Accuracy of landsat-TM and GIS rule-based methods for forest wetland classification in Maine☆
References (34)
Use of high-altitude aerial photography for inventorying forested wetlands in the United States
Forest Ecol. Management
(1990)A Comparison of Satellite and GIS Classification Techniques for Delineating Forested Wetlands
(1994)- et al.
A land use and land cover classification system for use with remote sensor data
U.S. Geological Survey Professional Paper 964
(1976) - et al.
Rule-based classification models: flexible integration of satellite imagery and thematic spatial data
Photogram. Engineering Remote Sens.
(1992) Introduction to Remote Sensing
(1987)Knowledge-based land use and land cover mapping
Tech. Papers, 1989 ACSM-ASPRS Annual Convention
(1989)A coefficient of agreement for nominal scales
Educational Psychol. Measur.
(1960)- et al.
A quantitative method to test for consistency and correctness in photo-interpretation
Photogram. Engineering Remote Sens.
(1983) - et al.
Accuracy of remotely sensed data: sampling and analysis procedures
- et al.
Assessing Landsat classification accuracy using discrete multivariate analysis statistical techniques
Photogram. Engineering Remote Sens.
(1983)
A Classification of Wetlands and Deepwater Habitats of the United States
A physically based transformation of thematic mapper data—the TM tasseled cap
IEEE Trans. Geosci. Remote Sens.
Application of the tasseled cap concept to simulated thematic mapper data
Photogram. Engineering Remote Sens.
Coastwatch—detecting change in coastal wetlands
Geo. Info Systems
ERDAS PC Field Guide
PC ARC/INFO Starter Kit
Application of satellite data for mapping and monitoring wetlands
Wetlands Subcommittee Technical Report 1
Cited by (152)
Impact of railways on land use and land cover change: Evidence from India
2023, Transportation Research Part D: Transport and EnvironmentClassifying vegetation communities karst wetland synergistic use of image fusion and object-based machine learning algorithm with Jilin-1 and UAV multispectral images
2022, Ecological IndicatorsCitation Excerpt :This paper used the testing samples data to quantitatively evaluate classification accuracy of different schemes and classifiers for mapping karst wetland vegetation communities. At the 95% confidence interval, the confusion matrix was established for nine classification schemes to calculate the overall accuracy and kappa coefficient, respectively (Sader et al., 1995). The user’s and producer’s accuracy, average accuracy (AA, the average value of user accuracy and producer accuracy) (Mui et al., 2015; Mahdavi et al., 2019) were also calculated to evaluate accuracy differences of vegetation communities.
Development of integrated wetland change detection approach: In case of Erdos Larus Relictus National Nature Reserve, China
2020, Science of the Total EnvironmentMonitoring the spatio-temporal dynamics of the wetland vegetation in Poyang Lake by Landsat and MODIS observations
2020, Science of the Total Environment
- ☆
This research was supported by NOAA Coastal Ocean Program, Coastwatch Change Analysis Program under Grant #NA26RG0420-01 to the Sea Grant Program of the University of Maine.
- 1
The authors extend their thanks to Dr. Robert Wall, Director of the UM Sea Grant Program, and his staff for administrative support. Cindy Paschal provided timely and efficient support in manuscript preparation, which was greatly appreciated. Constructive comments from anonymous reviewers also were appreciated and incorporated in the final manuscript. Maine Agriculture and Forestry Experiment Station External Publication #1882.