Kategori: Management Zones

To visualize field data and make informed decisions it is often necessary to compare layers on multiple synchronized views.

In GeoPard, you can visually compare up to four layers of data on one screen. All layers work synchronously when you zoom in/out or move the map for your convenience.

How do I enter split-screen mode? Select a field and click the layer comparison icon in the upper right corner of the screen. Then select any snapshots, field control areas, or other layers that you want to see on the same screen at the same time. Click Compare Layers. 

The layer comparison feature synchronizes maps, cursors, zoom levels. Also you have the ability to add/remove layers. Currently we support up to 4 data layers.

What are data layers in precision agriculture?

In precision agriculture, data layers refer to the different types of data that are collected and analyzed to make informed decisions about crop management. These layers may include:

• Soil data: Information about soil characteristics, such as nutrient levels, pH, and texture, which can inform decisions about fertilization and other soil management practices.
• Weather data: Data on current and historical weather patterns, including temperature, precipitation, and wind, can help farmers make decisions about planting, irrigation, and other practices.
• Crop data: Data on crop growth and health, including plant height, leaf area, and chlorophyll levels, can inform decisions about fertilization, irrigation, and pest management.
• Yield data: Information on crop yield and quality can help farmers make decisions about harvesting and marketing their crops.
• Topographic data: Information about the shape and elevation of the land can inform decisions about planting and irrigation, and can help identify areas that may be prone to erosion or other environmental problems.
• Remote sensing data: Data collected from satellites, drones, or other remote sensors can provide information on crop health, soil moisture, and other factors that can inform decisions about crop management.

By analyzing and integrating these different data layers, farmers can make more informed decisions about crop management, leading to more efficient and sustainable farming practices.

ZONES OPERATIONS ACROSS DIFFERENT LAYERS

In precision farming, field data collection and data-driven decision making are absolutely essential. As the next stage in the development of multi-layers analytics and finding dependencies across layers we introduce new module Zones Operations. 

There you can search for dependencies between different ag zones maps such as historical vegetation, topography including its derivatives, data from yield monitors, soil data, scanners, stability maps, and so on. This is a step forward in defining the most influenced areas and understanding the reasons for field heterogeneity. 

How can you identify the areas? 

First of all select field maps, you want to cross-investigate. A layer comparison view is a good approach to define specific agriculture zones for analyzing.

You may want to compare low yield potential and sloppy areas, most unstable zones and low vegetation, low electrical conductivity and yield, as applied fertilization map and current vegetation, and others.

Secondly, mark specific agriculture zones on every map you want to compare in the Zones Operations module. And finally, obtain a zone of interest. Note that it is possible to use more than two maps in analyses. 

How can you apply this knowledge? 

In addition to finding relationships that can help explain yield, it is possible to set yield goals for defined agriculture zones; to scout interesting areas; to reduce investments in such localized zones or build the plan of mitigating limiting factors and pull up underperforming areas knowing the underlying causes; to build agronomy plan using VRA practices. 

There are several examples of field insights on screenshots. Note that every field is unique and below-mentioned cases do not guarantee 100% same result for your field but it is a good way to start the investigation from. 

You are very welcome to share your agronomic practices by commenting on this post, contact the GeoPard Agriculture team directly. We are open to the feedback because we build the solution for you for a better understanding of field variability and managing it.

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.

What are splits in agriculture?

In agriculture, splits refer to the division or splitting of a field into different sections for various management practices.

This division allows farmers to apply different treatments or techniques to each section based on specific needs.

For example, farmers may split a field to apply different fertilizers, herbicides, or irrigation methods based on soil conditions or crop requirements.

Splits enable targeted and efficient application of resources, optimizing crop growth and minimizing costs while addressing specific challenges within different areas of the field.

Detecting changes that happened in the field during the last 1-2 weeks or 1-2 months or even a couple of years helps to get insights about crop development.

It can be used to:

• locate spots with similar performance across the 5-10-20 years and place the trials in areas with similar conditions to reduce the probability of mistakes,
• track the changes during the season and evaluate crop performance during the growth,
• recognize the damaged areas after a weather disaster or a disease or a pest attack and calculate damaged areas,
• detect the difference between the last 2 images and control the crop performance.

And all that and even more cases are covered with GeoPard Field Stability Zones. Especially, it will provide more insights together in combination with in-season and historical management zones.

Simply choose your field and satellite images to track the changes across them, control crops, and get insights about every spot in your field.

It’s no secret that we constantly enrich the GeoPard Agriculture solution and increase its value to users. Just look at the “coming soon” section of our website https://geopard.tech to get an idea of some features on the way.

Their prioritization can be challenging. Here, feedback and product demos come to the rescue. Thus, presenting our solution to many attendants of the World Agri-Tech Summit in London, we were able to adjust the delivery plan and release a new layers comparison feature just within a few days.

What is it about? You can visually compare field analytics side by side in a split view. It is possible to select any type of layers for comparison: imagery with natural or infrared colors, imagery with vegetation views, in-season or historical management zones. Two layers behave synchronously when you zoom-in / zoom-out or move a map for your conveniences.

How to enter the split view mode? Select your field and click compare layers icon in the top menu. On the split view screen, select the analytics layer using a searchable drop-down list located on the top.

What does it mean? Historical (multi-year) management zones are built based on 30+ years archive of satellite imagery.

Images with peak vegetation during every season are automatically selected as inputs for analytics. Otherwise, every such image represents a potential yield file for the related year.

Historical (multi-year) management zones provide insights about every spot in the field.

How can you use it? The field crop development pattern helps to know the agricultural area better and to apply the right decision with the right input rates in the right spots.

Historical management zones could be used as a blueprint for prescription (Rx) files for seeding, fertilization, zones based soil sampling.

We support all regions by request.

What are Multi-Year Zones?

Multi-Year Zones in precision agriculture refer to specific areas within a field that exhibit consistent and distinguishable patterns of crop growth and yield over multiple growing seasons.

These zones are identified using various technologies such as remote sensing, GPS mapping, and soil sampling.

By analyzing the data collected from these technologies, farmers and agronomists can identify patterns of variability within a field and create maps that distinguish areas of high productivity from those with lower yields.

This information can then be used to optimize crop management practices, such as varying planting density, adjusting irrigation and fertilization rates, and even implementing precision harvesting techniques.

They provide a valuable tool for precision agriculture as they allow farmers to make informed decisions about resource allocation and crop management, resulting in improved efficiency, reduced costs, and increased yields.

By understanding the variability within a field and tailoring management practices to each specific zone, farmers can maximize the potential of their land and resources.