Down-scaling BBS

As my several recent posts have mentioned, I’m working with BBS spatial data (i.e. route paths and start points). I wanted to “downscale” by splitting routes into smaller segments and looking at data sub-route level. Specifically, I needed to split routes into fifths. I needed to know what order the segments were in from the start of the route to match the finer-scale data.

Here’s how to do it…

Break up the accounted for routes (or maybe even raw data set?) into “good” and “bad” routes depending on if the start is nearest a segment for a matching route
Work with “good starts” and “good routes” (the easiest!)
1. identify the segments closest to the start point as the first segment of the route
  1. run near on the start points to find out which segment in the master file is closest
  2. use the near_FID to join with the FID of the route segment layer
  3. export the resultant start segments into their own layer (number them 1)
  4. remove join
2. delete the start segments from the master file of all the broken up segments of the route (select by location: identical to)
3. use select by location (touches the boundary of) to find the next closest line segment to the start in the master file, and number them 2
4. repeat 2-4 for the remaining segments, and number them accordingly
Work with bad starts: once the good routes are out of the data set, is the bad point now closest to a remaining matching segment?
1. break up those newly matched lines
2. put leftover points into yet another file
Look at remaining points to see if any more lines can be put to use

Given the numbering scheme recommended in the steps above, your segments should be numbered 1-5 on each route. I buffered those segments and averaged tree cover within each segment buffer. In order to match my segment numbering with the rest of my R code, I renamed the segments.

vcf_subroute <- read.dbf("landcover/bbs_segment_buffers.dbf")
vcf_subroute$interval <- paste("count",vcf_subroute$segment,"0",sep="")

The remainder of the code is similar to that described in the route-level MODIS post, just with the added level of the interval.

vcf_subroute <- vcf_subroute[,c("rteno","interval",grep("[[:digit:]]", names(vcf_subroute), perl=TRUE, value=TRUE))]
vcf_subroute <- melt(vcf_subroute,id=c("rteno","interval"))
vcf_subroute$variable <- as.character(vcf_subroute$variable)
vcf_subroute$Year <- str_extract(vcf_subroute$variable,"[[:digit:]]+")
vcf_subroute$var <- sapply(strsplit(vcf_subroute$variable, "[[:digit:]]+"),"[[",2)
vcf_subroute$variable <- NULL
vcf_subroute <- dcast(vcf_subroute,rteno + interval ~ var,fun.aggregate=mean)
vcf_subroute$rteno <- as.character(vcf_subroute$rteno)

The full script, to this point: bbs10vcf

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