Home  About us  Contact
 

Image Classification (image + classification)

Distribution by Scientific Domains
Humanities and Social Sciences75%

Selected Abstracts

Land Cover Characteristics in Ne Iceland with Special Reference to Jökulhlaup Geomorphology

GEOGRAFISKA ANNALER SERIES A: PHYSICAL GEOGRAPHY, Issue 3-4 2003
Petteri Alho
ABSTRACT Subglacial eruptions in Vatnajbkull have accounted for several jökulhlaups (glacial outburst floods) in the Northern Volcanic Zone (NVZ). These events and aeolian processes have had a considerable impact on the landscape evolution of the area. Most of this area is occupied by barren land cover; the northern margin of the barren land cover is advancing northwards, burying vegetation under wind-blown sediment. This paper presents a land-cover classification based on a supervised Landsat TM image classification with pre-processing and extensive field observations. Four land cover categories were identified: (a) lava cover (34.8%); (b) barren sediment cover (39.0%); (c) vegetation (25.1%); and (d) water and snow (1.1%). The mapping of sand transport routes demonstrates that a major aeolian sand transportation pathway is situated in the western part of the study area. The sedimentary formation elongated towards the northeast is evidence of active and continuous aeolian sand transportation towards the north. Interpretation of the satellite image suggests that four main areas are affected by jökulhlaups along the Jökulsáá Fjöllum: Ásbyrgi, Grímsstaðir, Herðubreið,Möðrudalur, and the Dyngjujökull sandur. In addition, jökulhlaup-related sediment cover (8%) in the study area, together with erosional features, are evidence of a severe and extensive jökulhlaup-induced process of land degradation. [source]

Remote sensing of permafrost-related problems and hazards

PERMAFROST AND PERIGLACIAL PROCESSES, Issue 2 2008
Andreas Kääb
Abstract Modern remote sensing techniques can help in the assessment of permafrost hazards in high latitudes and cold mountains. Hazard development in these areas is affected by process interactions and chain reactions, the ongoing shift of cryospheric hazard zones due to atmospheric warming, the large spatial scales involved and the remoteness of many permafrost-related threats. This paper reviews ground-based, airborne and spaceborne remote sensing methods suitable for permafrost hazard assessment and management. A wide range of image classification and change detection techniques support permafrost hazard studies. Digital terrain models (DTMs) derived from optical stereo, synthetic aperture radar (SAR) or laser scanning data are some of the most important data sets for investigating permafrost-related mass movements, thaw and heave processes, and hydrological hazards. Multi-temporal optical or SAR data are used to derive surface displacements on creeping and unstable frozen slopes. Combining DTMs with results from spectral image classification, and with multi-temporal data from change detection and displacement measurements significantly improves the detection of hazard potential. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Application of QuickBird and aerial imagery to detect Pinus radiata in remnant vegetation

AUSTRAL ECOLOGY, Issue 6 2010
NERISSA HABY
Abstract The invasion of Pinus radiata from long-term established plantations is contributing to the degradation of fragmented and isolated remnants of native vegetation. Within the south-east of South Australia, the 20 vegetation communities that occur within 500 m of a plantation edge are at risk, including nine state threatened communities. To plan effective mitigation strategies, the current extent and distribution of P. radiata needs to be ascertained. High spatial resolution, multispectral QuickBird imagery and aerial photography were used to classify P. radiata within eucalypt and acacia woodlands, melaleuca shrubland, modified pasture and an Eucalyptus globulus plantation. Unsupervised classification of aerial photography gave the best result showing reasonable conformity with the observed distribution of P. radiata at the site scale. However, the 9.4 ± 13.5 (SD) cover classified in the quadrats sampled for the accuracy assessment exceeded the 1.4 ± 2.4 (SD) P. radiata cover determined from an independent dataset. Only 30.1 ± 37.9% (SD) of trees within the quadrats and 9.40 ± 13.49% (SD) of their foliage cover were classified. Trees detected by partial classification of canopy were positively correlated with both tree height and canopy diameter. Overall, the low detection rates were attributed to insufficient spectral resolution. Using higher resolution imagery, together with an object-based image analysis or combination of multispectral and airborne digital image classification, restricted to large emergent adult trees using LiDAR analysis, is likely to improve adult P. radiata detection accuracy. [source]