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diversityEcosystem.R 1.62 KiB
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# load data
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library(openxlsx)
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lf.tab = read.xlsx("LANDFORM/Export_ZP_landform.xlsx")
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head(lf.tab)
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colnames(lf.tab)[2] = "prop_NA"
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library(rgdal)
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zp = readOGR("Extract_raster_zp(20_02_2020)", "CEPAZ_ZP")
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head(zp@data)
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library(raster)
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expoeo = raster("Extract_raster_zp(20_02_2020)/expoeo.tif")
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projection(expoeo)
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expons = raster("Extract_raster_zp(20_02_2020)/expons.tif")
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projection(expons)
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tpi = raster("Extract_raster_zp(20_02_2020)/extrtpi.tif")
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projection(tpi)
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pente = raster("Extract_raster_zp(20_02_2020)/pentezp2.tif")
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projection(pente)
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# ray = raster("Extract_raster_zp(20_02_2020)/rayextr.tif")
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# projection(ray) == projection(pente)
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# ray2 = resample(ray, pente, method = "ngb")
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# saveRDS(ray2, "ray2.rds")
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ray2 = readRDS("ray2.rds")
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ray2
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lf = raster("LANDFORM/landformsTPI_saga.tif")
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projection(lf)
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lf_proj = projectRaster(lf, pente, method = "ngb")
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lf.clip = crop(lf_proj, extent(pente))
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# saveRDS(lf.clip, file = "lf_clip.rds")
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# lf.clip = readRDS("lf_clip.rds")
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lf.clip
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projection(zp) == projection(expoeo)
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library(sp)
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zp_proj = spTransform(zp, crs(projection(pente)))
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#=========================
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zp_x = zp_proj[1,]
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expoeo.vec = extract(expoeo, zp_x)[[1]]
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expons.vec = extract(expons, zp_x)[[1]]
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projection(lf.clip) == projection(zp_x)
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lf.vec = extract(lf.clip, zp_x)[[1]]
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tab = data.frame( expoeo = expoeo.vec,
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                  expons = expons.vec,
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                  lf = ,
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                  ray = extract(ray2, zp_x)[[1]],
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                  pente = extract(pente, zp_x)[[1]],
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                  tpi = extract(tpi, zp_x)[[1]] )
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tab$lf = as.factor(tab$lf)
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library(FD)
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Dij = gowdis(tab)
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res_x = mean(as.vector(Dij))
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