FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1992996209> ?p ?o ?g. }

• W1992996209 abstract "REAL-TIME ENVIRONMENT MONITORING USING DATA FROM METEOSAT AND NOAA IMAGING SATELLITESH.A. van Ingen Schenau and J.C. VenemaNational Aerospace Laboratory NLR Postbus 90502, 1006 BM AMSTERDAM, The NetherlandsABSTRACTAn operational remote sensing system is described which supports the environment monitoring using the multi sensor - multi temporal data acquired by the geostationary and polar orbiting weather satellites. The information derived from the satellite images are maps on a continental scale with data on the estimated rainfall, the vegetation index (NDVI), and for experimental use, with data on the soil water available for crops. The operational system, called ARTEMIS, will meet the information requirements of the FAO monitoring programmes in the areas of food and feed security plant protection.1. INTRODUCTIONThis paper describes the ARTEMIS environment monitoring system which will support the Food and Agriculture Organization FAO in the task of large scale monitoring of the ecological conditions of Africa and Southwest Asia. ARTEMIS is an acronym for: Africa Real-Time Environment Monitoring using Imaging Satellites. The methods of environment monitoring are the result of recent research on satellite remote sensing and meteorology. The ARTEMIS system under development will be an operational system i.e. a system which executes daily computer operations to generate the thematic user products. These thematic data are processed in near real-time considering the agro-meteorological time scale with ten-day or decade intervals.The operational system acquires and processes images which are observed by the METEOSAT geostationary and the TIROS/NOAA polar orbiting satellites. These multi sensor- multi temporal data have a considerable potential for agro-meteorological use e.g. the estimation of rainfall, the observation of vegetation and the crop condition moni tori ng.2. MAIN OBJECTIVESThe major objective of the ARTEMIS system will be to support in FAO's Early Warning function of environment monitoring and in the Desert Locust survey control (Hielkema, 1980). The approach is to use primarily satellite images as input due to the scarcely available groundtruth and, if available, its limited reliability and to process these images to obtain thematic end-products for agro-meteorological use. Figure 1 shows the functional lay-out of the thematic data processing and depicts the information sets and processing functions.The multi-sensor data input is obtained by the real-time METEOSAT IR digital data covering the African continent and the NOAA AVHRR/GAC data covering Africa and Southwest Asia. A major step in the processing of multi-sensor data is the mapping of satellite images to a common geographic grid with cell of 7 km.The thematic data processing is based on a method of ten-day cumulation of METEOSAT IR data for rainfall estimation which is proposed by the meteorological department of the University of Reading (Milford and Dugdale, 1985) and a method of ten-day composition of NOAA VIS and NIR data to determine the vegetation index as demonstrated by NASA/GSFC (Tucker et al, 1985 and Townsend et al , 1985).From these primary end-products the crop moisture availability is calculated on basis of the crop-specific water balance. Also favourable green conditions for the breeding of the Desert Locust can be detected in the northern zone of Africa and Southwest Asia.3. RAINFALL ESTIMATION USING METEOSAT DATAThe method of rainfall estimation is based on the processing hourly thermal IR images which are received directly from the METEOSAT satellite and are stored during night and day. The algorithm developed by the Meteorological Department of the University of Reading is validated for the convective cloud systems in Sahelian zone. All pixels below a certain threshold temperature, which is specified for each pixel, will contribute" @default.
• W1992996209 created "2016-06-24" @default.
• W1992996209 creator A5032262779 @default.
• W1992996209 creator A5077692739 @default.
• W1992996209 date "1988-01-25" @default.
• W1992996209 modified "2023-10-03" @default.
• W1992996209 title "Real-Time Environment Monitoring Using Data From Meteosat And Noaa Imaging Satellites" @default.
• W1992996209 doi "https://doi.org/10.1117/12.942639" @default.
• W1992996209 hasPublicationYear "1988" @default.
• W1992996209 type Work @default.
