Precision Agriculture Mapping
The Food and Agriculture Organization (FAO) of the United Nations, the world’s population will reach 9.1 billion, 34 percent higher than today’s population, by 2050. Due to this expected growth, there is pressure throughout the world for higher agricultural production and reliable crop status information. To achieve these objectives, improved management of the world's agricultural resources is required, especially in developing countries.
WorldView-2 MS 1.6m Vegetation Index (WV-VI)* 20150109 / South Africa
Google Earth™ KMZ / WV-VI Index, Maize Pivot (Red High) 1.6m
(*) (NIR2 - Red) / (NIR2 + RED) = WV-VI
To make this happen it is first necessary to obtain reliable crop status information on not only the types, health status, quality, quantity, and location of these resources.
Geographic Information Systems (GIS) tools and online web resources can help farmers to conduct crop forecasting and manage their agriculture production by utilizing multispectral imagery collected by Satellites, fix wing Aircraft or Unmanned Aerial Vehicles (UAV's), and processed to provide NDVI and other vegetation soil indices, to identify crop stress. This data is used in regional GIS or CAD management systems and web portals. The ability of GIS to analyze and visualize agricultural environments and workflows has proven to be very beneficial to those involved in the farming industry.
When agriculture management software is not in place, vegetation and soil index imagery can be reviewed in Google Earth Pro™ for regional farmers to identify areas in the fields, requiring a closer analysis, to decide if additional irrigation or fertilization of the crop is required.
WorldView-2 NDVI Index and Moisture Map - South Africa
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Satellite images are very effective for larger areas with no requirements for permitting, mobilization/demobilization, and avoid any security issues. Satellite sensors deliver 16-Bit 4-Band (B,G,R,N) or 8-Band (C,B,G,Y,R,RE,N,N2) Multispectral pixel resolutions from 1.2-meter to 5m. Pansharpened vegetation indices can be delivered with a resolution of 30cm, 40cm, or 50cm, providing greater details for analysis. The high and medium resolution satellite sensors used for precision agriculture, acquire new Imagery when orders are placed, with minimum commitments of 50 to 100 Km², per area.
To download various NDVI samples and save or open the KMZ file in Google Earth Pro™, please click on one of the links below:
ESA Sentinel-2 Satellite Constellation
The Sentinel-2 Satellite sensors acquire 10m 4-band (BGRN) Multispectral, 20-meter 4-band RedEdge and 2-band Short Wave InfraRed (SWIR) and 60m 3-band Coastal Aerosol, Water Vapour, and SWIR Cirrus imagery providing a choice for a good selection to search for cloud-free Imagery for the Area Of Interest (AOI). This imagery is very suitable to deliver 10m resolution NDVI or other vegetation index Imagery and moisture maps in KMZ format. The KMZ vegetation index image files can be imported into Google Earth™, similar to the Images below. Because the Sentinel-2 satellite imagery, provided by the European Space Agency (ESA), can be downloaded for free and requires only vegetation and soil index image processing, providing a cost-effective Ag solution, covering large areas around the globe, where 10-meterm resolution is acceptable or desired due to limited financial resources.
The satellites in the SENTINEL-2 constellation will provide a revisit time of 5 days at the equator in cloud-free conditions.
To download a Tutorial to create polygon KML/KMZ files for a single or multiple areas in Google Earth Pro™, please click HERE.
Google Earth™ / Sentinel-2 NDVI** Vegetation Index - 20160719 - Michigan, U.S.A.
(**) (NIR - Red) / (NIR + Red) = NDVI
When the KMZ or shapefiles for the producing farm fields cannot be provided, SIC can deliver the Sentinel-2 satellite imagery and vegetation index (NDVI or SAVI) where crop stress can be identified on the Index and polygons can be produced and entered into a GPS tablet or handheld to locate the areas to be analyzed and treated in the field.
NDVI Scale from -1 Low Reflectance to +1 High Reflectance
The vegetation indices provided will cover multispectral reflectance values from 0.5 to 1.0 or any other suitable range.
Google Earth™/ Sentinel-2 Soil Adjusted Vegetation Index (SAVI***) - 20160711 - Alexandria, Egypt
(***) (NIR - Red) / (NIR + Red) x (1 + L) = SAVI L= 0.5 Constant soil factor for intermediate vegetation cover.
For areas throughout Africa and other regions around the World, experiencing agriculture production problems in quality or quantity, the Sentinel-2 satellite sensor can support the regional farmers and farm cooperatives, and other organizations, with timely and critical information.
For more information on how SIC can assist, please CONTACT US.
Normalized Difference Vegetation Index (NDVI)
The agriculture, forestry, and environmental industry are using the standard NDVI index for many years but with the availability of hyperspectral sensors and high-resolution Satellite sensors, such as WorldView-2 and WorldView-3, utilizing an expanded multispectral reflectance range, SIC can provide a variety of vegetation indices to filter the correct band combinations for vegetation, soil and environmental analysis to support crop, forest, and environmental project management.
CCCI - Canopy chlorophyll content index
OSAVI - Optimized soil-adjusted vegetation index
Managed Canopy Assessment
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Vegetation and Soil Index Maps
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