Remote sensing proxies of productivity and moisture predict forest stand type and recovery rate following experimental harvest. Nijland, W., Coops, N. C., Macdonald, S. E., Nielsen, S. E., Bater, C. W., White, B., Ogilvie, J., & Stadt, J. Forest Ecology and Management, 357:239–247, December, 2015. 17 citations (Crossref) [2021-09-18] QID: Q60136105
Remote sensing proxies of productivity and moisture predict forest stand type and recovery rate following experimental harvest [link]Paper  doi  bibtex   
@article{nijland_remote_2015,
	title = {Remote sensing proxies of productivity and moisture predict forest stand type and recovery rate following experimental harvest},
	volume = {357},
	issn = {03781127},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0378112715004594},
	doi = {10/f7zzp5},
	language = {en},
	urldate = {2021-09-18},
	journal = {Forest Ecology and Management},
	author = {Nijland, Wiebe and Coops, Nicholas C. and Macdonald, S. Ellen and Nielsen, Scott E. and Bater, Christopher W. and White, Barry and Ogilvie, Jae and Stadt, John},
	month = dec,
	year = {2015},
	note = {17 citations (Crossref) [2021-09-18]
QID: Q60136105},
	pages = {239--247},
}

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