NDVI Imaging, 2D Orthomosaics, 3D Topographical Imagery
Aerial Vision provides NDVI Imaging services for Ontario's agriculture industry. Our ability to make frequent flights means that images can be taken across different dates to see how a crop / turf has changed over time. Change detection images allow a crop or turf manager to quickly determine if the crop / turf is growing uniformly or if problems exist that are causing the vegetation stress.
NDVI Imaging can help:
Turf Management for Golf Courses
Vineyards Across Ontario
Actionable information that NDVI imaging can provide:
Plant stress and health
Nitrogen Management Solutions
Insect and pest plant diagnostics
Plant disease diagnosis
Develop farm plan
Guide cultivation plan
Develop harvest plan based on vigor
Utilizing UAVs for Digital Imaging Analysis (DIA)
Unmanned Aerial Vehicles (UAVs) are an exciting new remote sensing tool capable of acquiring high spatial resolution data. Our UAVs are capable of collecting hyper resolution visible, multispectral, and thermal imagery for application in precision agriculture. Traditional modes of data collection are not well suited to the detection of subtle but important changes in plant structure given low spatial resolutions.
Mapping with UAVs has the potential to provide imagery at an unprecedented spatial resolution. Our UAVs have several payload options including visible imagery, which is processed using feature matching and photogrammetric techniques to create Digital Surface Models (DSMs). A thermal infrared camera can be used to map soil moisture enabling assessment of irrigation efficiency, and multispectral camera enables the calculation of vegetation indices that relate to vegetation vigour and health.
The highest spatial resolution data available from conventional platforms such as satellites and manned aircraft is typically in the range of 20-100 cm/pixel. UAVs are capable of flying much lower and hence can collect imagery at a much higher resolution, even as detailed as 1 cm/pixel. The Temporal information of conventional systems is limited by the availability of aircraft platforms and orbit coverage patterns of satellites. For the purpose of monitoring highly dynamic vegetation such as that within vineyards, satellite sensors are very much limited due to unfavourable re-visit times.
The versatility of the UAV system is further enhanced by the fact that the data can be collected "on-demand", providing unprecedented Temporal information that spans the critical times in the crop growing season. The imagery produced from UAV collected data has a spatial resolution generally from 2 to 5 cm/pixel.
Normalized Difference Vegetation Index - NDVI Imaging
Plants typically absorb visible blue and visible red light while reflecting green and Near Infrared (NIR) light. The reason we see a plant as green is because it is reflecting the green light to our eyes. Plants also reflect the NIR light because the infrared light doesn't have enough energy to support photosynthesis. Healthy plants reflect green and NIR while absorbing blue and red light. As plants become sick, they don't reflect green and NIR as well. There is a mathematical algorithm (ENDVI) that works in conjunction with a special camera that captures both visible and infrared bands of light. By processing the picture with ENDVI algorithm, you get a new picture that shows where plants are happy and where they are not.
NDVI is one of the most successful of many attempts to simply and quickly identify vegetated areas and their "condition," and it remains the most well-known and used index to detect live green plant canopies in multispectral remote sensing data. Once the feasibility to detect vegetation had been demonstrated, users tended to also use the NDVI to quantify the photosynthetic capacity of plant canopies.
Enhanced Normalized Difference Vegetation Index (ENDVI)
ENDVI is a new way to analyze vegetation and other objects using visible blue, visible green and near infrared data. Traditionally, Normalized Difference Vegetation Index (NDVI) NDVI uses only red and near infrared data.
Digital cameras respond different than film, the camera has near infrared and visible bands in separate channels. Once you have the NIR isolated in a color channel, you can perform NDVI type measurements. With our NDVI cameras, the blue and green channels see visible light while the red sees the NIR.
The camera image is converted by processing the picture with specially developed software. The software looks at each pixel Red, Green, Blue value and using the values, calculates a vegetation index for that particular pixel. Depending on the value of the number, a particular color is assigned to that pixel. Each pixel in the original picture is evaluated and assigned a color. The process of assigning colors depending on the value is called False Color Mapping.