CASE STUDIES
AquaPixel identifies
Ben Machnes of AquaPixel writes: “Thrilled to see AquaPixel featured and recognized for our joint mission to make water intelligence Precise. Measurable. Real.
Huge thanks to Ira Dvir and Agrowing for the partnership, technology excellence, and trust in our vision. Together, we’re transforming remote sensing into environmental insight — empowering water authorities and decision-makers worldwide to safeguard one of our most vital resources.
Let’s make water certainty the new global standard.”
Captaim Aurelien Schlossman used Agrowing’s quad sensor with AI to detect human remains buried for three years!
https://www.linkedin.com/feed/update/urn:li:activity:7374068532772446210/How can LIDAR be an asset in the turf industry? This one image speaks volumes of data.
10 bands case study by Agrowing's partner
Almonds orchard; Downsampled NDVI orthophoto (100m altitude)
Detail, downsampled by 4!
AI-Enabled Potato-Blight Detection
Low altitude high-resolution multispectral imagery enables the use of Machine-Vision and Machine-Learning (AI) techniques, separating the brown Blight from the green leaves and the earth-brown. Resolution of sub 0.5mm per pixel, resulting from imagery acquisition from 3m altitude above the crop, enables detection of distinctive multispectral signatures of pests, diseases and nutrient deficiencies.
High Altitude NDVI
Agrowing's narrow bands,high-resolution, high dynamic-range sensors, produce the most detailed NDVI maps one can expect. Such detailed NDVI (and similar metrics) maps, are essential for spotting stressed and outlying areas of the field, at an early stage.
Spotting various degrees of blight is demonstrated in this potatoes test-field. The imagery was acquired from 100m altitude using Agrowing's R10C based sensor with NDVI lens.
The Invisible Revealed
The progression of Black Sigatoka in Banana leaves, and HLB in Citrus, is invisible at early dates.
Analyzing high-resolution multi-band multispectral data of wide dynamic-range, enables machine-detection of the invisible.
