Data Fusion in Agriculture Hands on Solutions for farmers and - PowerPoint PPT Presentation

AgriCircle Data Fusion in Agriculture Hands on Solutions for farmers and Scientists Peter Fröhlich August 2016 1

AgriCircle Vision Technology to produce more and healthier Food For Farmers • Financial Success • Subsistence • Less area needed to More Yield grow Food for people • Sustainability Less Emissions • Measurable decrease of Emissions in air, water and soil per qty. of Food • Better Nutrition 2

The AgriCircle Tool Easy to use GIS-Field Management as base 3

The AgriCircle Tool Datasets linked to AgriCircle by End of 2016 Satellite Data (Sentinel 2) Remote Sensing Weather Data (GeoTIFFs) (10 Years + 14days) Maschinery Data Emission Data Farmers Data 4

AgriCircle Innovation Current Projects at AgriCircle Quality improvement Optimal application Easier ensurance in ESA – revolutionary in vineyards of crop protection agriculture soil data - All projects are related to agronomy - We are working on the foundation to be able to plan and schedule robotic tasks - We work on an ICT-AGRI-Project in robotics in Europe that is focused on sensor fusion 5

Project Goals  Development of an integrated system for targeted quality guidance in viticulture thanks to the usage of the most innovative hardware and software  Creation of the basis for early detection of water stress and disease patterns  Identification of first new insights for the optimization of input application for the improvement of yield and taste  Start of data collection for step wise optimization of harvest time and leaf-wall management Higher Yield Constant Quality Less Emissions 6

Benefits Detect and Visualize the Invisible Water Stress can be made visible 1) Third Dimension (Red points on the field) Surface Covering and highly resoluted Aerial Overview. Fast detection and correction of management failures (from winter cutting to harvesting). Hyperspectral Images enable 2) Early Detection (before the conclusions for further factors which influence vine up to human eye detects it) its taste Hyperspectral Images have a higher spectrum than the human eye. Diseases and stresses are detected earlier. 3) Changes over Time Thanks to the data illustration on the AgriCircle Platform we create a temporal overview and show new insights 7

Action Steps Systematic Management of Wine Quality Goal: Active crop management for constant wine quality Measure Optimize Influence Manage More Constant Primary Optimization Goals:  Carotin  Hyperspectral Image  Flavour Profile Harvest Point  Terpene  Leaf-wall volume  Leaf-wall Management  Pyracine  Pest & Vitality (Leaf  Quantity Regulation  Anthocyan Colour) Süsse  Irrigation  Glycoside  Chlorophyll  Acid Secondary Optimization Goals:  Sugar  Soil Management  pH  Root cutting  Temporary Greening  Fertilisation  Plant Protection  Vine Cutting 8

AgriCircle Innovation What we are currently doing to get there Scan Vineyard with Collect data vertically Crop assessments on Chemical analysis of Hyperspectral Cam with caterpillar the ground grapes and leafs - In all cases we work with specialists and have established development and business partnerships - We are currently producing THE vineyard with the most complete dataset on the planet 9

AgriCircle Innovation Hyperspectral Camera and Drone Solution 10

AgriCircle Innovation Optimal application of Crop Protection Products 4 1 Data and Interface for insights from application latest Satellite map exchange technology with machinery and other FMIS Crop models Calculation of for PGR field variance application and application 3 rate and timing map 2 based on FMIS data and biomass - The first use case is around PGR-application - The project includes remote sensing data and ground truth data - The whole solution is around easy to use for farmers 11

AgriCircle Innovation Project Pillars Satellite process chain and data correction  The data process chain will provide access to all spectral bands of Copernicus  The system creates a base for other global products and uses to be built  The data shall be available for free for research projects and partners  A first choice of different crop indices shall be provided Calculation of crop vitality and variance  AgriCircle and specialists from ETH Zürich will calculate crop vitality and variance  Different indices will be tracked over time  Crop variance will be shown per field and area PGR Algorithm  The algorithm will combine remote sensing, ground truth and other datasets like weather and more  Datasets have been collected for more than 5 years Easy to use System  AgriCircle connects machines via ISOBUS that allows to send application maps to the tractor independent of its brand  The platform will also offer a REST API to connect via another FMIS and to provide access to other 3 rd parties (f.e. in R&D) 12

