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REMOTE SENSING, ‎2072-4292

Journal

  1. Cloud-Based Monitoring and Evaluation of the Spatial-Temporal Distribution of Southeast Asia’s Mangroves Using Deep Learning

    Lomeo, D. & Singh, M., 10 May 2022, In: REMOTE SENSING. 14, 10, 20 p., 2291.

    Research output: Contribution to journalArticlepeer-review

  2. Processing of VENµS Images of High Mountains: A Case Study for Cryospheric and Hydro-Climatic Applications in the Everest Region (Nepal)

    Bessin, Z., Dedieu, J. P., Arnaud, Y., Wagnon, P., Brun, F., Esteves, M., Perry, B. & Matthews, T., 1 Mar 2022, In: REMOTE SENSING. 14, 5, 1098.

    Research output: Contribution to journalArticlepeer-review

  3. Processing of VENµS Images in High Mountain: A Case Study for Cryospheric and Hydro-Climatic applications in the Everest Region (Nepal)

    Bessin, Z., Dedieu, J-P., Yves, A., Patrick, W., Fanny, B., Michel, E., Perry, L. B. & Matthews, T., 2022, (Accepted/In press) In: REMOTE SENSING.

    Research output: Contribution to journalArticlepeer-review

  4. Orthorectification of helicopter-borne high resolution experimental burn observation from infra red handheld imagers

    Paugam, R., Wooster, M. J., Mell, W. E., Rochoux, M. C., Filippi, J. B., Rücker, G., Frauenberger, O., Lorenz, E., Schroeder, W., Main, B. & Govender, N., 1 Dec 2021, In: REMOTE SENSING. 13, 23, 4913.

    Research output: Contribution to journalArticlepeer-review

  5. An improved cloud gap-filling method for longwave infrared land surface temperatures through introducing passive microwave techniques

    Dowling, T. P. F., Song, P., De Jong, M. C., Merbold, L., Wooster, M. J., Huang, J. & Zhang, Y., Sep 2021, In: REMOTE SENSING. 13, 17, 3522.

    Research output: Contribution to journalArticlepeer-review

  6. Spectral emissivity (SE) measurement uncertainties across 2.5 – 14 μm derived from a round-robin study made across international laboratories

    Langsdale, M., Wooster, M., Harrison, J., Koehl, M., Hecker, C., Hook, S., Abbott, E., Johnson, W., Maturilli, A., Poutier, L., Lau, I. & Brucker, F., 1 Jan 2021, In: REMOTE SENSING. 13, 1, p. 1-37 37 p., 102.

    Research output: Contribution to journalArticlepeer-review

  7. Inter-comparison of field- and laboratory-derived surface emissivities of natural and manmade materials in support of land surface temperature (LST) remote sensing

    Langsdale, M., Dowling, T., Wooster, M., Johnson, J., Grosvenor, M., De Jong, M., Johnson, W., Hook, S. & Rivera, G., 11 Dec 2020, (Accepted/In press) In: REMOTE SENSING. 32 p.

    Research output: Contribution to journalArticlepeer-review

  8. Predicting fine particulate matter (PM2.5) in the greater london area: An ensemble approach using machine learning methods

    Yazdi, M. D., Kuang, Z., Dimakopoulou, K., Barratt, B., Suel, E., Amini, H., Lyapustin, A., Katsouyanni, K. & Schwartz, J., 1 Mar 2020, In: REMOTE SENSING. 12, 6, 914.

    Research output: Contribution to journalArticlepeer-review

  9. Radiometric Calibration of ‘Commercial off the Shelf’ Cameras for UAV-Based High-Resolution Temporal Crop Phenotyping of Reflectance and NDVI

    Holman, F. H., Wooster, M. J., Hawkesford, M., Riche, A. & Castle, M., Jul 2019, In: REMOTE SENSING. 11, 14, 1657.

    Research output: Contribution to journalArticlepeer-review

  10. Correcting swath-dependent bias of MODIS FRP observations with quantile mapping

    Kaur, I., Hüser, I., Zhang, T., Gehrke, B. & Kaiser, J. W., May 2019, In: REMOTE SENSING. 11, 10, 1205.

    Research output: Contribution to journalArticlepeer-review

  11. Fire activity and fuel consumption dynamics in sub-Saharan Africa

    Roberts, G., Wooster, M. J., Xu, W. & He, J., 1 Oct 2018, In: REMOTE SENSING. 10, 10, 1591.

    Research output: Contribution to journalArticlepeer-review

  12. New Tropical Peatland Gas and Particulate Emissions Factors Indicate 2015 Indonesian Fires Released Far More Particulate Matter (but Less Methane) than Current Inventories Imply

    Wooster, M. J., Gaveau, D. L. A., Salim, M. A., Zhang, T., Xu, W., Green, D. C., Huijnen, V., Murdiyarso, D., Gunawan, D., Borchard, N., Schirrmann, M., Main, B. & Sepriando, A., Apr 2018, In: REMOTE SENSING. 10, 4, 495.

    Research output: Contribution to journalArticlepeer-review

  13. Assessment of Errors Caused by Forest Vegetation Structure in Airborne LiDAR-Derived DTMs

    Simpson, J. E., Smith, T. E. L. & Wooster, M. J., 28 Oct 2017, (E-pub ahead of print) In: REMOTE SENSING. 9, 11

    Research output: Contribution to journalArticlepeer-review

  14. Regional-scale high spatial resolution mapping of Aboveground Net Primary Productivity (ANPP) from field survey and Landsat data: A case study for the country of Wales

    Tebbs, E. J., Rowland, C. S., Smart, S. M., Maskell, L. C. & Norton, L. R., 14 Aug 2017, (E-pub ahead of print) In: REMOTE SENSING.

    Research output: Contribution to journalArticlepeer-review

  15. High Throughput Field Phenotyping of Wheat Plant Height and Growth Rate in Field Plot Trials Using UAV Based Remote Sensing

    Holman, F. H., Riche, A., Michalski, A., Castle, M., Wooster, M. J. & Hawkesford, M., 18 Dec 2016, In: REMOTE SENSING. 8, 12, 23 p.

    Research output: Contribution to journalArticlepeer-review

  16. Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

    Simpson, J. E., Wooster, M. J., Smith, T. E. L., Trivedi, M., Vernimmen, R. R. E., Dedi, R., Shakti, M. & Dinata, Y., 6 Dec 2016, In: REMOTE SENSING. 8, 12, 1000.

    Research output: Contribution to journalArticlepeer-review

  17. Remote sensing measures restoration successes, but canopy heights lag in restoring floodplain vegetation

    Dawson, S., Fisher, A., Lucas, R., Hutchinson, D., Berney, P., Keith, D., Catford, J. A. & Kingsford, R., 24 Jun 2016, In: REMOTE SENSING. 8, 7, 19 p.

    Research output: Contribution to journalArticlepeer-review

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