diff --git a/PROFOUND database/Processing/Create_Stand_Data.R b/PROFOUND database/Processing/Create_Stand_Data.R index d3e1402..2f61921 100644 --- a/PROFOUND database/Processing/Create_Stand_Data.R +++ b/PROFOUND database/Processing/Create_Stand_Data.R @@ -42,6 +42,12 @@ names(df) <- c("year", "species_id", "site_id", "dbhArith_cm", "ba_m2ha", "age" "stemBiomass_kgha", "rootBiomass_kgha") df$stem <- NULL +# biomass stock variables from t/ha into kg/ha because raw data values are in t/ha +df$foliageBiomass_kgha <- df$foliageBiomass_kgha * 1000 +df$branchesBiomass_kgha <- df$branchesBiomass_kgha * 1000 +df$stemBiomass_kgha <- df$stemBiomass_kgha * 1000 +df$rootBiomass_kgha <- df$rootBiomass_kgha * 1000 + #df <- dropDuplicates(df, Tree_Data$BilyKriz) #df <- df[ df$year %in% unique(Tree_Data$BilyKriz$year), ] Stand_Data$BilyKriz <- df @@ -174,15 +180,24 @@ cat(Soroe_LAI_2000_2013.df.des) # Description is all there df <- Soroe_LAI_2000_2013.df df$species_id <- "fasy" +# reduce to single lai measurement per year: +# use only July measurements since most often lai is measured in July in Soro +df <- df[which(!duplicated(df$year)),] head(df) names(df) <- gsub("LAI", "lai", names(df)) -Stand_Data$Soro<- df + #inFile <- "/home/trashtos/ownCloud/PROFOUND_Data/Processed/Soro/Standdata_for_DB.txt" #df <- read.table(inFile, header = T, sep = "\t") #df <- df[,colSums(is.na(df)) - + The PROFOUND database @@ -213,7 +213,8 @@ code > span.co { color: #888888; font-style: italic; } code > span.ot { color: #007020; } code > span.al { color: #ff0000; font-weight: bold; } -code > span.fu { color: #900; font-weight: bold; } code > span.er { color: #a61717; background-color: #e3d2d2; } +code > span.fu { color: #900; font-weight: bold; } +code > span.er { color: #a61717; background-color: #e3d2d2; } @@ -228,10 +229,10 @@

The PROFOUND database

Ramiro Silveyra Gonzalez, Christopher Reyer, Mats Mahnken, Florian Hartig

-

2020-03-29

+

2020-05-04

Abstract

-

This vignette provides an overview of the Profound databse for benchmarking forest vegetation models, in particular database structure, content, data policy and an overview of each forest site contained in the database.

+

This vignette provides an overview of the Profound database for benchmarking forest vegetation models, in particular database structure, content, data policy and an overview of each forest site contained in the database.

@@ -266,7 +267,7 @@

2020-03-29

Overview

The PROFOUND database (PROFOUND DB) brings together data from a wide range of data sources to evaluate vegetation models and simulate climate impacts at the forest stand scale. It includes 9 forest sites across Europe, and provides for them a site description as well as soil, climate, CO2, Nitrogen deposition, tree-level, forest stand-level and remote sensing data. Moreover, for a subset of 5 sites, also time series of carbon fluxes, energy balances and soil water are available.

-

For more details, see the ProfoundData website, as well as Reyer et al, The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-220, in review, 2019.

+

For more details, see the ProfoundData website, as well as Reyer et al, The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-220, in review, 2019.

Data Policy

@@ -1665,9 +1666,9 @@

Dataset CLIMATE

Total daily precipitation -rad_Jcm2day +rad_Jcm2 REAL -J cm-2 day-1 +J cm-2 Total daily global radiation @@ -3209,7 +3210,7 @@

Dataset MODIS

gpp_gCm2d REAL -gC m-2 d +gC m-2 d-1 Gross Primary Production. Valid range: -375 – 375. Fill value: NA. Spatial resolution 1 km. Temporal resolution: 8-day accumulation. MOD17A2 @@ -3223,7 +3224,7 @@

