Αποτελέσματα αναζήτησης

Είναι Είδος:[[is_a_kind_of::Artificial non-agricultural vegetated areas]] <br />

Είναι Είδος:[[is_a_kind_of::Artificial non-agricultural vegetated areas]] <br />

[[category:artificial areas]]

[[category::artificial areas]]

[[category:artificial areas]]

Είναι Είδος: [[is_a_kind_of::artificial surfaces]] <br /> Θέση: [[Item::Next to areas Papagos, Champs Elysees, frames and coordinates 37 ° 59 '0 "N 23 ° 46' 0"

[[category:artificial areas]]

[[category::artificial areas]]

[[category:artificial areas]]

...ος Τίτλος:''' «Remote sensing of impervious surfaces in the urban areas: Requirements, methods, Civco, D. L. (1993). Artificial neural networks for land-cover classification and mapping. International Jo

... and patches of forest, grasslands and sporadic occurrence of water areas (artificial and natural). Όνομα Κλειδιού: [[preferred_name::2.4.3.1 Agricultural areas with significant share of natural vegetation, and with prevalence of arable

...ble land, strips and patches of forest, grass communities and water areas (artificial and natural). Όνομα Κλειδιού: [[preferred_name::2.4.3.2 Agricultural areas with significant share of natural vegetation, and with prevalence of grassl

'''(Artificial reservoirs)''' Water areas created by man with prevailing regular shape.

..., Wu, C., 2008. Subpixel imperviousness estimation with IKONOS imagery: an artificial neural network approach. In: Weng, Q. (Ed.), Remote Sensing of Impervious S Shaban, M.A., Dikshit, O., 2001. Improvement of classification in urban areas by the use of textural features: the case study of Lucknow city, Uttar Prad

...e, C., 2010. Comparison of matching algorithms for DSM generation in urban areas from Ikonos imagery. Photogrammetric Engineering & Remote Sensing 76 (9), 1 ... extraction from high resolution satellite images and height data in urban areas. Proceeding of the 23rd Asian Conference on Remote Sensing, Kathmandu, Nepa