In order to access satellite images of your fields, get the weather forecast and other data, you need to add fields to your account first. There are several available options:
Start by clicking +ADD FIELD located in the right bottom corner of your screen.
A window with available options should pop up.
This option allows you to upload files containing pre-drawn field contours to the system. Currently, EOSDA Crop Monitoring supports 4 different format types: .shp, .kml, .kmz, .geojson.
You can either drag-and-drop files onto the web page or click Add your fields.
As soon as the field contours appear on the map along with the field card data in the right sidebar menu, click ADD TO MY FIELDS to complete the operation.
Or you can click Cancel (located just below the ADD TO MY FIELDS button) to abort.
A modal window will offer you two choices:
Add more information about the newly uploaded field to ensure maximum efficiency of monitoring.
*Accurate monitoring of vegetation development depends on the correctness of crop rotation data.
Files are uploaded through the standard process by clicking the “+ADD FIELD” button.
In case you upload .zip (.shp, .dbf, .prj, .shx), .kml, .kmz, or .geojson files that contain field parameters such as crop type, field name, group, sowing date, harvest date, notes, and season, a Fields upload manager window will open.
Here you will see the parameters of the fields present in the uploaded file. The system will automatically classify each parameter into a different column. Use a drop-down menu on top of every column to select the correct parameter for each data type. Here you can also select the “Skip” option for those parameters you don’t want to be visible on the platform.
When configuring parameters such as “Sowing date” and “Harvesting date,” it’s crucial to select the date format used in the file to ensure error-free data processing.
Notice: The selection of the sowing date is only enabled after the crop has been selected, and the selection of the harvesting date is only enabled after the sowing date has been specified.
Sowing date
Harvesting date
After selecting the parameters, you must ensure that the seasons, crops, and groups from the file match the corresponding seasons, crops, and groups on the platform.
For example, in the file, some fields may be associated with the 2023 season, while others may not have a specified season. In this case, the system will generate two season data options: “No data” and “2023” season. You can assign any seasons available in your account to these data options, and all fields will be loaded accordingly.
The same logic applies to crops and groups. You can assign crops and groups from a file to existing crops and groups in your account, ensuring that parameters are linked to fields and loaded with the specified attributes.
When specifying groups, you have the option to select an existing group from the list in your account or create a new one. To create a new group, simply enter the name of the group and click “add new group.”
Once all steps are finalized, you will see a map and your field list for the final data verification. If everything appears satisfactory, click “ADD TO MY FIELDS” button, and the fields will be saved with the set parameters in your account, within the seasons you selected during the upload process.
The file cannot be uploaded because EOSDA Crop Monitoring cannot determine the coordinates for the fields in the file.
The .shp file requires a .prj file which contains the source product’s coordinate system type.
Check the file format, you may be uploading an invalid format or there is an invalid file in the .zip archive
Overview of file formats that can be uploaded in the system:
This error occurs when the file you’re trying to upload is not a polygon shape but alabel, a point, a photo, a line, a road or some other unsupported element.
On EOSDA Crop Monitoring, you can only upload the files containing a polygon shape, i.e. an object in which there are at least three connected coordinate points all connected to each other.
The error occurs when the file that’s being uploaded exceeds 10 Mb. You can solve the problem by archiving the file in .zip, if it is a shape file. If .zip, .kml or .geojson files exceed 10 Mb,, – the most likely explanation is that there are too many objects (fields) contained within the file, and it is better to re-save these fields from your source by distributing them among 2 or more files.
This error tells you that the contours of some of the fields contained within the file overlap (intersect or cross each other), which does not allow for polygons to be correctly created on EOSDA Crop Monitoring. You need to review your fields and their contours at the source from which you are exporting them.
The error occurs when the area of the field whose contours you are trying to upload as a polygon shape is larger than 10,000 hectares or 24,710 acres. You need to edit the contours of the polygon at the source or draw the contours manually on EOSDA Crop Monitoring.
The Draw polygon option is employed to contour and add your field to the map.
After it’s done, click the SAVE TO MY FIELDS button and give the new field a name, select crop name, sowing date, and season of its cultivation. Then click SAVE to add a field to your Field List.
Sometimes the default map used in EOSDA Crop Monitoring may not reflect the current state of your fields.
If the field view differs from the actual situation on the ground, you can use the “Latest Image” layer, which allows you to see the most recent available satellite images for this area, which are weeks old, not years.
You can also choose other images to display if they are available for this area.
Select any other available image by clicking on the image date if the previous image did not suit you.
If there are no available images for the viewed area, you can move the visible area of the map to another location and search for images, or switch back to the default map.
Utilize the field right sidebar menu section to track, review or change activities related to your field with the features designed in EOSDA Crop Monitoring which are Edit field, Crop rotation, Weather today, and Scouting tasks.
You can edit your fields whenever you need by going to a three dots menu, then Edit on your Field List.
Or Edit on the right of the field card.