Dataset MODIS

psNet_gCm2d REAL -gC m-2 d +gC m-2 d-1 Net Photosynthesis (GPP – maintenance respiration). Valid range: -375 – 375. Fill value: NA. Spatial resolution 1 km. Temporal resolution: 8-day accumulation. MOD17A2 diff --git a/ProfoundData/vignettes/ProfoundData.html b/ProfoundData/vignettes/ProfoundData.html index 3a86619..8fc5e76 100644 --- a/ProfoundData/vignettes/ProfoundData.html +++ b/ProfoundData/vignettes/ProfoundData.html @@ -13,7 +13,7 @@ - + The ProfoundData R-package @@ -299,7 +299,8 @@ code > span.co { color: #888888; font-style: italic; } code > span.ot { color: #007020; } code > span.al { color: #ff0000; font-weight: bold; } -code > span.fu { color: #900; font-weight: bold; } code > span.er { color: #a61717; background-color: #e3d2d2; } +code > span.fu { color: #900; font-weight: bold; } +code > span.er { color: #a61717; background-color: #e3d2d2; } @@ -314,7 +315,7 @@

The ProfoundData R-package

Ramiro Silveyra Gonzalez, Christopher Reyer, Mats Mahnken, Florian Hartig

-

2020-03-29

+

2020-05-04

Abstract

This vignette provides an overview of the Profound data R package. For an overview about the database, see the separate vignette PROFOUNDdatabase.

@@ -359,13 +360,13 @@

2020-03-29

  • The queryDB function: parsing your own queries
  • The reportDB function
    • -
  • Using the databse via sql
    • +
  • Using the database via sql

    • ProfoundData R-package: using the PROFOUND database from R

    -

    The ProfoundData package serves as interface to access the PROFOUND database. Three main functions are included to achieve this goal: a browseData function for exploring the database, a getData function for downloading data fromm the database and a plotData function to quickly inspect any variable of the datasets.

    +

    The ProfoundData package serves as interface to access the PROFOUND database. Three main functions are included to achieve this goal: a browseData function for exploring the database, a getData function for downloading data from the database and a plotData function to quickly inspect any variable of the datasets.

    The functions allow to retrieve only data from one site and one dataset at a time. For downloading data of more than one dataset or of more than one site, the function should be called as many times as the number of desired sites or datasets. Additionally, flags and other parameters can be passed to the functions. The package also includes utilities functions to do tasks such as inspecting the data or writing NetCDF files.

    To see the suggested ciation for the package, run

    library(ProfoundData)
@@ -373,14 +374,14 @@ 
    ProfoundData R-package: using the PROFOUND database from R
    
 
    ## 
 ## To cite the 'ProfoundData' package in publications use:
 ## 
-##   Reyer, C. (2019). The PROFOUND Database for evaluating
-##   vegetation models and simulating climate impacts on forest
-##   stands. Submitted to Earth System Science Data.
+##   Reyer, C. (2019). The PROFOUND Database for evaluating vegetation
+##   models and simulating climate impacts on forest stands. Submitted to
+##   Earth System Science Data.
 ## 
-##   Reyer, C., Silveyra Gonzalez, R., Dolos, K., Hartig, F., Hauf,
-##   Y., Noack, M., … Frieler, K. (2019). The PROFOUND database for
-##   evaluating vegetation models and simulating climate impacts on
-##   forests [Data set]. https://doi.org/10.5880/pik.2019.008
+##   Reyer, C., Silveyra Gonzalez, R., Dolos, K., Hartig, F., Hauf, Y.,
+##   Noack, M., … Frieler, K. (2020). The PROFOUND database for evaluating
+##   vegetation models and simulating climate impacts on forests [Data
+##   set]. https://doi.org/10.5880/PIK.2020.006
 ## 
 ## To see these entries in BibTeX format, use 'print(<citation>,
 ## bibtex=TRUE)', 'toBibtex(.)', or set
@@ -390,18 +391,18 @@ 
    ProfoundData R-package: using the PROFOUND database from R
    
 
    First Steps
    
 
    
 
    Database download
    
-
    Profound database is provided in SQLite and can be downloaded either by hand at http://doi.org/10.5880/PIK.2019.008 or via the
    
+
    The Profound database is provided in SQLite and can be downloaded either by hand at http://doi.org/10.5880/PIK.2020.006 or via
    
 
-
    Per default, the database is downloaded into the currrent working directory, but you can specify another location in the function. The function returns the current databse location, which can be passed on the the setDB function (see below).
    
