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New cloud filter implemented in eoMapper

New state of the art cloud and cloud shadow filter is implemented in eoMapper service for precision agriculture and farm decision support. The left side image is the satellite data over fields north of Uppsala from August 22 and the right side images display the vegetation index based on data from August 22 from a free with cloud free data and from August 20 for the neighbouring field with clouds at the latest date.

Cloud shadows are handled with a multi temporal approach and do not effect the vegetation indices, a great improvement compared to other services. The images with the cloud shadow is from August 22 and the selected image for the field is from August 20.

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Forest analyses made easy -eoMapper

It is quite easy to make forest analyses with eoMapper, the online tool for precision cultivation, forestry and urban development.

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Go to www.eomapper.com  and create an account. This is necessary for us to save your processes for future use.Skärmavbild 2017-05-12 kl. 20.16.46

Select to start a new process, in this case change detection for clear cuts between 2016 and 2017.

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Draw a field boundary by clicking the vertexes and dubble klick to close the polygon. Do not make it to large as the processing time might be long.Skärmavbild 2017-05-12 kl. 20.34.15

Name the polygon as you please.

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Start the process and the available imagery over the area will be processed to identify areas that have been clear cut.

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If there are sufficient amount of available data the results of the change analyses will be displayed in red.

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Now yo can order the identified clear cut areas and download them as shape files or in geoJson format. The processes are also available by API.

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Please contact Geografiska informationsbyrån if you have any questions, are interested in API access or have suggestions of improvements.

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Precision farming made easy -eoMapper

It is quite easy to make analyses for farm management with eoMapper, the online tool for precision cultivation, forestry and urban development.

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Go to www.eomapper.com  and create an account. This is necessary for us to save your processes and field geometries for your future use.Skärmavbild 2017-05-12 kl. 20.16.46

Select to start a new process, in this case ‘Precision Farming’.

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Chose to draw a field boundary line, in Sweden there is the alternative to use agricultural block, i.e. LPIS geometries.

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Draw a field boundary, in this case half a quarter north of Presho in South Dakota, by clicking the vertexes so the line follows the field boundary and dubble klick to close the polygon.

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Name the polygon as you please, in this case Presho, but it could be your Farm name and a number. Press save.

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Start the process and the available imagery over the area will be analysed and cloud free images identified. The processes are made with Google Earth Engine and usually take under 1 minute to finalize. For the half quarter north of Presho there are five available images from April 1 2016 until now. At the moment only the latest scene is processed to a vegetation index (MSAVI2). Development to be able to chose between the images, to make time series analysis and for comparison between different years is on the way.

The vegetation index is shown with a brown to green legend showing bare land to lush vegetation. Use you local knowledge and decide which amount of Nitrogen that should be used per hectare dependent on the greenness of the vegetation. In this case the figures are filled for an extra spring nitrogen application. The greenest areas are considered to need less Nitrogen and more the lower the index become, the lowest index are considered to be to sparse and no fertilizer will be applied. This is hypothetical and local knowledge must be applied. Klick the next button to process the index to a Nitrogen load map.

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The proportion of Nitrogen in the fertilizer can be changed and the load will be adequately recalculated. Press order for prescription file alternatives.

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Press ‘Ladda ner’ to download the results in the preferred format.

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We will continuously add functionality to the service, focusing on the needs of grain farmers globally.

Please contact Geografiska informationsbyrån if you have any questions, are interested in API access or have suggestions of improvements.

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Vegetationsindex för Golfbanor

Med eoMapper.com är det enkelt att ta fram information om hur grön en golfbana är. Det kan användas både för skötsel av gräsytorna, laddar man hem en styrfil i geoJson så ingår indexvärdena. Men kan vara intressant inför helgens rundor. Det har varit kallt i april och maj och banorna skiljer sig mycket mellan norr och söder. Gå in och kolla själv på eoMapper.com

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Greenest pitch -check it out on eoMapper.com

eoMapper is developed for agtech purposes and use the power of Google Earth Engine to identify cloud free Sentinel-2 imagery globally, calculate vegetation indices and refine them to prescription files for fertilizers, pesticides or irrigation in combination with local knowledge of farmers.

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The vegetation indices could also be used to rank the pitches of the teams in the national football leagues in Europe.

