natgillin/translations-raw huggingface dataset:
The subsidy amounted to Ű120 000 per DIAS provider to cover three phases: technical readiness review of DIAS providers by the Commission, onboarding of paying agencies on one of the DIAS provider and operational use of the DIAS by the paying agencies in 2019. Although all the paying agencies we visited had found it useful to test for free a DIAS platform, most of them used their existing infrastructure or contracts as primary processing solutions for checks by monitoring in 2019. 
Subventionen uppgick till 120 000 euro per DIAS-leverantr och skulle tcka tre faser: kommissionens granskning av DIAS-leverantrernas tekniska beredskap, integrering av de utbetalande organen vid en av DIAS-leverantrerna och de utbetalande organens operativa uttnyttjande av DIAS 2019. ven om alla de utbetalande organ som vi beskte ansg att det hade varit vrdefullt att f testa en DIAS-plattform gratis, anvnde merparten av dem sina 12 CREODIAS, MUNDI, ONDA och SOBLOO.
Consequently, the value added by the CommissionŐs expenditure of Ű480 000 is yet to be established. 
Mervrdet av kommissionens utgifter p 480 000 euro har fljaktligen nnu inte faststllts.
40 According to our June 2019 survey, most paying agencies do not intend to move to a DIAS platform soon. 
40 De flesta utbetalande organ planerar inte att g ver till en DIAS-plattform i en nra framtid, enligt vr enkt frn juni 2019.
Our discussions with the paying agencies and expert panel between April and September 2019 highlighted the following uncertainties, delaying the move to DIAS providers. o 12 13 The cost of DIAS services now and in the future. 
Vid vra diskussioner med de utbetalande organen och expertpanelen mellan april och september 2019 framhlls att fljande oskerhetsfaktorer frsenar vergngen till DIAS-leverantrer: o Kostnaden fr DIAS-tjnster nu och i framtiden.
Due to the technicalities and the pay-per-use business models, most paying agencies do not know how much it would cost them to run checks by monitoring on DIAS platforms in their country or region. CREODIAS, MUNDI, ONDA and SOBLOO. 
P grund av de tekniska detaljerna och affrsmodellerna enligt principen om betalning utifrn anvndning vet inte merparten av de utbetalande organen hur mycket det skulle kosta fr dem att utfra kontroller genom vervakning p DIAS-plattformar i deras land eller region. o Att det finns fyra DIAS-leverantrer, som alla har olika teknik och struktur, komplicerar de utbetalande organens beslutsfattande.
While the Commission claims to have a solution for transferability of data from one DIAS platform to another, the paying agencies are not yet aware of it. This is complicated further by the uncertainty around the service continuity of some or all of the DIAS providers after the end of their contracts. 
Kommissionen hvdar att den har en lsning nr det gller dataverfring mellan DIAS-plattformar, men den knner de utbetalande organen nnu inte till. Detta kompliceras ytterligare av oskerheten kring kontinuiteten hos vissa eller alla DIAS-leverantrers tjnster nr deras avtal har lpt ut.
The results of research projects are yet to be exploited 41 Under its Horizon 2020 Research and Innovation programme the Commission has granted some Ű94 million to a range of research projects aiming to monitor agriculture using Copernicus Sentinel data14. 
Resultaten av forskningsprojekt har nnu inte utnyttjats 41 Inom Horisont 2020, ramprogrammet fr forskning och innovation, har kommissionen beviljat omkring 94 miljoner euro till en rad olika forskningsprojekt som syftar till att vervaka jordbruket med hjlp av data frn Copernicus Sentinel14.
Among these projects, we identified three which contributed directly to ongoing developments in CAP monitoring15. 
Bland dessa projekt identifierade vi tre som bidrog direkt till den pgende utvecklingen nr det gller GJP-vervakning15.
In addition, a key project that started in June 2019 is ÔNew IACS Vision in ActionŐ (NIVA), for which EU funding is expected to amount almost to Ű10 million. 