+
    Per default, the database is downloaded into the current working directory, but you can specify another location in the function. The function returns the current database location, which can be passed on to the setDB function (see below).
    
 
    
 
    
 
    Database connection
    
-
    For using a locally stored database with the ProfoundData package, the first step is to call the setDB. The function requires a valid absolute path to the PROFOUND database.
    
-
    myDB <- path.expand("/Users/florian/temp/ProfoundData.sqlite")
+
    For using a locally stored database with the ProfoundData package, the first step is to call setDB. The function requires a valid absolute path to the PROFOUND database.
    
+
-
    To check the database connection you can use the use getDB, which returns the database path and also informs about the database version.
    
+
    To check the database connection you can use getDB, which returns the database path and also informs about the database version.
    
 
-
    ## Database version is 0.2.0
    
+
    ## Database version is 0.3
    
 
    ## [1] "/Users/florian/temp/ProfoundData.sqlite"
    
 
    
 
    
@@ -829,7 +830,7 @@ 
    Data overviews of the available data
    
 
 bily_kriz
 3
-rad_Jcm2day
+rad_Jcm2
 3.706045e+05
 3.871684e+05
 3.418508e+05
@@ -971,7 +972,7 @@ 
    Data overviews of the available data
    
 3
 GFDLESM2M
 historical
-rad_Jcm2day
+rad_Jcm2
 3.780155e+05
 3.823430e+05
 3.557333e+05
@@ -1091,7 +1092,7 @@ 
    Data overviews of the available data
    
 3
 GFDLESM2M
 piControl
-rad_Jcm2day
+rad_Jcm2
 4.141776e+05
 3.772647e+05
 3.423868e+05
@@ -1211,7 +1212,7 @@ 
    Data overviews of the available data
    
 3
 GFDLESM2M
 rcp2p6
-rad_Jcm2day
+rad_Jcm2
 3.780991e+05
 3.964951e+05
 3.529131e+05
@@ -1331,7 +1332,7 @@ 
    Data overviews of the available data
    
 3
 GFDLESM2M
 rcp4p5
-rad_Jcm2day
+rad_Jcm2
 4.187450e+05
 3.932176e+05
 3.658412e+05
@@ -1451,7 +1452,7 @@ 
    Data overviews of the available data
    
 3
 GFDLESM2M
 rcp6p0
-rad_Jcm2day
+rad_Jcm2
 3.782895e+05
 3.776877e+05
 3.467031e+05
@@ -1571,7 +1572,7 @@ 
    Data overviews of the available data
    
 3
 GFDLESM2M
 rcp8p5
-rad_Jcm2day
+rad_Jcm2
 3.672316e+05
 3.959328e+05
 3.550359e+05
@@ -1691,7 +1692,7 @@ 
    Data overviews of the available data
    
 3
 HadGEM2ES
 historical
-rad_Jcm2day
+rad_Jcm2
 4.270536e+05
 3.921624e+05
 3.381196e+05
@@ -1811,7 +1812,7 @@ 
    Data overviews of the available data
    
 3
 HadGEM2ES
 piControl
-rad_Jcm2day
+rad_Jcm2
 4.408675e+05
 3.919564e+05
 3.673516e+05
@@ -1931,7 +1932,7 @@ 
    Data overviews of the available data
    
 3
 HadGEM2ES
 rcp2p6
-rad_Jcm2day
+rad_Jcm2
 3.877499e+05
 4.497789e+05
 3.776577e+05
@@ -2051,7 +2052,7 @@ 
    Data overviews of the available data
    
 3
 HadGEM2ES
 rcp4p5
-rad_Jcm2day
+rad_Jcm2
 4.036507e+05
 4.304601e+05
 3.571120e+05
@@ -2171,7 +2172,7 @@ 
    Data overviews of the available data
    
 3
 HadGEM2ES
 rcp6p0
-rad_Jcm2day
+rad_Jcm2
 4.420520e+05
 4.397051e+05
 3.743635e+05
@@ -2291,7 +2292,7 @@ 
    Data overviews of the available data
    
