fix tasseledCap coefficient and mv table to sysdata

NEWS

@@ -1,3 +1,8 @@
+RStoolbox 0.1.9
+=====================================
+Fixes:
+* corrected sign of greenness tasseledCap coefficient for Landsat5 TM band 1 (reported by Thomas Day)
+
 RStoolbox 0.1.8
 =====================================
 New:

R/tasseledCap.R

@@ -8,17 +8,27 @@
 #' @param ... Further arguments passed to writeRaster.
 #' @export 
 #' @details 
-#' Currently implemented: Landsat 4 TM, Landsat 5 TM, Landsat 7ETM+, Landsat 8 OLI and MODIS. Input data must be in top of atmosphere reflectance.
-#' Bands must be available in the correct order and irrelevant bands, such as Landsat Thermal Bands must be removed.
+#' Currently implemented: Landsat 4 TM, Landsat 5 TM, Landsat 7ETM+, Landsat 8 OLI and MODIS. 
+#' Input data must be in top of atmosphere reflectance.
+#' Moreover, bands must be provided in ascending order as listed in the table below. 
+#' Irrelevant bands, such as Landsat Thermal Bands must be omitted.
 #' Required bands are:
-#' \tabular{rrr}{
-#'  sat \tab bands \tab coefficients \cr
-#'  Landsat4TM \tab 1,2,3,4,5,7 \tab Crist 1985 \cr
-#'  Landsat5TM  \tab 1,2,3,4,5,7 \tab Crist 1985 \cr
-#'  Landsat7ETM \tab 1,2,3,4,5,7 \tab Huang 2002 \cr
-#'  Landsat8OLI \tab 2,3,4,5,6,7 \tab Baig 2014 \cr
-#'  MODIS \tab 1,2,3,4,5,6,7 \tab Lobser 2007 \cr
+#' \tabular{rrrl}{
+#'  sat \tab bands \tab coefficients \tab data unit\cr
+#'  Landsat4TM \tab 1,2,3,4,5,7 \tab Crist 1985 \tab reflectance \cr
+#'  Landsat5TM  \tab 1,2,3,4,5,7 \tab Crist 1985 \tab reflectance \cr
+#'  Landsat7ETM \tab 1,2,3,4,5,7 \tab Huang 2002 \tab reflectance \cr
+#'  Landsat8OLI \tab 2,3,4,5,6,7 \tab Baig 2014 \tab reflectance \cr
+#'  MODIS \tab 1,2,3,4,5,6,7 \tab Lobser 2007 \tab reflectance \cr
 #' }
+#' @references 
+#' Crist (1985) "A TM Tasseled Cap Equivalent Transformation for Reflectance Factor Data." Remote Sensing of Environment 17 (3): 301–306
+#' 
+#' Huang et al. (2002) "Derivation of a Tasselled Cap Transformation Based on Landsat 7 At-Satellite Reflectance." International Journal of Remote Sensing 23 (8): 1741–1748
+#' 
+#' Baig et al. (2014) "Derivation of a Tasselled Cap Transformation Based on Landsat 8 At-Satellite Reflectance." Remote Sensing Letters 5 (5): 423–431.
+#' 
+#' Lobser et al. (2007) "MODIS Tasselled Cap: Land Cover Characteristics Expressed through Transformed MODIS Data." International Journal of Remote Sensing 28 (22): 5079–5101.
 #' @return 
 #' Returns a RasterBrick with the thee bands: brigthness, greenness, and (soil) wetness. 
 #' @examples 
@@ -33,47 +43,9 @@ tasseledCap <- function(img, sat, ...) {
     sat <- tolower(sat)
     if(!sat %in% c("landsat4tm" , "landsat5tm" , "landsat7etm" ,"landsat8oli", "modis")) stop("Sensor not implemented. See ?tasseledCap for options.")     
 
+    if(nlayers(img) != nrow(.TCcoefs[[sat]])) stop("Number of layers does not match required number of layers")
 
