Full text: Proceedings of the Symposium on Global and Environmental Monitoring (Part 1)

~ refinement of the digital thematic mapping procedure 
( assessmGn t accuracy dependence on the different parameters, 
extendibi1ity in time/space and this way the reliability of the 
technology) 
— assessment of physical and biological aspects of crop growth 
and production, 
— measuring crop canopy variables throughout a crop cycle, 
— assessment on yield indicators using lower resolution (environ 
mental ) satellite data, 
~ refinement of the yield forecast models used, 
— advanced data acquisition and information dissemination(Remetey 
and Szentesi,1988). 
RS data sources(e.g.) Usage 
Geostationary sats (Meteosat) 0 
Pol,orbiting environmental sats(Meteor,TIROS) E 
Pol,orbiting Earth resources sats(Landsat,SPOT) S 
Other space imagery(Cosmos) E 
Airborne metric photographs(Wi1d RC20) 0 
Airborne multispectral scanner(S-500) C 
Aerial b/w,c imagery in VIS/IR/TIR 0 
Aerial thermal videotaping(AGA) 0 
Aerial thermal profi1er(AGA) C 
Aerial imaging spectrometry(Moniteq FLI) C,E 
Airborne passive microw.radiometer(BME MHT) C,E 
Airborne SLAR (BME MHT) C,E 
Light intensity detection and ranging(TLT LIDAR) C,E 
Terrain spectroradiometer(Exotech) E,S 
Weather radar 0 
Others(scatterometer,etc.) 
Table 1- Satellite, aerial and terrain RS data sources available 
in Hungary (E=experimental, C=campaign, S=semi-operationa1, 
O=operationa1) 
As far as the infrastructure is concerned, dedicated data 
processing hardware has been configured by the staff of Ft>MI 
Remote Sensing Centre to support application studies. The 
developed software system is running in a MicroVax compatible 
en vi r on men t. 
At the beginning the potential of the methods and processing 
system was studied in different projects (using basically per 
point classification approaches) for mapping and inventory of the 
most significant crops in Hungary. Recently a set of GIS 
supported image analysis methods have been developed and tested 
for the same purposes. After having promising preliminary results 
in crop yield forecast modelling (Ferencz, 1988), the methods and 
the processing system being developed for crop inventory can also 
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