Crop Health Monitoring Manually checking crops across a large area is the slowest and most labor-intensive method of monitoring crop health. Remote sensing and GIS in agriculture are lifesavers for this.
GIS-based precision agriculture can help you prioritize which crops need extra care. Imagery sensors on satellites and aircraft provide an advanced method for monitoring crop temperatures. An abnormally high temperature could indicate disease, pest infestation, or dehydration.
Livestock Monitoring Agriculture GIS software is essential for tracking animals’ movements in animal husbandry. GIS agriculture tools help farmers locate livestock on a farm and monitor their health, growth, fertility, and nutrition. Animal trackers and a portable device that can receive and display tracker data enable this application.
Insect And Pest Control Scouting large fields for pest infestations is wasteful. Deep learning algorithms and satellite data can assist in finding unhealthy spots.
EOSDA Crop Monitoring aids in detecting various risks, from weeds to crop diseases, by using field-collected vegetation indices. If the index map indicates low vegetation in a small area, meaning the possible presence of a parasite or disease there, a scout no longer has to investigate a large field. After identifying the probable infection zone using the vegetation index, you can use the Scouting feature to narrow your target area. Scouts can inspect the selected area and rapidly send photos of accomplished tasks and threat types using the EOSDA Crop Monitoring mobile app.
Identifying areas of low vegetation in the field to minimize the area for inspection with EOSDA Crop Monitoring.
Irrigation Control Dry spells, as well as extreme precipitation in low-lying areas without adequate drainage, can ruin crop output. Through agriculture GIS technology, farmers may assess the degree of water stress experienced by each crop and recognize visual patterns that suggest an oversupply or deficiency of water, which can be used to regulate irrigation.
Water stress is typically detected using the NDWI or NDMI indices. The NDMI index, available in EOSDA Crop Monitoring by default, ranges from -1 to 1, providing an intuitive interpretation of the data collected. Negative numbers around -1 indicate water shortages, whereas positive ones near 1 could indicate waterlogging.
Water deficiency identification with NDMI index on EOSDA Crop Monitoring.
