caa a22 4500 475762509 CHVBK 20180406123555.0 cr unu---uuuuu 170329e20000901xx s 000 0 eng 10.1023/A:1009619117138 doi (NATIONALLICENCE)springer-10.1023/A:1009619117138 Mandallaz Daniel Forest Inventory and Planning, ETH Zu¨rich, CH-8092, Zu¨rich, Switzerland aut Estimation of the spatial covariance in Universal Kriging: Application to forest inventory [Elektronische Daten] [Daniel Mandallaz] This paper presents a simple least squares procedure for estimating the spatial covariance and compares it with the numerically more difficult restricted maximum likelihood procedure. Thereafter, it compares design-based and kriging techniques for the estimation of spatial averages in the context of double sampling, as used in forest inventory, where terrestrial sample plots are combined with auxiliary information based on aerial photographs. A case study illustrates the theory. Kluwer Academic Publishers, 2000 least squares nationallicence restricted maximum likelihood nationallicence Kriging nationallicence two-phase two-stage sampling nationallicence Environmental and Ecological Statistics Kluwer Academic Publishers 7/3(2000-09-01), 263-284 1352-8505 7:3<263 2000 7 10651 https://doi.org/10.1023/A:1009619117138 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1009619117138 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Mandallaz Daniel Forest Inventory and Planning, ETH Zu¨rich, CH-8092, Zu¨rich, Switzerland aut NATIONALLICENCE 773 0- Environmental and Ecological Statistics Kluwer Academic Publishers 7/3(2000-09-01), 263-284 1352-8505 7:3<263 2000 7 10651 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer