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Remote Sensing

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5-Band
Remote Sensing Explorer

 

Model: XNiteCanon700NDVI  18 Megapixel DLSR 3-Band Vegetation Stress Camera Canon T5i

Model: XNiteCanon5DMK3NDVI  22.3 Megapixel DLSR 3-Band Vegetation Stress Camera Canon 5D MK 3

Model: XNiteNikonD7100NDVI  24.1 Megapixel DLSR 3-Band Vegetation Stress Camera Nikon D7100

Model: XNiteNikonD600NDVI  24.3 Megapixel DLSR 3-Band Vegetation Stress Camera Nikon D600

Model: XNiteNikonD800NDVI  36.8 Megapixel DLSR 3-Band Vegetation Stress Camera Nikon D800

Model: XNiteSonyNEX7NDVI  24.3 Megapixel DLSR 3-Band Vegetation Stress Camera Sony NEX7

 

 

 

Model: XNiteCanonELPH110NDVI  16.1 Megapixel Point & Shoot Lightweight 3-Band Vegetation Stress Camera

Canon PowerShot ELPH 300 HS 12 MP CMOS Digital Camera with Full 1080p HD Video

bulletELPH 110 Dimensions: 3.7 x 2.2 x 0.8 inches / 93.2 x 57.0 x 20.0mm
bulletELPH 110 Weight with Battery: 4.8 ounces / 135 grams
bulletELPH 110 Battery Life. Approximately 170 shots

 

Model: XNiteCanonSX260NDVI  12.1 Megapixel Point & Shoot Lightweight 3-Band Vegetation Stress Camera with GPS

Canon PowerShot SX230HS 12 MP Digital Camera with HS SYSTEM and DIGIC 4 Image Processor

bulletSX260 Dimensions: 4.2 x 2.4 x 1.29 inches / 106.3 x 61.0 x 32.7mm
bulletSX260 Weight with Battery: 8.15 ounces / 231 grames
bulletSX260 Battery Life: Approximately 230 shot

 

We offer a variety of cameras for remote sensing and monitoring vegetation.  We can make either a Blue-Green-NIR 680 to 800nm or a Green-Red-NIR 800 to 900nm version.  Our 5-band 2-camera system utilizes both types of cameras and comes with special software to automatically register and align the images to create a 5-layer data stack.

Our Remote Sensing Explorer (RSE) software is offered at a discounted price to purchasers of our cameras.  

Key Features

bulletRemote Sensing
bulletCan be used as a Chlorophyll Meter or
bulletPlant stress and health
bulletFertilizer Optimization
bulletNitrogen Management Solutions
bulletInsect and pest plant diagnostics
bulletPlant disease diagnosis
bulletCamouflage detection
bulletForrest Analysis
bulletPlant Identification
bulletEasy to Use
bulletUp to 18 Megapixels of resolution
bulletELPH110NDVI and SX260NDVI model is small, lightweight suitable for UAV's.
bulletELPH110NDVI and SX260NDVI optional firmware upgrade allows features such as timed interval shutter control and RAW pictures.
bulletSX260NDVI has a built in GPS

If you are not technically inclined, and you would like to learn more about the small vegetation stress camera, please go here.

 

Technical Description

Vegetation has light reflection bands and light absorption bands.  By looking at the relationship of the light absorption and reflection, plant health, stress, biomass and such can be measured.  Our Blue-Green-NIR cameras use blue as the absorption channel and NIR as the reflection channel.  These cameras perform quite well and as easy to use.  Historically, red was used as the reflection channel because, when sensing vegetation from space, the blue light was scattered more due to Rayleigh light scattering.  For fixed wing aircraft and UAV's, using blue as the plant absorption channel gives you better band discrimination.   

