NLCD land cover by area for each county in MO odd numbered years 2001-2023.

A dataset derived of Annual NLCD data- files were obtained via the FedData package (NLCD) and tigir package (county boundaries). NLCD data was reprojected to NAD83 UTM 15 N before areal calculations.

Usage

nlcd.area.tab

Format

cty

county name

yr

4 digit year

crop.sqkm

area in km^2 of crop

develop.sqkm

area in km^2 of developed

forest.sqkm

area in km^2 of forest

grass.sqkm

area in km^2 of grass

water.sqkm

area in km^2 of water

wetland.sqkm

area in km^2 of wetland

other.sqkm

area in km^2 of all other landcover types present

Details

See vignettes for examples on how to batch process

Cropping performed with terra::crop and the terra:mask

Area converted to square km based on a 30x30m cell size and summing all all pixels with in a given class. No other processing occurred.

Examples

if (FALSE) { # \dontrun{
#data processed as follows:



# list projected NLCD files in a folder
list.nlcd<-list.files(path='./prj_NLCD/',
                     pattern='.tif$',
                     full.names=TRUE)



MDCSpatialData::counties.mo->co



co%>%split(.$NAME)%>%
 map(.,~terra::vect(.x))->tmp

nlcd.fxn<-function(nlcd,
                  county,year){
 terra::rast(nlcd)->Z

 mo.co.list[[county]]->Q

 terra::crop(Z,Q)->P
 terra::mask(P,Q)%>%
   terra::freq()%>%
   rename(LC=value)%>%
   select(LC,count)%>%
   group_by(LC)%>%
   summarize(n.cells=sum(count))%>%
   ungroup()%>%
   mutate(pct.area=n.cells/sum(n.cells),
          area.sqkm=(n.cells*(30*30)/1E6),
          cty=county,
          yr=year)
}




crossing(list.nlcd,names(mo.co.list))%>%
 rename(path=1,
        county=2)%>%
 mutate(year=str_extract(path,pattern='20\\d{2}'))%>%
 pmap(~nlcd.fxn(..1,..2,..3))->nlcd.tab


bind_rows(nlcd.tab)%>%
  select(-n.cells,-pct.area)%>%
  mutate(LC=paste0(LC,'.sqkm'))%>%
  pivot_wider(names_from=LC,
              values_from=area.sqkm)->nlcd.area.tab
} # }