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[null,"1.","Record Nr.",null,"UNINA9910557874703321"]
[null,null,"Autore",null,"Švab Lenarčič Andreja"]
[null,null,"Titolo",null,"Uporaba lidarskih podatkov za klasifikacijo pokrovnosti"]
[null,null,"Pubbl/distr/stampa",null,"Ljubljana, : ZRC SAZU, Založba ZRC, 2015"]
[null,null,"Descrizione fisica",null,"1 electronic resource (113 p.)"]
[null,null,"Collana",null,"Prostor, kraj, čas ; 6"]
[null,null,"Soggetti",null,"Geographical information systems (GIS) & remote sensing"]
[null,null,"Lingua di pubblicazione",null,"Sloveno"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","The book presents a method to create a land cover map from lidar data (elevation, intensity and standard deviation of height). The intensity of the observed object depends on many factors and is therefore not easy to interpret. With careful study of the problem and implementing various improvements we managed to distinctively classify categories of grass, agricultural fields and asphalt. We used standard deviation of height to differentiate trees and buildings, because this was not possible using intensity data alone. On the basis of independent lidar data a high quality three dimensional land cover map of local area has been successfully generated. It distinguishes five basic categories, although more detailed sub-categories could be introduced if necessary. Once the methodology is determined, products can be generated fully automatically, with minimal effort and costs. The resulting maps are of very high positional and thematic accuracy with numerous advantages for local studies."]
[{"$nulls":4},"Knjiga opisuje postopek izdelave karte pokrovnosti iz podatkov lidarskega snemanja, kot so višina, intenziteta in standardni odklon višine. Intenziteta opazovanega objekta je odvisna od vrste dejavnikov in zato težavna za interpretacijo. Po njeni preučitvi in nekaterih izboljšavah smo zelo dobro razločili kategorije pokrovnosti trava, njive in asfalt, za razločitev dreves in stavb pa smo morali uporabiti še standardni odklon višin. Na osnovi samostojnih lidarskih podatkov smo uspeli izdelati kakovostno karto pokrovnosti krajevnega območja, ki loči pet osnovnih kategorij, po potrebi pa jih lahko ločimo tudi več. Ko je postopek izdelave karte znan, lahko karto izdelamo povsem samodejno, z minimalnim naporom in stroški. Pri tem dobimo karto "]
[{"$nulls":4},"zelo dobre položajne in tematske natančnosti, s številnimi prednostmi za krajevne študije."]