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
2021-11-05 09:34:38	ga_ls9c_ard_3-2-1_093071_2021-11-05_final.stac-item
2021-12-22 09:16:24	ga_ls9c_ard_3-2-1_089089_2021-12-21_final.stac-item
2021-12-28 11:53:05	ga_ls9c_ard_3-2-1_115079_2021-12-28_final.stac-item
2022-01-04 10:19:58	ga_ls9c_ard_3-2-1_100078_2022-01-04_final.stac-item
2022-01-05 09:27:09	ga_ls9c_ard_3-2-1_091085_2022-01-04_final.stac-item
2022-01-23 10:47:41	ga_ls9c_ard_3-2-1_105070_2022-01-23_final.stac-item
2022-02-02 11:24:46	ga_ls9c_ard_3-2-1_111070_2022-02-02_final.stac-item
2022-02-14 11:51:49	ga_ls9c_ard_3-2-1_115076_2022-02-14_final.stac-item
2022-02-16 09:58:09	ga_ls9c_ard_3-2-1_097070_2022-02-16_final.stac-item
2022-02-18 09:46:34	ga_ls9c_ard_3-2-1_095072_2022-02-18_final.stac-item
2022-03-01 09:28:41	ga_ls9c_ard_3-2-1_092074_2022-02-28_final.stac-item
2022-03-09 10:16:56	ga_ls9c_ard_3-2-1_100071_2022-03-09_final.stac-item
2022-04-06 09:06:16	ga_ls9c_ard_3-2-1_088080_2022-04-05_final.stac-item
2022-04-09 11:13:38	ga_ls9c_ard_3-2-1_109074_2022-04-09_final.stac-item
2022-04-21 09:57:44	ga_ls9c_ard_3-2-1_097070_2022-04-21_final.stac-item
2022-04-21 10:00:31	ga_ls9c_ard_3-2-1_097077_2022-04-21_final.stac-item
2022-04-29 09:11:04	ga_ls9c_ard_3-2-1_089077_2022-04-28_final.stac-item
2022-05-11 11:16:34	ga_ls9c_ard_3-2-1_109082_2022-05-11_final.stac-item
2022-05-12 10:18:56	ga_ls9c_ard_3-2-1_100077_2022-05-12_final.stac-item
2022-05-23 11:37:57	ga_ls9c_ard_3-2-1_113074_2022-05-23_final.stac-item
2022-06-08 10:03:29	ga_ls9c_ard_3-2-1_097085_2022-06-08_final.stac-item
2022-06-17 09:57:49	ga_ls9c_ard_3-2-1_096086_2022-06-17_final.stac-item
2022-06-19 09:44:42	ga_ls9c_ard_3-2-1_094084_2022-06-19_final.stac-item
2022-06-19 11:22:48	ga_ls9c_ard_3-2-1_110082_2022-06-19_final.stac-item
2022-06-23 09:16:56	ga_ls9c_ard_3-2-1_090076_2022-06-22_final.stac-item
2022-07-09 09:16:56	ga_ls9c_ard_3-2-1_090076_2022-07-08_final.stac-item
2022-07-12 11:24:18	ga_ls9c_ard_3-2-1_111070_2022-07-12_final.stac-item
2022-07-16 11:01:35	ga_ls9c_ard_3-2-1_107075_2022-07-16_final.stac-item
2022-07-25 10:55:57	ga_ls9c_ard_3-2-1_106076_2022-07-25_final.stac-item
2022-08-01 09:22:57	ga_ls9c_ard_3-2-1_091075_2022-07-31_final.stac-item
2022-08-08 09:33:59	ga_ls9c_ard_3-2-1_092087_2022-08-08_final.stac-item
2022-08-17 09:23:05	ga_ls9c_ard_3-2-1_091075_2022-08-16_final.stac-item
2022-08-19 09:10:44	ga_ls9c_ard_3-2-1_089075_2022-08-18_final.stac-item
2022-08-24 11:07:46	ga_ls9c_ard_3-2-1_108074_2022-08-24_final.stac-item
2022-08-29 09:52:14	ga_ls9c_ard_3-2-1_095086_2022-08-29_final.stac-item
2022-09-02 09:23:07	ga_ls9c_ard_3-2-1_091075_2022-09-01_final.stac-item
2022-09-03 10:03:35	ga_ls9c_ard_3-2-1_098068_2022-09-03_final.stac-item
2022-09-09 09:33:40	ga_ls9c_ard_3-2-1_092086_2022-09-09_final.stac-item
2022-09-14 11:24:46	ga_ls9c_ard_3-2-1_111070_2022-09-14_final.stac-item
2022-09-20 10:52:31	ga_ls9c_ard_3-2-1_105082_2022-09-20_final.stac-item
2022-09-29 09:06:42	ga_ls9c_ard_3-2-1_088080_2022-09-28_final.stac-item
2022-10-06 10:46:57	ga_ls9c_ard_3-2-1_105068_2022-10-06_final.stac-item
2022-10-06 10:49:45	ga_ls9c_ard_3-2-1_105075_2022-10-06_final.stac-item
2022-11-01 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-11-01_final.stac-item
2022-11-21 09:22:57	ga_ls9c_ard_3-2-1_091074_2022-11-20_final.stac-item
2022-11-26 09:41:28	ga_ls9c_ard_3-2-1_094074_2022-11-26_final.stac-item
2022-11-30 09:22:18	ga_ls9c_ard_3-2-1_090088_2022-11-29_final.stac-item
2022-12-08 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-12-08_final.stac-item
2022-12-09 09:12:10	ga_ls9c_ard_3-2-1_089078_2022-12-08_final.stac-item
2022-12-16 09:21:32	ga_ls9c_ard_3-2-1_090086_2022-12-15_final.stac-item
