remote sensing of koala habitat - Earth Sciences bibliographies - in Harvard style

In-text: (Ashman and Watchorn, 2019)

Your Bibliography: Ashman, K. and Watchorn, D., 2019. Quantifying landscape change as a consequence of plantation forestry expansion: a case study of the Koala Zone in south-west Victoria. Australian Forestry, 82(2), pp.116-122.

In-text: (Beranek et al., 2021)

Your Bibliography: Beranek, C., Roff, A., Denholm, B., Howell, L. and Witt, R., 2021. Trialling a real-time drone detection and validation protocol for the koala (Phascolarctos cinereus). Australian Mammalogy, 43(2), p.260.

In-text: (Coops, 2015)

Your Bibliography: Coops, N., 2015. Characterizing Forest Growth and Productivity Using Remotely Sensed Data. Current Forestry Reports, 1(3), pp.195-205.

In-text: (Corcoran et al., 2019)

Your Bibliography: Corcoran, E., Denman, S., Hanger, J., Wilson, B. and Hamilton, G., 2019. Automated detection of koalas using low-level aerial surveillance and machine learning. Scientific Reports, 9(1).

In-text: (Cristescu et al., 2021)

Your Bibliography: Cristescu, R., Gardiner, R., Terraube, J., McDonald, K., Powell, D., Levengood, A. and Frère, C., 2021. Difficulties of assessing the impacts of the 2019–2020 bushfires on koalas. Austral Ecology,.

In-text: (Howell et al., 2021)

Your Bibliography: Howell, L., Clulow, J., Jordan, N., Beranek, C., Ryan, S., Roff, A. and Witt, R., 2021. Drone thermal imaging technology provides a cost-effective tool for landscape-scale monitoring of a cryptic forest-dwelling species across all population densities. Wildlife Research, 49(1), pp.66-78.

In-text: (Law et al., 2017)

Your Bibliography: Law, B., Caccamo, G., Roe, P., Truskinger, A., Brassil, T., Gonsalves, L., McConville, A. and Stanton, M., 2017. Development and field validation of a regional, management‐scale habitat model: A koala <i>Phascolarctos cinereus</i> case study. Ecology and Evolution, 7(18), pp.7475-7489.

In-text: (Law et al., 2022)

Your Bibliography: Law, B., Gonsalves, L., Burgar, J., Brassil, T., Kerr, I., O’Loughlin, C., Eichinski, P. and Roe, P., 2022. Regulated timber harvesting does not reduce koala density in north-east forests of New South Wales. Scientific Reports, 12(1).

In-text: (Law et al., 2021)

Your Bibliography: Law, B., Kerr, I., Gonsalves, L., Brassil, T., Eichinski, P., Truskinger, A. and Roe, P., 2021. Mini‐acoustic sensors reveal occupancy and threats to koalas <i>Phascolarctos cinereus</i> in private native forests. Journal of Applied Ecology, 59(3), pp.835-846.

In-text: (Leigh et al., 2019)

Your Bibliography: Leigh, C., Heron, G., Wilson, E., Gregory, T., Clifford, S., Holloway, J., McBain, M., Gonzalez, F., McGree, J., Brown, R., Mengersen, K. and Peterson, E., 2019. Using virtual reality and thermal imagery to improve statistical modelling of vulnerable and protected species. PLOS ONE, 14(12), p.e0217809.

In-text: (Scarth, Phinn, Held and Mitchell, 2001)

Your Bibliography: Scarth, P., Phinn, S., Held, A. and Mitchell, D., 2001. Mapping koala habitat and eucalyptus trees: integration and scaling of field and airborne hyperspectral data&lt;/title&gt;. SPIE Proceedings,.

In-text: (Seabrook et al., 2003)

Your Bibliography: Seabrook, L., McAlpine, C., Phinn, S., Callaghan, J. and Mitchell, D., 2003. Landscape legacies: Koala habitat change in Noosa Shire, South-east Queensland. Australian Zoologist, 32(3), pp.446-461.

In-text: (Witt et al., 2020)

Your Bibliography: Witt, R., Beranek, C., Howell, L., Ryan, S., Clulow, J., Jordan, N., Denholm, B. and Roff, A., 2020. Real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal. PLOS ONE, 15(11), p.e0242204.

In-text: (Youngentob et al., 2011)

Your Bibliography: Youngentob, K., Renzullo, L., Held, A., Jia, X., Lindenmayer, D. and Foley, W., 2011. Using imaging spectroscopy to estimate integrated measures of foliage nutritional quality. Methods in Ecology and Evolution, 3(2), pp.416-426.

In-text: (Youngentob et al., 2015)

Your Bibliography: Youngentob, K., Yoon, H., Stein, J., Lindenmayer, D. and Held, A., 2015. Where the wild things are: using remotely sensed forest productivity to assess arboreal marsupial species richness and abundance. Diversity and Distributions, 21(8), pp.977-990.