Description Usage Format Details Source References Examples
Data frame containing field data gathered manually within the HiResAlp project 2013-2015. Data on volumetric soil moisture content are combined with topographic, vegetation and land use characteristics derived from different sources. Climatic drivers (preceding precipitation, air temperature, relative humidity, and incoming solar radiation) are measured in representative locations within the LTER site Matsch/Mazia. Land use and soil classifications were gained during intensive field investigations. Remote sensing products, like MODIS vegetation indices, accomplish the data set. The data set is a basis for better understanding of inter-dependencies between soil moisture, topography and atmosperic conditions/weather, land use and soil variability. It serves to investigate soil moisture variablility and stability in time and space. The campaigns aim to validate remote sensing products coming from satellites (e.g. RADARSAT2 or Sentinel images), accomplish high resolution NDVI and thermal maps (drone products) and, moreover, can be useful for calibrating hydrological models or data assimilation approaches (e.g. combining ground sensed data, EO observations and modeling).
1 | data("HiResAlp_MobileCampaigns")
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A data frame with 2443 observations on the following 58 variables.
ID
integer, ID of observation
CampaignType
Faktor, Topology of HiResAlp campaign, RADAR for campaigns considered for EO data calibration/validation (in MUNTATSCHINIG or MATSCH valley, in both regions if not indicated), DRONE for campaigns to accomplish drone field campaign
Datetime variables
date
Factor, Date of observation - format: yyyy-mm-dd
time
character, Time of observation - format: HH:MM:SS
year
integer, Year of observation - format: yyyy
month
integer, Month of observation
day
integer, Day of observation
DOY
integer, Day Of Year
season
character, Season ("DJF","MAM","JJA","SON")
vegPeriod
integer, Vegetation period: 1 - Apr. 1st to Nov. 1st, no Vegetation period: 0
Geographic location of measurement
longitude
numeric, geographical position longitude in degree
latitude
numeric, geographical position latitude in degree
utmx
numeric, geographical position x in meter
utmy
numeric, geographical position y in meter
Data measured with WET sensor
Sensor
character, name of sensor used
SoilMoisture_mean
numeric, Volumetric Soil Moisture (SMC) Mean Value (raw data); for "WET-2 Sensor, Delta-T" aggregation according to sampling strategy of HiResAlp Campaigns; for "HydroSense II, Campbell" aggregation of measurment which are very close (rounding of utm xy data)
SoilMoisture_sd
Volumetric Soil Moisture Standard Deviation (raw data)
SoilTemperature_mean
Soil Temperature Mean Value in degree Celsius; only available for "WET-2 Sensor, Delta-T"
SoilTemperature_sd
Soil Temperature Standard Deviation
Permittivity_mean
Soil Permittivity (Eb) Mean Value in mS/m; measure variable by sensor, used to derive SMC
Permittivity_sd
Soil Permittivity Standard Deviation
SoilMoisture_mean_Processed
numeric, Volumetric Soil Moisture Mean Value (processed data); for "WET-2 Sensor, Delta-T" SMC is calculated by the formula SMC = (sqrt(Eb) - a0) / a1, where the parameters a0 and a1 are soil specific paramters and have been estimated from the "HydroSense II, Campbell" data
Measurement location meta data
Landuse
Factor, Land Use Class derived from field campaign; Classes: 1-irr. Meadow; 2- non irr. Meadow; 3- addandoned Meadow; 4- Pasture; 5- Other; 6- Other: Shrubs; 7- Other: Forest; missing values were filled with Information derived from former vegetation survey in Matsch/Mazia valley - see below.
SoilCoverage
Factor, Soil Coverage Class derived from field campaign [percent]; Classes: 1- Bare Soil, 2- 0.25, 3- 0.50; 4- 0.75; 5- 1
VegetationHeight
Factor, Vegetation Height Class dervived from field campaign [cm]; Classes: 1- >10cm 2- [10cm;25cm]; 3- [25cm;50cm]; 4- [50cm;75cm]; 5- >75cm
Notes
character, Note taken during field campaign
Topographic and hydrological variables derived from digital elevation model
elevation
numeric, Elevation in m a.s.l. from DEM (resolution: 2.5m)
slope
numeric, Slope in degree derived from DEM (resolution: 2.5m)
aspect
numeric, Aspectin degree derived from DEM (resolution: 2.5m)
curvProfile
numeric, profile Curvature derived from DEM (resolution: 2.5m)
curvHorizon
numeric, horizon Curvature derived from DEM (resolution: 2.5m)
elevation
numeric, Elevation in m a.s.l. from DEM (resolution: 2.5m)
slope
numeric, Slope in degree derived from DEM (resolution: 2.5m)
aspect
numeric, Aspectin degree derived from DEM (resolution: 2.5m)
curvProfile
numeric, profile Curvature derived from DEM (resolution: 2.5m)
curvHorizon
numeric, horizon Curvature derived from DEM (resolution: 2.5m)
flowAccum
numeric, Flow Accumulation derived from DEM (resolution: 2.5m), calculation with SAGA GIS: Multiple Flow Direction based on Maximum Downslope Gradient (Qin et al. 2011)
TWI
numeric, Topographic Wetness Index derived from Slope and flowAccum (resolution: 2.5m), calculation with SAGA GIS: ln(a/tan(beta)), where a is the area of the hillslope per unit contour length that drains through any point, and tan(beta) is the local surface topographic slope (delta vertical) / (delta horizontal).
