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
2021-11-13 10:03:29	ga_ls9c_ard_3-2-1_097084_2021-11-13_final.stac-item
2021-11-17 09:22:52	ga_ls9c_ard_3-2-1_091076_2021-11-16_final.stac-item
2021-11-23 11:43:05	ga_ls9c_ard_3-2-1_114074_2021-11-23_final.stac-item
2021-12-04 11:00:35	ga_ls9c_ard_3-2-1_107071_2021-12-04_final.stac-item
2021-12-09 09:44:34	ga_ls9c_ard_3-2-1_094082_2021-12-09_final.stac-item
2021-12-09 09:45:22	ga_ls9c_ard_3-2-1_094084_2021-12-09_final.stac-item
2021-12-12 10:14:14	ga_ls9c_ard_3-2-1_099079_2021-12-12_final.stac-item
2021-12-16 09:47:52	ga_ls9c_ard_3-2-1_095075_2021-12-16_final.stac-item
2021-12-16 11:24:46	ga_ls9c_ard_3-2-1_111070_2021-12-16_final.stac-item
2021-12-20 09:26:21	ga_ls9c_ard_3-2-1_091083_2021-12-19_final.stac-item
2021-12-24 10:39:20	ga_ls9c_ard_3-2-1_103080_2021-12-24_final.stac-item
2022-01-01 11:25:10	ga_ls9c_ard_3-2-1_111071_2022-01-01_final.stac-item
2022-01-01 11:25:58	ga_ls9c_ard_3-2-1_111073_2022-01-01_final.stac-item
2022-01-04 10:22:22	ga_ls9c_ard_3-2-1_100084_2022-01-04_final.stac-item
2022-01-10 09:42:04	ga_ls9c_ard_3-2-1_094076_2022-01-10_final.stac-item
2022-01-12 11:11:22	ga_ls9c_ard_3-2-1_108083_2022-01-12_final.stac-item
2022-01-19 09:39:05	ga_ls9c_ard_3-2-1_093084_2022-01-19_final.stac-item
2022-02-07 11:47:17	ga_ls9c_ard_3-2-1_114080_2022-02-07_final.stac-item
2022-02-11 09:46:27	ga_ls9c_ard_3-2-1_094087_2022-02-11_final.stac-item
2022-02-27 09:44:16	ga_ls9c_ard_3-2-1_094082_2022-02-27_final.stac-item
2022-03-03 10:56:00	ga_ls9c_ard_3-2-1_106076_2022-03-03_final.stac-item
2022-03-22 11:26:04	ga_ls9c_ard_3-2-1_111074_2022-03-22_final.stac-item
2022-03-26 09:24:49	ga_ls9c_ard_3-2-1_091080_2022-03-25_final.stac-item
2022-03-29 11:32:36	ga_ls9c_ard_3-2-1_112075_2022-03-29_final.stac-item
2022-04-17 10:25:42	ga_ls9c_ard_3-2-1_101078_2022-04-17_final.stac-item
2022-04-22 10:44:58	ga_ls9c_ard_3-2-1_104080_2022-04-22_final.stac-item
2022-05-06 10:58:05	ga_ls9c_ard_3-2-1_106082_2022-05-06_final.stac-item
2022-05-14 10:09:44	ga_ls9c_ard_3-2-1_098085_2022-05-14_final.stac-item
2022-05-20 11:06:39	ga_ls9c_ard_3-2-1_108073_2022-05-20_final.stac-item
2022-05-20 11:07:27	ga_ls9c_ard_3-2-1_108075_2022-05-20_final.stac-item
2022-05-29 11:04:04	ga_ls9c_ard_3-2-1_107082_2022-05-29_final.stac-item
2022-06-15 10:09:21	ga_ls9c_ard_3-2-1_098084_2022-06-15_final.stac-item
2022-06-27 10:28:45	ga_ls9c_ard_3-2-1_102070_2022-06-27_final.stac-item
2022-07-27 10:45:37	ga_ls9c_ard_3-2-1_104081_2022-07-27_final.stac-item
2022-07-28 11:25:42	ga_ls9c_ard_3-2-1_111073_2022-07-28_final.stac-item
2022-08-06 11:20:25	ga_ls9c_ard_3-2-1_110075_2022-08-06_final.stac-item
2022-08-15 09:38:14	ga_ls9c_ard_3-2-1_093082_2022-08-15_final.stac-item
2022-09-02 11:04:47	ga_ls9c_ard_3-2-1_107082_2022-09-02_final.stac-item
2022-09-25 09:33:48	ga_ls9c_ard_3-2-1_092086_2022-09-25_final.stac-item
2022-10-06 10:50:57	ga_ls9c_ard_3-2-1_105078_2022-10-06_final.stac-item
2022-10-14 10:03:59	ga_ls9c_ard_3-2-1_097084_2022-10-14_final.stac-item
2022-10-24 10:39:30	ga_ls9c_ard_3-2-1_103080_2022-10-24_final.stac-item
2022-10-28 10:11:10	ga_ls9c_ard_3-2-1_099071_2022-10-28_final.stac-item
2022-11-04 10:19:18	ga_ls9c_ard_3-2-1_100076_2022-11-04_final.stac-item
2022-11-05 11:02:58	ga_ls9c_ard_3-2-1_107077_2022-11-05_final.stac-item
2022-11-07 10:52:14	ga_ls9c_ard_3-2-1_105081_2022-11-07_final.stac-item
2022-11-15 11:39:19	ga_ls9c_ard_3-2-1_113075_2022-11-15_final.stac-item
2022-11-22 11:45:05	ga_ls9c_ard_3-2-1_114074_2022-11-22_final.stac-item
2022-11-25 10:39:29	ga_ls9c_ard_3-2-1_103080_2022-11-25_final.stac-item
2022-11-28 11:07:59	ga_ls9c_ard_3-2-1_108074_2022-11-28_final.stac-item
