OrbitalViews
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My Field


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Contact:

Contact us by email and get help with your questions: "support@orbitalviews.eu"
We provide important insights through satellite and weather data. Let's discuss about potential use cases, improvements or just say hello.



Documentation:

Blue Marble 2012,
created from Suomi imagery

1. HowTo:

Search a location of interest and mark your field with "MyField". The processing of your data only takes some seconds depending on your internet connection speed. The buttons activate a corresponding map view.
Note: This is a Desktop WebApp which was not optimized for smartphones.



2. Live&Night Modus:

Live modus visualizes daily satellite pictures provided by Suomi NPP with a resolution of 250 meter. Therefore, the live view disappears if you zoom in to a higher level. Suomi NPP orbits the Earth about 14 times each day and was placed in a sun-synchronous orbit. He is equipped with various instruments for earth observation, e.g. radiometer or sounder. OrbitalViews visualizes its corrected reflectance (True Color) images from the last day. The night button shows the earth by night. This map has been released by NASA in 2012 and is also based on the Suomi NPP imagery. The Earth image on the right shows a blue marble as example. (https://en.wikipedia.org/wiki/Suomi_NPP)



3. Satellite Monitoring:

Satellite monitoring over vegetation helps farmers to improve their daily work and decreases costs and losses. The impact of environmental stress on the physiological processes of a plant defines a crop’s overall productivity. Unfavorable weather conditions can reduce yields by more than 70%. Drought stress during flowering can cause a delay in silking, disrupting anthesis. Drought stress in the two weeks following silking can reduce the crop growth rate by 20%. The current demand of fresh water for the private sector, industry and agriculture is unsustainable and globally increasing. The development of new and innovative irrigation solutions is required in order to support the increased demand. Satellite monitoring provides multispectral information which can be transformed into helpful information in order to prevent crop stress or yield reductions. The following sections introduce some applications of satellite and weather data for drought, irrigation or biomass monitoring.

Venice July 2017 - Sentinel



a) RGB:

RGB is a true color image and shows the most up to date picture of a location or field. The picture date and time is shown on the left side in the toolbar. Landsat 8/7 and Sentnel-2 are our data sources which provide continuous beautiful images of any location on Earth with a resolution of up to 10 meter per pixel. The illustrated RGB image shows Venice in Italy.



b) Biomass:

Biomass is calculated from a comparison of visible and near-infrared light which is reflected from vegetation. Healthy vegetation absorbs a major part of visible light while it also reflects a larger part of near-infrared light. Unhealthy or scarce vegetation reflects visible light mostly. Green pigments in leaves that is chlorophyll greatly absorb visible light for photosynthesis. Low values correspond to vegetation free regions e.g. and sand, buildings or snow are visualized in brown shades. High index values (0.6-0.8) denote high biomass. The color bar shows these shades from dark green to light green.



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Biomass colorbar

c) Plant Moisture

Moisture stands for moisture content in the leafs and is based on the NDWI index. NDWI is a good indicator of plant humidity and strongly related to plant water content. During droughts vegetation conditions can be affected by water stress which causes crop failure or lower crop production in areas without irrigation. An early recognition of such conditions can be advantageous for irrigation management in order to prevent yield reductions. The NDWI/Moisture product is dimensionless and varies between -1 to +1, depending on plant humidity but also on the vegetation type and cover. High values (blue shades) correspond to high vegetation water content and to high vegetation fraction cover. Low values show low vegetation water content and low vegetation fraction cover. Drought and water stress are not the only factors that can cause a decrease of NDWI values. Change in land covers or pests and diseases can also be responsible for such variation of the signal. Therefore this indicator must be used jointly with other indicators giving information on the deficit of rainfall /soil moisture in order to determine if the variation in the vegetation response (signal) is linked with a drought event or not.

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Moisture colorbar



d) Variance

Biomass variance visualizes the spatial disparity which is based on biomass differences. Mark the field correctly without any streets or buildings in order to get a very good result. The images below show a variance map of a center-pivot irrigation area where crops are watered with sprinklers in comparison to a daily water need map. The mean biomass value is shown in white. Negative deviations from the mean are visualized in blue shades and positive in red shades.



e) Water Need

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Visualization of an irrigated field with water needs and variance

By providing near-real time information about moisture, water consumption or evapotranspiration, water and agricultural management can be improved. An improvement of irrigation efficiency saves energy costs and water consumption.
Evapotranspiration (ET) is an important part of our calculation and describes the sum of evaporation and plant transpiration. It accounts for the movement of water to the air in form of water vapour. Transpiration refers to the movement of water within a plant and the subsequent loss of water as vapor through stomata in its leaves. Evapotranspiration is an important part of the water cycle and an integral part of the water need map. The water need map takes weather data like daily rain amount, temperature or wind speed and multispectral satellite data as input in order to compute the crop-specific water amount which needs to be applied. The toolbar shows the average elevation and ET0 over grass for the marked region or field.





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