 3
 HadGEM2ES
 rcp8p5
-rad_Jcm2day
+rad_Jcm2
 4.058588e+05
 4.509622e+05
 3.958738e+05
@@ -2411,7 +2412,7 @@ 
    Data overviews of the available data
    
 3
 IPSLCM5ALR
 historical
-rad_Jcm2day
+rad_Jcm2
 4.301708e+05
 3.964781e+05
 3.530505e+05
@@ -2531,7 +2532,7 @@ 
    Data overviews of the available data
    
 3
 IPSLCM5ALR
 piControl
-rad_Jcm2day
+rad_Jcm2
 4.056774e+05
 4.117241e+05
 3.646121e+05
@@ -2651,7 +2652,7 @@ 
    Data overviews of the available data
    
 3
 IPSLCM5ALR
 rcp2p6
-rad_Jcm2day
+rad_Jcm2
 4.192525e+05
 4.093297e+05
 3.755701e+05
@@ -2771,7 +2772,7 @@ 
    Data overviews of the available data
    
 3
 IPSLCM5ALR
 rcp4p5
-rad_Jcm2day
+rad_Jcm2
 4.138551e+05
 4.213282e+05
 3.825715e+05
@@ -2891,7 +2892,7 @@ 
    Data overviews of the available data
    
 3
 IPSLCM5ALR
 rcp6p0
-rad_Jcm2day
+rad_Jcm2
 4.427263e+05
 4.408261e+05
 3.666051e+05
@@ -3011,7 +3012,7 @@ 
    Data overviews of the available data
    
 3
 IPSLCM5ALR
 rcp8p5
-rad_Jcm2day
+rad_Jcm2
 3.585790e+05
 4.184550e+05
 3.585790e+05
@@ -3131,7 +3132,7 @@ 
    Data overviews of the available data
    
 3
 MIROC5
 historical
-rad_Jcm2day
+rad_Jcm2
 4.319353e+05
 4.356081e+05
 3.327256e+05
@@ -3251,7 +3252,7 @@ 
    Data overviews of the available data
    
 3
 MIROC5
 piControl
-rad_Jcm2day
+rad_Jcm2
 4.340896e+05
 4.622626e+05
 4.122271e+05
@@ -3371,7 +3372,7 @@ 
    Data overviews of the available data
    
 3
 MIROC5
 rcp2p6
-rad_Jcm2day
+rad_Jcm2
 4.015045e+05
 4.496680e+05
 3.932749e+05
@@ -3491,7 +3492,7 @@ 
    Data overviews of the available data
    
 3
 MIROC5
 rcp4p5
-rad_Jcm2day
+rad_Jcm2
 3.864426e+05
 4.578805e+05
 3.864426e+05
@@ -3611,7 +3612,7 @@ 
    Data overviews of the available data
    
 3
 MIROC5
 rcp6p0
-rad_Jcm2day
+rad_Jcm2
 4.104626e+05
 4.678674e+05
 4.053620e+05
@@ -3731,7 +3732,7 @@ 
    Data overviews of the available data
    
 3
 MIROC5
 rcp8p5
-rad_Jcm2day
+rad_Jcm2
 4.216762e+05
 4.793708e+05
 3.965346e+05
@@ -4394,7 +4395,7 @@ 
    CLIMATE_LOCAL
    
 p_mm
 relhum_percent
 airpress_hPa
-rad_Jcm2day
+rad_Jcm2
 wind_ms
 
 
@@ -4536,7 +4537,7 @@ 
    CLIMATE_ISIMIP
    
 p_mm
 relhum_percent
 airpress_hPa
-rad_Jcm2day
+rad_Jcm2
 wind_ms
 
 
@@ -4870,7 +4871,7 @@ 
    CLIMATE_ISIMIP
    
 p_mm
 relhum_percent
 airpress_hPa
-rad_Jcm2day
+rad_Jcm2
 wind_ms
 
 
@@ -4994,226 +4995,226 @@ 
    FLUX
    
 bily_kriz
 3
 2000
--38.78573
--39.59809
-15.209695
-15.86517
-97.83216
-2.408624
-102.09309
-2.440183
-138.66666
-3.967526
-145.19560
-4.126893
-58.23775
-7.234624
-67.81385
-7.632900
-107.9271
-4.083021
-110.7110
-4.281572
+-3.878573
+-3.959809
+1.5209695
+1.586517
+9.783216
+0.2408624
+10.209309
+0.2440183
+13.866666
+0.3967526
+14.519560
+0.4126893
+5.823775
+0.7234624
+6.781385
+0.7632900
+10.79271
+0.4083021
+11.07110
+0.4281572
 
