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Displaying 291 - 295 of 661GeoEye-1 and WorldView-2 pan-sharpened imagery for object-based classification in urban environments
The latest breed of very high resolution (VHR) commercial satellites opens new possibilities for cartographic and remote-sensing applications. In fact, one of the most common applications of remote-sensing images is the extraction of land-cover information for digital image base maps by means of classification techniques. The aim of the study was to compare the potential classification accuracy provided by pan-sharpened orthoimages from both GeoEye-1 and WorldView-2 (WV2) VHR satellites over urban environments.
Examining the relationships between land cover and greenhouse gas concentrations using remote-sensing data in East Asia
Measurements of land-cover changes suggest that such shifts may alter atmospheric concentrations of greenhouse gases (GHGs). However, owing to the lack of large-scale GHG data, a quantitative description of the relationships between land-cover changes and GHG concentrations does not exist on a regional scale. The Greenhouse Gases Observing Satellite (GOSAT) launched by Japan on 23 January 2009 can be of use in investigating this issue.
Requirements for labelling forest polygons in an object-based image analysis classification
The ability to spatially quantify changes in the landscape and create land-cover maps is one of the most powerful uses of remote sensing. Recent advances in object-based image analysis (OBIA) have also improved classification techniques for developing land-cover maps. However, when using an OBIA technique, collecting ground data to label reference units may not be straightforward, since these segments generally contain a variable number of pixels as well as a variety of pixel values, which may reflect variation in land-cover composition.
Identification of potential land cover changes on a continental scale using NDVI time-series from SPOT VEGETATION
The identification of land cover changes on a continental scale is a laborious and time-consuming process. A new methodology is proposed based exclusively on SPOT VGT data, illustrated for the African Continent using GLC2000 as reference to select 26 distinct land cover types (classes).
Crop and water productivity, profitability and energy consumption pattern of a maize-based crop sequence in the North Eastern Himalayan Region, India
Mono-cropping is the most common farming practice followed in the North Eastern Hilly Region (NEHR) of India and farmers leave the land fallow after harvesting the main crop. The identification of suitable sequential crops is essential to increase the cropping intensity, land-use efficiency and overall productivity of the land. Therefore, a study was carried out during 2008–09, 2009–10 and 2010–11 on maize (rainy season) followed by table pea, mustard, French bean and groundnut (post rainy season). Sequence crops were imposed with paddy straw mulch at 5.0 t ha⁻¹ and without mulch.