@InProceedings{SerratoSousPinzPard:2011:CoDeMo,
author = "Serrato, Jeniffer Trejos and Sousa J{\'u}nior, Manoel de
Ara{\'u}jo and Pinz{\'o}n, Federico Pinz{\'o}n and Pardi
Lacruz, Mar{\'{\i}}a Silvia",
affiliation = "Grupo de Investigaci{\'o}n en Geom{\'a}tica Aplicada - GIGA
Universidad del Valle - Cali, Valle del Cauca, Colombia and
{Universidade Federal de Santa Maria - UFSM} and Universidad del
Valle - Cali, Valle del Cauca, Colombia and {CRECTEALC – Campus
Brasil}",
title = "Comparaci{\'o}n del modelo markoviano y de regresi{\'o}n para
predicci{\'o}n de cambios en el uso y cobertura del suelo en la
zona central del Departamento del Meta-Colombia",
booktitle = "Anais...",
year = "2011",
editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio
Soares",
pages = "6532--6539",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 15. (SBSR).",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
keywords = "prediction of change, Markov chain, regression model, land
use/land cover, linear spectral mixture model, predicci{\'o}n de
cambios, cadenas de Markov, modelo de regresi{\'o}n, uso y
cobertura de suelo, modelo lineal de mezcla espectral.",
abstract = "To propose new methodologies for the sustainable management of the
natural resources, some techniques for the prediction of changes
in the land use have been implemented. Those techniques allow to
estimate tendencies in the landscape dynamics in the time. To
contribute with this purpose, this work compare two empirical
models regression model and Markov chain model - focused in
predicting land use change, verifying advantages and disadvantages
of each one. Land use classes such as oil palm, urban area,
agriculture, water, sand areas, bare soil and forest, were mapped
from classification of three images: a 1988 TM/Landsat, an
ETM+/Landsat 7 from 2000 and a 2005 CCD/CBERS 2 of the year 2005.
Linear spectral mixture model was applied to the different bands.
The area of land use classes were computed in each one of the
images and dates and the regression model with better adjustment
were estimated. With these models, projections for the years 2010,
2012 and 2015 were made. The second prediction were calculated
through the Markov chain transition matrix for the periods
1988-2000 and 2000-2005, and projections were calculated for 2010,
2012 and 2015. Finally, the results of the Markov chain transition
matrix were compared with those obtained by regression models. The
better predictive performance was obtained with the Markov chains
for each of the land use classes. However, the regression models
had good performance for the classes of oil palm and urban areas.
It could also be verified the applicability of these techniques
for agricultural areas under great exploitation.",
conference-location = "Curitiba",
conference-year = "30 abr. - 5 maio 2011",
isbn = "{978-85-17-00056-0 (Internet)} and {978-85-17-00057-7 (DVD)}",
language = "es",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "3ERPFQRTRW/3A3TJ2H",
url = "http://urlib.net/rep/3ERPFQRTRW/3A3TJ2H",
targetfile = "p0614.pdf",
urlaccessdate = "2021, Jan. 20"
}