Mapping field-scale soil organic carbon with unmanned aircraft system-acquired time series multispectral images. Soil and Tillage Research, 196, p.104477 (2020).

[J15]. Serbin, S. *, Wu, J., Ely, K., Kruger, E., Meng, R. et al., From the Arctic to the tropics: multi‐biome prediction of leaf mass per area using leaf reflectance, New Phytologist, DOI:10.1111/nph.16123(2019).

Peer reviewed papers before 2018

[J14]. Veraverbeke, S. *, Dennison, P., Gitas, L., Hulley, G., Kalashnikova, O., Katagis, T., Kuai, L., Meng, R., Roberts, D., and Stavros, N., Hyperspectral remote sensing of fire: state-of-the-art and future perspectives, Remote Sensing of Environment, 216, 105-121 (2018).

[J13]. Meng, R. *, Dennison, P., Zhao, F., Shendryk, L., Cook, B., Havanan, R., and Serbin, S.P., Mapping canopy defoliation by insect herbivory at the individual tree level using bi-temporal airborne imaging spectroscopy and LiDAR measurements, Remote Sensing of Environment, 215,170-183(2018).

[J12]. Meng, R. *, Wu, J., Zhao, F., Cook, B., Havanan, R., and Serbin, S.P., Measuring post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using airborne imaging spectroscopy and LiDAR, Remote Sensing of Environment, 210,282-296(2018).

[J11]. Wu, J. *, Kobayashi, H., Starks, S.C., Meng, R., Guan, K., et al., Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest. New Phytologist, 217,1507-1520 (2018).

[J10]. Meng, R. *, Wu, J., Schwager, K., Zhao, F., Dennison, P.E., Cook, B., Brewer, K., Green, T.M., and Serbin, S.P., Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem. Remote Sensing of Environment, 191, 95-109 (2017).

[J9]. Ning, J. *, Gao, Z., Meng, R., Xu, F., and Gao, M., Analysis of relationships between land surface temperature and land use changes in the Yellow River Delta. Frontiers of Earth Science, 2, 444-456, (2018).

[J8]. Wu, J. *, Serbin, S.P., Xu, X., Chen, M., Meng, R., Saleska, S.R., and Rogers, A., The phenology of leaf quality and its within-canopy variation is essential for accurate modeling of photosynthesis in tropical evergreen forests. Global Change Biology, 23:4814-4827 (2017).

[J7]. Zhang, L*., Wei, Y. D., and Meng, R., Spatiotemporal dynamics and spatial determinants of urban growth in Suzhou, China, Sustainability, 9, 193 (2017).

[J6]. Zhao, R. F. *, Meng, R., Huang, C., Zhao, A. F., Gong, P., Yu, L., Zhu, Z.,  Long-term post-disturbance forest recovery in the Greater Yellowstone Ecosystem analyzed using Landsat time series stack, Remote Sensing, 8(11), 898 (2016).

[J5]. Meng, R. *, Dennison, P., Huang, C.,  Moritz, M., D’ Antonio, C., Effects of fire severity and post-fire climate on short-term vegetation recovery of mixed-conifer and red fir forests in the Sierra Nevada Mountains of California, Remote Sensing of Environment, 171, 311-325 (2015).

[J4]. Meng, R. *, Zhao, F., Sun, K., Zhang, R., Huang, C., Yang, J., Analysis of the 2014 “APEC Blue” in Beijing using more than one decade of satellite observations: lessons learned from radical emission control measures, Remote Sensing, 7, 15224-15243 (2015).

[J3]. Meng, R. *, Dennison, P., Spectroscopic analysis of green, desiccated and dead tamarisk canopies, Photogrammetric Engineering & Remote Sensing, 81(3), 199-207 (2015).

[J2]. Meng, R. *, Dennison, P., D’ Antonio, C., Moritz, M., Remote sensing analysis of vegetation recovery following short-interval fires in southern California shrublands, PLoS ONE, 9(10): e110637 (2014).

[J1]. Meng, R. *, Dennison, P., Jamison., L, van Riper, C., Nager, P., Hultine, K., Bean, D., Dudley, T., Detection of tamarisk defoliation by the northern tamarisk beetle based on multi-temporal Landsat 5 Thematic Mapper imagery, GIScience & Remote Sensing, 49, 510-37 (2012).

Conference proceedings

[O1].Zhao, F., Meng, R., Gu, H. and Serbin, S., 2019, July. Assessing Post-Fire Tree Mortality and Biomass Change by Integrating Lidar and Hyperspectral data. In IGARSS 2019-2019 IEEE

International Geoscience and Remote Sensing Symposium (pp. 7346-7349). IEEE.

[O2] Meng.R.,  et al. A UAS Platform for Assessing Spectral, Structural, and Thermal Patterns of Arctic Tundra Vegetation, IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium(2019).

[O3]. Meng, R., Yang, D., McMahon, A., Hantson, W., Hayes, D., Breen, A. and Serbin, S., 2019, July. A UAS Platform for Assessing Spectral, Structural, and Thermal Patterns of Arctic Tundra Vegetation. In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 9113-9116). IEEE.

[O4]. Meng, R., Gao, Z., Land cover classification based on the MODIS-EVI time-series imagery using decision tree method, Remote Sensing and Modeling of Ecosystems for Sustainability VI (Proceedings of SPIE), Vol.7454, 745410(2009).

[O5]. Gao, Z., Meng, R., Gao, W., 100a climate change and its impact on vegetation ecological zoning in China, Remote Sensing and Modeling of Ecosystems for Sustainability VI (Proceedings of SPIE), Vol.7454, 745411(2009).

Book chapter

[B1]. Meng, R., Zhao, R. F., Remote sensing characterization of burn effects - burned area and burn severity, Invited book chapter for Remote sensing of hydro-meteorological hazards, CRS/Taylor & Francis 261-281(2017).