Detection of urban tree canopy from very high resolution imagery using an object based classification

Urban classification by pixel and object-based approaches for very high resolution imagery

An Object-Based Classification Approach in Mapping Tree Mortality Using High Spatial Resolution Imagery

In California, a newly discovered virulent pathogen (Phytophthora ramorum) has killed thousands of trees, including tanoak (Lithocarpus densiflorus), coast live oak (Quercus agrifolia), and black oak (Quercus kelloggii). Mapping the distribution of overstory mortality associated with the pathogen is an important part of disease management. In this study, we developed an object-based approach, i...

Mapping Urban Tree Species Using Very High Resolution Satellite Imagery: Comparing Pixel-Based and Object-Based Approaches

We assessed the potential of multi-spectral GeoEye imagery for biodiversity assessment in an urban context in Bangalore, India. Twenty one grids of 150 by 150 m were randomly located in the city center and all tree species within these grids mapped in the field. The six most common species, collectively representing 43% of the total trees sampled, were selected for mapping using pixel-based and...

An object-based classification approach for high-spatial resolution Imagery

With the recent availability of commercial high resolution remote sensing multispectral imagery from sensors such as IKONOS and QuickBird, we can’t get the accuracy of land-cover classification expected using pixel-based approach. In this paper, we bring about object-based approach combined with the nearest neighbor to classify the QuickBird image of LianYungang city. Firstly, the image is segm...

Comparing Machine Learning Classifiers for Object-Based Land Cover Classification Using Very High Resolution Imagery

This study evaluates and compares the performance of four machine learning classifiers—support vector machine (SVM), normal Bayes (NB), classification and regression tree (CART) and K nearest neighbor (KNN)—to classify very high resolution images, using an object-based classification procedure. In particular, we investigated how tuning parameters affect the classification accuracy with differen...