A new showcase in iMap from Indiana

In our WebGIS application we present our portfolio of ag-map products for nearly the entire state of Indiana/USA.
You find the full article
here.


Flood monitoring with Sentinel-1 radar data in northern Germany

In December and January we observed widespread and long-lasting flooding in Germany. With Sentinel-1 data you can map the spatial and temporal dimensions well. The full report you may find here.


Yield prediction for agricultural crops

For the field crops winter wheat , winter barley and winter rapeseed we made a yield prediction on a farm in Germany with quite a good result. The full report you may find here.


Blast of Kakhovka dam in Ukraine

In the Ukraine the Kakhovka dam was destroyed. The flooded area was monitored with Sentinel-1 SAR data. The article with few maps showing the situation before and after the event you find  here.


Paddy rice cultivation in the northern Italian region of Piedmont

In northern Italy is the biggest rice cultivation area of Europe. The ESVI allows to monitor the irrigation regime and the growth of biomass in the rice paddies.
The full article you find here.


Yield prediction based on the vegetation index ESVI in Argentina

We use Sentinel-1 SAR data and generate a vegetation index out of it. This vegetation index ESVI can be transformed directly and precisely in yield for various field crops. We don’t need additional data like weather or soil data.
The full article you find here.


Yield prediction for arable crops based on ESVI

For a region in Germany / Thuringia we modelled the yield for arable crops like wheat, barley and rapeseed based on #Sentinel-1 #SAR data.
The full article you may find here.


Sentinel-1 SAR data to visualize the growth-dynamic in cropland

From Slovakia we show examples for monitoring the growht-dynamic with #Sentinel-1 #SAR data.
The full article you may find here.


New showcase for California in iMap

A new showcase in iMap presenting our popular map products like #ESVI (enhanced SAR Vegetation Index), #SWI (SAR Water Index), #CC (pseudo-true Color Composite), #EVO (Evolution) a color composite over a period of 3 succeeding acquisitions based on ESVI and #GCB (Gradual Change of Biomass), which is a map product that shows the recent change based on ESVI.
The full article you find here.


Forest fires in the Gironde region in France

We used #Sentinel-1 #SAR data and here our vegetation index #ESVI to demonstrate that the detected footprint compares very well with optical infrared data from #FIRMS. Occasionally it may happen, that optical data is disturbed by dense smoke. Despite to that SAR can penetrate aerosols and clearly indicate the destroyed area.
You can download the article.


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