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A novel geospatial machine learning approach to quantify no..:
Kang, Jing
;
Zhang, Bailing
;
Dang, Anrong
International Journal of Applied Earth Observation and Geoinformation. 128 (2024) - p. 103712 , 2024
Link:
https://doi.org/10.1016/j.jag.2024.103712
RT Journal T1 <Title>A novel geospatial machine learning approach to quantify non-linear effects of land use/land cover change (LULCC) on carbon dynamics</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.jag.2024.103712&Exemplar=1&LAN=DE A1 Kang, Jing A1 Zhang, Bailing A1 Dang, Anrong PB Elsevier BV YR 2024 SN 1569-8432 JF International Journal of Applied Earth Observation and Geoinformation VO 128 SP 103712 LK http://dx.doi.org/https://doi.org/10.1016/j.jag.2024.103712 DO https://doi.org/10.1016/j.jag.2024.103712 SF ELIB - SuUB Bremen
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