Data Upload
Upload Heat Pulse Data
Supported formats: ICT JSON, CSV, Legacy text files (.txt, .csv, .json, .dat)
Clock Drift Correction (Optional)
Correct clock drift assuming the first pulse time was correct (synced at data collection start).
Device Time (at collection end)
What time did the logger show?
Actual Time (at collection end)
What was the actual time?
Trim Incomplete Days (Optional)
Remove first and/or last day if they contain less than 23 hours of data. This is recommended for daily aggregation analyses.
Upload Weather Data (Optional)
CSV format with datetime, temperature, and relative humidity columns
VPD Options
Vapour pressure deficit is calculated automatically when weather data is loaded.
Data Summary
Probe & Wood Configuration
Probe Configuration
Tree Properties
Load Existing Configuration (Optional)
Upload an existing wood properties YAML file to edit.
Configuration Status
Wood Properties Configuration
Primary measurements for wood density and moisture content.
Measure fresh weight immediately after sampling, then oven-dry until weight is stable.
Auto-calculated Densities:
These are calculated automatically from your weight and volume measurements.
Dual Density Measurements:
Measure BOTH densities on the same sample. Volume cancels out!
The wound around the probe affects the measured sapwood area.
Initial Wound Configuration:
Temporal Wound Tracking (Optional):
Dates auto-populate from loaded heat pulse data range (after any trimming). Adjust manually if needed to match original sensor installation dates.
Initial wound = drill bit + 2 × wound addition. Default: 2.0 + 2(0.3) = 2.6 mm
Optional - tree-specific measurements for scaling calculations.
Site coordinates for predawn window calculation.
Physical constants for wood and sap. Defaults from Burgess et al. (2001).
Basic Properties:
Thermal Constants:
Automatically calculated properties based on measurements.
Set acceptable ranges for quality control.
Export Configuration
Download your wood properties configuration as a YAML file. Derived properties will be automatically calculated if measurements are provided.
Probe Configuration Visualisation
Visual representation of probe placement relative to tree anatomy.
Heat Pulse Velocity Calculations
Select Calculation Methods
Select one or more heat pulse velocity calculation methods:
Quality Check Settings
Configure quality control checks applied after calculation:
Illogical Values
Statistical Outliers
These settings control outlier detection sensitivity and data validation. Lower thresholds are more strict, higher are more lenient.
Run Calculations
Calculation Results
Interactive Visualisation - Raw (Uncorrected) HPV
View raw heat pulse velocity calculations to identify outliers, missing data, and quality issues before applying corrections.
Plot Controls
Methods to Display
Sensor Position
Tip: Select only one sensor for faster plot rendering with large datasetsQuality Flags to Display
Time Range
Set the date/time range to display. Updates automatically when you use the range slider.
Display Options
Data Cleaning & Filtering
Interpolation Settings
Creates a straight line between valid points. For single missing points, this is the simple average of before/after values.
Uses weighted average of surrounding valid points. Window size is automatically determined based on gap size. Good for noisy data.
Quality Flags to Interpolate
Filter by Method/Sensor (optional)
Leave all unchecked to apply to all methods/sensors
Heat Pulse Velocity Time Series
Plot Information & Quality Control
Plot Information
Quality Control Summary
Pulse Trace Controls
Selected Pulse
Sensor Position
Calculation Parameters
Vary the parameters to see the effect on the trace and velocities in real time. Defaults match the calculation step.
Live Velocity
Calculation Windows
Show calculation windows used by each method. Heat pulse injection is at t=0.
Pulse Temperature Trace
Spacing Correction
About Changepoint-Based Correction
Note: View Tab 4 (Visualise Raw HPV) first to identify data quality before correction.
This approach detects baseline shifts in daily minimum velocities caused by probe movement (tree swelling/shrinkage).
