Abstract Density and undeveloped land can be identified using digital transformation through remote sensing data. This study aims to map the distribution of building densities with Normalized Difference Built-Up Index (NDBI) Urban (UI), analyze comparison NDBI UI methods, relationship between on in Banjarmasin City. The data used obtain density image Landsat 8 Oli Tirs. method separate built ar...

In this paper we face the problem of covering a physical area with acoustic signals emitted by different sources, and we present a declarative and effective solution based on Constraint Logic Programming over Finite Domains. After a testing phase on toy examples, we have successfully applied the code to the solution of a real-world placement problem.

Urban built-up area information is required by various applications. However, urban built-up area extraction using moderate resolution satellite data, such as Landsat series data, is still a challenging task due to significant intra-urban heterogeneity and spectral confusion with other land cover types. In this paper, a new method that combines spectral information and multivariate texture is p...

Built-up area extraction from polarimetric SAR (PolSAR) imagery has a close relationship with urban planning, disaster management, etc. Since the buildings have complex geometries and may be misclassified as forests due to the significant cross-polarized scattering, built-up area extraction from PolSAR data is still a challenging problem. This paper proposes a new urban extraction method for Po...

In this paper, we present a dense matching algorithm which utilizes the corner and edge features of images to increase the reliability and to speed up the process of dense matching of two uncalibrated images. The major problem of classical area-based dense matching algorithms is the high computational time resulting from intensive correlation calculations for match candidates. Although some met...

This paper presents a methodology for recognizing, identifying and classifying built objects in dense urban areas, using a morphospectral approach applied to VNIR/SWIR hyperspectral image (HySpex). This methodology contains several image processing steps: Principal Components Analysis and Laplacian enhancement, Feature Extraction of segmented build-up objects, and supervised classification from...

Given a set of high-resolution remote sensing images covering different scenes an unsupervised approach to simultaneously detect possible built-up areas from them. The motivation behind is that the frequently recurring appearance patterns or repeated textures corresponding to common objects of interest (e.g., built-up areas) in the input image data set can help us discriminate built-up areas fr...