Zobrazeno 1 - 10
of 19
pro vyhledávání: '"L M G Fonseca"'
Autor:
H. N. Bendini, L. M. G. Fonseca, C. A. Bertolini, R. F. Mariano, A. S. Fernandes Filho, T. H. Fontenelle, D. A. C. Ferreira
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-M-1-2023, Pp 33-39 (2023)
Irrigation is important for agricultural production and is often decisive for this, especially in arid and semi-arid areas, where precipitation is insufficient. In Brazil, irrigated agriculture is responsible for 46% of withdrawals from water bodies
Externí odkaz:
https://doaj.org/article/b5d4f7a5a19f46d89c9b37d8e08cb621
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2022, Pp 841-847 (2022)
The Brazilian Savanna is the second largest biogeographical region in Brazil and present different vegetation types, consisting mostly of tropical savannas, grasslands, and forests. The forest types have different tree cover and floristic composition
Externí odkaz:
https://doaj.org/article/1736b5ca7f0a47ca8b5836ff9c6888b5
Autor:
C. A. Almeida, D. M. Valeriano, L. Maurano, L. Vinhas, L. M. G. Fonseca, D. Silva, C. P. F. Santos, F. S. R. V. Martins, F. C. B. Lara, J. S. Maia, E. R. Profeta, L. O. Santos, F. C. O. Santos, V. Ribeiro
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol IV-3-W2-2020, Pp 47-52 (2020)
Monitoring the conversion of native vegetation has challenged Brazilian government and scientists since the 1980s. In the case of the Amazonian forests, the Amazon Gross Deforestation Monitoring Project - PRODES has developed an effective methodology
Externí odkaz:
https://doaj.org/article/b1ec0231d8504e2aa7c7dbbf836d08dc
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-3-W12-2020, Pp 91-95 (2020)
Segmentation is a fundamental problem in image processing and a common operation in Remote Sensing, which has been widely used especially in Geographic Object-Based Image Analysis (GEOBIA). In this paper, we propose a new unsupervised segmentation al
Externí odkaz:
https://doaj.org/article/56396ec1d37348ac973c0baee319d681
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-3-W12-2020, Pp 557-562 (2020)
Pasture and croplands play an important role in Brazil’s economic and political scenarios, once its PIB (Raw Internal Product) is mainly based on what is exported from the rural production, such as meat and soybean, and government, with its regulat
Externí odkaz:
https://doaj.org/article/63c3d7d18e5146249362e31126963fd2
Autor:
A. K. Neves, T. S. Körting, L. M. G. Fonseca, C. D. Girolamo Neto, D. Wittich, G. A. O. P. Costa, C. Heipke
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-3-2020, Pp 505-511 (2020)
Large-scale mapping of the Brazilian Savanna (Cerrado) vegetation using remote sensing images is still a challenge due to the high spatial variability and spectral similarity of the different characteristic vegetation types (physiognomies). In this p
Externí odkaz:
https://doaj.org/article/6dea6743abdd47179297418c1fb5492e
Autor:
H. N. Bendini, L. M. G. Fonseca, M. Schwieder, P. Rufin, T. S. Korting, A. Koumrouyan, P. Hostert
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2020, Pp 953-960 (2020)
The Cerrado biome in Brazil covers approximately 24% of the country. It is one of the richest and most diverse savannas in the world, with 23 vegetation types (physiognomies) consisting mostly of tropical savannas, grasslands, forests and dry forests
Externí odkaz:
https://doaj.org/article/5b55b3d0a3d448beb176a2747dd25201
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-3-W11, Pp 79-84 (2020)
Monitoring changes on Earth’s surface is a difficult task commonly performed using multi-spectral remote sensing images. The absence of surface information in optical images due to the presence of cloud, low temporal resolution and sensors defects
Externí odkaz:
https://doaj.org/article/1ccaa57bda124b0cb35500ee80bf62dd
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B8, Pp 845-850 (2016)
The objective of this research is to classify agricultural land use in a region of the Cerrado (Brazilian Savanna) biome using a time series of Enhanced Vegetation Index (EVI) from Landsat 8 OLI. Phenological metrics extracted from EVI time series, a
Externí odkaz:
https://doaj.org/article/d8ee31f8155840b79e2a821072d1d1e3
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B7, Pp 883-889 (2016)
Advances in geotechnologies and in remote sensing have improved analysis of urban environments. The new sensors are increasingly suited to urban studies, due to the enhancement in spatial, spectral and radiometric resolutions. Urban environments pres
Externí odkaz:
https://doaj.org/article/9dd16464e95b43e192fb84c005af3bdb