Ett viktigt projekt som startade i juni 2019 r dessutom ÓNew IACS Vision in ActionÓ (NIVA), fr vilket EU:s finansiering frvntas uppg till nstan 10 miljoner euro.
It aims to modernise the integrated administration and control system used by paying agencies, by making efficient use of digital solutions and e-tools to reduce administrative burden and improve environmental performance. 
Det syftar till att modernisera det integrerade administrations-och kontrollsystem som utbetalande organ anvnder genom effektiv 14 Beloppet avser det totala EU-bidrag som planerats fr 34 forskningsprojekt.
42 The ESA funded a project, exploring how the Copernicus Sentinels could be utilised to modernise and simplify the CAP. 
42 ESA finansierade ett projekt som underskte hur Copernicus Sentinelsatelliterna skulle kunna utnyttjas fr att modernisera och frenkla GJP.
In July 2017, a consortium of five companies working together with paying agencies in six Member States16 started the project called Sen4CAP. 
I juli 2017 startade ett konsortium av fem fretag i samarbete med utbetalande organ i sex medlemsstater16 ett projekt kallat Sen4CAP.
The aim of this project is to provide algorithms, products, workflows and examples of good practice for generating satellite-derived markers and information relevant to CAP monitoring. 
Syftet med detta projekt r att tillhandahlla algoritmer, produkter, arbetsflden och exempel p god praxis fr att generera satellitmarkrer och satellitinformation fr GJP-vervakning.
43 A preliminary version of the Sen4CAP processing system (see Figure 7) became available in May 2019 and a final version is planned for early 2020. 
43 En preliminr version av Sen4CAP-processystemet (se figur 7) blev tillgnglig i maj 2019, och en slutlig version ska enligt planerna vara klar i brjan av 2020.
Paying agencies can thus use the Sen4CAP products as a basis for developing their own systems for checks by monitoring, but they will need to customise the algorithms to local circumstances. 
Utbetalande organ kan fljaktligen anvnda Sen4CAP-produkterna som en grund fr att utveckla egna system fr kontroller genom vervakning, men de kommer att behva anpassa algoritmerna till lokala frhllanden.
16 Czechia, Italy (5 regions), Lithuania, Netherlands, Romania and Spain (Castile and Leon). 
16 Tjeckien, Italien (fem regioner), Litauen, Nederlnderna, Rumnien och Spanien (Kastilien-Lon).
Since April 2019, France has been involved in the project (1 region, 1 department). 
Sedan april 2019 har Frankrike deltagit i projektet (en region och ett department).
Some Member States took action to deploy the new technologies for direct payments 45 We expected Member States to take adequate steps for deploying new imaging technologies for CAP monitoring. 
Vissa medlemsstater vidtog tgrder i syfte att infra de nya teknikerna fr direktstd 45 Vi frvntade oss att medlemsstaterna skulle vidta lmpliga tgrder fr att kunna infra nya bildtekniker fr GJP-vervakning.
Consequently, we have reviewed whether the paying agencies: o implemented checks by monitoring in the 2019 claim year; o used the Copernicus Sentinel data systematically to check some of the aid requirements; o used geo-tagged photos or drones; o participated in EU or ESA-funded research projects concerning the use of the new technologies; and o carried out pilot projects to test the use of the new technologies. 
Drfr granskade vi huruvida de utbetalande organen o tillmpade kontroller genom vervakning anskningsret 2019, o anvnde data frn Copernicus Sentinel systematiskt fr att kontrollera vissa stdkrav, o anvnde geotaggade foton eller drnare, o deltog i EU-eller ESA-finansierade forskningsprojekt om anvndning av de nya teknikerna, o genomfrde pilotprojekt fr att testa anvndning av de nya teknikerna.
15 paying agencies made selective use of checks by monitoring in 2019 46 As shown in Figure 8, for the 2019 claim year 15 out of 66 paying agencies in five Member States have implemented checks by monitoring on all or part of the area for which they are responsible, for all or some aid schemes. 