2023-01-12 10:34:40	ga_ls9c_ard_3-2-1_103068_2023-01-12_final.stac-item
2023-01-14 10:27:52	ga_ls9c_ard_3-2-1_101082_2023-01-14_final.stac-item
2023-02-03 09:58:27	ga_ls9c_ard_3-2-1_097070_2023-02-03_final.stac-item
2023-02-07 09:35:21	ga_ls9c_ard_3-2-1_093074_2023-02-07_final.stac-item
2023-02-07 11:12:14	ga_ls9c_ard_3-2-1_109069_2023-02-07_final.stac-item
2023-02-19 09:57:33	ga_ls9c_ard_3-2-1_097068_2023-02-19_final.stac-item
2023-02-26 10:09:36	ga_ls9c_ard_3-2-1_098083_2023-02-26_final.stac-item
2023-02-27 10:50:04	ga_ls9c_ard_3-2-1_105076_2023-02-27_final.stac-item
2023-03-05 10:13:20	ga_ls9c_ard_3-2-1_099077_2023-03-05_final.stac-item
2023-03-15 09:10:16	ga_ls9c_ard_3-2-1_089074_2023-03-14_final.stac-item
2023-03-15 09:10:40	ga_ls9c_ard_3-2-1_089075_2023-03-14_final.stac-item
2023-03-20 11:08:04	ga_ls9c_ard_3-2-1_108075_2023-03-20_final.stac-item
2023-03-21 10:09:15	ga_ls9c_ard_3-2-1_099067_2023-03-21_final.stac-item
2023-03-21 10:10:26	ga_ls9c_ard_3-2-1_099070_2023-03-21_final.stac-item
2023-03-25 11:25:44	ga_ls9c_ard_3-2-1_111073_2023-03-25_final.stac-item
2023-04-08 11:37:35	ga_ls9c_ard_3-2-1_113072_2023-04-08_final.stac-item
2023-04-16 09:11:34	ga_ls9c_ard_3-2-1_089078_2023-04-15_final.stac-item
2023-04-16 10:49:39	ga_ls9c_ard_3-2-1_105076_2023-04-16_final.stac-item
2023-04-18 10:34:06	ga_ls9c_ard_3-2-1_103068_2023-04-18_final.stac-item
2023-04-19 11:19:22	ga_ls9c_ard_3-2-1_110073_2023-04-19_final.stac-item
2023-04-28 09:34:13	ga_ls9c_ard_3-2-1_093073_2023-04-28_final.stac-item
2023-05-17 10:02:33	ga_ls9c_ard_3-2-1_098067_2023-05-17_final.stac-item
2023-05-24 10:15:00	ga_ls9c_ard_3-2-1_099083_2023-05-24_final.stac-item
2023-05-25 09:20:58	ga_ls9c_ard_3-2-1_090087_2023-05-24_final.stac-item
2023-06-14 10:27:24	ga_ls9c_ard_3-2-1_102068_2023-06-14_final.stac-item
2023-06-17 09:26:35	ga_ls9c_ard_3-2-1_091086_2023-06-16_final.stac-item
2023-06-26 09:21:13	ga_ls9c_ard_3-2-1_090088_2023-06-25_final.stac-item
2023-07-11 10:13:30	ga_ls9c_ard_3-2-1_099079_2023-07-11_final.stac-item
2023-09-07 09:11:20	ga_ls9c_ard_3-2-1_089077_2023-09-06_final.stac-item
2023-09-11 10:27:32	ga_ls9c_ard_3-2-1_101082_2023-09-11_final.stac-item
2023-09-12 11:08:00	ga_ls9c_ard_3-2-1_108075_2023-09-12_final.stac-item
2023-10-05 09:34:33	ga_ls9c_ard_3-2-1_093073_2023-10-05_final.stac-item
2023-10-10 09:58:20	ga_ls9c_ard_3-2-1_096086_2023-10-10_final.stac-item
2023-10-15 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-10-15_final.stac-item
2023-10-25 09:12:21	ga_ls9c_ard_3-2-1_089079_2023-10-24_final.stac-item
2023-11-06 09:34:12	ga_ls9c_ard_3-2-1_093072_2023-11-06_final.stac-item
2023-11-07 10:17:04	ga_ls9c_ard_3-2-1_100071_2023-11-07_final.stac-item
2023-11-09 10:03:08	ga_ls9c_ard_3-2-1_098067_2023-11-09_final.stac-item
2023-11-26 10:52:30	ga_ls9c_ard_3-2-1_105082_2023-11-26_final.stac-item
2023-12-05 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-12-05_final.stac-item
2023-12-11 10:07:36	ga_ls9c_ard_3-2-1_098078_2023-12-11_final.stac-item
2023-12-12 10:50:05	ga_ls9c_ard_3-2-1_105076_2023-12-12_final.stac-item
2023-12-17 11:08:40	ga_ls9c_ard_3-2-1_108076_2023-12-17_final.stac-item
2023-12-18 10:10:16	ga_ls9c_ard_3-2-1_099069_2023-12-18_final.stac-item
2023-12-19 09:17:26	ga_ls9c_ard_3-2-1_090076_2023-12-18_final.stac-item
2023-12-28 09:15:14	ga_ls9c_ard_3-2-1_089086_2023-12-27_final.stac-item
2024-01-04 10:55:50	ga_ls9c_ard_3-2-1_106075_2024-01-04_final.stac-item
2024-01-07 09:51:25	ga_ls9c_ard_3-2-1_095084_2024-01-07_final.stac-item
2024-01-19 10:13:47	ga_ls9c_ard_3-2-1_099078_2024-01-19_final.stac-item
2024-02-04 10:16:13	ga_ls9c_ard_3-2-1_099084_2024-02-04_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years