Crop rotation data displays historical crop types that used to grow on the field as well as the current growing crop type. This information is extremely useful. For instance, sugar beet planted on the same field two years in a row can cause diseases of the crops that’ll grow there afterwards. Correct crop rotation data includes 3 components: name of the crop, sowing date, and the season when the crop was or is going to be harvested.
Note: It is necessary you click on the exact sowing date in the calendar box. Make sure the selected date looks blue in the calendar.
Log in every morning to follow the weather:
This will help you stay up-to-date and react to changes in a timely manner.
E.g. You’ve planned to apply fertilizer and it is going to rain.
In order to send a scout to the field, you should create a scouting task. This task is automatically sent to the mobile application where a scout can pick it up for further execution. To perform the action, click the + ADD NEW TASK button at the bottom of the Task list or assign a task by selecting one of your fields.
Drop a pointer on the area you want to inspect and the New task window pops up. It contains the preview of your field with a pointer and field coordinates. Fill in the appropriate boxes with Task name, Description, and Assignee, and click SAVE. Once it’s done, the task immediately appears on your task list, as well as on the mobile application connected to your account.
Currently we use Sentinel-2 sensor and satellite images with no more than 60% cloudiness. In this way, the collected statistics includes representative selection and excludes outside factors.
Below are the most commonly used vegetation indices that are presented in EOSDA Crop Monitoring:
NDVI or Normalized Difference Vegetation Index
NDVI is calculated according to the way a plant reflects and absorbs solar radiation at different wavelengths. The index allows for identification of problem areas of the field at different stages of plant growth for timely response. Pay attention to the areas where NDVI values differ considerably. For example, the areas of a field that have an extremely low NDVI rate may indicate problems with pests or plant diseases; and the areas with an abnormally high NDVI signalize the occurrence of weeds.
NDRE or Normalized Difference RedEdge*
NDRE is an indicator of photosynthetic activity of a vegetation cover used to estimate nitrogen concentrations in plant leaves in the middle and at the end of a season. It allows you to detect the oppressed and aging vegetation and is used to identify plant diseases. It also makes it possible to optimize the timing of the harvest.
*The red-edge band is a narrow band in the vegetation reflectance spectrum between the transition of red to near infra-red.
MSAVI or Modified Soil-Adjusted Vegetation Index
MSAVI allows you to determine the presence of vegetation in the early stages of emergence when there is a lot of bare soil. The index minimizes the effect of bare soil on the display of vegetation maps. Based on the index, you can build maps for differential fertilizer application in the early stages of crop growth.
ReCI or Red-edge Chlorophyll Index
ReCI is an index of photosynthetic activity of a vegetative cover, sensitive to the content of chlorophyll in leaves. Since the level of chlorophyll is directly related to the level of nitrogen in the crop, the index allows you to identify the areas of the field that have yellow or faded leaves, which may require additional fertilizer application.
Currently, one moisture index is available on the platform:
NDMI or Normalized Difference Moisture Index
NDMI describes the crop’s water stress level and is calculated as the ratio between the difference and the sum of the refracted radiation in the near-infrared and SWIR spectrums. The interpretation of the absolute value of the NDMI makes it possible to immediately recognize the areas in which the farm or field is experiencing water stress. NDMI is easy to interpret: its values vary between -1 and 1, and each value corresponds to a different agronomic situation, independently of the crop
NDVI, NDRE, MSAVI, ReCI, NDMI are indices that can be selected either from the left drop-down menu or the three-dots menu on the small panel above the analytics window.
Using a small panel above the analytics window, you are able to download e.g. the NDVI map in .tiff or .shp formats. Shape format gives you the pixel-by-value NDVI at each point and TIFF format shows a regular image with the NDVI applied.
To expand the statistics to check the index of your field, use the small panel above the analytics window. Statistics can be displayed in hectares or percentage.
We do not upload satellite images with more than 60% cloudiness. When using an index, there should be no outside factors that can influence the whole picture. With this said, we consider the possibility of getting value from 60% cloudy images as a positive one. Statistics displays in ha and percentage. Clouds are displayed as a white mask over the field.
Shows all images that are less than 60% cloudy. When you pick a date, you see a satellite image with an index applied for that day.
Note: You can see an image preview by hovering over the date on the timeline.
Elevation map is a digital model that visualizes differences in elevation across your field. The model allows agronomists to detect potentially problem areas of the field:
and other types.
Combined with other data (NDVI, productivity map, and others), elevation map helps to identify and eliminate factors which impede vegetation development.
This model also allows you to measure field area with more accuracy. It is crucial to know the exact area of your field to correctly calculate the amount of seedlings, fuel, and time required to perform field activities.
How to find the elevation map?
By default, you see the NDVI values of your field on the map. In order to see the differences in elevation, click on the index panel and select the elevation map from the drop-down list.
Now you can see the differences in elevation across your field.
