Coastwide Reference Monitoring System (CRMS) 2018 Site 0396 land-water classification data

Wetland restoration efforts conducted by the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in Louisiana rely on monitoring efforts to determine the efficacy of these efforts. The Coastwide Reference Monitoring System (CRMS) was developed to assist in a multiple-reference approach that uses aspects of hydrogeomorphic functional assessments and probabilistic sampling for monitoring. The CRMS program includes a suite of approximately 398 sites that encompass the range of hydrological and ecological conditions for each stratum. As part of CRMS, land and water classifications are created from Digital Orthophoto Quarter Quadrangles (DOQQs) approximately every three years at all CRMS sites. A DOQQ is a raster image in which displacement in the image caused by sensor orientation and terrain relief has been removed and combines the image characteristics of a photo with geometric qualities of a map. The DOQQs generated for this project consist of 2018 Color Infrared (CIR) Digital Imagery. These images were classified into land and water categories using a threshold of the near infrared (NIR) band, followed by supervised and unsupervised classification. Initial classification results are then reviewed by multiple image analysts to identify and manually recode errors. The final land-water classifications are intended to serve as both geographic and quantitative assessments of landscape composition on the date of acquisition. Four previous assessments have been conducted (2005, 2008, 2012, and 2015/2016). Once the program creates enough data points for statistical analyses, these data will be used for land area change rate calculation.

路易斯安那州依托《沿海湿地规划、保护与恢复法案》（Coastal Wetlands Planning, Protection and Restoration Act, CWPPRA）开展的湿地修复工作，需通过监测评估此类修复举措的实施成效。全海岸参考监测系统（Coastwide Reference Monitoring System, CRMS）由此开发，旨在支撑采用水文地貌功能评估与概率抽样方法的多参考点监测方案。CRMS项目共包含约398个监测站点，覆盖各分层的水文与生态条件范围。作为CRMS的核心工作之一，所有CRMS站点每三年左右便会基于数字正射影像四分幅（Digital Orthophoto Quarter Quadrangles, DOQQs）生成土地与水体分类成果。数字正射影像四分幅属于栅格影像，已消除传感器姿态与地形起伏导致的影像位移，兼具航空影像的成像特质与地图的几何精度。本项目所使用的DOQQs数据为2018年彩色红外（Color Infrared, CIR）数字影像。研究人员先通过近红外（near infrared, NIR）波段阈值法完成初步分类，随后结合监督分类与非监督分类完成土地与水体类别的划分。初步分类结果将由多名影像分析师复核，以识别并手动修正分类误差。最终的土地-水体分类成果，可用于获取影像采集当日景观组成的地理与定量评估信息。该项目此前已完成四次评估（2005年、2008年、2012年及2015/2016年）。待项目积累足够用于统计分析的数据点后，相关数据将用于计算陆地面积变化速率。