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COPERNICUS HACKATHONPOLSKA
Challenge: Monitoring of agricultural fields
Martyna Gatkowska
Implemented by: Organised by: Local partners:
Implemented by: Organised by: Local partners:
Challenge: Monitoring of agricultural fields
Presentation Plan:
1. Challenge description2. Overview of satellite data applicable to challenge and operating services delivering
the data3. Use cases
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Challenge: Monitoring of agricultural fields
Challenge description
• Agriculture is being monitored with the application of satellitedata since 1970s… so a lot has been done so far…
• But still there is a need for comprehensive, high temporal and spatial resolution, high quality, automatic system for cropsmonitoring
• Another challenge could be assessing the crops need for fertilizerswhich could be translated into precision farming machines
• Last but not least application of satellite data for agriculturalinsurance is also in demand
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Challenge: Monitoring of agricultural fields
Implemented by: Organised by: Local partners:
Challenge: Monitoring of agricultural fields
Implemented by: Organised by: Local partners:
Challenge: Monitoring of agricultural fields
Implemented by: Organised by: Local partners:
Challenge: Monitoring of agricultural fields
Crop recognition – Crops’s classification
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Challenge: Monitoring of agricultural fields
www.asap.farmer.pl
Crop recognition – Crops’s classification
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Challenge: Monitoring of agricultural fields
Implemented by: Organised by: Local partners:
Challenge: Monitoring of agricultural fields
SATELLITE DATA APPLIED FOR MONITORING AGRICULTURAL FIELDS
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Challenge: Monitoring of agricultural fields
SATELLITE DATA:
• Low resolution:• MODIS,
• NOAA AVHRR
• Medium resolution:• Landsat 8,
• Sentinel 2,
• High resolution:• WorldView II,
• PLANETSCOPE
AERIAL IMAGERY
PROXIMAL SENSING
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Challenge: Monitoring of agricultural fields
Moderate Resolution Imaging Spectroradiometer- MODIS
• 36 spectral bands
• Spatial resolution: 250 – 1000 m;
• Temporal resolution: 12 h;
• Applications for monitoring of fields:– Crops’ condition in global, Continental
and national scale,
– Surface temperature,
– Snow cover
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Challenge: Monitoring of agricultural fields
Advanced Very High Resolution Radiometer- NOAA AVHRR
• 5 spectral bands
• Spatial resolution: 1000 m;
• Temporal resolution: 24 h;
• Applications for monitoring of fields:– Crops’ condition in global,
Continental and nationalscale,
– Surface temperature,
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Challenge: Monitoring of agricultural fields
Landsat 8:
• Spatial resolution: 30 days
• Temporal resolution: 16 days;
• Monitoring of crops condition, temperature stress and crops recognition
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Challenge: Monitoring of agricultural fields
Sentinel 2a i 2b
• Temporal resolution: 5 dni;
• Spatial resolution: 10 m
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Challenge: Monitoring of agricultural fields
Sentinel 2a i 2b
• Temporal resolution: 5 dni;
• Spatial resolution: 10 m
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Challenge: Monitoring of agricultural fields
WorldView
• On demand
• Spatial resolution:– Panchromatic – 0,46 m;
– Multispectral – 1,84 m
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Challenge: Monitoring of agricultural fields
PLANETSCOPE
• Constellation of 200 + satellites
• Full globe coverage app. every 24 h
• Spatial resolution: 3m
• 4 spectral bands – RGB + NIR
• https://www.planet.com/products/planet-imagery/
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Challenge: Monitoring of agricultural fields
Does spatial resolutions matters for agricultural applications?
10 m 20 m 30 m
60 m 100 m 250 m
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Challenge: Monitoring of agricultural fields
Aerial imagery
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Challenge: Monitoring of agricultural fields
Proximal sensing
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Challenge: Monitoring of agricultural fields
HOW SATELLITE CAN SERVE MONITORING OF AGRICULTURAL FIELDS?
