3.4.2. Change detection metrics type B (change_B)
- Purpose: Annual forest cover loss mapping. Specifically designed for low capacity PC (minimal requirement: 8GB RAM, at least 50GB free disk volume). This metric set is designed for annual change detection.
- Interval: Annual (January 1 – December 31).
- 16-day interval data: Two years of data is required (current and preceding).
- Naming convention: Metrics_change_B.xlsx
- Metric generation code: https://glad.umd.edu/gladtools/Tools/compute_metrics_pheno_B.zip
- Classification code parameters: Use keyword “change_B” to specify this metric set.
- Require at least 5GB RAM.
- The metrics dataset size for one tile / one year is 2.2GB.
This metric set is design to allow annual change detection. It is similar to the change_A metric type with a few differences:
- The number of metrics was significantly reduced to accommodate low capacity PC.
- Only two years of data is used limiting model sensitivity to changes that occurred in the preceding year. However, this metric set may still confuse changes that occurred at the end of the growing season of the preceding year with the changes that happened in the corresponding (“current”) year.
The metric methodology is similar to change_A type.
Metric types and naming conversion
The metrics for each tile is stored in a separate folder as a single-band UInt16 bit GeoTIFF files. The generic naming conversion is the following:
YYYY – corresponding year
B – spectral band or index
T –time-series from which the statistics were extracted. “c” represent the current year (time-series C), “p“ stands for the preceding year (time-series P) and “dif” stands for a time-series of per-16-day interval differences between (time-series D). Regression and standard deviation metrics, which are calculated from the entire time-series, does not have this name section.
S – statistic
2018_blue_c_max.tif - The metric represents the value of the normalized surface reflectance of the Landsat blue band during the year 2018.
In addition to spectral metrics, the metric generation software produces a set of technical layers including the number of cloud-free 16-day composites, gap-filling algorithm outputs, and data quality.
The table Metrics_change_B.xlsx has details on the bands, indices, and computed statistics.
The following software should be installed to generate metrics:
- ActivePerl (https://www.activestate.com/products/activeperl/)
- GLAD_1.0 complete package (https://glad.umd.edu/gladtools/Complete_package/GLAD_1.0_master.zip)
- Download all required 16-day composites
- Download and install software
- Make a list of tiles to process (single column, tile names only – see example tiles.txt).
- Use the following command to compute metrics:
> perl C:/GLAD_1.0/metrics_change_B.pl <tile_list> <year> <input folder> <output folder> <threads>
> perl C:/GLAD_1.0/metrics_ change _B.pl tiles.txt 2018 D:/Data D:/Metrics 1
The command parameters are:
Input folder: the folder with 16-day composite data. It should contain tile data in subfolders.
Output folder: will be created by the code, tile data will be recorded into subfolders.
Threads: the number of parallel processes. The parameter should be increased only if:
- A computer has a multi-core processor (e.g., Intel Xeon)
- The RAM can hold several processes simultaneously. Each process will use 5GB RAM. To get the total RAM usage, multiply 5GB by the number of processes.