- Step 1: Detect changepoints that divide data into segments
- Step 2: Apply separate Burgess corrections per segment
- Step 3: Review segment-specific results
Based on Burgess et al. (2001) with PELT changepoint detection
Define Zero-Flow Changepoints
Detects changepoints when BOTH VPD AND sap flow are stable during pre-dawn periods. This dual-criterion approach eliminates false positives from stem refilling and provides higher confidence in baseline detection.
Please upload weather data in Tab 1 and calculate VPD before using this method.
VPD Stability Criteria
Sap Flow Stability Criteria
Detection Settings
Site coordinates for dawn calculation:
Edit full location details in Step 2 → Tree Properties.
Detected Dual-Stable Changepoints:
Changepoints where BOTH VPD and sap flow are stable. Shown as purple dotted lines on plot.Automatically detect baseline shifts in daily minimum velocities using PELT changepoint detection.
Detected Changepoints:
Detected changepoints shown as orange dotted lines on plot. Click[+]
to add individually or use button below to add all.
Add a changepoint at a specific date/time where you know the baseline shifted.
Current Changepoints:
Confirmed changepoints shown as red dashed lines with baselines. Click[X]
to remove.
Step 2: Apply Spacing Correction
Offset Model (Shape)
Gradient: Continuous - linearly interpolates the baseline between points. Anchors Required
Correction Math (Physics)
Linear: Simple empirical subtraction. Robust for large offsets and non-HRM methods.
Daily Minimum Velocities with Changepoints
Tip: Click any date on the plot to populate the Manual tab for adding a changepoint.
Spacing Correction Results
No results yet. Define changepoints and run spacing correction.
Each segment between changepoints gets separate Burgess correction coefficients.
Wound Correction
Apply wound correction for probe reinstallations.
About Wound Correction
Wound correction accounts for the wound created by probe installation, which expands over time as wound tissue forms.
- Initial Installation: First date of data with initial wound size (drill bit + wound tissue)
- Reinstallations: Add dates when probe was removed and reinstalled with measured wound diameter
- Temporal Tracking: Wound diameter is interpolated linearly between dates
Based on Burgess et al. (2001) and ICT International Appendix 23.1
Initial Installation
Wood Properties Configuration:
Drill bit diameter and wound tissue addition are loaded from your wood properties YAML file.Manage Reinstallations
Current Reinstallations:
Click[X]
to remove a reinstallation.
Final Measurement (Growth Rate)
Apply Wound Correction
Temporal Wound Diameter
No temporal wound tracking defined. Set final measurement date and diameter to see wound growth over time.
Wound Correction Results
No results yet. Apply wound correction to see results.
Wound correction coefficients (B) applied over time.
Method Calibration
Calibrate secondary methods to a primary method using linear regression.
About Calibration
Review the diagnostic plots on the right to evaluate calibration quality for each method.
The segmented regression plot shows the breakpoint where methods diverge.
You can use auto-detected thresholds or set manual values per method.
Recommended: Apply AFTER spacing and wound corrections
Configuration
Enhanced regression tests whether a quadratic model better describes the post-breakpoint relationship and adds a third plot when detected.
Threshold Settings
Apply Calibration
Calibration Applied
Calibration Diagnostics - Review Before Applying
Calibration Validation
Verify the quality of method calibration by comparing raw vs. calibrated velocities against the HRM baseline.
Plot Controls
Calibration States
Toggle Raw and Calibrated tracesMethods to Show
HRM is always shown as baselineTime Range
Calibration Validation
Selectable DMA (sDMA) Method Switching
Apply Selectable Dual Method Approach (sDMA) to switch between calibrated methods based on recalculated Peclet numbers and flow conditions.
About sDMA
sDMA (Selectable Dual Method Approach) automatically switches between methods based on flow conditions.