-    d <- list(NULL, c("brightness", "greenness", "wetness"))
-    coefs <- list(
-            landsat4tm = matrix(c(
-                            # Crist 1985
-                             0.2043,  0.4158,  0.5524, 0.5741,  0.3124,  0.2303, 
-                            -0.1063, -0.2819, -0.4934, 0.7940, -0.0002, -0.1446,
-                             0.0315,  0.2021,  0.3102, 0.1594, -0.6806, -0.6109
-    ), ncol=3, dimnames = d),
-            landsat5tm = matrix( c(
-                            # Crist 1985
-                            0.2043,  0.4158,  0.5524, 0.5741,  0.3124,  0.2303, 
-                            0.1063, -0.2819, -0.4934, 0.7940, -0.0002, -0.1446,
-                            0.0315,  0.2021,  0.3102, 0.1594, -0.6806, -0.6109)
-                    , ncol = 3, dimnames = d),
-            landsat7etm= matrix(c( 
-                            # Huang 2002
-                             0.3561,  0.3972, 0.3904, 0.6966, 0.2286, 0.1596, 
-                            -0.3344, -0.3544,-0.4556, 0.6966,-0.0242,-0.2630,
-                             0.2626,  0.2141, 0.0926, 0.0656,-0.7629,-0.5388)
-                    #       0.0805, -0.0498 ,0.1950,-0.1327, 0.5752,-0.7775, 
-                    #      -0.7252, -0.0202, 0.6683, 0.0631,-0.1494,-0.0274, 
-                    #       0.4000, -0.8172, 0.3832, 0.0602,-0.1095, 0.0985 
-                    , ncol = 3, dimnames = d),          
-            landsat8oli= matrix(c(
-                            # Baig et al (2014)
-                            0.3029, 0.2786, 0.4733, 0.5599, 0.5080, 0.1872,
-                            -0.2941,-0.2430,-0.5424, 0.7276, 0.0713,-0.1608,
-                            0.1511, 0.1973, 0.3283, 0.3407,-0.7117,-0.4559), ncol = 3, dimnames = d),    
-            modis = matrix(c(
-                            #Lobser & Cohen (2007) 
-                            0.4395, 0.5945, 0.2460, 0.3918, 0.3506, 0.2136, 0.2678, 
-                            -0.4064, 0.5129,-0.2744,-0.2893, 0.4882,-0.0036,-0.4169,
-                            0.1147, 0.2489, 0.2408, 0.3132,-0.3122,-0.6416,-0.5087), ncol = 3, dimnames = d)
-    #ikonos = matrix(c(NA)),
-    #spot = matrix(c(NA)),
-    #rapideye = matrix(c(NA)),
-    )
-    if(nlayers(img) != nrow(coefs[[sat]])) stop("Number of layers does not match required number of layers")
-
-    tct <- function(x, cof = coefs[[sat]]) {
+    tct <- function(x, cof = .TCcoefs[[sat]]) {
         x %*% cof 
     }
 
@@ -82,4 +54,5 @@ tasseledCap <- function(img, sat, ...) {
 
 
 
-
+
+

data-raw/generate_sysdata.R

@@ -116,7 +116,6 @@
 		)
 ) 
 
-
 exponents <- c(-4, -2, -1, -.7, -.5)
 for(s in names(.LANDSATdb)){
 	for(sen in names(.LANDSATdb[[s]])) {
@@ -142,6 +141,49 @@ for(s in names(.LANDSATdb)){
 
 
 
+## Tasselled Cap Coefficients
+d <- list(NULL, c("brightness", "greenness", "wetness"))
+.TCcoefs <- list(
+        landsat4tm = matrix(c(
+                        # Crist 1985
+                        0.2043,  0.4158,  0.5524, 0.5741,  0.3124,  0.2303, 
+                        -0.1063, -0.2819, -0.4934, 0.7940, -0.0002, -0.1446,
+                        0.0315,  0.2021,  0.3102, 0.1594, -0.6806, -0.6109),
+                ncol=3, dimnames = d),
+        landsat5tm = matrix( c(
+                        # Crist 1985
+                        0.2043,  0.4158,  0.5524, 0.5741,  0.3124,  0.2303, 
+                        -0.1063, -0.2819, -0.4934, 0.7940, -0.0002, -0.1446,
+                        0.0315,  0.2021,  0.3102, 0.1594, -0.6806, -0.6109)
+                , ncol = 3, dimnames = d),
+        landsat7etm= matrix(c( 
+                        # Huang 2002
+                        0.3561,  0.3972, 0.3904, 0.6966, 0.2286, 0.1596, 
+                        -0.3344, -0.3544,-0.4556, 0.6966,-0.0242,-0.2630,
+                        0.2626,  0.2141, 0.0926, 0.0656,-0.7629,-0.5388)
+                #       0.0805, -0.0498 ,0.1950,-0.1327, 0.5752,-0.7775, 
+                #      -0.7252, -0.0202, 0.6683, 0.0631,-0.1494,-0.0274, 
+                #       0.4000, -0.8172, 0.3832, 0.0602,-0.1095, 0.0985 
+                , ncol = 3, dimnames = d),          
+        landsat8oli= matrix(c(
+                        # Baig et al (2014)
+                        0.3029, 0.2786, 0.4733, 0.5599, 0.5080, 0.1872,
+                        -0.2941,-0.2430,-0.5424, 0.7276, 0.0713,-0.1608,
+                        0.1511, 0.1973, 0.3283, 0.3407,-0.7117,-0.4559), ncol = 3, dimnames = d),    
+        modis = matrix(c(
+                        #Lobser & Cohen (2007) 
+                        0.4395, 0.5945, 0.2460, 0.3918, 0.3506, 0.2136, 0.2678, 
+                        -0.4064, 0.5129,-0.2744,-0.2893, 0.4882,-0.0036,-0.4169,
+                        0.1147, 0.2489, 0.2408, 0.3132,-0.3122,-0.6416,-0.5087), ncol = 3, dimnames = d)
+#ikonos = matrix(c(NA)),
+#spot = matrix(c(NA)),
+#rapideye = matrix(c(NA)),
+)
+
+
+
+
+
 ## *******************************************************************************************************************
 ## Save internal data
-save(.ESdistance, .LANDSATdb, .DATATYPEdb, file = "R/sysdata.rda", compress = "gzip")
+save(.ESdistance, .LANDSATdb, .DATATYPEdb,.TCcoefs, file = "R/sysdata.rda", compress = "gzip")