Elevations are visualized as different hues, from dark-green low areas to dark-red high areas. Moreover, by hovering over the map, you will be able to see the actual altitude of any point on your field as meters above the sea level.
To better understand the elevation variations of your field, check how the color scheme correlates with the elevation values. Just click on the expand icon in the lower right corner.
Now you see how much area a corresponding elevation takes up on your field and which color hue is used to represent it.
In addition, you can also download the elevation map as a .tiff file by clicking on the download icon in the lower right corner.
The analytics window automatically unfolds on the bottom of the screen by selecting the field.
Graphs that display a representation of NDVI (normalized difference vegetation index) are in the center of this window.
There is also the possibility of years comparison, thus you can monitor how your crop is developing compared to data collected in the past. To visualize the data for the specific date, hover over the curve.
Each curve can be disabled by clicking the corresponding colored buttons on the legend. This allows you to disable the unnecessary items and compare indices for years of interest.
To view weather data on the graph, select the required data type from the Weather data drop-down list.
Temperature data includes:
Moisture data includes:
Min temperature curve shows the history of minimum temperatures occurring in your field over a period of time. Whenever this curve crosses the Cold stress mark at -6°C, your winter crops are at risk of damage or failure. Track the curve and react when it is approaching the cold stress. Over time, you can build trends based on this graph to better protect your crops.
Max temperature curve represents the history of maximum temperatures in the field over a period of time. Whenever it crosses the Heat stress mark at +30°C, your crops are at risk of experiencing drought conditions. Track the curve and react when it is approaching the heat stress. Over time, you can build trends based on this graph to better protect your crops.
Precipitation graph reflects the history of precipitation on the field measured in mm. You can build trends based on this graph and adjust irrigation and fertilization planning to increase efficiency.
Surface soil moisture curve represents the change in the amount of water in the top few centimetres of the soil over time. Based on this data, you can make better-informed decisions on irrigation.
Root zone soil moisture curve shows the change in the amount of water available to crop roots over time. Improve your water management by making decisions based on this data.
Use Growth Stages to get to know what stage your crop is on right now. If not needed, you are always able to hide the curve from being displayed by clicking on the Growth Stages.
Note! You should add info about crop rotation to see growth stages of your crops.
By default, it shows one year period or the date range selected on the calendar.
If you set a date range and want to get the default year period view, click Update.
Crop | Disease Risk | Growth Stages | Yield Estimation | Variety | Weather Risk | Index risk |
---|---|---|---|---|---|---|
Onions | ||||||
Olive | ||||||
Winter barley | ||||||
Grapes | ||||||
Radicchio | ||||||
Celery | ||||||
Rapeseed | ||||||
Lemons | ||||||
Apple | ||||||
Fruit | ||||||
Vegetables | ||||||
Citrus | ||||||
Tuber crops | ||||||
Garlic | ||||||
Spring barley | ||||||
Sorghum | ||||||
Oranges | ||||||
Tobacco | ||||||
Avocado | ||||||
Kale | ||||||
Pear | ||||||
Cucumber | ||||||
Paprika | ||||||
Vineyard | ||||||
Coffee | ||||||
Mixed cereals | ||||||
Tomatoes | ||||||
Cassava | ||||||
Bananas | ||||||
Winter rapeseed | ||||||
Eggplant | ||||||
Turnip | ||||||
Peach | ||||||
Endive | ||||||
Lettuce | ||||||
Melon | ||||||
Olive tree | ||||||
Cherry | ||||||
Buckwheat | ||||||
Cereal | ||||||
Mustard | ||||||
Peanuts | ||||||
Iceberg lettuce | ||||||
Romaine lettuce | ||||||
Sorghum sudanense | ||||||
Triticosecale | ||||||
Snap Peas | ||||||
Cauliflower | ||||||
Broccoli | ||||||
Green beans | ||||||
Table grapes | ||||||
Plum | ||||||
Strawberry | ||||||
Spring rapeseed | ||||||
Asparagus | ||||||
Chilli | ||||||
Bitter melon | ||||||
Silage sorghum | ||||||
Silage corn (Maize) | ||||||
Winter rye | ||||||
Winter triticale | ||||||
Carrot | ||||||
Winter cereals | ||||||
Canola | ||||||
Rice | ||||||
Cotton | ||||||
Rye | ||||||
Potatoes | ||||||
Oats | ||||||
Peas | ||||||
Soybeans | ||||||
Sugar beet | ||||||
Corn (Maize) | ||||||
Groundnut | ||||||
Pigeonpea | ||||||
Cowpea | ||||||
Chickpea | ||||||
Mungbean | ||||||
Fababean | ||||||
Millet | ||||||
Sweet potato | ||||||
Sunflower | ||||||
Winter sorghum | ||||||
Oilseed crops | ||||||
Sugarcane | ||||||
Spring cereals | ||||||
Beans | ||||||
Wheat | ||||||
Pulses | ||||||
Winter wheat | ||||||
Spring triticale |