Land-cover Sub-pixel Classification Using Linear Mixture Model on Landsat Etm + Data in Egypt
نویسندگان
چکیده
One of the most important problems facing land cover mapping effort in Egypt is intensive and mixed landcover areas, which represent the majority of agricultural productive areas. This study was carried out to evaluate the possibility of using Linear Mixture Model as a sub pixel classification technique to extract fraction images from Landsat Enhanced Thematic Mapper data, which may help in future to increase the accuracy of landcover mapping in the mixed agricultural areas . In this study, Linear Mixture Model was applied to classify the main land covers in the study area and the different agricultural types. Relationship between fraction images and NDVI was determined. The fraction images were compared with ground truth data for validation .
منابع مشابه
Fuzzy Classification of Mediterranean Type Forest Using Envisat Meris Data
The aim of this study was to classify Envisat MERIS and Landsat ETM satellite sensor imagery using fuzzy classification techniques such as, linear mixture modelling and artificial neural networks. The images were classified successfully using these two techniques. The fuzzy results were more accurate then hard classification. Landsat ETM imagery was classified using maximum likelihood classifie...
متن کاملLandsat Etm Sub-pixel Analysis of Urban Landscape Using Fuzzy C- Means Clustering and Differentiated Impervious Surface Classes
Fuzzy c-means clustering (FCM) algorithm has been used to analyze the sub-pixel composition of medium spatialresolution satellite image (i.e., Landsat ETM). As urban landscape shows complex patterns of land cover composition and setting, it is difficult to have high accuracy in estimating urban land cover composition from Landsat image because of the mixed pixel problem. This study evaluates th...
متن کاملComparing the Capability of Sentinel 2 and Landsat 8 Satellite Imagery in Land Use and Land Cover Mapping Using Pixel-based and Object-based Classification Methods
Introduction: Having accurate and up-to-date information on the status of land use and land cover change is a key point to protecting natural resources, sustainable agriculture management and urban development. Preparing the land cover and land use maps with traditional methods is usually time and cost consuming. Nowadays satellite imagery provides the possibility to prepare these maps in less ...
متن کاملAssimilation of endmember variability in spectral mixture analysis for urban land cover extraction
Variable Endmember Constrained Least Square (VECLS) technique is proposed to account endmember variability in the linear mixture model by incorporating the variance for each class, the signals of which varies from pixel to pixel due to change in urban land cover (LC) structures. VECLS is first tested with a computer simulated three class endmember considering four bands having small, medium and...
متن کاملSnow-cover mapping in forests by constrained linear spectral unmixing of MODIS data
A snow-cover mapping method accounting for forests (SnowFrac) is presented. SnowFrac uses spectral unmixing and endmember constraints to estimate the snow-cover fraction of a pixel. The unmixing is based on a linear spectral mixture model, which includes endmembers for snow, conifer, branches of leafless deciduous trees and snow-free ground. Model input consists of a land-cover fraction map and...
متن کامل