15 utbetalande organ anvnde kontroller genom vervakning selektivt 2019 46 Ssom framgr av figur 8 tillmpade 15 av de 66 utbetalande organen i fem medlemsstater kontroller genom vervakning p hela eller delar av den areal som de ansvarade fr inom alla eller vissa stdsystem anskningsret 2019.
Figure 8 also shows seven Member States participating in Sen4CAP project. 
Figur 8 visar ven sju medlemsstater som deltar i Sen4CAP-projektet.
Figure 8 Đ Use of checks by monitoring and participation in the Sen4CAP project in 2019 30 Source: ECA based on information obtained from the Commission and visited Member States. 
Figur 8 Đ Anvndning av kontroller genom vervakning och deltagande i Sen4CAP-projektet 2019 31 Klla: Revisionsrtten, p grundval av information frn kommissionen och beskta medlemsstater.
47 Taking into account the technical guidelines drafted by the JRC, these 15 paying agencies have developed diverse methodologies for monitoring the different aid scheme requirements applicable in their regions (see Figure 9 and Box 1). 
47 Med beaktande av JRC:s tekniska riktlinjer har dessa 15 utbetalande organ tagit fram diverse metodologier fr vervakning av de olika stdsystemkrav som gller i deras regioner (se figur 9 och ruta 1).
Crop types, agricultural practices and agro-climatic conditions are important factors that come into play. 
Grdtyper, jordbruksmetoder och odlings-och klimatfrhllanden r viktiga faktorer som spelar en roll.
32 Box 1 Examples of methodologies and use of Sentinel data for checks by monitoring in 2019 In Belgium (Flanders), the paying agency monitors the eligibility requirements for three schemes. 
33 Ruta 1 Exempel p metodologier och anvndning av Sentineldata fr kontroller genom vervakning 2019 I Belgien (Flandern) vervakar det utbetalande organet stdkraven i tre system.
For those schemes, farmers have to show use of their land for some form of agricultural activity. 
Inom de systemen mste jordbrukarna visa att de anvnder marken till ngon form av jordbruksverksamhet.
An artificial intelligence algorithm, trained using a time series of Sentinel 1 and 2 images (in combination with the information contained in the farmersŐ declarations), predicts the probability that each parcel belongs to one of five classes (arable land, grassland, leguminous crops, fallow and non-eligible). 
En artificiell intelligens-algoritm, trnad att anvnda en tidsserie med Sentinel 1-och 2-bilder (i kombination med informationen i jordbrukarnas deklarationer), frutsger sannolikheten att varje skifte tillhr en av fem kategorier (kermark, grsmark, baljvxter, mark i trda och icke stdberttigande mark).
Parcels where the outcome of the algorithm does not match the farmerŐs declaration are flagged red and followed up with a field visit. 
Skiften dr resultatet av algoritmen inte verensstmmer med jordbrukarens deklaration rdflaggas och fljs upp med ett fltbesk.
Where the outcome of the algorithm is inconclusive (yellow flag), parcels are followed up on screen and, if necessary, with a field visit. In 2019, permanent crops are excluded from this process, as they are verified using an update of the LPIS. 
Nr resultatet av algoritmen r obedmbart (gul flagga) fljs de berrda skiftena upp p bildskrm och vid behov genom ett fltbesk. r 2019 r permanenta grdor undantagna frn denna process, eftersom de kontrolleras genom en uppdatering av LPIS.
In Spain (Castile and Leon), the paying agency monitors the requirements for nine schemes. 
I Spanien (Kastilien-Lon) vervakar det utbetalande organet kraven i nio system.
For the basic schemes, it is sufficient to check whether the use of land is as arable land, as grassland or for permanent crops. 
Nr det gller grundsystemen rcker det att kontrollera om marken anvnds som kermark eller grsmark eller fr permanenta grdor.
More precise crop identification is required for greening and voluntary coupled support (VCS). 
