RFC 3: Temporal Properties

Author: Andreas Janz

Contact: andreas.janz@geo.hu-berlin.de

Started: 2021-12-24

Last modified: 2021-12-26

Status: Proposed


It is proposed to implement functions or methods for reading and writing temporal properties from/to QGIS PAM, while also concidering the existing QgsRasterLayerTemporalProperties layer properties for QgsRasterLayer.

A survey of software (QGIS, GDAL, ENVI, Google Earth Engine) and EO product metadata formats (Landsat, Sentinel-2, EnMAP, DESIS) shows that there is no clear naming convention for temporal properties. We observe two types of temporal annotation: a) specification of a scene center time, and b) specification of a temporal range (start time and end time).

The specification of scene center time may be sufficient for individual images (e.g. a single Landsat scene), but is not suitable for larger area products like daily MODIS composite products, or other derived cloud-free composites using scenes from a temporal range (e.g. a full year).

Thus, we propose to use the more general temporal range concept. Usecases where a center time is sufficient, may just specify the start time.

We further propose to support spectral-temporal timeseries stacks (e.g. a stack of Landsat images, or a stack of cloud-free full-year NDVI composites). This would allow proper plotting of spectral-temporal timeseries profiles, which is currently (v3.9) not well supported in the EnMAP-Box.

API support will be implemented in the enmapboxprocessing.rasterreader.RasterReader class.


Temporal property naming convensions in software and EO product metadata formats are quite diverse.


QGIS has functionality for managing temporal properties (QgsRasterLayerTemporalProperties) of a QgsRasterLayer:

<qgis._core.QgsRasterLayerTemporalProperties object>
<qgis._core.QgsDateTimeRange object>
PyQt5.QtCore.QDateTime(2021, 12, 24, 0, 0, 0, 0)
PyQt5.QtCore.QDateTime(2021, 12, 25, 0, 0, 0, 0)

The GDAL Raster Data Model suggests to specify ACQUISITIONDATETIME as dataset-level IMAGERY-domain metadata:

# see https://gdal.org/user/raster_data_model.html#imagery-domain-remote-sensing
  <Metadata domain="IMAGERY">
    <MDI key="ACQUISITIONDATETIME">2021-12-24T12:30:42.123</MDI>

ENVI files may specify the acquisition time as dataset-level ENVI-domain metadata:

  <Metadata domain="ENVI">
    <MDI key="acquisition_time">2021-12-24T12:30:42.123</MDI>

GeoTiff files may specify the TIFFTAG_DATETIME baseline TIFF tag as dataset-level metadata:

    <MDI key="TIFFTAG_DATETIME">2019:12:12 19:10:18</MDI>

Since some software use the TIFFTAG_DATETIME to store file creation/manipulation time, and EO data provider don’t use it to specify acquisition time, we propose to ignore it.

Google Earth Engine

Google Earth Engine images specify system:time_start and system:time_end properties in milliseconds since Unix Epoch (1970-01-01T00:00:00):

Image MODIS/006/MOD09GA/2012_03_09
        system:time_start: 1331251200000        # 2012-03-09T00:00:00
        system:time_end: 1331337600000          # 2012-03-10T00:00:00
Landsat products

Landsat products specify DATE_ACQUIRED and SCENE_CENTER_TIME properties in the *MTL.txt metadata file:

    DATE_ACQUIRED = 2021-07-24
    SCENE_CENTER_TIME = "09:56:22.1248370Z"
Sentinel-2 products

Sentinel-2 products specify PRODUCT_START_TIME and PRODUCT_STOP_TIME properties in the MTD_MSIL2A.xml metadata file:

<n1:Level-2A_User_Product ...
EnMAP and DESIS products

EnMAP and DESIS products specify startTime and endTime properties in the METADATA.xml metadata file:

<hsi_doc ...>
PRISMA products

PRISMA products specify Product_StartTime and Product_StopTime properties in each HE5 sub-dataset:


The survey shows that there is no clear naming convention for temporal properties. We observe two types of temporal annotation: a) specification of a scene center time, and b) specification of a temporal range (start time and end time).

All formats only take single scene images into account. None of the formats is suitable for specifying temporal properties of a timeseries stack (e.g. a stack of Landsat images, or a stack of cloud-free full-year NDVI composites), where each band may have an individual temporal range.

The here proposed approach will integrate temporal property handling into QGIS PAM management, while honoring well known software format and naming conventions, and available QgsRasterLayerTemporalProperties information. This allows to set/update temporal properties for QgsRasterLayer objects, which is critical for GUI applications. It also takes care of information stored as GDAL PAM.

