Multi-Layer Analytics

Maps generated with a single data layer and several data layers.

Precision agriculture is capable of generating vast amounts of data in the form of yield data, satellite imagery, and soil fertility, among others. Lack of easy-to-use cloud precision software toolkits that assist crop producers in converting field data layers into useful knowledge and actionable recommendations limits the application of precision agricultural technologies. In precision agriculture, management zones are areas within a field that have similar yield potential based on soil type, slope position, soil chemistry, microclimate, and/or other factors that influence crop production. The producer’s knowledge of a field is a very important piece of the process. Management zones are thought of as a mechanism to optimize crop inputs and yield potential.
The big challenge is to build management zones that perfectly reflect field variability. A combination of different layers like satellite imagery, soil fertility, topography derivatives, and yield monitor data is the next logical step to generate more responsive management zones.

Multi-layer analytics (also known as integrated analysis) is becoming a part of the GeoPard geospatial analytics engine.

Classic combinations of integrated analysis parameters include one or more of yield data, NDVI map, elevation, and soil sensor physicochemical characteristics. GeoPard supports these parameters and in addition, allows the inclusion of other field data layers either already available in the system or uploaded directly by the user (soil sampling, yield datasets, etc.). As a result, you are free to operate with the complete set of parameters doing integrated analytics:

Yield data
Remote sensing data:
    –   Potential productivity map (single-year and multi-year)
    –   Stability/variation map
    –   Vegetation indices NDVI, EVI2, WDRVI, LAI, SAVI, OSAVI, GCI, GNDVI
    –   Digital elevation
    –   Slope
    –   Curvature
    –   Wetness index
    –   Hillshades
Soil data:
    –   pH
    –   CEC (cation exchange capacity)
    –   SOM (soil organic matter)
    –   K (potassium)
    –   Thin topsoil depth, lower available water holding capacity (drought-prone soil)
    –   EC (electrical conductivity)
    –   and other chemical attributes available in the uploaded dataset

It’s important to emphasize that custom factors are configured on top of every data layer to assign the desired layer weight. You are very welcome to share your integrated analytics use cases, and build management zones maps based on your knowledge of the field while selecting data sources and their weights in GeoPard.

Pictures in this blog containes a sample field with data layers (like a productivity map covering 18 years, digital elevation model, slope, hillshade, 2019 yield data) and various combinations of integration analytics maps. You can follow steps of evolution of management zones while extending integration analytics with an additional data layer.

Share Farm and its data

The agricultural business is teamwork.

Frequently it is necessary to share farm data with your ag consultant, agronomist, trusted advisor, farmer, colleague, or service provider. GeoPard has a very simple nevertheless powerful mechanism of sharing your farm data and all the underlying data we provide for you (Satellite monitoring, Zones, Topography) or you uploaded by yourself (Soil data, Yield data, other ingested data layers).

An owner of a farm can give access to it in the “User Profile” -> “Share” section. You put your colleagues’ email and we share the farm and all the data under the farm with another GeoPard account.

An owner of a farm can revoke access at any time by clicking the “Stop sharing” button under the “User Profile” -> “Share” section.

A user who has been shared a farm has some kind of a “read” access to the farm and fields under it. It means that the user, for example, can’t delete the farm. But he is free to delineate new management zones or any other analytics. It can be very useful when you do collaborative preparation of Management zones for planting/fertilizing/spraying.

All GeoPard URLs are bookmarkable, it means that a URL fully contains the state of the application. After you share any GeoPard’ URL with your colleague, he will see exactly the same state of the map that you shared.

With GeoPard Agriculture all the data is under your control and at your fingertips for spatial analysis and Rx files creation.

Merge and Split Zones

Nobody knows his field better than a farmer or agronomist who works with the field for many years. That’s why any algorithm-based analytics often needs to be validated and adjusted by a professional using his deep knowledge of the field.

Merge and split zones feature allows a professional to make a few important things: 

  • Split polygons
  • Merge polygons
  • Assign a polygon or a complete zone to another class

These adjustments can be applied for any data layer and it is a very useful feature to prepare YOUR perfect zones for precision ag operations like VR seeding, fertilizing or spraying.

GeoPard showcased at FoodHub NRW expo

Last week GeoPard team presented at the Foodhub NRW expo in Neuss, Germany.

Our speaker session was about the state of Precision Agriculture, past, present, and the future.
In detail, we described a few examples of how decision support tools and data analysis helps to implement data-driven crop farming practices in different regions: the US, Canada, Europe.

We are proud to be in the epicenter of innovations in the crop farming industry.

It was great to meet a lot of food startups. Agriculture is one of the biggest industries in the world and we need more innovations and collaborations between corporates and startups across the value chain.