Mer exakt identifiering av grdor krvs nr det gller miljanpassning och frivilligt kopplat std (FKS).
The paying agency thus performs a classification (26 crop classes and 9 non-crop classes) using a machine-learning algorithm trained with the farmersŐ declarations for crop classes and using other data sources to identify non-crop classes. 
Det utbetalande organet gr d en klassificering (26 kategorier av grdor och 9 kategorier av icke-grdor) med hjlp av en algoritm fr maskininlrning trnad med jordbrukarnas deklarationer nr det gller kategorier av grdor och med hjlp av andra datakllor fr att identifiera kategorier av icke-grdor.
The classification is performed with time series of Sentinel 2 images (in combination with climate data, and information on elevation, aspect and slope). 
Klassificeringen grs med tidserier av Sentinel 2-bilder (i kombination med klimatdata och information om hjd, vderstreck och lutning).
Other types of markers have been developed also, e.g. related to crop type, or to detect certain events (for example, the preparation of land for growing crops). 
Andra typer av markrer har ocks tagits fram, till exempel avseende grdtyp eller fr att upptcka vissa hndelser (t.ex. beredning av mark fr odling av grdor).
Parcels above a certain financial threshold are followed up in the office (see Figure 5) and if still inconclusive, then with a field visit. 
Skiften ver ett visst finansiellt trskelvrde fljs upp i det utbetalande organets lokaler (se figur 5), och om de fortstter att vara obedmbara efter det grs ett fltbesk.
48 Although radar data from Sentinel-1 are not impaired by the presence of cloud cover, they are used less often by paying agencies because they are more difficult to process and interpret. 
48 ven om radardata frn Sentinel 1 inte frsmras av frekomsten av ett molntcke anvnds de inte lika ofta av de utbetalande organen eftersom de r svrare att behandla och tolka.
However, some paying agencies (Belgium-Flanders and Denmark) have integrated them successfully in their machine learning algorithms while others use them for detecting grassland mowing (Italy). 
Vissa utbetalande organ (i Flandern i Belgien och i Danmark) har integrerat dem p ett framgngsrikt stt i sina algoritmer fr maskininlrning, medan andra anvnder dem fr att upptcka sltter av vall (Italien).
49 Table 3 shows for the key area aid scheme (Basic payment scheme), the four paying agencies we visited ended up with different proportions of yellow and red parcels for possible further follow-up. 
49 Nr det gller det viktigaste systemet fr arealstd (ordningen fr grundstd) visar tabell 3 att de fyra utbetalande organ som vi beskte kom fram till olika andelar gula och rda skiften fr eventuellt ytterligare uppfljning.
The variations between the proportions of red/yellow flagged parcels are mainly due to the size of parcels farmed, type of the parcels/activities monitored (mowing activity is easier to detect than grazing) and the methodologies applied (e.g. the number and accuracy of markers). 
Variationerna mellan de rd-/gulflaggade skiftenas andelar beror framfr allt p de odlade skiftenas storlek, typ av skiften/verksamheter som vervakas (sltterverksamhet r lttare att upptcka n bete) och de metodologier som tillmpas (t.ex. markrernas antal och precision).
Nevertheless, the maximum proportion of parcels requiring field inspection for these paying agencies is 1 %. 
Den maximala andelen skiften dr en fltinspektion krvs fr dessa utbetalande organ r dock 1 %.
Table 3 Đ Summary of first results of the 2019 checks by monitoring for BPS (as provided by paying agencies by 07/01/ 2020) 33 Country (Region) Total area of parcels monitored (ha) Total number of parcels monitored Parcels flagged red/ yellow following automated processing Red/ yellow flagged parcels followed -up in the office Red/ yellow flagged parcels inspected in the field Belgium (Flanders) 599 545 397 568 3.5 % 1.5 % 1.0 % Denmark 2 537 188 506 717 11.2 % 11.1 % 0.1 % Italy (6 monitored provinces) 1 104 491 718 692 3.3 % 1.0 % unknown Spain (Castile and Leon) 329 029 128 479 2.9 % 1.9 % 0.2 % Source: PayingagenciesinBelgium(Flanders),Denmark,Italy(AGEA)andSpain(CastileandLeon) 50 Our survey shows that, in 2020, a further 13 paying agencies in eight Member States intend to start checks by monitoring. 
