nzd0001-0001 Transect

Te Hiku Community, Far North District, Northland, New Zealand / Aotearoa

The trend fit is not valid due to insufficient data points.

The trend fit is not valid due to a trend value of

Root Mean Square Error (RMSE) is too high.

The trend fit is not valid because the root mean square error (RMSE) of 22.03 is higher than the noise threshold of 4.866 , indicating that the variability in the data is high enough for the trend to be considered unreliable.

The linear regression accounts for none of the variance.

The linear regression accounts for a low proportion of the variance.

The trend fit is only moderately valid.

The trend fit has a high R² score.

The trend fit has an excellent R² score.

Prediction

Transect Data Characteristics

Linear model results for all transects can be downloaded here . This transect contains 192 data points, with 164 no-NaN values. The data spans from August 17, 1999 to July 23, 2025 , and the transect is oriented at 359.04 degrees.

Linear model results for all transects can be downloaded . This transect contains data points, with no-NaN values. The data spans from to .

Data Production

Linear model results for all transects can be downloaded . The data for this transect was not updated during the current processing cycle ( ). The current version of the data is identical to the previous version. The graph below illustrates the data this transect was derived from, and provides links to (1) the input transect data, (2) the full transect regression data, and (3) a link to a secondary publication.crate describing the CoastSat methodology (Analysis).

Data Production

This transect has been updated on August 01, 2025 during the current processing cycle, and was processed using the instrument Batch Process NZ Application . The graph below illustrates the data flow from the previous timeseries to the current timeseries, and provides links to (1) the previous and current timeseries data files, (2) the instrument used for processing, and (3) a link to a secondary publication.crate describing the CoastSat methodology (Analysis).

View, download, and comment on the batch process instrumentation here .

While the data for this transect was updated during the current processing cycle ( ), only empty rows were appended.

Data Appended to Transect

The table below shows the appended data for this transect, described by the processes within the Data-Preprocessing subgraph in Figure X.

dates	nzd0001-0001 (meters)	satname
June 29, 2025	316.27	L8
July 23, 2025	337.51	L9

Transect Data Characteristics

Linear model results for all transects can be downloaded . This transect contains data points, with no-NaN values. The data spans from to , and the transect is oriented at degrees.

Linear model results for all transects can be downloaded . This transect contains data points, with no-NaN values. The data spans from to .

Data Production

This transect has been updated on during the current processing cycle, and was processed using the instrument . The graph below illustrates the data flow from the previous timeseries to the current timeseries, and provides links to (1) the previous and current timeseries data files, (2) the instrument used for processing, and (3) a link to a secondary publication.crate describing the CoastSat methodology (Analysis).

While the data for this transect was updated during the current processing cycle ( ), only empty rows were appended.

Data Appended to Transect

Data Production

This transect's data is from an external dataset, the Pacific Rim Dataset . This version ( ) of the dataset used for this transect was published on by from .

This release is associated with the following research articles(s):

Micropublication Data

This micropublication is part of the CoastSat project, which aims to monitor coastal change using satellite imagery. It is based on this version of the interface.crate , and this version of the CoastSat GitHub repository.

Micropublication publication.crate

This publication.crate is avaliable for download Link null Text here . It contains all data and resources required to reproduce the analysis and results presented in this micropublication.

Threshold Values for Narrative Generation

The following tables summarize the threshold values used to determine the validity of the trend fit and the conditions under which the trend is shown in the narrative content.

Threshold Values

	Threshold	Actual Value	Description
Zero R2 score	< 0	0	R² score below which the regression line fits worse than a flat model
Low R2 score	< 0.3	0	R² score below which the trend fit is not valid
Moderate R2 score	< 0.3	0	R² score below which the trend fit is only moderately valid
High R2 score	< 0.8	0	R² score indicating a strong trend fit
Excellent R2 score	< 1	0	R² score indicating a perfect fit

Trend and Noise Thresholds

	Threshold	Actual Value	Description
Minimum Points for Valid Regression	10	164	Minimum number of non-NaN points for the linear regression to be considered plausible
Trend Threshold	0.01	-0.19	Threshold for trend value to be considered significant
Noise Threshold	4.866	22.03	Threshold for noise, based on the RMSE and trend value
Weak Trend Threshold	0.05	0.19	Threshold for weak trend, in m/year
Strong Trend Threshold	0.1	0.19	Threshold for strong trend, in m/year