Special UNISPACE III volume

Marsteller, Deborah

Bibliographic data

Monograph

Persistent identifier:: 856485039

Author:: Marsteller, Deborah

Title:: Special UNISPACE III volume

Sub title:: including: ISPRS Workshop on "Resource Mapping from Space", ISPRS-EARSeL Workshop on "Remote Sensing for the Detection, Monitoring and Mitigation of Natural Disasters", ISPRS-NASA Seminar on "Environment and Remote Sensing for Sustainable Development", July 1999, Vienna, Austria

Scope:: IV, 170 Seiten

Year of publication:: 1999

Place of publication:: Coventry

Publisher of the original:: RICS Books

Identifier (digital):: 856485039

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: ISPRS Workshop on "Resource Mapping from Space"

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: OPERATIONAL CROP MONITORING AND PRODUCTION FORECAST BY REMOTE SENSING IN HUNGARY. G. Csornai. Cs. Wirnhardt, Zs. Suba. P. Somogyi, G. Nador, L. Martinovich, L. Tikász, A. Kocsis, Gy. Zelei, M. Lelkes

Document type:: Monograph

Structure type:: Chapter

International Archives of Photogrammetry and Remote Sensing. Vol. XXXII Part 7C2, UNISPACE III, Vienna, 1999 45 I5PR5 UNISPACE m - ISPRS Workshop on “Resource Mapping from Space” 9:00 am -12:00 pm, 22 July 1999, VIC Room B Vienna, Austria ISPRS OPERATIONAL CROP MONITORING AND PRODUCTION FORECAST BY REMOTE SENSING IN HUNGARY G. Csomai. Cs. Wirnhardt, Zs. Suba. P. Somogyi, G. Nador, L. Martinovich, L. Tikasz, A. Kocsis, Gy. Zelei, M. Lelkes FOMI Remote Sensing Centre, Institute of Geodesy', Cartography and Remote Sensing H-l 149 Budapest, Bosnyak ter 5. Phone: 36-1-252-7898, fax: 36-1-252-8282 E-mail: gabor.csomai@rsc.fomi.hu KEY WORDS: Operational, Crop Monitoring, Production Forecast. Area Assessment, Integrated Landsat-AVHRR Yield Model, Robust Yield Prediction, CROPMON, Waterlog Monitoring ABSTRACT The Hungarian Agricultural Remote Sensing Program led to a concise methodology that could further be applied operationally. First the main results of a substantial R+D investment and methodology plus validation results are summarized in the paper. The crops area assessment, through the processing of multitemporal Landsat and IRS-1C/1D data proved to be efficient at county level because of the accuracy of thematic classification. The novel combined high resolution images + NOAA AVHRR series based crop yield forecast methodology performed well for the major crops (8) at county level. A novel robust method that combines land use information with NOAA AVHRR time series for yield prediction is also introduced. Based on the experiences of the first 3 operational years (from 1997) a general evaluation on the Operational Crop Monitoring and Production Forecast Program (CROPMON) is given. The CROPMON system is a good platform for additional projects implementation as in the case of a serious waterlog assessment and impact analysis in spring, 1999. 1. BACKGROUND Up to 1990 the crop production was based on some 1400 co operative or state farms in Hungary. The crop information system used their reports that were obligatory by law. This information system worked fairly well. Because of the dramatic changes in the Hungarian economy and also in the agriculture, the former crop information system became inadequate. The land privatisation brought dramatic changes in the holdings and parcel sizes, the number of farm owners or operators, the agricultural technology and investments. In this very quick transition, the need for an efficient information system became even more imperative. The priority Hungarian Agricultural Remote Sensing Program (HARSP) was launched in 1980 and has been implemented by FÔMI Remote Sensing Centre (FÓMI RSC). The final objective of the program was to introduce remote sensing to the operational agro information system in Hungary. The operational system was expected to be capable to monitor crops in the entire country', providing accurate, timely and reliable information on the area of the major crops, their development quantitatively. This should be accompanied by problems areas delineation (focusing to drought assessment), plus the provision of reliable yield forecast and final yield estimates. These data are to be available at the country as well as the counties (19) levels. The main users of the information includes, primarily the Ministry of Agriculture and Regional Development (MoARD) and gradually the grain processing and trading companies and associations, the farmers and their different organisations, associations. Even in the third years of operations and having a lot of experience to meet the strict accuracy and deadline requirements there is a continuous improvement in the technology applied. This leads to a number of additional applications offered by this system. 2. THE TWO MAIN PERIODS OF THE PROGRAM The HARSP (1980-99) program can be divided to two main periods: • tlte development of the methodology basis, the crop mapping and area assessment methods plus the yield forecast models and validation (1980-96) and • the operational period (1997-99). The final, most intensive period (1993-96) was the break through in the development. This resulted in an operationally ready to use technology that had been validated prior to the operational phase on a 16 counties sample from quite a diverse crop years period: 1991-96 (Csomai et. al., 1998). 2.1. The operational crop area assessment method The method was developed by FOMI RSC. It applies high resolution satellite data series (e.g. Landsat, IRS-1C/1D, SPOT) in as a multitemporal digital image analysis procedure for file crop identification and area estimation (Csornai et al., 1983). This approach was thoroughly tested by 1990 up to 3 counties region (Csornai et. al., 1990). It was found that the traditional agro information system in Hungary, can only be surpassed in accuracy if advanced digital image analysis was used (Csornai et. al., 1997). This approach also provides reliable crop maps, which are necessary to the crop development monitoring and production forecast models.

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