TY - JOUR
T1 - Wetland mapping in the Upper Midwest United States: an object-based approach integrating lidar and imagery data
T2 - An object-based approach integrating lidar and imagery data
AU - Rampi, Lian P.
AU - Knight, Joseph F.
AU - Pelletier, Keith C.
PY - 2014/5
Y1 - 2014/5
N2 - This study investigated the effectiveness of using high resolution data to map wetlands in three ecoregions in Minnesota. High resolution data included multispectral leaf-off aerial imagery and lidar elevation data. These data were integrated using an Object-Based Image Analysis (OBIA) approach. Results for each study area were compared against field and image interpreted reference data using error matrices, accuracy estimates, and the kappa statistic. Producer's and user's accuracies were in the range of 92 to 96 percent and 91 to 96 percent, respectively, and overall accuracies ranged from 96-98 percent for wetlands larger than 0.20 ha (0.5 acres). The results of this study may allow for increased accuracy of mapping wetlands efforts over traditional remote sensing methods.
AB - This study investigated the effectiveness of using high resolution data to map wetlands in three ecoregions in Minnesota. High resolution data included multispectral leaf-off aerial imagery and lidar elevation data. These data were integrated using an Object-Based Image Analysis (OBIA) approach. Results for each study area were compared against field and image interpreted reference data using error matrices, accuracy estimates, and the kappa statistic. Producer's and user's accuracies were in the range of 92 to 96 percent and 91 to 96 percent, respectively, and overall accuracies ranged from 96-98 percent for wetlands larger than 0.20 ha (0.5 acres). The results of this study may allow for increased accuracy of mapping wetlands efforts over traditional remote sensing methods.
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U2 - 10.14358/PERS.80.5.439
DO - 10.14358/PERS.80.5.439
M3 - Article
AN - SCOPUS:84901407766
SN - 0099-1112
VL - 80
SP - 439
EP - 448
JO - Photogrammetric Engineering and Remote Sensing
JF - Photogrammetric Engineering and Remote Sensing
IS - 5
ER -