Search ga_ls9c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2021-12-06 10:52:35	ga_ls9c_ard_3-2-1_105082_2021-12-06_final.stac-item
2021-12-13 09:21:24	ga_ls9c_ard_3-2-1_090086_2021-12-12_final.stac-item
2021-12-21 10:05:38	ga_ls9c_ard_3-2-1_098073_2021-12-21_final.stac-item
2021-12-25 09:41:19	ga_ls9c_ard_3-2-1_094074_2021-12-25_final.stac-item
2022-01-14 09:22:55	ga_ls9c_ard_3-2-1_090090_2022-01-13_final.stac-item
2022-01-19 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-01-19_final.stac-item
2022-01-21 09:25:08	ga_ls9c_ard_3-2-1_091080_2022-01-20_final.stac-item
2022-01-28 11:11:49	ga_ls9c_ard_3-2-1_108084_2022-01-28_final.stac-item
2022-02-15 09:22:53	ga_ls9c_ard_3-2-1_090090_2022-02-14_final.stac-item
2022-03-12 09:13:20	ga_ls9c_ard_3-2-1_089082_2022-03-11_final.stac-item
2022-03-21 09:06:43	ga_ls9c_ard_3-2-1_088081_2022-03-20_final.stac-item
2022-03-24 09:39:12	ga_ls9c_ard_3-2-1_093085_2022-03-24_final.stac-item
2022-03-28 09:13:39	ga_ls9c_ard_3-2-1_089083_2022-03-27_final.stac-item
2022-04-04 10:54:43	ga_ls9c_ard_3-2-1_106073_2022-04-04_final.stac-item
2022-04-11 09:24:46	ga_ls9c_ard_3-2-1_091080_2022-04-10_final.stac-item
2022-04-20 09:20:52	ga_ls9c_ard_3-2-1_090086_2022-04-19_final.stac-item
2022-04-24 10:27:49	ga_ls9c_ard_3-2-1_102068_2022-04-24_final.stac-item
2022-04-27 09:23:50	ga_ls9c_ard_3-2-1_091078_2022-04-26_final.stac-item
2022-08-08 09:32:00	ga_ls9c_ard_3-2-1_092082_2022-08-08_final.stac-item
2022-08-08 11:06:05	ga_ls9c_ard_3-2-1_108070_2022-08-08_final.stac-item
2022-08-09 10:09:41	ga_ls9c_ard_3-2-1_099068_2022-08-09_final.stac-item
2022-08-19 10:52:49	ga_ls9c_ard_3-2-1_105083_2022-08-19_final.stac-item
2022-08-27 10:02:11	ga_ls9c_ard_3-2-1_097080_2022-08-27_final.stac-item
2022-09-06 10:34:52	ga_ls9c_ard_3-2-1_103069_2022-09-06_final.stac-item
2022-09-16 09:35:56	ga_ls9c_ard_3-2-1_093076_2022-09-16_final.stac-item
2022-09-16 09:37:08	ga_ls9c_ard_3-2-1_093079_2022-09-16_final.stac-item
2022-09-18 11:00:05	ga_ls9c_ard_3-2-1_107070_2022-09-18_final.stac-item
2022-09-25 09:34:36	ga_ls9c_ard_3-2-1_092088_2022-09-25_final.stac-item
2022-10-05 11:46:10	ga_ls9c_ard_3-2-1_114077_2022-10-05_final.stac-item
2022-10-11 09:30:15	ga_ls9c_ard_3-2-1_092077_2022-10-11_final.stac-item
2022-10-13 09:19:31	ga_ls9c_ard_3-2-1_090081_2022-10-12_final.stac-item
2022-10-13 10:53:37	ga_ls9c_ard_3-2-1_106069_2022-10-13_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-10-25 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-10-25_final.stac-item
2022-11-03 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-11-03_final.stac-item
2022-11-03 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-11-03_final.stac-item
2022-11-06 11:45:51	ga_ls9c_ard_3-2-1_114076_2022-11-06_final.stac-item
2022-11-10 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-11-10_final.stac-item
2022-11-15 09:58:26	ga_ls9c_ard_3-2-1_097070_2022-11-15_final.stac-item
2022-11-16 09:06:48	ga_ls9c_ard_3-2-1_088080_2022-11-15_final.stac-item
2022-11-17 09:51:16	ga_ls9c_ard_3-2-1_095083_2022-11-17_final.stac-item
2022-11-19 11:13:48	ga_ls9c_ard_3-2-1_109073_2022-11-19_final.stac-item
2022-11-20 10:19:22	ga_ls9c_ard_3-2-1_100076_2022-11-20_final.stac-item
2022-11-22 11:46:41	ga_ls9c_ard_3-2-1_114078_2022-11-22_final.stac-item
2022-11-24 09:57:26	ga_ls9c_ard_3-2-1_096083_2022-11-24_final.stac-item
2022-12-03 09:51:12	ga_ls9c_ard_3-2-1_095083_2022-12-03_final.stac-item
2022-12-03 11:26:06	ga_ls9c_ard_3-2-1_111073_2022-12-03_final.stac-item
2022-12-14 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-14_final.stac-item
2022-12-20 10:32:29	ga_ls9c_ard_3-2-1_102078_2022-12-20_final.stac-item
2022-12-21 11:17:44	ga_ls9c_ard_3-2-1_109083_2022-12-21_final.stac-item
