Hi Jonathan I tried that.. But I am but the results don?t make sense:
head(NDVIStackDf)
x y NDVI1 NDVI2 NDVI3 NDVI4 NDVI5 NDVI6 NDVI7 NDVI8 NDVI9 NDVI10 NDVI11 NDVI12 1 29.42809 -1.002081 0.7196462 0.6093929 0.614475 0.7851786 0.799475 0.7241929 0.5946000 0.5948500 0.6585143 0.7874357 0.8305786 0.7774929 2 29.43662 -1.002081 0.7103154 0.5823500 0.572225 0.7867429 0.794050 0.7445643 0.6033786 0.5635429 0.6421857 0.7802786 0.8300643 0.7886786 3 29.44514 -1.002081 0.7303692 0.6254571 0.599350 0.7771143 0.785850 0.7510071 0.6404571 0.6197286 0.6770929 0.7686786 0.8169571 0.7957786 4 29.45367 -1.002081 0.7641923 0.6890714 0.657850 0.7936786 0.809975 0.7805429 0.6769643 0.6590714 0.7165357 0.7843357 0.8283286 0.8231500 5 29.46220 -1.002081 0.8057769 0.7500714 0.718175 0.8208786 0.838575 0.8126500 0.7345786 0.7359571 0.7661214 0.8087214 0.8442643 0.8380071 6 29.47073 -1.002081 0.8065615 0.7627071 0.730550 0.8142214 0.841100 0.8252000 0.7574786 0.7425071 0.7590571 0.8025071 0.8518357 0.8430286
head(rainStackDf)
x y rain1 rain2 rain3 rain4 rain5 rain6 rain7 rain8 rain9 rain10 rain11 rain12 1 29.42917 -1.004167 66 68 85 116 105 61 40 85 110 125 118 85 2 29.43750 -1.004167 66 69 85 117 106 61 40 85 110 125 119 86 3 29.44583 -1.004167 66 68 84 116 106 60 39 84 110 124 118 85 4 29.45417 -1.004167 65 67 83 116 105 60 39 83 108 123 117 84 5 29.46250 -1.004167 65 68 83 117 106 59 38 83 109 124 118 84 6 29.47083 -1.004167 66 68 84 118 107 59 38 83 110 125 119 85
mystackDf <- stack(NDVIStackDf, rainStackDf) head(mystackDf)
values ind 1 29.42809 x 2 29.43662 x 3 29.44514 x 4 29.45367 x 5 29.46220 x 6 29.47073 x Is there a better way maybe without using data frames? I tried stacking the stacks too:
s1 <- stack(NDVIStack, rainStack)
Error in compareRaster(x) : different number or columns
rainStack
class : RasterStack dimensions : 1287, 1321, 1700127, 12 (nrow, ncol, ncell, nlayers) resolution : 0.008333333, 0.008333333 (x, y) extent : 29.425, 40.43333, -11.725, -1 (xmin, xmax, ymin, ymax) coord. ref. : +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0 names : rain1, rain2, rain3, rain4, rain5, rain6, rain7, rain8, rain9, rain10, rain11, rain12 min values : 7, 5, 31, 13, 0, 0, 0, 0, 0, 0, 22, 32 max values : 391, 392, 563, 746, 473, 159, 109, 106, 164, 247, 349, 464
NDVIStack
class : RasterStack dimensions : 1258, 1291, 1624078, 12 (nrow, ncol, ncell, nlayers) resolution : 0.008526982, 0.008525437 (x, y) extent : 29.425, 40.43333, -11.725, -1 (xmin, xmax, ymin, ymax) coord. ref. : +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0 names : NDVI1, NDVI2, NDVI3, NDVI4, NDVI5, NDVI6, NDVI7, NDVI8, NDVI9, NDVI10, NDVI11, NDVI12 min values : -0.1524615, -0.1353071, -0.1970500, -0.1632071, -0.1919250, -0.1647286, -0.1665000, -0.1693357, -0.1852643, -0.1733714, -0.1555357, -0.1682571 max values : 0.9153615, 0.9013000, 0.9295500, 0.9134643, 0.9421750, 0.9158357, 0.9000071, 0.9009786, 0.8733571, 0.8792429, 0.9151357, 0.9233000 Thanks Justin
On Jun 30, 2014, at 5:55 PM, Jonathan Greenberg <jgrn at illinois.edu> wrote:
Justin: It would make more sense, if you insist on working with data.frames, for you to create a single stack with all of your predictor and response variables, and then do your extraction -- that way you don't need to worry about a merge after the fact. The chances of the coordinates being EXACT I suspect are very low, which is why the merge() is failing. Basically: mystack <- stack(meanTempStackDf, rainStackDf) ... Then you can extract the data. --j On Mon, Jun 30, 2014 at 6:22 AM, Justin Michell <jwm302 at gmail.com> wrote:
Dear Niandou No I have not received any feedback. I do have some thoughts though. Is it possible/or at least would it make sense to get values in NDVI layer (average of nearby cells?) at the coordinates of raster values in other layers which one wants to merge with? I am not very well versed in these things so it?s just a thought- not sure how it would be implemented in R. Regards Justin On Jun 27, 2014, at 3:58 PM, ISSAKA NIANDOU, Yacouba <niandouy at who.int> wrote:
Niandou
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-- Jonathan A. Greenberg, PhD Assistant Professor Global Environmental Analysis and Remote Sensing (GEARS) Laboratory Department of Geography and Geographic Information Science University of Illinois at Urbana-Champaign 259 Computing Applications Building, MC-150 605 East Springfield Avenue Champaign, IL 61820-6371 Phone: 217-300-1924 http://www.geog.illinois.edu/~jgrn/ AIM: jgrn307, MSN: jgrn307 at hotmail.com, Gchat: jgrn307, Skype: jgrn3007