Premium
Spatially balanced sampling and ground‐level imagery for vegetation monitoring on reclaimed well pads
Author(s) -
Curran Michael F.,
Cox Samuel E.,
Robinson Timothy J.,
Robertson Blair L.,
Rogers Karen J.,
Sherman Zoe A.,
Adams Todd A.,
Strom Calvin F.,
Stahl Peter D.
Publication year - 2019
Publication title -
restoration ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.214
H-Index - 100
eISSN - 1526-100X
pISSN - 1061-2971
DOI - 10.1111/rec.12956
Subject(s) - land reclamation , transect , vegetation (pathology) , environmental resource management , sampling (signal processing) , land cover , environmental science , site selection , computer science , land use , geography , civil engineering , ecology , engineering , medicine , archaeology , filter (signal processing) , pathology , law , political science , computer vision , biology
Land reclamation associated with natural gas development has become increasingly important to mitigate land surface disturbance in western North America. Since well pads occur on sites with multiple land use and ownership, the progress and outcomes of these efforts are of interest to multiple stakeholders including industry, practitioners and consultants, regulatory agents, private landowners, and the scientific community. Reclamation success criteria often vary within, and among, government agencies and across land ownership type. Typically, reclamation success of a well pad is judged by comparing vegetation cover from a single transect on the pad to a single transect in an adjacent reference site and data are collected by a large number of technicians with various field monitoring skills. We utilized “SamplePoint” image analysis software and a spatially balanced sampling design, called balanced acceptance sampling, to demonstrate how spatially explicit quantitative data can be used to determine if sites are meeting various reclamation success criteria and used chi‐square tests to show how sites in vegetation percent cover differ from a statistical standpoint. This method collects field data faster than traditional methods. We demonstrate how quantitative and spatially explicit data can be utilized by multiple stakeholders, how it can improve upon current reference site selection, how it can satisfy reclamation monitoring requirements for multiple regulatory agencies, how it may help improve future seed mix selection, and discuss how it may reduce costs for operations responsible for reclamation and how it may reduce observer bias.