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Challenge: Monitoring of agricultural fields
Applications of satellite data for agriculture:
• Estimation of yields and biomass
• Estimation of nutrients
• Stress conditions assessment
• Weeds detection and estimation
• Soil composition
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Challenge: Monitoring of agricultural fields
Vegetation indexes
• Index database – a database of remote sensingindices
• https://www.indexdatabase.de/
• Number of indices: 519
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Challenge: Monitoring of agricultural fields
Index database – a database of remotesensing indices
Application:Number of indices:
Examplary indices:
Agriculture – general 22Normalized Difference Nitrogen Index, Atmospherically Resistant Vegetation Index , NDVI
Parametersdescribing crops
4Crop water stress index, Green leaf index, Calibrated NDVI, SAVI
Monitoring of cropsyield
2NDVIhyper - Normalized Difference Pigment specific normalised difference, Calibrated NDVI
Productionmonitoring
1Calibrated NDVI
Precision agriculture 4
Canopy Chlorophyll Content Index, Crop waterstress index, Normalized Difference NormalizedDifference 790/670, Normalized difference red edge index
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Challenge: Monitoring of agricultural fields
Normalized Difference NIR/Red Normalized Difference Vegetation Index - NDVI
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Challenge: Monitoring of agricultural fields
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Challenge: Monitoring of agricultural fields
NDVI – applications and limitations
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Challenge: Monitoring of agricultural fields
NDVI – zastosowanie i ograniczenia
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Challenge: Monitoring of agricultural fields
Soil Adjusted Vegetation Index - SAVI
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Challenge: Monitoring of agricultural fields
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Challenge: Monitoring of agricultural fields
Comparison of NDVI and SAVI values:
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Challenge: Monitoring of agricultural fields
Comparison of NDVI and SAVI values:
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Challenge: Monitoring of agricultural fields
Normalized Difference Red Edge index (NDRE)
• NDRE is an index that can only be formulated when the Red edge band is available in a sensor.
• It is sensitive to chlorophyll content in leaves (how green a leaf appears), variability in leaf area, and soil background effects.
• NDRE is applicable for monitoring the variability in fertilizer requirements or foliar Nitrogen, not necessarily Nitrogen availability in the soil.
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Challenge: Monitoring of agricultural fields
CCCI – Chlorophyl Canopy Content Index
Applications:• leaf chlorophyll content• plant vigor• stress detection• fertilizer demand• Nitrogen uptake
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Challenge: Monitoring of agricultural fields
NDSI – Normalized Difference Soil Index
• 𝑁𝐷𝑆𝐼 =middle infrared−green
middle infrared+green
• Differentiat the bare soil from crops;
• Enables to monitor the soils parameters within the field
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Challenge: Monitoring of agricultural fields
NDSI vs. Electromagnetic scanning
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Challenge: Monitoring of agricultural fields
NDSI vs. NDVI
Polygon Average NDVI values
1_1 0,79
1_2 0,80
2_1 0,64
2_2 0,64
2_3 0,65
3_1 0,68
4_1 0,63
5_1 0,76
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Challenge: Monitoring of agricultural fields
Homogenous polygons
+ +
DTM NDSI NDVI
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Challenge: Monitoring of agricultural fields
NDWI – Normalized Difference Water Index
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Challenge: Monitoring of agricultural fields
MV 2017-11-07MV 2017-11-13MV 2017-11-19RGB 2017-11-14CIR 2017-11-14
RGB 2017-11-14CIR 2017-11-14NDWI 2017-11-14 MV 2017-11-07MV 2017-11-13MV 2017-11-19MV 2017-11-25
MV 2017-11-25NDWI 2017-11-14
Dane optyczne Dane radarowe
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Challenge: Monitoring of agricultural fields
Pow.: 72,3 haWoda: 0,6 ha
Pow.: 14,7 haWoda: 4,5 ha
Pow.: 24,3 haWoda: 1,6 ha
Pow.: 12,1 haWoda: 6,4 ha
Pow.: 11,6 haWoda: 2,5 ha
Implemented by: Organised by: Local partners:
Challenge: Monitoring of agricultural fields
Few tips about satellite data applications for agriculture!
• Keep in mind the limitations such as: spatial and temporal resolution
• Remember every crop type is different!
• Validate your work
• Collect in-situ data when possible
• Use additional data!