Integration with MyJohnDeere Ops Center

The team at GeoPard is pleased to announce their integration with the MyJohnDeere Operations Center. MyJohnDeere customers can now seamlessly upload their data into the GeoPard system, where they can do an advanced data analysis, compare information to other data sets, and create detailed Variable Rate Application (VRA) maps for seeding, fertilizing and spraying. These maps can then be wirelessly sent back to the MyJohnDeere Operations center and subsequently to fleets and machinery via a cloud-to-cloud connection, with no need for a USB stick.  
Moreover, GeoPard provides automated synchronization of crop monitoring, detailed topography analytics, machinery and soil scanner data for MyJohnDeere clients.

Agronomists, agribusinesses, precision agriculture specialists, and equipment dealerships can all utilize the GeoPard platform as a means to collate many data sets for optimal analysis. From the John Deere Operations Center, field boundaries, seeding (as-planted) data, as-applied fertilizer maps, as-applied crop protection, tillage data, and yield data can all be imported to GeoPard and cross-analyzed. This integration has simplified the data analysis process for multiple parties and stakeholders by providing them with a smooth-running analytical engine to gain new insights about relevant land parcels and logistics. 

“Growers, JohnDeere dealerships, and ag consultants need solutions to get informed data-based decisions. We are proud to collaborate with John Deere to enable GeoPard precision agriculture analytics solutions for John Deere clients via wireless integration with MyJohnDeere portal,” said Dmitry Dementiev, co-founder of GeoPard Agriculture.

This collaboration optimizes all the benefits of precision agriculture to users by making the creation of complex and personalized VRA maps increasingly accessible and simple to navigate and manage. Prescription maps can be sent back to the JD Ops Center and to machinery in a streamlined process that promotes efficiency and accuracy for the VRA of multiple inputs.

About John Deere Ops Center: John Deere Ops Center is a digital platform of agricultural corporation John Deere, where users can manage the logistics and services of their machine fleets and equipment. The data is stored securely in user accounts and allows customers to share and analyze their data systems via the internet and IoT devices, optimizing the efficiency of fleet and land management.  Learn more at:

About GeoPard Ag: Geopard is an AgTech company whose mission is to develop accessible and affordable enterprise-level analytics for sustainable agriculture. Their platform allows you to simplify the complexities of precision agriculture through tools and services like VRA map creation and multi-layer yield, soil, topography, ground scanners and satellite data analytics. Learn more at:

Realize 5-10% more yield in potatoes

At GeoPard we value our customers and their needs above all else, so we are pleased to share this success story from one of our clients Databoerin, an innovative smart farming consultancy firm from the Netherlands.

Our goal is to provide professionals in this field with access to cutting-edge technologies and advanced data analysis so that everyone can benefit from the implementation of precision agriculture. Nothing makes our team at GeoPard happier than seeing our technology being used to improve yields and help farmers, and we sincerely appreciate the business of our valued clients like Databoerin.

Use Case: fertilizing potatoes with GeoPard maps to realize 5-10% more yield

We have been making maps for fertilizing potatoes for a number of years now. The Sentinel-2 satellite data in the Geopard platform provide an excellent starting point for this.

Optimal nitrogen fertilization is fertilization that is tailored as closely as possible to the needs of the crop. It is not easy to determine this, especially on soils where a lot of nitrogen can mineralize in the soil. The best chance of success is nitrogen division. At the beginning of the season a basic fertilization is given (about 60% of the recommended amount) of a combination of manure and fertilizer. The fertilizer ensures that the growth of the plant starts. The manure has a slower effect and mineralization depends on the weather conditions.

With the additional fertilization in the period around the closure of the crop, we can match the needs of the crop as closely as possible. We determine the needs of the crop on the basis of the chlorophyll content in the leaf. The chlorophyll content has a direct relationship with the amount of nitrogen absorbed.

Side-dressing VRA map for the fertilizer spreader

Within a day after Sentinel’s cloud-free images were taken, the Geopard platform provides the processed images with the chlorophyll index RedEdgeChlorophyll that we use in the calculation to determine the amount of nitrogen absorbed. Based on the crop-growth model, the optimal uptake of nitrogen is calculated and the difference is converted into a VRA map for the fertilizer spreader.

Practical tests of a number of years have shown that an additional yield of 5-10% can be achieved with the use of the same amount of fertilizer, but better distributed over the plot.

Distribution of vegetation one month after side-dressing fertilizer

An additional advantage is the more even development of the crop. The differences, which remain mostly visible after fertilization, are the differences in potato varieties, visible in the EVI2-index. The even position of the crop also ensures uniform protection against phytophthora and uniform ripening before harvest.

Nicole Bartelds, Director and Smart farming advisor at Databoerin.