• W1992996209 sameAs 1992996209 @default.
• W1992996209 citedByCount "0" @default.
• W1992996209 crossrefType "proceedings-article" @default.
• W1992996209 hasAuthorship W1992996209A5032262779 @default.
• W1992996209 hasAuthorship W1992996209A5077692739 @default.
• W1992996209 hasConcept C127413603 @default.
• W1992996209 hasConcept C141505278 @default.
• W1992996209 hasConcept C146978453 @default.
• W1992996209 hasConcept C153294291 @default.
• W1992996209 hasConcept C16405173 @default.
• W1992996209 hasConcept C19269812 @default.
• W1992996209 hasConcept C205649164 @default.
• W1992996209 hasConcept C2778755073 @default.
• W1992996209 hasConcept C39399123 @default.
• W1992996209 hasConcept C39432304 @default.
• W1992996209 hasConcept C41008148 @default.
• W1992996209 hasConcept C539469273 @default.
• W1992996209 hasConcept C58640448 @default.
• W1992996209 hasConcept C62649853 @default.
• W1992996209 hasConcept C87717796 @default.
• W1992996209 hasConcept C93692415 @default.
• W1992996209 hasConceptScore W1992996209C127413603 @default.
• W1992996209 hasConceptScore W1992996209C141505278 @default.
• W1992996209 hasConceptScore W1992996209C146978453 @default.
• W1992996209 hasConceptScore W1992996209C153294291 @default.
• W1992996209 hasConceptScore W1992996209C16405173 @default.
• W1992996209 hasConceptScore W1992996209C19269812 @default.
• W1992996209 hasConceptScore W1992996209C205649164 @default.
• W1992996209 hasConceptScore W1992996209C2778755073 @default.
• W1992996209 hasConceptScore W1992996209C39399123 @default.
• W1992996209 hasConceptScore W1992996209C39432304 @default.
• W1992996209 hasConceptScore W1992996209C41008148 @default.
• W1992996209 hasConceptScore W1992996209C539469273 @default.
• W1992996209 hasConceptScore W1992996209C58640448 @default.
• W1992996209 hasConceptScore W1992996209C62649853 @default.
• W1992996209 hasConceptScore W1992996209C87717796 @default.
• W1992996209 hasConceptScore W1992996209C93692415 @default.
• W1992996209 hasLocation W19929962091 @default.
• W1992996209 hasOpenAccess W1992996209 @default.
• W1992996209 hasPrimaryLocation W19929962091 @default.
• W1992996209 hasRelatedWork W1590285225 @default.
• W1992996209 hasRelatedWork W160113176 @default.
• W1992996209 hasRelatedWork W1991105877 @default.
• W1992996209 hasRelatedWork W1997371831 @default.
• W1992996209 hasRelatedWork W2013322769 @default.
• W1992996209 hasRelatedWork W2015859926 @default.
• W1992996209 hasRelatedWork W2016765077 @default.
• W1992996209 hasRelatedWork W2020313136 @default.
• W1992996209 hasRelatedWork W2027821470 @default.
• W1992996209 hasRelatedWork W2042297529 @default.
• W1992996209 hasRelatedWork W2093408583 @default.
• W1992996209 hasRelatedWork W2101467062 @default.
• W1992996209 hasRelatedWork W2133000191 @default.
• W1992996209 hasRelatedWork W239349951 @default.
• W1992996209 hasRelatedWork W2960145708 @default.
• W1992996209 hasRelatedWork W349355100 @default.
• W1992996209 hasRelatedWork W49725853 @default.
• W1992996209 hasRelatedWork W647765656 @default.
• W1992996209 hasRelatedWork W750389096 @default.
• W1992996209 hasRelatedWork W884405206 @default.
• W1992996209 isParatext "false" @default.
• W1992996209 isRetracted "false" @default.
• W1992996209 magId "1992996209" @default.
• W1992996209 workType "article" @default.