 
 bily_kriz
 3
 2001
--32.77164
--36.29736
-11.523480
-11.77295
-51.97413
-2.064628
-54.90414
-2.072944
-86.48057
-3.049352
-99.01904
-3.346192
-77.40778
-3.178191
-78.30948
-4.676769
-116.1664
-2.044694
-112.0838
-2.611838
+-3.277164
+-3.629736
+1.1523480
+1.177295
+5.197413
+0.2064628
+5.490414
+0.2072944
+8.648057
+0.3049351
+9.901904
+0.3346192
+7.740778
+0.3178191
+7.830948
+0.4676770
+11.61664
+0.2044694
+11.20838
+0.2611837
 
 
 bily_kriz
 3
 2002
--36.58319
--37.97092
-9.151159
-11.09704
-63.96572
-1.678422
-59.06654
-2.507639
-103.28778
-2.665789
-98.69803
-3.657584
-73.20840
-3.276043
-54.78220
-3.948784
-114.9007
-2.011733
-121.0953
-2.635683
+-3.658319
+-3.797092
+0.9151159
+1.109704
+6.396572
+0.1678421
+5.906655
+0.2507639
+10.328778
+0.2665789
+9.869803
+0.3657584
+7.320840
+0.3276043
+5.478220
+0.3948784
+11.49007
+0.2011733
+12.10953
+0.2635683
 
 
 bily_kriz
 3
 2003
--91.17122
--90.71734
-11.427876
-12.15067
-113.99077
-2.434624
-113.01510
-2.925302
-205.16419
-4.039363
-203.70148
-5.157969
-85.56300
-3.735950
-93.86853
-5.552283
-177.0804
-2.699202
-186.4835
-4.224106
+-9.117121
+-9.071734
+1.1427876
+1.215067
+11.399078
+0.2434624
+11.301510
+0.2925302
+20.516419
+0.4039363
+20.370148
+0.5157969
+8.556300
+0.3735950
+9.386853
+0.5552283
+17.70804
+0.2699202
+18.64835
+0.4224106
 
 
 bily_kriz
 3
 2004
--84.57856
--83.56907
-27.092536
-39.38024
-63.33830
-1.440231
-63.31870
-1.718276
-146.77583
-3.967510
-150.77614
-5.129495
-103.02871
-4.847279
-93.67065
-5.601932
-174.2867
-4.021578
-182.9802
-4.963656
+-8.457856
+-8.356907
+2.7092536
+3.938024
+6.333830
+0.1440231
+6.331870
+0.1718276
+14.677583
+0.3967510
+15.077614
+0.5129495
+10.302871
+0.4847279
+9.367065
+0.5601932
+17.42867
+0.4021577
+18.29802
+0.4963656
 
 
 bily_kriz
 3
 2005
--79.08237
--82.49708
-8.661794
-12.04517
-52.72831
-2.710158
-59.54222
-2.576154
-134.15438
-5.274783
-142.76343
-5.185471
-60.53836
-6.489167
-68.58801
-8.837533
-182.7498
-5.116223
-198.8996
-5.399609
-
-
-bily_kriz
-3
-2006
--64.37540
--65.07293
-24.926481
-27.89668
-78.65130
-2.017064
-79.05678
-1.689278
-144.79195
-4.331742
-146.42456
-3.842385
-80.37568
-5.130079
-83.52022
-4.773277
-191.4361
-3.560452
-187.8914
-3.345761
+-7.908237
+-8.249708
+0.8661794
+1.204516
+5.272831
+0.2710158
+5.954222
+0.2576154
+13.415438
+0.5274783
+14.276343
+0.5185471
+6.053836
+0.6489167
+6.858801
+0.8837533
+18.27498
+0.5116223
+19.88996
+0.5399609
+
+
+bily_kriz
+3
+2006
+-6.437540
+-6.507293
+2.4926481
+2.789668
+7.865130
+0.2017064
+7.905678
+0.1689278
+14.479195
+0.4331742
+14.642456
+0.3842385
+8.037567
+0.5130079
+8.352022
+0.4773277
+19.14361
+0.3560452
+18.78914
+0.3345761
 
