Asset Details
Do you wish to reserve the book?
Spatially Clustered Survey Designs
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Spatially Clustered Survey Designs
Do you wish to request the book?
Spatially Clustered Survey Designs
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Spatially Clustered Survey Designs
2024
Overview
Direct observation, through surveys, underpins nearly all aspects of environmental sciences. Survey design theory has evolved to make sure that sampling is as efficient as possible whilst remaining robust and fit-for-purpose. However, these methods frequently focus on theoretical aspects and often increase the logistical difficulty of performing the survey. Usually, the survey design process will place individual sampling locations one-by-one throughout the sampling area (e.g. random sampling). A consequence of these approaches is that there is usually a large cost in travel time between locations. This can be a huge problem for surveys that are large in spatial scale or are in inhospitable environments where travel is difficult and/or costly. Our solution is to constrain the sampling process so that the sample consists of spatially clustered observations, with all sites within a cluster lying within a predefined distance. The spatial clustering is achieved by a two-stage sampling process: first cluster centres are sampled and then sites within clusters are sampled. A novelty of our approach is that these clusters are allowed to overlap and we present the necessary calculations required to adjust the specified inclusion probabilities so that they are respected in the clustered sample. The process is illustrated with a real and on-going large-scale ecological survey. We also present simulation results to assess the methods performance. Spatially clustered survey design provides a formal statistical framework for grouping sample sites in space whilst maintaining multiple levels of spatial-balance. These designs reduce the logistical burden placed on field workers by decreasing total travel time and logistical overheads.Supplementary materials accompanying this paper appear on-line.
Publisher
Springer US,Springer,Springer Nature B.V
Subject
