Quantifying Uncertainty in Land-Use/Land-Cover Classification Accuracy: A Stochastic Simulation Approach
نویسندگان
چکیده
منابع مشابه
Status of land cover classification accuracy assessment
The production of thematic maps, such as those depicting land cover, using an image classification is one of the most common applications of remote sensing. Considerable research has been directed at the various components of the mapping process, including the assessment of accuracy. This paper briefly reviews the background and methods of classification accuracy assessment that are commonly us...
متن کاملA Bayesian Framework for Quantifying Uncertainty in Stochastic Simulation
When we use simulation to estimate the performance of a stochastic system, the simulation often contains input models that were estimated from real-world data; therefore, there is both simulation and input uncertainty in the performance estimates. In this paper, we provide a method to measure the overall uncertainty while simultaneously reducing the influence of simulation estimation error due ...
متن کاملSequential Land Cover Classification
Land cover classification using remotely sensed data is a critical first step in large-scale environmental monitoring, resource management and regional planning. The classification task is made difficult by severe atmospheric scattering and absorption, seasonal variation, spatial dependence, complex surface dynamics and geometries, and large intra-class variability. Most of the recent research ...
متن کاملA Robust Texture Analysis and Classification Approach for Urban Land-Use and Land-Cover Feature Discrimination
Attempts to analyze urban features and to classify land use and land cover directly from high-resolution satellite data with traditional computer classification techniques have proven to be inefficient for two primary reasons. First, urban landscapes are composed of complex features. Second, traditional classifiers employ spectral information based on single pixel value and ignore a great amoun...
متن کاملImproving the Accuracy of Land Use and Land Cover Classification of Landsat Data Using Post-Classification Enhancement
Classifying remote sensing imageries to obtain reliable and accurate land use and land cover (LULC) information still remains a challenge that depends on many factors such as complexity of landscape, the remote sensing data selected, image processing and classification methods, etc. The aim of this paper is to extract reliable LULC information from Landsat imageries of the Lower Hunter region o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Environmental Science
سال: 2021
ISSN: 2296-665X
DOI: 10.3389/fenvs.2021.628214