Approach and Results – Work Stream 1 Overview work stream 1 1 Sentinel 2 data interface Farmer requests data for his fields 1) Process Satellite Image Storage of indexed file images:  One index for Germany  Approx. 20 pics per 2) Atmospheric and cloud field and year corrections 3) Calculation of indexed file image t used for PGR modelling Indexed satellite image series is 13 loaded to FMIS for relevant fields

Approach and Results – Work Stream 2 Overview work stream 2 2 Calculation of crop vitality and variance S2 index file series with :  Field shape  Indexed satellite image over time Is used in combination with drone field trial data for PGR application t Correlate index with crop vitality is modeled based on gathered data. Based on vitality variance (in %) is calculated Variance is display in GIS- application map as a shape file 14

Approach and Results – Work Stream 3 Overview work stream 3 3 Crop models for PGR application Trial-data for PGR that includes:  Crop & Variety drilled  Drilling date  Fertilizer applied  Fertilizer planned  Crop Protection applied  Soil type and pH  BBCH AgriCircle application map includes:  Field shape  S2 index files  Application Variance (0- 100%) (WS2) PGR-Algorithm that uses local as well as remote sensing data AgriCircle historic weather data  Temp. Sum  Soil Temp. Sum  Sunshine hours (Sum)  Rain Sum 15

Approach and Results – Work Stream 4 Overview work stream 4 4 Platform Integration and interface for application map exchange Algorithm Conversion to ISOBUS Interface to Tractor and other FMIS Integration Format Open Interface to other FMIS Output: Input:  Crop Application Map with:  Dosage  Drilling date  Variety  Fertilizer applied  Crop Protection applied  Soil type  pH  BBCH Integration of Shape-ISOXML PGR algorithm converter that Universal logger box allows into AgriCircle and allows to transfer machine independent use connect it with application map of application map application map 16

AgriCircle Innovation Innovation partnerships 17

AgriCircle Innovation Innovation partnerships – EnMAP - HyperspecSat • Full range VNIR/SWIR (420 nm – 2450 nm) satellite imaging spectrometer for quantitative surface parameter retrieval • Frequent coverage for monitoring on global basis • Pixelsize: 30 m • Repeat cycle of 27 days • ± 30 ° off-nadir pointing for frequent revisit (≤ 4 days ) • GFZ scientific PI supported by international science team • Launch in 2018 • Further hyperspectral missions in planning: HISUI, SHALOM, HySPIRI, PRISMA 18

AgriCircle Innovation Phenotyping – With first of its kind trial site Continuous scans for agronomic purposes for more than 5 years 19

AgriCircle Innovation Knowing what Indices to be used for which Situation 20

AgriCircle What makes us different Platform First truly geo-based farm management system that allows farmer to view and track activities based on 1 agronomy in the field 2 First farm management tool that tracks CO 2 emissions in the field Connects data to optimize yields and saves costs through more precise application of crop protection, 3 fertilizer and seeds Organization 4 High innovation drive combined with a very competitive cost structure 5 Farmer centered product focus that puts agronomy first 6 Independent from any large player or industry 21

Collaboration How is this relevant to me 1. We can deliver the agronomy to schedule robotic tasks 2. We do partner in innovation with other companies and know different funding schemes in Europe 3. We will provide APIs for development linked to our portal soon – Just ask what you need 22

Contacts Peter Fröhlich CEO MBA-HSG, Ing. Agr. FH T: +41 79 871 99 88 peter.froehlich@agricircle.com Daniel Markward AgriCircle AG COO, Chairman Herrenberg 35 MBA-HSG CH-8640 Rapperswil T: +41 79 227 98 24 www.agricircle.com daniel.markward@agricircle.com 23

Q&A 24