To find out how GeoPard can provide geospatial analytics that inform your agricultural business or operation, please contact us and we would be delighted to help.

SoilOptix® Data Analysis in Precision Agriculture Platform GeoPard

The importance of healthy soil systems in agriculture have been historically undervalued, but innovative agtech co

The importance of healthy soil systems in agriculture have been historically undervalued, but innovative agtech companies like SoilOptix® are shifting this paradigm with data that supports both farmers and local environments. Precision agriculture is creating increasingly economic and sustainable systems with modern technologies that can measure vital aspects of land composition, ensuring crops and livestock are managed as efficiently as possible. SoilOptix ® facilitates this type of sustainable land management by enabling the accurate collection of soil data without doing a labour-intensive soil sampling. 

Soil Data & Variable Rate Application (VRA) maps

Variable rate Lime application based on SoilOptix® pH levels. The cost of product is calculated by GeoPard

A main reason for global topsoil loss has been the mismanagement of fertilizers, pesticides, irrigation systems, and other agro-inputs on a large scale. It is not economically feasible to apply the same amount of, for example, high Nitrogen fertilizers over an area where only a fraction is lacking in Nitrogen. This is also commonly done with the comprehensive application of lime to balance out acidic soils, despite the fact that only a few specific soil patches with a low pH may need it. Assuming a monotonous soil composition across large areas simplifies what is one of nature’s most complex systems. This is where SoilOptix® data contributes immense value to farmers, who can view maps that specify exactly where and in what quantities different types of fertilizers and other inputs need to be applied via VRA. This not only saves costs for farmers, but also contributes to the longevity of that land parcel, which may have otherwise been over-fertilized and expedited the eutrophication of nearby lakes and water sources. Precision agriculture is all about providing agricultural systems with tools for economic and sustainable development, and this is demonstrated by using soil data to maintain and create healthy soil systems that are actually cheaper to amend. As GeoPard co-founder Dmitry Dementiev says:

“Modern precision agriculture is the synergy of agronomy, technology, software, hardware, all of which optimize sustainable and economic decision making. We are happy to work with SoilOptix®, and analyze soil data from the soil ground scanners to provide real time value to agronomists.” 

Understanding SoilOptix® data through GeoPard

Importing SoilOptix® data into GeoPard can simplify the process of understanding soil mineral composition by providing clearly mapped value gradients that are designed for VRA. The variety of soil elements that SoilOptix® technology measures can be viewed with different layers in GeoPard, and can be compared and contrasted to better visualize patterns and correlations in a land parcel. It is also possible to create Rx maps with a multi-layer approach, where users can combine and cross-analyze SoilOptix® data with GeoPard data sets like historical vegetation, topography, yield, or soil moisture.

“The appetite for soil data as part of this modern precision agriculture system is ever increasing as demand for a more healthy soil landscape evolves. We are happy to have GeoPard as part of the platforms working with SoilOptix® data to enable growers and agronomists with the tools to accurately and visually analyze and manage their fields.” – Zachary Harmer, North America Sales & Global Support Manager at SoilOptix®

Moreover, GeoPard is capable of automatically create a complete topography profile with soil scanners data and with the latest updates also to create a 3d map of a scanned field

3d map of a field was created in GeoPard Agriculture platform using the data from SoilOptix® scanner. The 3d map is overlaid by pH management zones (later used for variable rate lime application) from SoilOptix®.

This data compatibility between GeoPard and SoilOptix® exemplifies the expression ‘work smarter not harder’, by providing agribusinesses and agronomists with the tools and multi-layer analysis needed to optimize yields and save costs on inputs. 

Advanced Statistics For Management Zones In Precision Agriculture

The accurate calculation of statistics is a cornerstone of precision agriculture data analysis. GeoPard has added more detailed statistical calculations to the zones created on the platform to ensure that your maps and the analytic conclusions you draw from them are precise and reliable. 

Advanced statistics are calculated per zone, containing the attributes: minimum and maximum values of the vegetation index (or other attributes), medianaveragestandard deviation, and the sum of all the values in the zone. The median is the middle value of a dataset that has been numerically ordered, as opposed to the average. This relates to the standard deviation, which reflects how the data is arranged around the average value. A low standard deviation suggests that the data in a given zone is grouped closely around the average, whereas a high standard deviation indicates that the zone data is spread out more widely around the average. The sum attribute is simply the total sum of all pixel values in that zone. Before any stats are calculated for your zones, all the outliers or anomalous data points are removed to prevent the creation of misleading statistics that do not accurately reflect your zone data. 

After the manual amendments of zones through the Merge/Split tool, zone statistics are recalculated based on the new zone geometries. This allows for a refined and accurate understanding of data distribution inside and across zones.

