forestSAS-package: An R package for forest spatial structure analysis systems

In Zongzheng/forestSAS: An R package for forest spatial structure analysis systems

Description

In recent years, there has been considerable interest in a group of neighborhood-based structural parameters that properly express the spatial structure characteristics of tree populations and forest communities and have strong operability for guiding forestry practices.forestSAS package provide more important information and allow us to better understand and analyze the fine-scale spatial structure of tree populations and stand structure.

Details

Forest structure commonly refers to a distribution pattern of tree attributes within a forest ecosystem. Similarly, tree population structure describes the distribution characteristics of individuals of conspecifics within a community, and the spatial structure of a tree population is largely determined by the relationships among neighboring groups of trees.

Author(s)

Zongzheng Chai, [e-mail]

References

None

Examples

data(tree.ppp)
##Get the tree attributies of nearest neighbour 
nnindices<-nnIndex(tree.ppp,N=4,
            smark=c("sp.code","dbh.cm","storey",
               "crownwid.m","group","biomass.kg",
               "quality","x","y"),buffer=FALSE)

#Species mingling
M<-fsasN4(nnindices$nnsp.code,match.fun=mingling)
M
#Stand storey differation degree
H<-fsasN4(nnindices$nnstorey,match.fun=differ)
H
#Tree successional degree
S<-fsasN4(nnindices$nngroup,match.fun=ideal,para="Climax")
S
#Tree quality ideal state
Q<-fsasN4(nnindices$nnquality,match.fun=ideal,
          para=c("Excellent","Good"))
Q
#Tree corwding degree
C<-fsasN4(nnoverlap(nnindices$nncrownwid.m,
         nnindices$nndist),match.fun=crowding)
C
#Tree uniform angle index
W<-fsasN4(nnangle(nnindices$nndist,nnindices$nnx,
           nnindices$nny)$nnangle,
          match.fun=uniform.angle,para=72)
W
#Tree dominance
U<-fsasN4(nnindices$nndbh.cm,match.fun=dominance)
U
#Tree biomass dominance
B<-fsasN4(nnindices$nnbiomass.kg,match.fun=dominance)
B

##Compute the structrue heterogeneity of index
M.pv<-pv(M$result$index,optm=1)
M.pv
H.pv<-pv(H$result$index,optm=1)
H.pv
S.pv<-pv(S$result$index,optm=1)
S.pv
Q.pv<-pv(Q$result$index,optm=1)
Q.pv
C.pv<-pv(C$result$index,optm=0.5)
C.pv
W.pv<-pv(W$result$index,optm=0.5)
W.pv
U.pv<-pv(U$result$index,optm=0)
U.pv
B.pv<-pv(B$result$index,optm=0)
B.pv

##Compute total forest saptial structrue heterogeneity 
#based on the average of indices preference value 
IAVE<-pv(index=c(M$meanI,H$meanI,S$meanI,Q$meanI,
                       C$meanI,W$meanI,U$meanI,B$meanI),
               optm=c(1,1,1,1,0.5,0.5,0,0))
IAVE

##Compute total forest saptial structrue heterogeneity 
#based on the preference value of indices average 
IPVE=mean(M.pv,H.pv,S.pv,Q.pv,C.pv,W.pv,U.pv,B.pv)
IPVE

Zongzheng/forestSAS documentation built on May 10, 2019, 1:59 a.m.