#1 of the pitches investigated is Parc de Princes, home pitch of Paris Saint Germain

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Followed by #2 Estadio Santiago Bernabéu, home pitch of Real Madrid

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#3 Anfield is the home pitch of Liverpool FC

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#4 with just a glimpse through the ceiling is the Estádio do Dragão, home pitch of Porto

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#5 is Villa Park, home pitch of Aston Villa, with a significant shadow effect in the south east corner

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#6 Allianz arena, home pitch Bayern München has a semi artificial turf and hence a low vegetation index.

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#7 Stade Marcel Picot seems to be a semi artificial turf as well

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#8 Nya Parken, home pitch of IFK Norrköping is a artificial turf and has hence a vegetation index resembling bare land.

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If interested you can log in to eoMapper.com and check out your favorite teams home pitch. Hopefully there will be data available.

 

 

 

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Innovativ informationsinhämtning med drönare och satellit

Geografiska informationsbyrån har beviljats stöd för att bild en innovationsgrupp med syfte att undersöka möjligheterna att ta fram en effektiv och tydlig process för informationsinhämtning om mark- och grödtillstånd i jordbruksmark med en kombination av industridrönare med högkvalitativa flygbildskameror och fria satellitdata från Copernicusprogrammet.

Stödet delas ut av Jordbruksverket och är en del av satsningar finansierade av Europeiska jordbruksfonden och avser innovationer inom området att återställa, bevara och främja ekosystem kopplade till jordbruk, trädgård och rennäring.

.EU-flagga+Europeiska+jordbruksfonden+färg

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We map farmland

At www.eoMapper.com we deliver the latest cloud free Sentinel 2 imagery for precision farming and and agricultural management where ever you need it.

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Powered by Google Earth Engine and utilizing the free data of the Copernicus program eoMapper deliver up to date vegetation indices and prescription files globally. Explore a new world of data at www.eomapper.com.

eomapper

Made by Earth Observation professionals for managers and practitioners at small to large farm enterprises.

 

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Geografiska informationsbyrån i ESA BIC

Idag har Geografisk informationsbyrån blivit antaget till ESA-BIC Sverige som ett av 8 start-up företag med potential att förändra användningen av rymdteknik i Sverige och globalt.

Geografiska informationsbyrån deltar med konceptet eoMapper.

eoMapper använder satellitbilder och smarta dataanalyser så att lantbrukare, markägare och -förvaltare enkelt kan skapa sig överblick över sina verksamheter och innehav. Rätt åtgärder kan sättas in på rätt ställe och vid rätt tidpunkt. Skogsmaskiner kan åka direkt till insektsskadade bestånd, virkesköpare kan identifiera avverkningsmogen skog och lantbrukare kan sprida näring där den gör som mest nytta.

dalby

eoMapper skapar värde och förbättrar lönsamheten med detaljerade beslutsunderlag och kontinuerligt uppdaterad data.

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We map forest

Forest mapping is at the heart of what we do at Geografiska informationsbyrån. As forest comprise vast areas it is as made for remote sensing and EO. Forest information can be produced for a wide range of costumers with different information needs. It might be an investor who wants to learn more about the background of the company and the natural assets it possess, a NGO investigating the exploitation of natural resources in a far off region or a company that wants to follow up harvests or other forestry practices within it’s own holdings.

timber_roadsSentinel 2 mosaic over parts of Liberia displaying the emergence of a timber road network and the subsequent partial harvest of the tropical forest.

In som geographic regions the optical sensors on Sentinel 2 and related satellites mostly detect the light reflected by clouds. In those regions Sentinel 1 is an interesting alternative with active radar, penetrating clouds and revealing the situation on the ground . Palm oil plantations in Indonesia can for example be monitored in an efficient way with Sentinel 1. Giving good opportunities to display if the pal oil produced comes from a sustainable source or from areas with past or ongoing deforestation.

sumatraSentinel 1 image over parts of Sumatra displaying both natural forest and palm oil plantations, shrimp paddies and the Taman National Park.

For detection of forest damage a combination of optic and radar satellite data is useful. With optic data changes in greenness and leaf area can be detected and small changes in both health and caused by management can thus be monitored.  Radar data can be used to detect and estimate the effects of wind throws even if the sky continues to be cloudy as often during winter and autumn.

windthrowsClearings of different sizes displayed with a plant phenology index at a test site in mid Sweden.

With very high resolution imagery the status of individual trees can be monitored and single tress detected an mapped. This is of interest for both forestry and park management. In combination with lidar data more information can be extracted and presented as texture and height are important information distinguishing between trees, shrubs and other vegetation.

TradkarteringTrees mapped in the southern Swedish city Jönköping, displaying the analytical strength in the combination of EO and lidar data.