Yosef Harvey CORTES MILLAN, Universidad Distrital Francisco Jose de Caldas, Colombia
Precision agriculture contemplates the temporal and spatial review of vegetation for decision making, this is how this document presents a methodology for the acquisition of information from places where there is no robust agricultural information, which can be obtained from fusion of satellite images and analysis of spectral indices derived from them. In this way, image fusions will be used, such as Brovey Transform, multiplication method, Wavelet Daubechies and Coiflet transforms, as well as the use of NDVI, GNDVI and DVI spectral indices for PlanetScope and Worldview 3 scenes, resulting in information of higher spatial resolution, accurate for the optimization of these processes, which can be validated from the spectral behavior of the coverages, as well as with image quality indices.
The fusion of satellite images is an effective tool when it comes to carrying out precision agriculture studies in greater detail, eliminating disparities and providing greater spatial richness of a scene, which will result in greater purchasing power of information of the same.
From the implemented methodology, it is highlighted that satellite information can be obtained from a band similar to the near infrared with a high correlation that will allow the execution of spectral indexes of agricultural areas that did not have this information, and that from them it will be possible to characterize coverages in a more precise and optimal way, giving evidence of the state of the vegetation, needs of the same for appropriate decision making.
Finally, from the analysis and validation of the spectral signatures, as well as from the quantitative evaluation of the image quality indexes, it is concluded that the reflectance obtained from the coverages is as expected based on the theory, and gives evidence that the NIR fused synthetic scene presents an adequate degree of correspondence and exceeds the expectations.
Mots clés : Precision agriculture|Image fusion|Spectral indices|Wavelet Daubechies|Wavelet Coiflet
A105482YC