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Showing items 1 through 9 of 203.
  1. Library Resource
    Journal Articles & Books
    December, 2011
    China

    The Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud and land Elevation Satellite (ICESat) provides elevation data with very high accuracy which can be used as ground data to evaluate the vertical accuracy of an existing Digital Elevation Model (DEM). In this article, we examine the differences between ICESat elevation data (from the 1064 nm channel) and Shuttle Radar Topography Mission (SRTM) DEM of 3 arcsec resolution (90 m) and map-based DEMs in the Qinghai-Tibet (or Tibetan) Plateau, China.

  2. Library Resource
    Journal Articles & Books
    December, 2012

    Effects of incorporating multi-seasonal information into image classifications for large-scale land cover mapping are investigated. Data from four Landsat7 ETM+ scenes (March, May, June 2002, September 1999) were included step-wise into classifications by discriminant analysis to document their relevance for classification accuracy. The classification using all four images reached a maximum accuracy of 69.2%, significantly higher compared with single-date classifications and showing less fluctuations in classification accuracy.

  3. Library Resource
    Journal Articles & Books
    December, 2012

    A disaggregated approach to land cover survey is developed utilising data primitives. A field methodology is developed to characterise five attributes: species composition, cover, height, structure and density. The utility of these data primitives, as land cover ‘building blocks’ is demonstrated via classification of the field data to multiple land cover schema. Per-pixel classification algorithms, trained on the basis of the classified field data, are utilised to classify a SPOT 5 satellite image. The resultant land cover maps have overall accuracies approaching 80%.

  4. Library Resource
    Journal Articles & Books
    December, 2013
    China

    Accurate and timely land cover change detection at regional and global scales is necessary for both natural resource management and global environmental change studies. Satellite remote sensing has been widely used in land cover change detection over the past three decades. The variety of satellites which have been launched for Earth Observation (EO) and the large volume of remotely sensed data archives acquired by different sensors provide a unique opportunity for land cover change detection.

  5. Library Resource
    Journal Articles & Books
    December, 2014

    Image segmentation is a basic and important procedure in object-based classification of remote-sensing data. This study presents an approach to multi-scale optimal segmentation (OS), given that single-scale segmentation may not be the most suitable approach to map a variety of land-cover types characterized by various spatial structures; it objectively measures the appropriate segmentation scale for each object at various scales and projects them onto a single layer. A 1.8 m spatial resolution Worldview-2 image was used to perform successive multi-scale segmentations.

  6. Library Resource
    Journal Articles & Books
    December, 2014

    A new locally-adaptive image classification method LAGMA (Locally-Adaptive Global Mapping Algorithm) has been developed to meet requirements of land cover mapping over large areas using remote-sensing data. The LAGMA involves the grid-based supervised image classification using classes’ features estimated locally in classified pixels’ surrounding from spatially distributed reference data.

  7. Library Resource
    Journal Articles & Books
    December, 2014

    Potential data sets for landcover classification, such as Landsat (or pre-processed data such as the National Land Cover Dataset (NLCD)), are often too coarse for fine-scale research needs or are cost-prohibitive (Quickbird, Ikonos and Geoeye). Repeated attempts at classifying high spatial resolution data, National Agricultural Imagery Program (NAIP) imagery, based on traditional techniques, such as a maximum likelihood supervised classification, have failed to produce a product with sufficient accuracy.

  8. Library Resource
    Journal Articles & Books
    December, 2013
    South Africa, Southern Africa

    Natural vegetation and crop-greening patterns in semi-arid savannas are commonly monitored using normalized difference vegetation index (NDVI) values from low spatial resolution sensors such as the Advanced Very High Resolution Radiometer (AVHRR) (1 km, 4 km) and Moderate Resolution Imaging Spectroradiometer (MODIS) (250 m, 500 m). However, because semi-arid savannas characteristically have scattered tree cover, the NDVI values at low spatial resolution suffer from the effect of aggregation of near-infrared and red energy from adjacent vegetated and non-vegetated cover types.

  9. Library Resource
    Journal Articles & Books
    December, 2014
    Europe

    The land surface models used in numerical weather forecasts and hydrological applications rely on the accuracy of land cover maps available from satellite remote sensing to simulate the energy and water balance at the surface of the Earth. While the impact of classification accuracy on land surface simulations has already been reported, little attention has been paid on the consequences of land cover map uncertainty driven by geolocation accuracy.

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