The increasing expansion of rubber plantations throughout East and Southeast Asia urgently requires improved methods for effective mapping and monitoring. The phenological information from rubber plantations was found effective in rubber mapping. Previous studies have mostly applied rule-pixel-based phenology approaches for rubber plantations mapping, which might result in broken patches in fra...

In the dwindling natural mangrove today, mangrove reforestation projects are conducted worldwide to prevent further losses. Due to monoculture and the low survival rate of artificial mangroves, it is necessary to pay attention to mapping and monitoring them dynamically. Remote sensing techniques have been widely used to map mangrove forests due to their capacity for large-scale, accurate, effic...

This study focuses on the comparison between the classical and object-oriented image classifications of remote sensing imagery in the arid area. Due to its special geographic environment and socio-economic contexts, the land cover and its spatio-temporal pattern in aridzone is very different from those in coastal area, thus some conventional methods of remote sensing image classification may no...

The prevailing concerns on ecological and environmental issues, occurring especially at regional to global scales, have prompted significant advances on the use of remote sensing data for the estimation of land cover information at sub-pixel level. However, the quality of such classification products, as well as the performance of the classification protocol employed, are difficult to quantify....

Image holistic scene understanding based on image intrinsic characteristics and conditional random fields is proposed. The model integrates image scene classification, image semantic segmentation and object detection. 1) For the scene classification, we use method of PHOW feature extraction plus KPCA dimensional reduction to obtain feature information for each image. 2) For object detection sec...

This paper presents a Learning Vector Quantization (LVQ)-based temporal tracking method for semi-automatic video object segmentation. A semantic video object is initialized using user assistance in a reference frame to give initial classification of video object and its background regions. The LVQ training approximates video object and background classification and use them for automatic segmen...