Segmentation and classification are two imperative, yet challenging tasks in image analysis
for remote-sensing applications. In the former, an image is divided into spatially continuous …

In this paper, a hierarchical probabilistic graphical model is proposed to tackle joint
classification of multiresolution and multisensor remote sensing images of the same scene …

High-spatial-resolution images play an important role in land cover classification, and object-
based image analysis (OBIA) presents a good method of processing high-spatial-resolution …

Multisource image analysis that leverages complementary spectral, spatial, and structural
information benefits fine-grained object recognition that aims to classify an object into one of …

Grassland resources guarantee the balance of ecosystems and the sustainable
development of animal husbandry. Spatial information is essential for grass resource …

Precise vegetation maps of mountainous areas are of great significance to grasp the
situation of an ecological environment and forest resources. In this paper, while multi-source …

This paper proposed a new remote sensing observation capability evaluation model
(RSOCE) based on analytic hierarchy process to quantitatively evaluate the capability of …

Multimodal remote sensing data analysis can strongly improve the characterization of
physical phenomena on Earth's surface. Nonetheless, nonidealities and estimation …

Ikot Abasi coastal area in Southern Nigeria, have witnessed enormous human activities
which include commercial agriculture, industrial activities and urban development over the …

Accurate and time-efficient classification methods for multitemporal imagery and satellite
image time series are important tools required to support the rapid and reliable extraction of …