LandWISE 2015 Presenter Ian Yule
A presentation by Ian Yule, Reddy Pullanagari, Gabor Kereszturi, Matt Irwin, Ina Draganova, Pip McVeagh, Tommy Cushnahan, Eduardo Sandoval.
Remote sensing methods are becoming much more accessible for end users in terms of access to results and the method in which they are presented. They can be developed into systems for herbage analysis which will measure every square meter of a farm or river catchment and publish the results in the form of a map, as below, rather than complex hyperspectral analytical measurements.
The team at Massey University have been using a hyperspectral imaging tool called Fenix. It is flown in an aircraft usually at around 500-800 m above ground level and has been used to measure hill country properties within New Zealand in the first instance. The map below shows the level of ME in pasture for an example scene, but the major nutrients can also be mapped in this way.
The catalyst for purchasing the sensor was the Ravensdown/ MPI, funded PGP project; Pioneering to Precision: Fertiliser Application to Hill Country.
The first scientific objective of the project is to map the nutrient concentration of pasture over hill country properties. The business objective is to provide much better information around the productivity of hill country in order to calculate the fertiliser requirements more accurately and improve the overall utilisation of nutrients.
Previous work indicated that significant financial benefit could be achieved from this approach. This is the first time that an imaging tool has been used and this is important because it overcomes many of the difficulties of on-the- ground sampling and then using these samples to represent the whole farm. It is basically impossible to capture the true variability of these properties from ground sampling.
The sensor detects light in the Visible (VIS), Near Infrared (NIR) and short wave infrared (SWIR) parts of the electromagnetic spectrum. This gives it the ability to determine the bio-chemical properties of vegetation that it observes. It has been shown to be a very robust technology for laboratory analysis and this new development takes it out of the laboratory and in the field.
The images captured in strips are mosaiced together in order to develop a single image for the whole area. Each pixel has 448 different layers of information, corresponding to 448 different wavebands which make up the spectral signature for each pixel. It is by comparing the spectral signature using a number of statistical techniques that the nutrient concentration within the vegetation can be identified.
The big advantages with this approach are that the results can be presented in the form of a map, information can be produced quickly with limited need for laboratory based chemical analysis. All of the complex statistical and analysis processes have happened in the background and the results can be presented with in a Geographical Information System (GIS). In a GIS environment data can be linked to decision making software which will help farmers decide on the optimal fertiliser policy for the farm.
Acknowledgement. The image was produced from a survey from the PGP Project, Pioneering to Precision: Fertiliser application in hill country, which is funded by Ravensdown Fertiliser Cooperative and the Ministry for Primary Industries MPI.
New Zealand Centre for Precision Agriculture, Massey University, Institute of Agriculture and Environment. Palmerston North, New Zealand.
John Chapman is the Product Specialist for seeding and cultivation equipment at 
ASL software, (LandWISE Yield Estimation software) and apps for pipfruit and irrigation industries) have developed a ground cover measurement tool. We used it to map MicroFarm onion crop canopies and found good correlation with final yields.
