Category Archives: Data Analytics

Interoperability for Agriculture

Palmerston North, Friday 8th December 2017

From Landcare Research:

Few activities are more tied to location and the geospatial landscape than agriculture. Agricultural businesses, research and policy makers rely on quantitative data about soils, water, weather, inputs, productivity, outputs, and markets.   This summit will tackle the big questions on big data for agriculture in New Zealand and globally: how to make it really work for farmers, policy-makers, markets and consumers?

Presentations and workshops will cover

  • Precision Agriculture
  • Environmental Data and Information
  • The Internet of Things and new sensor technologies
  • Applications and mobile
  • Privacy, security and protections
  • Maps and models  – current and future
  • Collaborations  and standards in action

Join international geospatial experts along with local innovators in Palmerston North for this one day Summit.

Date Friday 8th December 2017
Time 9.00am – 4.00pm
Agenda See here>
Enquiries Christine Harper harperc@landcareresearch.co.nz

Australasian Precision Agriculture Symposium

Dan Bloomer attended the 20th Symposium on Precision Agriculture in Sydney.

The PA Symposium brings together farmers, growers, researchers, advisors and industry to discuss and absorb developments. Speakers covered cutting edge research, on-farm application by researchers, advisors and farmers, and industry background information such as the state of telecommunications and data ownership.

As Brett Whelan told delegates, “The purpose of precision agriculture has always been to increase the number of correct decisions made in the businesses of crop and animal management. It is a logical step in the evolution of agricultural management systems toward increased efficiency of inputs relative to production, minimized waste and improved product quality, traceability and marketability.”

Crop and soil sensing continues to develop, and there is increasing use of new approaches. Canopy assessment has relied heavily on NDVI, the 1970s vegetation index chosen for distinguishing forest from desert and ocean.  In recent years a wider range of sensors capturing more light bands (blue, green, red and infrared) have become affordable and available. Some look at red-edge and thermal infra-red, two bands often related to crop stress of some form.  Off the shelf cameras that fit simple UAVs are within farm budgets now.

Ian Yule described research with hyperspectral sensors that capture very detailed images with hundreds of light bands. Hundreds of ground control samples provide “real” information and enormous amounts of data get analysed to identify relationships. The capacity of this to determine species, plant nutrient status and other useful information is remarkable. The current research equipment and processing is very expensive but assume price drops as commercialisation progresses.

Machine vision including object shape, texture and colour is being used to recognise individual objects such as plants, parts of plants or specific weeds. Discussing robotics research to guide decision making on vegetable farms Zhe Xu noted, “If a human can recognise something, a machine can be taught to as well.” Get used to artificial intelligence, neural programming and autonomous phenotyping!

We presented our own onions research which is using smartphone cameras to capture very useful crop development information quickly and cost effectively. Combined with crop models and web based calculation we can predict final yields with fair accuracy early enough to support crop management decisions.  

An Australian vegetable research project is using similar approaches to support decision making in carrot crops and investigating others with promise.  That team includes researchers and farmers, and is increasingly using yield monitors for crops such as potatoes and carrots. Converting yield data to value allows farmers to estimate costs of variability and how much to invest to fix problem areas.

Data capture, communications and analysis was a key theme.  Kim Bryceson described the establishment of a sensor network and analytics using IoT (internet of things) tools at Queensland University Gatton.  Rob Bramley explained a process that predicted sugar yields at regional scale to promote better fertiliser management in that industry. Patrick Filippi presented a “big data” approach to predicting grain yield.

The data revolution is changing our world in ways we can’t yet imagine. The increasing amount of things measured, the spatial scale and time span of collection and development of data science to analyse huge streams of information revolutionise our understanding. These are exciting times. Some jobs are going to go, but others will be created as we require completely new skills for jobs not heard of a decade ago. 

“We are all in the position of making decisions from a limited understanding or a particular perspective, working with biological systems that are incredibly complex and impossible to fully understand, “ said Ian Yule. “Recent experience with new sensing technologies and data processing has produced new information that challenges our preconceived ideas and understandings,” he said.

The PA Symposium is presented by SPAA, the Society for Precision Agriculture Australia, and the Precision Agriculture Laboratory at the University of Sydney. There has always been a New Zealand presence because while some details are unique, the tools and processes are for the most part generic. 

Counting buds and berries

James Beech and Tony Cooper are data scientists and the principals of Precision AI Ltd. Tony and James will present to “LandWISE 2017: Are we ready for automation?” and discuss how machine vision and machine learning can be used to automate such things as counting buds, shoots and fruits in orchards and vineyards. 

Capturing quality imagery with changing light conditions, when your target is hiding behind leaves and you are traveling at speed on bumpy ground is quite a challenge. Identifying and quantifying the things you are interested in is a challenge as well.

What are the tools that can help? How close are we to automatically collecting this type of data?

James has over 15 years’ experience in software development, advanced analytics and data visualisation.

James specialises in open data, data infrastructures, business intelligence dashboards and predictive modelling. James is has particular interest in the application of big data through the use of statistical and analytic techniques to solve business problems. His experience spans across financial services, telecommunications and the agricultural sectors.

Tony has a distinguished track record in predictive analytics and data mining. His specialties include machine learning and computer vision. 

Tony has made exciting advances in quantitative research and received industry accolades. He holds a Bachelor of Science (Hons.) in Statistics and Computer Science from Massey University and a Master of Science in Statistics from Stanford University (USA).

Integrating Public and Private Spatially-based Data

Aaron McCallion

Very pleased to confirm Aaron McCallion as a speaker at our Annual AgTech Conference LandWISE 2017: Are we ready for automation?

Aaron’s presentation will focus on how public and private data are being integrated to provide better land management outcomes.

For example, a recent European initiative has used data integration to automate pesticide application to crops in a way that protects adjacent natural ecosystems through the use of legal buffer zones identifiable by machine readable maps. 

In New Zealand, integration of public and private data is being piloted to assist Maori land owners in achieving economic returns within their environmental, social and cultural values.  This is being enabled through open government data initiatives that include legal land titles, vegetation cover maps, soil databases, digital elevation models and remote sensing.

The impact of different land management approaches can be assessed when such public data is combined with private data that includes historic land use practices, climate monitoring, ecosystem health indicators, inputs and financial data.

Visual representation of this spatial data in interactive mapping and analysis tools can then allow users to understand land management issues as well as aid the identification of risk mitigation or restorative strategies.  

Aaron will discuss what is needed for such approaches to be effective,  and ethical and legal requirements that need to be maintained with respect to privacy where the public or private data could identify individuals.

Aaron McCallion is Executive Director of Waka Digital, a leading Information Technology firm established in 2006 to deliver IT and communications based products and services. 

Aaron combines system dynamics modelling, economics and management with his understanding of sustainable development and environmental restoration. His skills include assessment of effectiveness, efficiency, user satisfaction and accessibility to measure or improve the usability of new or existing products or services, including prototypes.

He is a Key Researcher in the MBIE programme, Oranga Taiao, Oranga Tangāta – Knowledge and Toolsets to Support Co-Management of Estuaries and previously in the MBIE gold-rated programme, Manaaki Taha Moana-Enhancing Coastal Ecosystems for Iwi. (2009-2015)

Aaron has a BBS from Massey University and an M.B.A. through the global program operated jointly by Sejong University in Korea and Syracuse University in the United States.