Information derived from vegetation survey 2015 in Matsch/Mazia valley by Michaela Plaikner
StrukturCL
integer, Structure type class
StruturTyp
Factor, Structure Type label
NutzungCL
integer, current Land Use class
AktuelleNutzung
Factor, current Land Use label
VegTypCL
integer, Vegetation type class
VegLab3
Factor, Vegetation Type Label 3; very specific e.g. "Goldhaferwiese"
VegLab2
Factor, Vegetation Type Label 2; e.g. "Sekundaere Rasengesellschaften"
VegLab1
Factor, Vegetation Type Label 1; general e.g. "FETTWEIDEN UND FETTRASEN"
TrittID
integer, Damage by treads (cattle, sheep, ...) class
Trittschaeden
Factor, Damage by treads label
VegShapeID
numeric, ID of shapes in vegetation map; useful for extracting additional information
Information derived from former vegetation survey in Matsch/Mazia valley
landuseID
numeric, Land Use class
landuseLabel
Factor, Land Use type label
Information derived from soil survey in Matsch/Mazia valley in 2011
soilID
numeric, Soil class
soilID
Factor, Soil type
soilID
Factor, Texture class
soilID
Factor, Soil type in GEOtop model
Information on atmospheric condition / weather (base stations P2 - 1500 m a.s.l and B3 - 2000 m a.s.l.)
Temp
Air Temperature in degC, mean value for day of observation
RH
Relative Humidity in percent, mean value for day of observation
SolarRadiation
Incoming Solar Radiation in W/m2, mean value for day of observation
antecedentRain1_B3
Rainfall Amount in mm, 24 hours before measurement, station B3
antecedentRain3_B3
Rainfall Amount in mm, 3 days before measurement, station B3
antecedentRain5_B3
Rainfall Amount in mm, 5 days before measurement, station B3
antecedentRain10_B3
Rainfall Amount in mm, 10 days before measurement, station B3
antecedentRain10_B3
Rainfall Amount in mm, 40 days before measurement, station B3
antecedentRain1_P2
Rainfall Amount in mm, 24 hours before measurement, station P2
antecedentRain3_P2
Rainfall Amount in mm, 3 days before measurement, station P2
antecedentRain5_P2
Rainfall Amount in mm, 5 days before measurement, station P2
antecedentRain10_P2
Rainfall Amount in mm, 10 days before measurement, station P2
antecedentRain10_P2
Rainfall Amount in mm, 40 days before measurement, station P2
Remote Sensing Data (e.g. MODIS, RADARSAT)
radarsat_smc
RADARSAT soil moisture product
MODIS.start.date
Date of first MODIS product retrieved
MODIS.end.date
Date of last MODIS product retrieved
MODIS.NDVI.mean
numeric, MODIS Normalized Diverence (NDVI) mean values, EO map resolution 250m, [0;1]
MODIS_EVI
numeric, MODIS EVI mean value, extension of NDVI, EO map resolution 250m, [0;1]
MODIS data are point wise extracted using the functionalities of MODIStools. In specific the functions MODISSubsets
and MODISsummary
were used for a time period of 14 days araound the observation day. Data sources see below.
MODIS Vegetation Index Products (NDVI and EVI): MOD13Q1 (16-Day L3 Global 250m) https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mod13q1
MODIS Evapotranspiration (ET and LE): MOD16A2 (8-day Global 1km) ftp://ftp.ntsg.umt.edu/pub/MODIS/NTSG_Products/MOD16/
Qin et al. (2011): An approach to computing topographic wetness index based on maximum downslope gradient., Precision Agriculture, 12(1), 32-43. http://doi.org/10.1007/s11119-009-9152-y
Tuck et al. (2014). MODISTools - downloading and processing MODIS remotely sensed data in R. Ecology and Evolution, 4(24), 4658<e2><80><93>4668. http://doi.org/10.1002/ece3.1273
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