update DataDownloadApplication

FarmmapsDataDownload/ShowGeotiff.r

@@ -0,0 +1,114 @@
+# ShowGeotiff.r
+# Have a look at a downloaded satellite image and check if stats are correctly calculated
+# I downloaded and calculated the stats for the polygon defined in C:\git\FarmMapsApiClient_WURtest\FarmmapsDataDownload\DataDownloadInput.json
+# in which I set "SatelliteBand": "wdvi" and in which in the console I requested the image for date '2022-03-08'
+
+library(raster)
+library(sf)
+library(rgdal)
+setwd("C:/git/FarmMapsApiClient_WURtest/FarmmapsDataDownload/bin/Debug/netcoreapp3.1/Downloads")
+
+# FarmmapsDataDownload
+fileGeotiff <- "sentinelhub_test_BvdTFieldlabG92_20220308.tif"
+lenfilename <- nchar(fileGeotiff)
+year <- substr(fileGeotiff,lenfilename-11,lenfilename-8)
+imgdate <- substr(fileGeotiff,lenfilename-11,lenfilename-4)
+
+stk.sentinelhub <- stack(x=fileGeotiff)
+# plot(stk.sentinelhub) shows 6 plots (6 bands)
+# 1. ndvi
+# 2. wdvi Note wdvi-red
+# 3. ci-red
+# 4. natural: red
+# 5. natural: green
+# 6. natural: blue
+names(stk.sentinelhub) <- c("ndvi","wdvired","ci-red","red","green","blue")
+plot(stk.sentinelhub)
+crs(stk.sentinelhub)
+# CRS arguments: +proj=longlat +datum=WGS84 +no_defs
+stk.sentinelhub.rd <- projectRaster(stk.sentinelhub, crs = CRS('+init=EPSG:28992'))
+crs(stk.sentinelhub)
+
+r.sentinelhub.rd.wdvi <- subset(stk.sentinelhub.rd,2)
+dev.off()
+plot(r.sentinelhub.rd.wdvi,main=paste("wdvi",imgdate),xlab="RDX",ylab="RDY")
+cellStats(r.sentinelhub.rd.wdvi,'mean')	# 0.2252725
+
+# Convert the .rd.wdvi raster to WGS84
+r.sentinelhub.wgs84.wdvi <- projectRaster(r.sentinelhub.rd.wdvi, crs = CRS('+init=EPSG:4326'))
+
+# Draw a polygon on top of the raster
+# Polygon pol from C:\git\FarmMapsApiClient_WURtest\FarmmapsDataDownload\DataDownloadInput.json
+pol <- data.frame(id = 1, wkt = gsub("\n","",'POLYGON((
+      5.563472073408009 52.547554398144172,
+      5.567425915520115 52.547725375100377,
+      5.567917474269188 52.540608459298582,
+      5.563878143678981 52.54048022658143,
+      5.563472073408009 52.547554398144172
+      ))'))
+
+
+pol.wgs84 <- st_as_sf(pol, wkt = 'wkt', crs = CRS('+init=EPSG:4326'))
+pol.rd <- st_transform(pol.wgs84, "+init=epsg:28992")
+
+#Calculate approximate middle of polygon
+res <- as.data.frame(do.call("rbind", lapply(st_geometry(pol.wgs84), st_bbox)))
+res$latmid <- (res$ymax+res$ymin)/2.0
+res$lonmid <- (res$xmax+res$xmin)/2.0
+res
+      # xmin     ymin     xmax     ymax  latmid   lonmid
+# 1 5.563472 52.54048 5.567917 52.54773 52.5441 5.565695
+
+# Have a look at both polygons
+# wg84
+dev.off()
+plot(r.sentinelhub.wgs84.wdvi,main=paste("wdvi",imgdate),xlab="LON",ylab="LAT")
+plot(pol.wgs84,add=TRUE, col="transparent",border="red")
+# RD
+dev.off()
+plot(r.sentinelhub.rd.wdvi,main=paste("wdvi",imgdate),xlab="RDX",ylab="RDY")
+plot(pol.rd,add=TRUE, col="transparent",border="red")
+
+# Clip the polygon from the full rectangle figure
+r.sentinelhub.rd.wdvi.pol <- mask(r.sentinelhub.rd.wdvi,pol.rd)
+r.sentinelhub.wgs84.wdvi.pol <- mask(r.sentinelhub.wgs84.wdvi,pol.wgs84)
+dev.off()
+plot(r.sentinelhub.wgs84.wdvi.pol,main=paste("wdvi",imgdate),xlab="LON",ylab="LAT")
+plot(pol.wgs84,add=TRUE, col="transparent",border="red")
+#That's what we want! 