Tabell 3 Đ Sammanfattning av de frsta resultaten av 2019 rs kontroller genom vervakning inom ordningen fr grundstd (enligt uppgifter frn utbetalande organ fram till den 7 januari 2020) 34 Land (region) De vervakad e skiftenas totala areal (ha) Totalt antal vervakad e skiften Skiften som rd-/gulflaggat s efter automatis k behandling Rd-/gulflagga de skiften som fljts upp i det utbetaland e organets lokaler Rd-/gulflagga de skiften som inspektera ts p fltet Belgien (Flandern) 599 545 397 568 3,5 % 1,5 % 1,0 % Danmark 2 537 188 506 717 11,2 % 11,1 % 0,1 % Italien (sex vervakade provinser) 1 104 491 718 692 3,3 % 1,0 % oknt Spanien (Kastilien-Lon) 329 029 128 479 2,9 % 1,9 % 0,2 % Klla: Utbetalande organ i Belgien (Flandern), Danmark, Italien (AGEA) och Spanien (Kastilien-Lon) 50 Vr enkt visar att ytterligare 13 utbetalande organ planerar att inleda kontroller genom vervakning 2020.
This would mean that in 2020, 28 paying agencies in 13 Member States might be applying checks by monitoring approach for some aid schemes and for part of the area for which they are responsible (see Figure 10). 
Det skulle innebra att 28 utbetalande organ i 13 medlemsstater 2020 eventuellt kommer att tillmpa kontroller genom vervakning fr vissa stdsystem och delar av den areal som de ansvarar fr (se figur 10).
In order to be ready for implementation in 2020, 11 of those 13 paying agencies have invested in IT infrastructure and carried out pilot projects. 
Fr att frbereda sig fr genomfrande 2020 har 11 av de 13 utbetalande organen investerat i it-infrastruktur och genomfrt pilotprojekt. tta har ven frbttrat kvaliteten p sina
Eight have also improved the quality of their LPIS and made changes to organisational processes. 
LPIS och ndrat organisatoriska processer.
Six of them have already had consultations with farmers' associations. 
Sex av dem har redan haft samrd med sammanslutningar av jordbrukare.
Paying agencies also use new imaging technologies in their work outside checks by monitoring 51 Many paying agencies, even those that do not use checks by monitoring, are using new imaging technologies for other aspects of their work (see Figure 11). 
Utbetalande organ anvnder ven nya bildtekniker i annat arbete n kontroller genom vervakning 51 Mnga utbetalande organ, ven de som inte tillmpar kontroller genom vervakning, anvnder nya bildtekniker i andra delar av sitt arbete (se figur 11).
52 Ad-hoc use of Sentinel images for visual checks and geo-tagged photos are the most widespread. 
52 Tillfllig anvndning av Sentinelbilder fr visuella kontroller och geotaggade foton r vanligast.
Almost half of the paying agencies use geo-tagged photos, usually taken by their inspectors rather than by farmers. 
Nstan hlften av de utbetalande organen anvnder geotaggade foton som i regel tas av deras inspektrer och inte av jordbrukare.
53 In addition to the 15 paying agencies, which implemented checks by monitoring in 2019, 12 paying agencies replied that they use the Copernicus Sentinel data or other satellite data for checks on aid applications. 
53 Utver de 15 utbetalande organ som tillmpade kontroller genom vervakning 2019, svarade 12 utbetalande organ att de anvnder data frn Copernicus Sentinel eller annan satellitdata fr att kontrollera stdanskningar.
