A Preliminary Assessment of Hyperspectral Remote Sensing Technology for Mapping Submerged Aquatic Vegetation in the Upper Delaware River National Parks (USA)  

作　　者：Slonecker Terrence Kalaly Siddiq Young John Furedi Mary Ann Maloney Kelley Hamilton Don Evans Richard Zinecker Elizabeth 

机构地区：[1]U.S. Geological Survey, National Civil Applications Center, Reston, Virginia, USA [2]U.S. Geological Survey, Earth Resources Observation and Science Center (EROS), Sioux Falls, South Dakota, USA [3]U.S. Geological Survey, Leetown Science Center, Kearneysville, West Virginia, USA [4]Western Pennsylvania Conservancy, Harrisburg, Pennsylvania, USA [5]U.S. Geological Survey, Leetown Science Center, Wellsboro, Pennsylvania, USA [6]National Park Service, Beach Lake, Pennsylvania, USA [7]U.S. Geological Survey, Eastern Geographic Science Center, Reston, Virginia, USA

出　　处：《Advances in Remote Sensing》2018年第4期290-312,共23页遥感技术进展（英文）

摘　　要：Hyperspectral remote sensing of submerged aquatic vegetation is a complex and difficult process that is affected by unique constraints on the energy flow profile near and below the water surface. In addition, shallow, winding, lotic systems, such as the Upper Delaware River, present additional remote sensing problems in the form of specular reflectance, variable depth and constituents in the water column and sometimes extremely weak signal strength due to absorption and scattering in the water column that can be statistically overwhelmed by the reflectance from upland vegetation in any individual image scene. Here we test hyperspectral imagery from the Civil Air Patrol’s (CAP), Airborne Real-time Cueing Hyperspectral Enhanced Recon (ARCHER) system in the scenic waters of two National Parks on the Upper Delaware River. A number of unique image processing problems were encountered, including specular reflectance from winding lotic systems, variable depth and flow dynamics of the riverine environment, and disproportionate signal strength from surface reflectance in this riverine environment. These problems were solved by applying a specular reflectance removal algorithm, applying field data collections to classification results and masking upland vegetation so as to not statistically overwhelm the weak reflectance signal from surface and near-surface water. Much was learned about conducting imaging spectroscopy in such difficult conditions. Important results include successful mapping of Submerged Aquatic Vegetation (SAV) presence/absence, advantages of upland masking of the reflectance signal, and a number of processing approaches that are unique to this environment. In this paper we summarize our results and identify unique issues that must be addressed in this environment.Hyperspectral remote sensing of submerged aquatic vegetation is a complex and difficult process that is affected by unique constraints on the energy flow profile near and below the water surface. In addition, shallow, winding, lotic systems, such as the Upper Delaware River, present additional remote sensing problems in the form of specular reflectance, variable depth and constituents in the water column and sometimes extremely weak signal strength due to absorption and scattering in the water column that can be statistically overwhelmed by the reflectance from upland vegetation in any individual image scene. Here we test hyperspectral imagery from the Civil Air Patrol’s (CAP), Airborne Real-time Cueing Hyperspectral Enhanced Recon (ARCHER) system in the scenic waters of two National Parks on the Upper Delaware River. A number of unique image processing problems were encountered, including specular reflectance from winding lotic systems, variable depth and flow dynamics of the riverine environment, and disproportionate signal strength from surface reflectance in this riverine environment. These problems were solved by applying a specular reflectance removal algorithm, applying field data collections to classification results and masking upland vegetation so as to not statistically overwhelm the weak reflectance signal from surface and near-surface water. Much was learned about conducting imaging spectroscopy in such difficult conditions. Important results include successful mapping of Submerged Aquatic Vegetation (SAV) presence/absence, advantages of upland masking of the reflectance signal, and a number of processing approaches that are unique to this environment. In this paper we summarize our results and identify unique issues that must be addressed in this environment.

关 键 词：LOTIC systems SUBMERGED AQUATIC VEGETATION Didymo germinata HYPERSPECTRAL Remote Sensing HYPERSPECTRAL processing methods 

分 类 号：R73[医药卫生—肿瘤]