A key feature is the support for timeseries stacks, that is a prerequisite for proper plotting of spectral-temporal timeseries data, which is not well supported in the EnMAP-Box. We currently (v3.9) only support single content timeseries stacks (e.g. a stack of NDVI bands). where time information is specified as decimal years in the ENVI-domain wavelength item. This quite hacky approach is well known in the ENVI Classic community for creating temporal profile plots.

We propose the following approach for fetching band-specific temporal properties.


Band-wise temporal start time and end time properties are fetched with the following priorisation:

1. Look at QGIS PAM band-level default-domain. This is mainly relevant for GUI applications, where we need to set/update temporal properties using QgsRasterLayer objects:

startTime: QDateTime = layer.customProperty('QGISPAM/band/42//start_time')
endTime = layer.customProperty('QGISPAM/band/42//end_time')
  1. Look at GDAL PAM band-level default-domain:

    startTime = parseDateTimeString(gdalDataset.GetRasterBand(42).GetMetadataItem('start_time'))
    endTime = parseDateTimeString(gdalDataset.GetRasterBand(42).GetMetadataItem('end_time'))

3. Look at GDAL PAM dataset-level IMAGERY-domain. This follows the GDAL Raster Data Model specification, that assumes the ACQUISITIONDATETIME to be set to this location:

centerTime = parseDateTimeString(gdalDataset.GetMetadataItem('ACQUISITIONDATETIME', 'IMAGERY'))

3. Look at GDAL PAM dataset-level ENVI-domain. This follows the behaviour of the ENVI driver, that sets the acquisition time to this location:

centerTime = parseDateTimeString(gdalDataset.GetMetadataItem('acquisition_time', 'ENVI'))

Note that the parseDateTimeString function is assumed to parse timestamps into QDateTime objects. It is proposed to support the following formats:

2021-12-24                  # date
2021-12-24T12:30:42.123...  # date time
1640349042123               # Unix epoche timestamp in milliseconds since 1970-01-01T00:00:00.000

Also note that we don’t support the various sensor product and software naming conventions presented in the survey above. We assume that the acquisition time is properly set to the GDAL PAM dataset-level IMAGERY-domain during product import.

Guide line 1:

If you need to set band-wise temporal properties in a processing algorithm: set it to the GDAL PAM band-level default-domain. This way, i) the information is accessible with the GDAL API, and ii) consecutive band subsetting via gdal.Translate and gdal.BuildVrt can easily copy the band domains to the destination dataset.

Guide line 2:

If you need to set/update metadata in a GUI application: set it to QGIS PAM. This is most flexible and secure. The temporal properties are i) available as custom layer properties, ii) stored in the QGIS project, and iii) can be saved to QML layer style files.

Guide line 3:

Do not update GDAL PAM *.aux.xml file, while the corresponding source is opened as a QgsRasterLayer in QGIS. QGIS will potentially overwrite any changes, when closing the layer.


Technically, we don’t need any new functions or methods, because we fully rely on QGIS PAM and the QgsRasterLayerTemporalProperties.

But, the handling of property keys, and the assurance of fetching priorities, can be tedious and should be encapsulated in util functions or methods. An example implementation is given by the RasterReader class.

To query temporal properties for band 42, we can use:

from enmapboxprocessing.rasterreader import RasterReader

reader = RasterReader(layer)
startTime = reader.startTime(42)
endTime = reader.endTime(42)
centerTime = reader.centerTime(42)  # derives temporal range center time

In case of a standart image, where all bands share the same time range, you may skip the band number:

startTime = reader.startTime()
endTime = reader.endTime()
centerTime = reader.centerTime()

To set temporal properties use:

# for band 42
reader.setStartTime(startTime, 42)
reader.setEndTime(endTime, 42)

# for each band

Find the band whose center time is closest to christmas eve. If multiple bands match, the first is returned.:

bandNo = reader.findCenterTime(QDateTime(2021, 12, 24, 18, 00))

Use temporal properties and spectral properties (see RFC 2) together for a full description of a spectral-temporal timeseries:

for bandNo in range(1, layer.bandCount() + 1):
    startTime, endTime = reader.temporalRange(bandNo)
    centerTime = reader.centerTime(bandNo)
    wavelength = reader.wavelength(bandNo)
    print(startTime, endTime, centerTime, wavelength)