Management zones statistics in GeoPard

As always, GeoPard values transparency throughout all aspects of the platform. During the aggregation of classified data into zones, all details are smoothed and hidden without metrics to show what happened, so the results of the data aggregation are provided through statistics. It is also always possible to backpedal and extract the original values from your zones to recheck them or to utilize them in your own models. You never need to worry about losing your original data in GeoPard. Statistics are of high value in determining map accuracy and are calculated for zones based on any data layer of your choice, including yield, ground sensors, satellite, topography, and multi-layer. 

GeoPard presents zone statistics in a highly readable and straightforward manner, which can be seen in the example images below. At GeoPard we want to make it easy for you to be confident in the decisions you are making about your fields by providing you with the best and most comprehensive access to statistical calculations we can.

3D Topography Maps in precision agriculture

3d topography model overlaid with the Field Potential map

GeoPard is making history by being the first company to automate the online creation of high-resolution 3D topography maps with their new 3D mapping tool. In just a few seconds, users can generate maps that contain and simplify the complex variability in the topography and relief data of a given area. GeoPard is continuing their mission to make such resources more accessible, and users do not need a powerful computer or specialized skills to produce and analyze these novel maps. 

This 3D mapping tool can be used with any base layer, including LIDAR topography, slopes, soil agrochemical properties, data from yield/as-applied/as-planted datasets, ground scanners and even vegetation indices. Additionally, any cover map like zones from yield, historical vegetation, organic matter, electrical conductivity, or pH distribution can be utilized on top of the base layer. The maps generated through this tool can help users better understand how relief and topography influence soil properties, vegetation, and yield, and contribute to a better visual and analytical understanding of how to manage individual land parcels. 

It is important to say, that it is a live 3d model that works directly in the browser without any 3rd party programs or extensions installation. You can rotate, zoom in and zoom out, and change cover maps to understand fields better.

The way topography affects vegetative growth has a significant impact on crop yield, which you can read more about in a previous blog post here. This places in perspective the value of the GeoPard 3D mapping tool, which can improve our knowledge about yield potentials and inform planting patterns. Whatsmore, 3D modeling provides insight into how watersheds feed into your land and the pathways water takes when infiltrating your soil. GeoPard’s topographic maps can relay essential information about surface and subsurface drainage inefficiencies, allowing irrigation and drainage systems to be reworked to optimize soil water availability for your crops. GeoPard is aiming high with the development of new tools like this and is constantly trying to improve and refine our global understanding of just how accurate field-level analytics for precision agriculture can be. If you are interested in knowing more about how this terrain data is collected, feel free to check out this post to learn more!

How the Soil Brightness Index enables Sustainable agriculture Practices

The Soil Brightness Index (SBI) is a valuable tool that can be used to do an express analysis of your soils, and is calculated by GeoPard based on satellite imagery. It is the fifteenth index on the GeoPard platform, it improves accessibility to soil analyses for those users who do not have access to soil sampling or electrical conductivity data, as it is collected via remote sensing

Soil Brightness Index calculated in GeoPard Agriculture platform

Soil brightness works as a proxy for soil organic matter, sands, and salinity areas, and is becoming an increasingly important index for studying changes in soil conditions over time. This is particularly relevant in measuring and monitoring soil degradation and soil erosion patterns, which are both critical environmental concerns around the world. A major goal of precision agriculture is to foster and contribute to more sustainable agricultural land management, and remote sensing is becoming an increasingly valuable technology with the resolution of satellite images improving so rapidly over time (1). Soil degradation and erosion are global issues, but also impact the longevity of individual agricultural operations and local environments. The most productive tier of a soil system is the topsoil, and when it becomes eroded farmers often need to increase production costs to maintain the same yields. Once topsoil has disappeared from a given area of land, erosion continues to degrade the stripped soil in a positive feedback cycle that creates an uneven land surface afflicted with rills and gullies, making efficient crop cultivation even more challenging (2). The Soil Color index can be used in multi-layer analysis with other indices to monitor changes in soils, like erosion patterns, which in turn can tell us vital information about crop productivity

Agronomists, growers and agribusinesses alike should appreciate how the information relayed by the SBI takes on the most value when it is used to inform decision-making about sustainable soil management and mitigate practices that may hinder it.

1. Marques, M. J., Alvarez, A., Carral, P., Sastre, B., & Bienes, R. (2020). The use of remote sensing to detect the consequences of erosion in gypsiferous soils. International Soil and Water Conservation Research8(4), 383-392.2. Seitz, S., Goebes, P., Puerta, V. L., Pereira, E. I. P., Wittwer, R., Six, J., … & Scholten, T. (2019). Conservation tillage and organic farming reduce soil erosion. Agronomy for Sustainable Development39(1), 1-10.

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