 
 bily_kriz
 3
 2007
--75.93613
--74.22389
-31.515550
-27.52587
-110.94775
-3.409521
-95.03352
-3.798527
-184.80026
-4.826859
-181.54589
-5.190658
-94.69553
-7.085845
-69.07559
-7.696311
-193.1778
-3.219596
-186.9977
-4.493286
+-7.593613
+-7.422389
+3.1515550
+2.752587
+11.094775
+0.3409521
+9.503352
+0.3798527
+18.480026
+0.4826859
+18.154589
+0.5190658
+9.469553
+0.7085845
+6.907559
+0.7696311
+19.31778
+0.3219596
+18.69977
+0.4493286
 
 
 bily_kriz
 3
 2008
--83.49085
--82.75882
-36.022763
-29.02647
-100.60264
-1.775322
-93.38333
-1.995026
-181.80827
-3.722435
-181.59439
-3.912224
-104.22396
-8.265871
-102.95398
-6.246577
-202.5231
-4.299510
-204.7656
-3.643597
+-8.349085
+-8.275882
+3.6022763
+2.902647
+10.060264
+0.1775322
+9.338333
+0.1995026
+18.180827
+0.3722435
+18.159439
+0.3912224
+10.422396
+0.8265871
+10.295398
+0.6246577
+20.25231
+0.4299510
+20.47656
+0.3643597
 
 
 
@@ -5275,7 +5276,7 @@ 
    SITES
    
 
    A text description can be obtained from SITEDESCRIPTION
    
 
 
-
    ## [1] "The ICOS site Sorø (DK-Sor in the FLUXNET and ICOS data bases) is located in Denmark at an elevation of 40 m.a.s.l.. The climate is warm temperate and fully humid with a mean annual temperature of 9°C and annual precipitation sum of 774 mm during the period 1996-2010. The soil has been classified as an Alfisols/Molisols. Potential natural vegetation is deciduous broad-leaved forest dominated by Fagus sylvatica. Other species occurring in the area are Fraxinus excelsior, Larix decidua, Picea abies, Quercus spp., Acer spp. However, the region is mostly used as cropland. Data on tree DBH are reconstructed from tree ring measurement (Babst et al. 2014) and historical management information for the time period from 1944 to 2010. The mean DBH of this Fagus sylvatica stand was 29 cm in the year 2010. More information about the site can be found in Ladekarl (2001), Pilegaard et al. (2003, 2011), and Wu et al. (2013)."
    
+
    ## [1] "The ICOS site Sorø (DK-Sor in the FLUXNET and ICOS data bases) is located in Denmark at an elevation of 40 m.a.s.l.. The climate is warm temperate and fully humid with a mean annual temperature of 9°C and annual precipitation sum of 774 mm during the period 1996-2010. The soil has been classified as an Alfisols/Molisols. Potential natural vegetation is deciduous broad-leaved forest dominated by Fagus sylvatica. Other species occurring in the area are Fraxinus excelsior, Larix decidua, Picea abies, Quercus spp., Acer spp. However, the region is mostly used as cropland. Data on tree DBH are reconstructed from tree ring measurement (Babst et al. 2014) and historical management information for the time period from 1994 to 2017. The mean DBH of this Fagus sylvatica stand was 41 cm in the year 2017. More information about the site can be found in Ladekarl (2001), Pilegaard et al. (2003, 2011), and Wu et al. (2013)."

