Used data:

o Satellite: Landsat.
o Resolution: 30 m/píxel
o Bands: VIS, NIR y SWIR
o Years: 1990 a 1997.
o Period: late spring and summer.

Brief description:

To carry out the work, the Landsat images were first analyzed for the presence of any evidence of irrigation presence in the plots indicated by the customer, between the late spring and summer of the years 90 to 97, and the dates on which the highest probability of irrigation was observed were chosen.

To select the images, it was taken into account that they should be close to the end of spring, since this is the time when a cereal crop should have at least one support irrigation to remain green once the possible winter rains have ceased and the water reserve in the soil has been reduced, so the climatology of each year was also taken into account to determine if there were late rains that could condition the results.

From the downloaded images of the selected dates, several vegetation indices were calculated and statistics were generated for each of the indicated plots to determine the degree of probability of the presence of at least one supporting irrigation.

Note: There is a rating embedded within this post, please visit this post to rate it. ]]> https://tycgis.com/en/project-irrigation-certification-of-a-farm-using-satellite-images-in-albacete-spain/feed/ 0 https://tycgis.com/en/project-mapsens-agro-system-for-control-and-optimization-of-pruning-clearing-works-for-oil-wells/ https://tycgis.com/en/project-mapsens-agro-system-for-control-and-optimization-of-pruning-clearing-works-for-oil-wells/#respond Sat, 15 Aug 2020 11:40:39 +0000 https://tycgis.com/?p=9273 In this project TYC GIS worked on the development of a system to control and optimize the pruning/clearing of 135 oil wells in the Castilla and Chichimene fields (Colombia) with Mapsens® Agro.

The work began with the generation of detailed orthoimages of the locations and a digitalization of the vegetated and built-up areas. From this point on, these areas have been analyzed monthly with multispectral satellites. Monthly measurements have also been taken to relate vegetation height/development with the photosynthetic activity value to generate a predictive model to help plan maintenance works.

All this information is loaded into Mapsens® Agro for consultation. To improve its analysis, specific functionalities have been developed: a well finder/locator, pruning indexes (growth, clearing and stable), vegetation height estimation function, and a summary table of the general status of each well with areas worked, evolution, etc.

Customer:

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