- Step 1: Select secondary method and Péclet threshold
- Step 2: Apply sDMA switching logic
Peclet number determines the theoretical validity limit of HRM. When Pe ≥ threshold, sDMA switches to the secondary method.
sDMA Configuration
Sensor Positions:
Secondary Methods:
Select one or more methods to apply sDMA switching.sDMA will be applied to all selected sensor/method combinations.
sDMA Results
Visualise switching points: HRM below threshold, secondary method above.
No sDMA results yet. Follow the steps on the left to apply sDMA switching.
sDMA Validation - Interactive Time Series
Compare HRM baseline, calibrated secondary methods, and sDMA results in an interactive time series plot.
Plot Controls
Methods to Display
Select specific methods to showSensor Position
Time Range
Select date range to display
Display Options
sDMA Validation
Sap Flux Density (Jv)
Convert corrected heat pulse velocity (Vh) to sap flux density (Jv), with an inline time-series plot.
About Sap Flux Density Conversion
Sap flux density (Jv) represents the volume of sap flowing through a unit area of sapwood per unit time.
- Formula: Jv = Z × Vh
- Z factor: Wood-specific conversion factor calculated from wood properties
- Units: cm³/cm²/hr (equivalent to cm/hr sap velocity)
- Sensors: Conversion applied to all sensor positions (inner + outer) for radial integration
Based on Burgess et al. (2001) after Barrett et al. (1995)
Recommended Workflow:
- Calculate raw heat pulse velocity (Vh)
- Apply spacing correction
- Apply wound correction (optional)
- Convert to sap flux density (Jv) - all sensors
- Integrate across sapwood area → tree-level water use (Step 9)
Conversion Settings
Select Methods:
Flux density will be calculated for all available sensor positions (inner and outer). Both sensors are required for radial integration across the sapwood.
Wood Properties:
Z factor (sap flux conversion factor) is calculated from your wood properties.Heat-Capacity Temperature:
Sap Flux Density Results
No flux density data yet. Click 'Convert to Sap Flux Density (Jv)' to begin.
Methods to Display
Sensor Position
Display
Flux density conversion is complete. Proceed to Step 9: Radial Integration to integrate across the sapwood and calculate whole-tree water use.
Radial Integration — Tree Water Use
Integrate sap flux density across the sapwood area for whole-tree water use (Q), with inline hourly and daily plots.
About Radial Integration
Radial integration scales sap flux density (Jv) across the sapwood area to estimate whole-tree water use (Q).
- Inputs: Flux density at each sensor position (inner + outer)
- Geometry: DBH, sapwood thickness, and bark thickness define the sapwood annulus
- Output: Whole-tree water use Q (L/hr, L/day)
Linear decay after Pausch et al. (2000)
Tree Water Use Integration
Convert to flux density first (Step 8: Sap Flux Density).
Tree Dimensions:
Tree Water Use Results
No tree water use data yet. Convert flux density first (Step 8), then click 'Calculate Tree Water Use (Q)'.
Methods to Display
Display
Hourly (L/hr)
Whole-tree water use integrated across sapwood area. Click-drag to zoom, double-click to reset zoom.Daily (L/day)
Daily totals of tree water use. Grouped bars show multiple methods side-by-side.Tree water use calculation is complete. Proceed to Step 10: Temporal Aggregation for temporal summaries.
Temporal Aggregation
Aggregate flux density data to daily/weekly/hourly summaries for temporal analysis.
Aggregation Settings
Data Type
Temporal Aggregation
Plot Type
Summary Statistics
Aggregated Data
Interactive Visualisation - Corrected HPV
View corrected heat pulse velocity data after applying spacing corrections and/or wound corrections.
Plot Controls
Methods to Display
Sensor Position
Tip: Select only one sensor for faster plot rendering with large datasetsQuality Flags to Display
Time Range
Set the date/time range to display. Updates automatically when you use the range slider.
Display Options
Data Cleaning & Filtering
Interpolation Settings
Creates a straight line between valid points. For single missing points, this is the simple average of before/after values.
Uses weighted average of surrounding valid points. Window size is automatically determined based on gap size. Good for noisy data.
