Do you know how precision agriculture can help you as a farmer or someone related to agro-business? It can upsurge economic efficiency (15%) through the optimal distribution of agriculture input resources while also reducing your agriculture input costs in crop production to 40%. At the same time, it also helps indicate crop productivity zones in terms of yield. It is worth noting that an average difference in yield in high and low crop productivity zones can go as far as 400%.
How It Works
GeoPard champions sustainability in the agriculture sector. Remember that there is no better alternative than big data analytics to achieve sustainability and precision agriculture in our times. Our precision agriculture solution stores satellite data, machinery data, high-density scanner data, topography, drone imagery, and soil sampling data for accumulating big analytics.
As a result, our solution generates maps, automated recommendations, benchmarking, a complete land profile, sustainability such as carbon offsets, and biodiversity. You can monitor it through the mobile, web, agriculture machinery and equipment, and other platforms and solutions.
As we know, agriculture entails different seasons throughout the year. Concerning that, GeoPard helps automate your agronomy workflows in all those seasonal activities. These include season planning, soil sampling, seeding, fertilizing, spraying, desiccation, and post-harvest analysis.
GeoPard Tools and Benefits
Here we explore the tools and benefits GeoPard offers its clients as its services.
GeoPard offers a combination of data layers. Depending on the available layers, you can delineate management zones with the flexibility to set a weight for each layer. Let’s consider a quick example here. You can select 8 Years of historical Productivity as weight=1 andSlope as weight=-1.
Different layers combine and give valuable data for making appropriate decisions. For example, satellite imagery can combine with soil EC (electrical conductivity) data as well as soil sampling can shake hands with topography. Alike there might also be a mix of multiple vegetation indices.
Automated Field Potential Maps and Heterogeneity
While benefiting from GeoPard, you can automate multi-year field-potential maps – for up to 30 years and the last five years stacked – that is very close to actual yield data. With the help of the heterogeneity index, you can prioritize agricultural activities and benchmark fields.
3D maps help manage individual land parcels and grasp how topography impacts soil properties, vegetation, and yield. At the same time, geospatial dependencies can also be learned between data layers. You can also combine a base layer and a cover zones map. For the sake of your information, the base layer may include topographic, slope, relief positions, soil properties, or vegetation distribution. On the other hand, the cover zones map may incorporate zones from yield, historical vegetation, organic matter, electrical conductivity, and pH distribution.
Furthermore, the exciting thing is that you can visualize the 3D model immediately in the browser and do not have to install any additional software or plugins.
With the help of the topography profile, you can have a complete sense of the topographic profile, ranging from elevation, slope, aspect, and hillshade to relief position, ruggedness, and roughness. The story doesn’t end here, and you can build the profile on top of remote sensing or machinery datasets. It also allows you to utilize all the given derivatives on pixel base in external Artificial-Intelligence models. Its examples include slope and local relief position zones.
When you leverage the automated scouting tool from GeoPard, locations needing the scouting and understanding of limiting factors are automatically detected. Valuable areas are also identified for comprehensive analytics. Since you can monitor the results on the mobile application, you should also understand the features it can offer and the platforms it usually uses. The app can equally work offline for comments and photos and use both IOS and Android on smartphones and tablets.
Soil sampling at periodic intervals across the field is essential. Each field bears different soils with distinctive crop attributes and soil characteristics. Therefore, it is crucial to delineate the landscape of the field into different zones of management. The complete step of soil sampling ranges from planning soil sampling (zonal and grid) to VRA maps based on soil data.
You can split and merge zones through the GeoPard solution to make essential things. E.g., you can split polygons, merge polygons, and even assign a polygon or a complete zone to another class.
Soil Brightness Index
Understanding variations in soil conditions over time is significant. You can achieve it through soil brightness as it operates as a proxy for sands, organic matter, and salinity areas. What’s more, it helps measure and monitors soil erosion patterns and soil degradation.
Stability Maps / Change Detection
Do you want to understand the stability and variation of vegetation from season to season? While exploiting the GeoPard’s platform, you can detect the most stable and varying spots in the field during any period. It can vary from the last few weeks to a few months or even a couple of years.
The Intersection of Data Layers
GeoPard helps you identify the most valuable areas for extended analysis, such as soil, scouting, and plant sampling. Likewise, it can also assist with enhancing agronomic practices. But the point to keep in mind is that it is possible through overlapping different management zones based on distinguished layers to define dependencies between data layers.
As-Applied and As-Planted Data Analysis
With the help of GeoPard, you can monitor the VRA (Variable Rate Application) execution results. It may include comparing planned and applied maps such as VRA maps. Other than that, it is also helpful for calculating the ROI of variable rate technology.
Clouds and Shadows Detection
With the help of proprietary algorithms, GeoPard offers high accuracy of clouds and shadow detections. You will be surprised to know that compared to around 80% accuracy provided by competitors, the accuracy of the GeoPard algorithm is about 95%. Apart from the higher accuracy than competitors, we enable higher quality by automating more than our competitors. Our solution detects partially-cloudy and cloudy images through an advanced image filter to verify decisions.
Statistics for Zones
While utilizing GeoPard, you can calculate statistics on zone level based on data layers used in zone creation. It includes yield, satellite, ground sensors, topographic, multi-layer, etc. The covered metrics are Minimum, Maximum, Average, Median, Sum, and Standard Deviation.
Integrated Data Sources
GeoPard understands the formats in which both humans and AI models can interpret data. While providing data in relevant forms, the platform also delivers calibrated, corrected, and standardized data. Concerning that, GeoPard is developing an automated Radar Data processing pipeline. Along these lines, it is also working on launching solutions related to the Carbon and Sustainability topics. These solutions will aid in estimating vegetation on cloudy days, detecting agricultural operations like tillage & sowing, analyzing cover crops, and estimating soil moisture & physical conditions.News