Some paying agencies have also been involved in key research projects such as Sen4CAP (see paragraph 42), Sentinels Synergy for Agriculture (SensAgri), Reinforcing CAP (RECAP) or Earth Observation for Agriculture (EO4AGRI). 
Vissa utbetalande organ har ven deltagit i viktiga forskningsprojekt som Sen4CAP (se punkt 42), Sentinels Synergy for Agriculture (SensAgri), Reinforcing CAP (RECAP) eller Earth Observation for Agriculture (EO4AGRI).
54 Our survey results showed that eight out of 59 paying agencies had used drones. 
54 Vra enktresultat visade att tta av de 59 svarande utbetalande organen hade anvnt drnare.
In Denmark, the paying agencyŐs inspectors use drones to check areas that are difficult to access, reducing the health and safety risk to them, as well as the time needed for checks. 
I Danmark anvnder de utbetalande organens inspektrer drnare fr att kontrollera arealer som r svra att komma t, vilket minskar riskerna fr deras hlsa och skerhet samt den tid kontrollerna tar.
Paying agencies most often mention limited autonomy and regulatory restrictions as reasons for not making greater use of drones. 
De utbetalande organen anger oftast begrnsad autonomi och rttsliga hinder som skl till att de inte anvnder drnare i strre utstrckning.
Obstacles hampering deployment of the new technologies 55 Our survey identified a number of obstacles, which delay the implementation of checks by monitoring by paying agencies (see Figure 12). 
Hinder fr infrande av de nya teknikerna 55 Vr enkt identifierade ett antal hinder som gr att de utbetalande organens infrande av kontroller genom vervakning frsenas (se figur 12).
These include developing IT infrastructure, adapting internal processes and changing organisational structure to support effective use of checks by monitoring. 
Bland dem ingr utveckling av it-infrastruktur, anpassning av interna processer och ndring av organisationsstrukturen fr att stdja en ndamlsenlig anvndning av kontroller genom vervakning.
57 Our discussions with paying agencies and experts highlighted three key challenges: o investing in the new monitoring approach while faced with uncertainty about the post-2020 CAP17 (for which the Commission proposed a new delivery model and a new area monitoring system to be set up by the Member States); o developing innovative IT solutions, such as the processing of time series of Sentinel data (high volume of data) and machine-learning algorithms (rather than 17 Proposal for a Regulation of the European Parliament and of the Council on the financing, management and monitoring of the common agricultural policy and repealing Regulation (EU) 1306/2013. 
57 Vid vra diskussioner med utbetalande organ och experter framhlls fljande tre centrala utmaningar: o Investering i den nya vervakningsmetoden samtidigt som det rder oskerhet om GJP efter 202017 (fr vilken kommissionen har freslagit en ny genomfrandemodell och ett nytt arealvervakningssystem som medlemsstaterna ska upprtta). o Utveckling av innovativa it-lsningar, ssom behandling av tidsserier av Sentineldata (stor datavolym) och algoritmer fr maskininlrning (i stllet fr 17 Frslag till Europaparlamentets och rdets frordning om finansiering, frvaltning och vervakning av den gemensamma jordbrukspolitiken och om upphvande av frordning (EU) nr 1306/2013.
standard image-processing tools) where some paying agencies lack relevant expertise; and o achieving potential synergies between agencies by working together (either across the EU or in voluntary groups). 
standardverktyg fr bildbehandling), nr vissa utbetalande organ samtidigt saknar relevant sakkunskap. o Uppnende av potentiella synergieffekter mellan organ genom samarbete (antingen i hela EU eller i frivilliga grupper).
This could be valid for the pre-processing of Copernicus Sentinel data, archiving, or for the provision of very high-resolution images for the follow-up of small parcels (see paragraph 34). 
Detta skulle kunna glla frbehandling av data frn Copernicus Sentinel, arkivering eller tillhandahllande av mycket hgupplsta bilder fr uppfljningen av sm skiften (se punkt 34).