    DATASETS

    @@ -5292,7 +5293,7 @@

    collapse

    ##  [1] "record_id"      "site"           "site_id"        "date"          
 ##  [5] "forcingDataset" "day"            "mo"             "year"          
 ##  [9] "tmax_degC"      "tmean_degC"     "tmin_degC"      "p_mm"          
-## [13] "relhum_percent" "airpress_hPa"   "rad_Jcm2day"    "wind_ms"
    +## [13] "relhum_percent" "airpress_hPa" "rad_Jcm2" "wind_ms"

    We recommend to unset collapse when downloading SOIL data because in many cases SOIL is a collection of tables.

    @@ -5329,7 +5330,7 @@

    forcingDataset, forcingCondition

    p_mm relhum_percent airpress_hPa -rad_Jcm2day +rad_Jcm2 wind_ms @@ -5471,7 +5472,7 @@

    forcingDataset, forcingCondition

    p_mm relhum_percent airpress_hPa -rad_Jcm2day +rad_Jcm2 wind_ms @@ -5728,10 +5729,10 @@

    The plotData function

    Normal plotting

    A simple plot call looks like

    -

    +

    Or for TREE data

    -

    Note that the argument automaticPanels defines whether the plot in a panel.

    +

    Note that the argument automaticPanels defines whether to plot in a panel.

     -

    +

    @@ -5802,13 +5803,13 @@

    The queryDB function: parsing your own queries

    The reportDB function

    -

    This function makes possible to create reates a site-by-site report of all avalaible data in the PROFOUND database. The summary is created with a rmarkdown document, which is rendered and saved as a html document. The report provdes an exhaustive description and visualization of the PROFOUND database.

    +

    This function permits creating a site-by-site report of all avalaible data in the PROFOUND database. The summary is created with a rmarkdown document, which is rendered and saved as a html document. The report provides an exhaustive description and visualization of the PROFOUND database.

    The function requires a path where to save the html document. If no path is specified, the working directory will be used as output directory.

    -

    Please note that creating the report it might take several minutes.

    +

    Please note that creating the report might take several minutes.

    -
    -

    Using the databse via sql

    +
    +

    Using the database via sql

    To access the database you can use an SQLite database explorer such as SQLiteStudio. Such software allows to visualize and download data through an interface, as well as writing SQL statements. Further information on SQLite characteristics can be found on the SQLite website. Besides, there are plenty of resources about using SQL like this one

    diff --git a/README.md b/README.md index aee3b75..6a7423d 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # The Profound dataset for checking and benchmarking of dynamic vegetation models -The PROFOUND database is a collection of data for calibrating, validating and benchmarking dynamic vegetation models, created by [Cost Action FP1304 PROFOUND](https://twitter.com/FP1304Profound). The database itself, including document and description of the dasta, is hosted by the Potsdam Institute for Climate Research [http://doi.org/10.5880/PIK.2019.008](http://doi.org/10.5880/PIK.2019.008). You can dowload the database either there, or, via the R pacakge (see below). The source code that was used to create the database is available [here](https://github.com/COST-FP1304-PROFOUND/ProfoundData/tree/master/PROFOUND%20database). +The PROFOUND database is a collection of data for calibrating, validating and benchmarking dynamic vegetation models, created by [Cost Action FP1304 PROFOUND](https://twitter.com/FP1304Profound). The database itself, including documentation and description of the data, is hosted by the Potsdam Institute for Climate Research [http://doi.org/10.5880/PIK.2020.006](http://doi.org/10.5880/PIK.2020.006). You can download the database either there, or, via the R package (see below). The source code that was used to create the database is available [here](https://github.com/COST-FP1304-PROFOUND/ProfoundData/tree/master/PROFOUND%20database). ## Installing the ProfoundData R package @@ -17,7 +17,7 @@ devtools::install_github(repo = "COST-FP1304-PROFOUND/ProfoundData", subdir = "ProfoundData", dependencies = T, build_vignettes = T) ``` -Below the status of the automatic Travis CI tests on the master branch (if this doesn load see [here](https://travis-ci.org/COST-FP1304-PROFOUND/ProfoundData)) +Below the status of the automatic Travis CI tests on the master branch (if this doesn't load see [here](https://travis-ci.org/COST-FP1304-PROFOUND/ProfoundData)) [![Build Status](https://travis-ci.org/COST-FP1304-PROFOUND/ProfoundData.svg?branch=master)](https://travis-ci.org/COST-FP1304-PROFOUND/ProfoundData)