2022-12-03 09:52:24	ga_ls9c_ard_3-2-1_095086_2022-12-03_final.stac-item
2022-12-05 09:34:28	ga_ls9c_ard_3-2-1_093072_2022-12-05_final.stac-item
2022-12-05 09:38:28	ga_ls9c_ard_3-2-1_093082_2022-12-05_final.stac-item
2022-12-07 09:26:07	ga_ls9c_ard_3-2-1_091082_2022-12-06_final.stac-item
2022-12-07 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-12-06_final.stac-item
2022-12-10 09:57:49	ga_ls9c_ard_3-2-1_096084_2022-12-10_final.stac-item
2022-12-14 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-14_final.stac-item
2022-12-14 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-12-14_final.stac-item
2022-12-21 11:18:08	ga_ls9c_ard_3-2-1_109084_2022-12-21_final.stac-item
2023-01-02 10:04:00	ga_ls9c_ard_3-2-1_097084_2023-01-02_final.stac-item
2023-01-05 10:33:43	ga_ls9c_ard_3-2-1_102081_2023-01-05_final.stac-item
2023-01-10 10:50:38	ga_ls9c_ard_3-2-1_105077_2023-01-10_final.stac-item
2023-01-17 09:21:03	ga_ls9c_ard_3-2-1_090085_2023-01-16_final.stac-item
2023-01-29 11:19:56	ga_ls9c_ard_3-2-1_110073_2023-01-29_final.stac-item
2023-02-03 09:58:03	ga_ls9c_ard_3-2-1_097069_2023-02-03_final.stac-item
2023-02-27 10:51:40	ga_ls9c_ard_3-2-1_105080_2023-02-27_final.stac-item
2023-03-03 10:23:44	ga_ls9c_ard_3-2-1_101072_2023-03-03_final.stac-item
2023-03-08 10:46:11	ga_ls9c_ard_3-2-1_104082_2023-03-08_final.stac-item
2023-03-11 11:14:40	ga_ls9c_ard_3-2-1_109076_2023-03-11_final.stac-item
2023-03-17 10:35:12	ga_ls9c_ard_3-2-1_103070_2023-03-17_final.stac-item
2023-04-03 11:23:27	ga_ls9c_ard_3-2-1_110083_2023-04-03_final.stac-item
2023-04-05 09:33:00	ga_ls9c_ard_3-2-1_092085_2023-04-05_final.stac-item
2023-04-14 09:22:20	ga_ls9c_ard_3-2-1_091074_2023-04-13_final.stac-item
2023-04-24 10:00:35	ga_ls9c_ard_3-2-1_097077_2023-04-24_final.stac-item
2023-04-26 09:45:48	ga_ls9c_ard_3-2-1_095071_2023-04-26_final.stac-item
2023-05-05 11:22:45	ga_ls9c_ard_3-2-1_110082_2023-05-05_final.stac-item
2023-05-16 11:02:10	ga_ls9c_ard_3-2-1_107077_2023-05-16_final.stac-item
2023-05-18 10:49:23	ga_ls9c_ard_3-2-1_105076_2023-05-18_final.stac-item
2023-05-21 09:43:45	ga_ls9c_ard_3-2-1_094082_2023-05-21_final.stac-item
2023-05-29 10:27:33	ga_ls9c_ard_3-2-1_102068_2023-05-29_final.stac-item
2023-07-03 09:24:22	ga_ls9c_ard_3-2-1_091080_2023-07-02_final.stac-item
2023-07-04 10:09:15	ga_ls9c_ard_3-2-1_098084_2023-07-04_final.stac-item
2023-07-19 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-07-19_final.stac-item
2023-07-29 10:03:36	ga_ls9c_ard_3-2-1_097085_2023-07-29_final.stac-item
2023-08-01 10:27:46	ga_ls9c_ard_3-2-1_102068_2023-08-01_final.stac-item
2023-08-04 11:04:17	ga_ls9c_ard_3-2-1_107082_2023-08-04_final.stac-item
2023-08-09 11:23:40	ga_ls9c_ard_3-2-1_110084_2023-08-09_final.stac-item
2023-08-13 09:20:28	ga_ls9c_ard_3-2-1_090085_2023-08-12_final.stac-item
2023-10-16 09:20:56	ga_ls9c_ard_3-2-1_090085_2023-10-15_final.stac-item
2023-10-16 10:57:49	ga_ls9c_ard_3-2-1_106080_2023-10-16_final.stac-item
2023-10-19 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-10-19_final.stac-item
2023-10-21 11:14:46	ga_ls9c_ard_3-2-1_109076_2023-10-21_final.stac-item
2023-10-23 09:23:31	ga_ls9c_ard_3-2-1_091076_2023-10-22_final.stac-item
2023-10-25 10:49:38	ga_ls9c_ard_3-2-1_105075_2023-10-25_final.stac-item
2023-11-01 09:19:14	ga_ls9c_ard_3-2-1_090081_2023-10-31_final.stac-item
2023-11-01 10:57:43	ga_ls9c_ard_3-2-1_106080_2023-11-01_final.stac-item
2023-11-17 09:22:29	ga_ls9c_ard_3-2-1_090089_2023-11-16_final.stac-item
2023-11-21 10:33:31	ga_ls9c_ard_3-2-1_102081_2023-11-21_final.stac-item
2023-11-22 11:14:48	ga_ls9c_ard_3-2-1_109076_2023-11-22_final.stac-item
2024-02-16 10:35:41	ga_ls9c_ard_3-2-1_103071_2024-02-16_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