2022-12-22 10:22:30	ga_ls9c_ard_3-2-1_100084_2022-12-22_final.stac-item
2022-12-26 09:57:23	ga_ls9c_ard_3-2-1_096083_2022-12-26_final.stac-item
2022-12-27 10:37:52	ga_ls9c_ard_3-2-1_103076_2022-12-27_final.stac-item
2022-12-28 11:24:19	ga_ls9c_ard_3-2-1_110084_2022-12-28_final.stac-item
2022-12-29 10:25:55	ga_ls9c_ard_3-2-1_101077_2022-12-29_final.stac-item
2023-01-09 10:03:24	ga_ls9c_ard_3-2-1_098067_2023-01-09_final.stac-item
2023-01-19 10:43:32	ga_ls9c_ard_3-2-1_104075_2023-01-19_final.stac-item
2023-01-24 09:25:14	ga_ls9c_ard_3-2-1_091080_2023-01-23_final.stac-item
2023-01-24 11:00:55	ga_ls9c_ard_3-2-1_107072_2023-01-24_final.stac-item
2023-02-02 10:56:04	ga_ls9c_ard_3-2-1_106075_2023-02-02_final.stac-item
2023-02-05 11:25:47	ga_ls9c_ard_3-2-1_111072_2023-02-05_final.stac-item
2023-02-10 10:07:27	ga_ls9c_ard_3-2-1_098077_2023-02-10_final.stac-item
2023-04-22 11:51:27	ga_ls9c_ard_3-2-1_115076_2023-04-22_final.stac-item
2023-04-25 10:40:39	ga_ls9c_ard_3-2-1_104069_2023-04-25_final.stac-item
2023-04-26 09:52:12	ga_ls9c_ard_3-2-1_095087_2023-04-26_final.stac-item
2023-04-28 11:11:30	ga_ls9c_ard_3-2-1_109069_2023-04-28_final.stac-item
2023-04-28 11:13:30	ga_ls9c_ard_3-2-1_109074_2023-04-28_final.stac-item
2023-05-02 10:48:18	ga_ls9c_ard_3-2-1_105073_2023-05-02_final.stac-item
2023-05-28 09:50:16	ga_ls9c_ard_3-2-1_095083_2023-05-28_final.stac-item
2023-05-28 11:24:46	ga_ls9c_ard_3-2-1_111072_2023-05-28_final.stac-item
2023-06-01 09:24:21	ga_ls9c_ard_3-2-1_091080_2023-05-31_final.stac-item
2023-06-27 11:37:48	ga_ls9c_ard_3-2-1_113074_2023-06-27_final.stac-item
2023-06-28 10:41:01	ga_ls9c_ard_3-2-1_104071_2023-06-28_final.stac-item
2023-06-29 09:49:49	ga_ls9c_ard_3-2-1_095082_2023-06-29_final.stac-item
2023-07-20 11:46:37	ga_ls9c_ard_3-2-1_114080_2023-07-20_final.stac-item
2023-07-21 10:51:48	ga_ls9c_ard_3-2-1_105082_2023-07-21_final.stac-item
2023-07-21 10:52:12	ga_ls9c_ard_3-2-1_105083_2023-07-21_final.stac-item
2023-07-25 10:27:27	ga_ls9c_ard_3-2-1_101083_2023-07-25_final.stac-item
2023-07-27 11:52:01	ga_ls9c_ard_3-2-1_115078_2023-07-27_final.stac-item
2023-08-02 09:38:57	ga_ls9c_ard_3-2-1_093085_2023-08-02_final.stac-item
2023-08-04 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-08-04_final.stac-item
2023-08-05 11:46:22	ga_ls9c_ard_3-2-1_114079_2023-08-05_final.stac-item
2023-08-08 10:39:36	ga_ls9c_ard_3-2-1_103082_2023-08-08_final.stac-item
2023-10-16 10:54:37	ga_ls9c_ard_3-2-1_106072_2023-10-16_final.stac-item
2023-10-17 09:59:48	ga_ls9c_ard_3-2-1_097074_2023-10-17_final.stac-item
2023-10-19 09:51:03	ga_ls9c_ard_3-2-1_095083_2023-10-19_final.stac-item
2023-10-23 11:00:01	ga_ls9c_ard_3-2-1_107070_2023-10-23_final.stac-item
2023-10-28 11:21:42	ga_ls9c_ard_3-2-1_110078_2023-10-28_final.stac-item
2023-10-29 10:24:52	ga_ls9c_ard_3-2-1_101075_2023-10-29_final.stac-item
2023-10-31 10:12:53	ga_ls9c_ard_3-2-1_099076_2023-10-31_final.stac-item
2023-11-16 10:12:53	ga_ls9c_ard_3-2-1_099076_2023-11-16_final.stac-item
2023-11-18 11:41:51	ga_ls9c_ard_3-2-1_113082_2023-11-18_final.stac-item
2023-11-19 10:46:14	ga_ls9c_ard_3-2-1_104082_2023-11-19_final.stac-item
2023-11-20 11:24:44	ga_ls9c_ard_3-2-1_111070_2023-11-20_final.stac-item
2023-11-20 11:25:08	ga_ls9c_ard_3-2-1_111071_2023-11-20_final.stac-item
2023-11-21 10:29:55	ga_ls9c_ard_3-2-1_102072_2023-11-21_final.stac-item
2023-11-22 09:35:31	ga_ls9c_ard_3-2-1_093075_2023-11-22_final.stac-item
2023-11-22 11:17:59	ga_ls9c_ard_3-2-1_109084_2023-11-22_final.stac-item
2023-11-24 09:27:34	ga_ls9c_ard_3-2-1_091086_2023-11-23_final.stac-item
2023-11-26 10:52:06	ga_ls9c_ard_3-2-1_105081_2023-11-26_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years