References

  • Bernal, B., Murray, L. T., & Pearson, T. R. (2018). Global carbon dioxide removal rates from forest landscape restoration activities. Carbon balance and management, 13(1), 1-13.
  • Cantera, I., Cilleros, K., Valentini, A., Cerdan, A., Dejean, T., Iribar, A., … & Brosse, S. (2019). Optimizing environmental DNA sampling effort for fish inventories in tropical streams and rivers. Scientific Reports, 9(1), 1-11.
  • ESA, 2015. SENTINEL-2 User Handbook, vol. 1, pp. 64.
  • Ewers, R.M., Banks-Leite, C., (2013) Fragmentation Impairs the Microclimate Buffering Effect of Tropical Forests. PLoS ONE 8(3): e58093. https://doi.org/10.1371/journal.pone.0058093
  • Farr, T. G. et al., 2007, The Shuttle Radar Topography Mission, Rev. Geophys., 45, RG2004, doi:10.1029/2005RG000183
  • Fragal, Everton Hafemann, Thiago Sanna Freire Silva, and Evlyn Márcia Leão de Moraes Novo. “Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm.” Acta Amazonica 46 (2016): 13-24.
  • Kennedy, R. E., Yang, Z., & Cohen, W. B. (2010). Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr—Temporal segmentation algorithms. Remote Sensing of Environment, 114(12), 2897-2910. https://doi.org/10.1016/j.rse.2010.07.008
  • Kennedy, E.R.; Cohen, W.B.; Schroeder, T.A. Trajectory-based change detection for automated characterization of forest disturbance dynamics. Remote Sens. Environ. 2007, 110, 370–386.
  • Kennedy, R. E., Yang, Z., Gorelick, N., Braaten, J., Cavalcante, L., Cohen, W. B., & Healey, S. (2018). Implementation of the LandTrendr algorithm on google earth engine. Remote Sensing, 10(5), 691.
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  • Maeda, E.E., Nunes, H.M., Calders, K., Mendes de Moura, Y., Raumonen, P., Tuomisto, H., Verley, P., Vincent, G., Zuquim, G., Camargo, J.L. (2022). Shifts in structural diversity of Amazonian forest edges detected using terrestrial laser scanning. Remote Sensing of Environment, 271, 112895, 0034-4257, https://doi.org/10.1016/j.rse.2022.112895.
  • Magnago, L., Rocha, M., Meyer, L., Martins, S., Meira-Neto, J. (2015). Microclimatic conditions at forest edges have significant impacts on vegetation structure in large Atlantic forest fragments. Biodiversity and Conservation. 01. 01-30. 10.1007/s10531-015-0961-1.
  • Nunes, M.H., Camargo, J.L.C., Vincent, G. et al. Forest fragmentation impacts the seasonality of Amazonian evergreen canopies. Nat Commun 13, 917 (2022). https://doi.org/10.1038/s41467-022-28490-7
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  • Planet. (2021) Planet and NICFI partnership data
  • Potapov, P., Li, X., Hernandez-Serna, A., Tyukavina, A., Hansen, M. C., Kommareddy, A., … and Hofton, M. (2021). Mapping global forest canopy height through integration of GEDI and Landsat data. Remote Sensing of Environment, 253, 112165.
  • Reygadas, Y., Spera, S., Galati, V., Salisbury, D. S., Silva, S., & Novoa, S. (2021). Mapping forest disturbances across the Southwestern Amazon: tradeoffs between opensource, Landsat-based algorithms. Environmental Research Communications, 3(9), 091001.
  • Ruan, H. T., Wang, R. L., Li, H. T., Liu, L., Kuang, T. X., Li, M., & Zou, K. S. (2022). Effects of sampling strategies and DNA extraction methods on eDNA metabarcoding: A case study of estuarine fish diversity monitoring. Zoological research, 43(2), 192.
  • Saah, D., Johnson, G., Ashmall, B., Tondapu, G., Tenneson, K., Patterson, M., … & Chishtie, F. (2019). Collect Earth: An online tool for systematic reference data collection in land cover and use applications. Environmental Modelling & Software, 118, 166-171.
  • Silva Junior, C. H. L., Heinrich, V. H., Freire, A. T., Broggio, I. S., Rosan, T. M., Doblas, J., … and Aragão, L. E. (2020). Benchmark maps of 33 years of secondary forest age for Brazil. Scientific data, 7(1), 1-9.
  • Soille, P., and Vogt, P. (2009). Morphological segmentation of binary patterns. Pattern recognition letters, 30(4), 456-459.
  • Souza Jr, C. M., Z. Shimbo, J., Rosa, M. R., Parente, L. L., A. Alencar, A., Rudorff, B. F., … & Azevedo, T. (2020). Reconstructing three decades of land use and land cover changes in brazilian biomes with landsat archive and earth engine. Remote Sensing, 12(17), 2735. https://doi.org/10.3390/rs12172735
  • Tenneson, K., Patterson, M.S., Jadin, J., Rosenstock, T., Mulia, R., Kim, J., Quyen, N., Poortinga, A., Nguyen, M.P., Bogle, S., Dilger, J., Marlay, S., Nguyen, Q.T., Chishtie, F., and D. Saah. 2021. Commodity-Driven Forest Loss: A Study of Southeast Asia. Washington DC. 196pp. report

Fun Background Reads

  • Grantham, H. S., A. Duncan, T. D. Evans, K. R. Jones, H. L. Beyer, R. Schuster, J. Walston et al. “Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity.” Nature communications 11, no. 1 (2020): 5978.
  • Proença, Vânia, Laura Jane Martin, Henrique Miguel Pereira, Miguel Fernandez, Louise McRae, Jayne Belnap, Monika Böhm et al. “Global biodiversity monitoring: from data sources to essential biodiversity variables.” Biological Conservation 213 (2017): 256-263.

Our Publications

  • Dyson, Nicolau, Tenneson, … Saah (in review) Coupling remote sensing and eDNA to monitor environmental impact: A pilot to quantify the environmental benefits of sustainable agriculture in the Brazilian Amazon. pre-print