Landuse vector data generalisation is to derive a new landuse dataset or map from an initial dataset by removing the minor details. The generalised results should delineate the dominant landuse characteristics of important landuse types in a reduced map space or a theme-specific application. The generalisation process are guided and controlled by a set of generalisation rules serving for the re...

The landuse or land-cover map depicts the physical coverage of the Earth’s terrestrial surface according to its use. Landuse map generation from remotely sensed images is one of the challenging tasks of remote sensing technology. In this article, motivated from group forming behavior of real ants, we have proposed two novel ant based (one supervised and one unsupervised) algorithms to automatic...

Two landuse grids were available for these catchments; one in 1995 was derived from satellite imagery and contained a relatively undifferentiated landuse classification (lumping all forest types into one category); the other in 2003 was derived from a mix of satellite imagery, ground truthing, and mapping, and better differentiated between landuse types (dividing forest types into evergreen, de...

Landuse change in metropolitan areas is largely focused on the dynamic nature of urban landuse change. In this research, a spatial statistical model was used to support decision-making with regard to urban growth predictions in the urban fringe of Beijing, China. The model adopted in this study was based on the integration of remote sensing, geographical information systems, and multivariate ma...

Artificial Neural Network (ANN) is an important Artificial Intelligence (AI) and Machine Learning (ML) method used in various remote sensing applications such as image classification, pattern recognition etc.One of important remote sensing applications is the landuse classification i.e. classification of satellite data into various landuse classes such as forest, waterbody, snowcover etc. Landu...

An OpenStreetMap (OSM) landuse and landcover product (LULC) was published under osmlanduse.org. The product is based on the globally accessible OSM-data and the landuse classes orient themselves towards the legend of the Coordination of Information on the Environment (CORINE). Specific OSM tags are used to create classes in OSM LULC. The product is freely accessible and a first prototype for a ...

This paper analyses the effect of spatial input data resolution on the simulated effects of regional scale landuse scenarios using the TOPLATS model. A data set of 25 m resolution of the central German Dill catchment (693 km2) and three different landuse scenarios are used for the investigation. Landuse scenarios in this study are field size scenarios, and depending on a specific target field s...

This study examines the use of image processing and remote sensing in landuse changes mapping for Palladam Taluk between 1972(Topographic sheets) and 2011(satellite images). The layers of landuse map (1972) were digitized by heads-up digitization method in Quantum GIS (QGIS) software environment. Similarly the layers of landuse map (2011) were developed by supervised classification of satellite...

It is now common to use data from two or more sensors for land cover change detection. Since the spatial and spectral resolutions of different sensors vary significantly, the ability to discriminate the land cover also varies greatly. In this paper the applications of landuse change detection including area statistics, temporal trajectories and spatial pattern are discussed. The area statistics...

The Alps provide a high habitat diversity for plant species, structured by broadand fine-scale abiotic site conditions. In man-made grasslands, vegetation composition is additionally affected by the type of landuse. We recorded vegetation composition in 216 parcels of grassland in 12 municipalities representing an area of 170 70 km in the south-eastern part of the Swiss Alps. Each parcel was ch...