Blue-Green-NIR 680 to 800nm Cameras

bulletBlue Channel    - Visible Blue Light
bulletGreen Channel - Visible Green Light
bulletRed Channel     - Near Infrared from 680nm to 800nm

Blue-Green-NIR 680nm to 800nm

 

 

For those that want the NIR signal in the blue channel, we can also make a Green-Red-NIR 800 to 900nm camera.  Note that the NIR bands are different with the two sorts of cameras.

aGreen-Red-NIR 800 to 900nm

bulletBlue Channel    - NIR 800 to 900nm
bulletGreen Channel - Visible Green Light
bulletRed Channel     - Visible Red

 

 

 

With the same WB setting, you can assume that camera sensor response curves will look very similar to each other.  While sensors will have different sensitivities due primarily to pixel size, all the sensors are silicon based devices with similar Color Filter Array (CFA) dyes.

We can also add an optional Blue-Green notch filter to the camera either as a separate filter for the DLSR's or as an integrated filter for the point and shoot cameras. 

 Adding the Blue-Green notch filter will give better band discrimination at the cost of lower overall sensitvity.

We have created a vegetation stress camera that allows you to take one picture and get the visible blue light in the blue channel, visible green light in the green channel and get the near infrared light the red channel.  By evaluating the red versus the blue and green  channels, you can quickly get information about vegetation as well as minerals, bodies of water, camouflaged object detection and more.  Healthy plants have a strong near infrared reflectivity, sometimes called the "Red Edge".  Our non-destructive, easy, remote sensing camera allows for quick and accurate analysis.  The ratio of the near infrared reflectivity to the visible reflectivity can give you information on the plants health, discern bodies of water, barren land, shrubbery, rainforests, minerals and more.  Aerial photographs with our camera can allow farmers to quickly asses the health of their crops spotting disease, sick plants, weeds and other variations.

How to measure vegetation stress with our camera and convert image to a scaled NDVI picture

bulletTake a picture with our camera.
bulletUsing our RSE software or other compatible software to process the picture.
bulletLook at picture

Traditionally, the NDVI ratio was calculated with special Kodak infrared film which had the unusual property of the blue channel capturing the infrared and the red and green channel capturing the visible red and green.  Kodak has discontinued this film.  With our digital camera, the blue channel captures the visible while the red captures the near infrared, which is the reverse of the Kodak film. Taking pictures with our camera and then finding the RGB values for any point using a program such as Photoshop, you can get a direct reading of both near infrared and visible light.  Using our camera makes the process simple and easy.

Advantages over Chlorophyll Meters

bulletMuch more information.  Most Chlorophyll meters use two pixels.  One infrared and one visible.  Our cameras have 12 to 18 million pixels of data in each picture!
bulletLower Cost
bulletEasier to use
bulletLive LCD display
bulletHuge post processing potential using our RSE software.
bulletMeasurements may be done from far distances including aerial.  Chlorophyll meters must almost make contact with the leaf.

 

Quick and easy chlorophyll measurements of plants without damaging the leaf.  Because chlorophyll is reflective in the hear IR and because a unhealthy plant has a drop in chlorophyll, comparing the hear IR reflection to the visible green or blue will give you a non-destructive way to assess plant health.  The NDVI cameras can be used to monitor the growth and health status many agricultural products including corn, wheat, rice, cotton, oranges.  Fertilizer optimization is possible by allowing the user to see if plants are over or under fertilzed.

Since the 3-band camera includes the visible blue and green bands, the user can discriminate between bodies of water and plants. 

This camera can also be used to detect camouflaged objects.  While a camouflaged object may be hard to detect in normal human visible colors, often the dyes and pigments used to camouflage the object have different responses in the hear IR.

Picture of a bag with a normal camera                                                   Picture of a bag with a Canon NDVI

Noite that in the second picture, the zippers on the bag are red while the normal camera see a black bag.  This effect occurs because the color dyes used on the zippers happen to reflect infrared light while the black leather does not.

 

Please note that we no longer support ImageJ for post processing the images.  Our new RSE software is over 100x faster, much easier to use and gives the customer many more options for exploring the data.

 

Normal Healthy Lawn

Regular Picture                                                                                               NDVI Processed Picture

 

 

 

 

                                

 

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Last modified: June 18, 2015