Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Michelle C. A. Picoli"'
Autor:
Ana C. Rorato, Michelle C. A. Picoli, Judith A. Verstegen, Gilberto Camara, Francisco Gilney Silva Bezerra, Maria Isabel S. Escada
Publikováno v:
Land, Vol 10, Iss 3, p 267 (2021)
This study investigates the main threats related to environmental degradation that affect Amazonian Indigenous Lands (ILs). Through a cluster analysis, we group ILs according to the set of common environmental threats that occur within and outside th
Externí odkaz:
https://doaj.org/article/ccf8433c68e142e7aed720de7d5fd653
Publikováno v:
Land, Vol 9, Iss 12, p 506 (2020)
Many of the world’s agricultural frontiers are located in the tropics. Crop and cattle expansion in these regions has a strong environmental impact. This paper examines land use and land cover transformations in Brazil, where large swaths of natura
Externí odkaz:
https://doaj.org/article/c2f4022649674f469c398aabbe4f58cb
Autor:
Karine R. Ferreira, Gilberto R. Queiroz, Lubia Vinhas, Rennan F. B. Marujo, Rolf E. O. Simoes, Michelle C. A. Picoli, Gilberto Camara, Ricardo Cartaxo, Vitor C. F. Gomes, Lorena A. Santos, Alber H. Sanchez, Jeferson S. Arcanjo, José Guilherme Fronza, Carlos Alberto Noronha, Raphael W. Costa, Matheus C. Zaglia, Fabiana Zioti, Thales S. Korting, Anderson R. Soares, Michel E. D. Chaves, Leila M. G. Fonseca
Publikováno v:
Remote Sensing, Vol 12, Iss 24, p 4033 (2020)
Recently, remote sensing image time series analysis has being widely used to investigate the dynamics of environments over time. Many studies have combined image time series analysis with machine learning methods to improve land use and cover change
Externí odkaz:
https://doaj.org/article/aea3e037496347fa836f2a93ba4c1304
Publikováno v:
Remote Sensing, Vol 12, Iss 18, p 3062 (2020)
Recent applications of Landsat 8 Operational Land Imager (L8/OLI) and Sentinel-2 MultiSpectral Instrument (S2/MSI) data for acquiring information about land use and land cover (LULC) provide a new perspective in remote sensing data analysis. Jointly,
Externí odkaz:
https://doaj.org/article/b5d54af4fbbe45518fa7c16a3fe25aa7
Autor:
João V. R. Guerrero, Elton V. Escobar-Silva, Michel E. D. Chaves, Guilherme A. V. Mataveli, Vandoir Bourscheidt, Gabriel de Oliveira, Michelle C. A. Picoli, Yosio E. Shimabukuro, Luiz E. Moschini
Publikováno v:
Forests, Vol 11, Iss 9, p 988 (2020)
Over the decades, hydropower complexes have been built in several hydrographic basins of Brazil including the Amazon region. Therefore, it is important to understand the effects of these constructions on the environment and local communities. This wo
Externí odkaz:
https://doaj.org/article/c29b22664be84353a9bff8a8b2549d69
Autor:
Michelle C. A. Picoli, Ana Rorato, Pedro Leitão, Gilberto Camara, Adeline Maciel, Patrick Hostert, Ieda Del’Arco Sanches
Publikováno v:
Land, Vol 9, Iss 1, p 20 (2020)
Demand for agricultural exports in Brazil has stimulated the expansion of crop production and cattle raising, which has caused environmental impacts. In response, Brazil developed public policies such as the new Forest Code (FC) and supply chain arra
Externí odkaz:
https://doaj.org/article/d9181b38420241a1b40665d86241cebd
Publikováno v:
Engenharia Agrícola, Vol 34, Iss 6, Pp 1245-1255 (2014)
Some models have been developed using agrometeorological and remote sensing data to estimate agriculture production. However, it is expected that the use of SAR images can improve their performance. The main objective of this study was to estimate th
Externí odkaz:
https://doaj.org/article/41834331e8e14bb0bebef3bc78b77fdc
Autor:
Ana C Rorato, Gilberto Camara, Maria Isabel S Escada, Michelle C A Picoli, Tiago Moreira, Judith A Verstegen
Publikováno v:
Environmental Research Letters, Vol 15, Iss 10, p 1040a3 (2020)
The Brazilian Amazon has the highest concentration of indigenous peoples in the world. Recently, the Brazilian government sent a bill to Congress to regulate commercial mining in indigenous lands. This work analyzes the risks of the proposed mining b
Externí odkaz:
https://doaj.org/article/8511d4ee08074622b67f185b6f337386