+
+# Now compare the stats
+cellStats(r.sentinelhub.wgs84.wdvi,'mean')	# [1] 0.2250987 # Stats from rectangle, WGS84
+cellStats(r.sentinelhub.rd.wdvi,'mean')	# [1] 0.2252725 # Stats from rectangle, RD. Almost but not exactly same as above
+cellStats(r.sentinelhub.wgs84.wdvi.pol,'mean')	# [1] 0.2275067 # Stats from raster clipped by polygon, WGS84
+cellStats(r.sentinelhub.rd.wdvi.pol,'mean')	# [1] 0.2275073 # Stats from raster clipped by polygon, RD. Almost but not exactly same as above
+# file satelliteStats_test_BvdTFieldlabG92_20220308.csv
+# "wdvi" "mean": 0.22744397204465
+# Mean in csv corresponds with cellStats calculated from clipped tif!
+# So while the tif returned is a non-clipped image, the downloaded statistics are from the clipped image
+# Exactly as we wanted.
+cellStats(r.sentinelhub.wgs84.wdvi.pol,'median')	# Error in .local(x, stat, ...) : invalid 'stat'. Should be sum, min, max, sd, mean, or 'countNA'
+r.sentinelhub.wgs84.wdvi.vals <- values(r.sentinelhub.wgs84.wdvi)
+median(r.sentinelhub.wgs84.wdvi.vals)	# [1] NA
+median(r.sentinelhub.wgs84.wdvi.vals,na.rm=TRUE)	# [1] 0.2318
+r.sentinelhub.wgs84.wdvi.pol.vals <- values(r.sentinelhub.wgs84.wdvi.pol)
+median(r.sentinelhub.wgs84.wdvi.pol.vals)	# [1] NA
+median(r.sentinelhub.wgs84.wdvi.pol.vals,na.rm=TRUE)	# [1] 0.2338
+# file satelliteStats_test_BvdTFieldlabG92_20220308.csv
+# "wdvi" "mean": 0.233799993991851
+# Median is same as for median(r.sentinelhub.wgs84.wdvi.pol.vals,na.rm=TRUE)
+#   in csv corresponds with cellStats calculated from clipped tif!
+# So while the tif returned is a non-clipped image, the downloaded statistics are from the clipped image
+# Exactly as we wanted.
+cellStats(r.sentinelhub.wgs84.wdvi,'countNA')	# [1] 27896
+ncell(r.sentinelhub.wgs84.wdvi)	# [1] 272718
+cellStats(r.sentinelhub.wgs84.wdvi,'countNA') / ncell(r.sentinelhub.wgs84.wdvi)	# [1] 0.1022888	# 10% no data? doesn't show in the plot?
+cellStats(r.sentinelhub.wgs84.wdvi.pol,'countNA')	# [1] 57625
+summary(r.sentinelhub.wgs84.wdvi.pol.vals)	# shows the same: NA's: 57625
+ncell(r.sentinelhub.wgs84.wdvi.pol)	# [1] 272718
+populationCount = ncell(r.sentinelhub.wgs84.wdvi.pol) - cellStats(r.sentinelhub.wgs84.wdvi.pol,'countNA')
+populationCount # [1] 215093
+# file satelliteStats_test_BvdTFieldlabG92_20220308.csv
+# "wdvi" "populationCount": 214688
+# similar but not same
+