Spatial variability of biophysical multispectral indexes under heterogeneity and anisotropy for precision monitoring
ABSTRACT The study aimed to characterize the spatial structure of variability of biophysical indexes of vegetation through images obtained by Unmanned Aerial Vehicles under strong heterogeneity and anisotropy, using geostatistical procedures. Plots with different types and densities of culture were...
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| Format: | Article |
| Language: | English |
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Universidade Federal de Campina Grande
2023-08-01
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| Series: | Revista Brasileira de Engenharia Agrícola e Ambiental |
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| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662023001100848&tlng=en |
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| author | Valeria R. Lourenço Abelardo A. de A. Montenegro Ailton A. de Carvalho Lizandra de B. de Sousa Thayná A. B. Almeida Thiago F. S. de Almeida Bárbara P. Vilar |
| author_facet | Valeria R. Lourenço Abelardo A. de A. Montenegro Ailton A. de Carvalho Lizandra de B. de Sousa Thayná A. B. Almeida Thiago F. S. de Almeida Bárbara P. Vilar |
| author_sort | Valeria R. Lourenço |
| collection | DOAJ |
| description | ABSTRACT The study aimed to characterize the spatial structure of variability of biophysical indexes of vegetation through images obtained by Unmanned Aerial Vehicles under strong heterogeneity and anisotropy, using geostatistical procedures. Plots with different types and densities of culture were evaluated in a didactic vegetable garden. Five vegetation indexes obtained from aerial multispectral camera images were evaluated parallel with geostatistical analysis and anisotropy investigation for multiscale spatial modeling. For the studied domain, geometric anisotropy was identified for the biometric indexes. The spherical model presented a better fit when anisotropy was not considered, whereas the exponential model had the best performance in the anisotropic analysis. Contrasting targets were better identified in multispectral images and considering anisotropy. The Soil-Adjusted Vegetation Index is recommended for similar applications. |
| format | Article |
| id | doaj-art-145488059f2e4ce7a0dcde05a1f2aa88 |
| institution | Kabale University |
| issn | 1807-1929 |
| language | English |
| publishDate | 2023-08-01 |
| publisher | Universidade Federal de Campina Grande |
| record_format | Article |
| series | Revista Brasileira de Engenharia Agrícola e Ambiental |
| spelling | doaj-art-145488059f2e4ce7a0dcde05a1f2aa882025-08-20T03:54:33ZengUniversidade Federal de Campina GrandeRevista Brasileira de Engenharia Agrícola e Ambiental1807-19292023-08-01271184885710.1590/1807-1929/agriambi.v27n11p848-857Spatial variability of biophysical multispectral indexes under heterogeneity and anisotropy for precision monitoringValeria R. Lourençohttps://orcid.org/0000-0001-9662-5918Abelardo A. de A. Montenegrohttps://orcid.org/0000-0002-5746-8574Ailton A. de Carvalhohttps://orcid.org/0000-0001-8783-649XLizandra de B. de Sousahttps://orcid.org/0000-0001-5283-2958Thayná A. B. Almeidahttps://orcid.org/0000-0002-2172-4732Thiago F. S. de Almeidahttps://orcid.org/0009-0007-0254-9792Bárbara P. Vilarhttps://orcid.org/0009-0002-4693-2527ABSTRACT The study aimed to characterize the spatial structure of variability of biophysical indexes of vegetation through images obtained by Unmanned Aerial Vehicles under strong heterogeneity and anisotropy, using geostatistical procedures. Plots with different types and densities of culture were evaluated in a didactic vegetable garden. Five vegetation indexes obtained from aerial multispectral camera images were evaluated parallel with geostatistical analysis and anisotropy investigation for multiscale spatial modeling. For the studied domain, geometric anisotropy was identified for the biometric indexes. The spherical model presented a better fit when anisotropy was not considered, whereas the exponential model had the best performance in the anisotropic analysis. Contrasting targets were better identified in multispectral images and considering anisotropy. The Soil-Adjusted Vegetation Index is recommended for similar applications.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662023001100848&tlng=enUAVspatial correlationSAVIprecision agriculture |
| spellingShingle | Valeria R. Lourenço Abelardo A. de A. Montenegro Ailton A. de Carvalho Lizandra de B. de Sousa Thayná A. B. Almeida Thiago F. S. de Almeida Bárbara P. Vilar Spatial variability of biophysical multispectral indexes under heterogeneity and anisotropy for precision monitoring Revista Brasileira de Engenharia Agrícola e Ambiental UAV spatial correlation SAVI precision agriculture |
| title | Spatial variability of biophysical multispectral indexes under heterogeneity and anisotropy for precision monitoring |
| title_full | Spatial variability of biophysical multispectral indexes under heterogeneity and anisotropy for precision monitoring |
| title_fullStr | Spatial variability of biophysical multispectral indexes under heterogeneity and anisotropy for precision monitoring |
| title_full_unstemmed | Spatial variability of biophysical multispectral indexes under heterogeneity and anisotropy for precision monitoring |
| title_short | Spatial variability of biophysical multispectral indexes under heterogeneity and anisotropy for precision monitoring |
| title_sort | spatial variability of biophysical multispectral indexes under heterogeneity and anisotropy for precision monitoring |
| topic | UAV spatial correlation SAVI precision agriculture |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662023001100848&tlng=en |
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