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Abstract : Dynamic change of vegetation has become a very
sensitive problem in China due to climate variability and human's
disturbances in the Yellow river basin. Dynamic simulation and forecast
of vegetation are regarded as an effective measure to decision support
for local government. This paper presents a new method to support the
local government's effort in ecological protection. In integrates
cellular automata (CA) -artificial neural network (ANN) model with
Geographical information system (GIS) and remote sensing. The proposed
method includes three major steps: (1) to extract control factors; (2)
to integrate CA and ANN models; (3) to simulate the selected area using
CA-ANN model. The results indicted that the integrated approach can
rapidly find condition of future vegetation cover that satisfy
requirement of local relative department. It has demonstrated that the
proposed method can provide valuable decision support for local
government. the result indicts that NDVI of the vegetation has an
increasing trend and characteristics of distribution concentration
trend, but the change rate is become lower from the year 2007 to 2014
compared with the changes from the year 2000 to 2007.
https://hal.inria.fr/hal-01055400 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Tuesday, August 12, 2014 - 5:39:31 PM Last modification on : Thursday, March 5, 2020 - 5:42:20 PM Long-term archiving on: : Wednesday, November 26, 2014 - 11:11:46 PM
Zhenyu Cai, Xiaohua Wang. Research on Vegetation Dynamic Change
Simulation Based on Spatial Data Mining of ANN-CA Model Using
Time Series of Remote Sensing Images. Third IFIP TC 12 International Conference on Computer and Computing Technologies in Agriculture III (CCTA), Oct 2009, Beijing, China. pp.551-557, ⟨10.1007/978-3-642-12220-0_80⟩. ⟨hal-01055400⟩