Quality Flags to Interpolate
Filter by Method/Sensor (optional)
Leave all unchecked to apply to all methods/sensors
Heat Pulse Velocity Time Series
Plot Information & Quality Control
Plot Information
Quality Control Summary
Pulse Trace Controls
Selected Pulse
Sensor Position
Calculation Parameters
Vary the parameters to see the effect on the trace and velocities in real time. Defaults match the calculation step.
Live Velocity
Calculation Windows
Show calculation windows used by each method. Heat pulse injection is at t=0.
Pulse Temperature Trace
Probe Configuration Builder
Create or edit probe configuration YAML files for use in sap flow analysis workflows.
Probe Configuration Builder
Create or edit probe configuration YAML files for use in sap flow analysis workflows. Upload an existing YAML to edit, or create a new configuration from scratch.
Load Existing Configuration (Optional)
Upload an existing probe configuration YAML file to edit.
Configuration Status
Probe Configuration
Define the spatial arrangement of thermistor sensors relative to the heater.
Probe Insertion
If probe is not fully inserted (e.g., due to external spacer for thin bark/sapwood), enter spacer thickness.
Physical dimensions and sensor positions.
Select calculation methods compatible with this probe configuration.
Compatible Methods
Recommended Methods
Select the subset of methods recommended for this configuration.
Export Configuration
Wood Properties Builder
Create or edit wood properties YAML files for use in sap flow analysis workflows.
Load Existing Configuration (Optional)
Upload an existing wood properties YAML file to edit.
Configuration Status
Wood Properties Configuration
Primary measurements for wood density and moisture content.
Measure fresh weight immediately after sampling, then oven-dry until weight is stable.
Auto-calculated Densities:
These are calculated automatically from your weight and volume measurements.
Dual Density Measurements:
Measure BOTH densities on the same sample. Volume cancels out!
The wound around the probe affects the measured sapwood area.
Initial Wound Configuration:
Temporal Wound Tracking (Optional):
Dates auto-populate from loaded heat pulse data range (after any trimming). Adjust manually if needed to match original sensor installation dates.
Initial wound = drill bit + 2 × wound addition. Default: 2.0 + 2(0.3) = 2.6 mm
Optional - tree-specific measurements for scaling calculations.
Site coordinates for predawn window calculation.
Physical constants for wood and sap. Defaults from Burgess et al. (2001).
Basic Properties:
Thermal Constants:
Automatically calculated properties based on measurements.
Set acceptable ranges for quality control.
Export Configuration
Download your wood properties configuration as a YAML file. Derived properties will be automatically calculated if measurements are provided.
Reproducible Code Generation
Generate executable R scripts that reproduce your Shiny analysis workflow using sapfluxr functions.
About Code Generation
This tool generates executable R code that reproduces your entire Shiny analysis workflow.
- Purpose: Scientific reproducibility
- Output: Self-contained R script
- Usage: Run in R console or RStudio
- Benefits: Publication-ready, auditable, reusable
Tracked Steps:
Export Options
No analysis steps recorded yet. Perform analysis in other tabs.
Generated R Script
Code will appear here after you perform analysis steps in the app.
Analysis Steps Breakdown
Data Export
Download any dataset produced in the pipeline as CSV or R binary (.rds / .rda) at any time.
Export Options
Download any dataset produced so far. The list of available datasets grows as you complete each step of the pipeline.
- CSV - universal; one file per dataset (zipped if several).
-
RDS
- one R object via
readRDS(); preserves date/time and factor types. -
RDA
- reloads under original names via
load()(the lazydata()style).
Download
Preview
Application Settings
Configure global application settings and plot visual styles.
Plot Visual Settings
Customise the colours, line thickness, and styles for all time-series plots. Changes will be applied globally once saved.
Method Colours
Outer sensors typically use a darker version of the colour, while Inner sensors use a lighter version.Outer:
Inner: