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

78 results

Time (local)	Label
2021-11-13 10:02:18	ga_ls9c_ard_3-2-1_097081_2021-11-13_final.stac-item
2021-12-22 10:49:41	ga_ls9c_ard_3-2-1_105075_2021-12-22_final.stac-item
2022-01-04 10:17:35	ga_ls9c_ard_3-2-1_100072_2022-01-04_final.stac-item
2022-01-05 11:04:02	ga_ls9c_ard_3-2-1_107080_2022-01-05_final.stac-item
2022-01-19 09:39:29	ga_ls9c_ard_3-2-1_093085_2022-01-19_final.stac-item
2022-01-19 11:11:59	ga_ls9c_ard_3-2-1_109069_2022-01-19_final.stac-item
2022-02-15 10:54:11	ga_ls9c_ard_3-2-1_106071_2022-02-15_final.stac-item
2022-02-22 09:28:12	ga_ls9c_ard_3-2-1_091088_2022-02-21_final.stac-item
2022-03-09 10:16:56	ga_ls9c_ard_3-2-1_100071_2022-03-09_final.stac-item
2022-03-11 11:47:03	ga_ls9c_ard_3-2-1_114080_2022-03-11_final.stac-item
2022-03-12 10:49:50	ga_ls9c_ard_3-2-1_105076_2022-03-12_final.stac-item
2022-03-24 09:34:25	ga_ls9c_ard_3-2-1_093073_2022-03-24_final.stac-item
2022-03-28 10:46:33	ga_ls9c_ard_3-2-1_105068_2022-03-28_final.stac-item
2022-04-09 09:33:33	ga_ls9c_ard_3-2-1_093071_2022-04-09_final.stac-item
2022-05-12 10:16:56	ga_ls9c_ard_3-2-1_100072_2022-05-12_final.stac-item
2022-06-05 11:07:53	ga_ls9c_ard_3-2-1_108076_2022-06-05_final.stac-item
2022-06-09 09:06:40	ga_ls9c_ard_3-2-1_088082_2022-06-08_final.stac-item
2022-06-09 10:45:33	ga_ls9c_ard_3-2-1_104082_2022-06-09_final.stac-item
2022-07-30 09:33:41	ga_ls9c_ard_3-2-1_093071_2022-07-30_final.stac-item
2022-07-30 11:16:57	ga_ls9c_ard_3-2-1_109082_2022-07-30_final.stac-item
2022-08-02 10:04:13	ga_ls9c_ard_3-2-1_098070_2022-08-02_final.stac-item
2022-08-08 09:28:00	ga_ls9c_ard_3-2-1_092072_2022-08-07_final.stac-item
2022-08-22 11:19:44	ga_ls9c_ard_3-2-1_110073_2022-08-22_final.stac-item
2022-08-26 09:16:56	ga_ls9c_ard_3-2-1_090075_2022-08-25_final.stac-item
2022-08-30 10:29:06	ga_ls9c_ard_3-2-1_102070_2022-08-30_final.stac-item
2022-09-11 10:53:26	ga_ls9c_ard_3-2-1_106069_2022-09-11_final.stac-item
2022-09-20 09:12:03	ga_ls9c_ard_3-2-1_089078_2022-09-19_final.stac-item
2022-09-20 10:49:44	ga_ls9c_ard_3-2-1_105075_2022-09-20_final.stac-item
2022-09-29 09:07:30	ga_ls9c_ard_3-2-1_088082_2022-09-28_final.stac-item
2022-10-14 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-10-14_final.stac-item
2022-10-28 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-10-28_final.stac-item
2022-11-03 09:37:38	ga_ls9c_ard_3-2-1_093080_2022-11-03_final.stac-item
2022-11-05 09:25:17	ga_ls9c_ard_3-2-1_091080_2022-11-04_final.stac-item
2022-11-08 09:58:37	ga_ls9c_ard_3-2-1_096086_2022-11-08_final.stac-item
2022-11-27 10:28:19	ga_ls9c_ard_3-2-1_101083_2022-11-27_final.stac-item
2022-11-29 10:11:57	ga_ls9c_ard_3-2-1_099073_2022-11-29_final.stac-item
2022-12-15 10:09:59	ga_ls9c_ard_3-2-1_099068_2022-12-15_final.stac-item
2022-12-25 09:14:31	ga_ls9c_ard_3-2-1_089084_2022-12-24_final.stac-item
2022-12-29 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-12-29_final.stac-item
2022-12-29 10:28:18	ga_ls9c_ard_3-2-1_101083_2022-12-29_final.stac-item
2022-12-31 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-12-31_final.stac-item
2023-03-30 10:03:18	ga_ls9c_ard_3-2-1_098068_2023-03-30_final.stac-item
2023-04-15 11:46:52	ga_ls9c_ard_3-2-1_114080_2023-04-15_final.stac-item
2023-04-24 10:01:47	ga_ls9c_ard_3-2-1_097080_2023-04-24_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
2023-05-11 10:45:40	ga_ls9c_ard_3-2-1_104082_2023-05-11_final.stac-item
2023-05-25 09:20:34	ga_ls9c_ard_3-2-1_090086_2023-05-24_final.stac-item
2023-05-31 10:20:46	ga_ls9c_ard_3-2-1_100082_2023-05-31_final.stac-item
2023-06-01 09:27:56	ga_ls9c_ard_3-2-1_091089_2023-05-31_final.stac-item
2023-06-03 10:48:52	ga_ls9c_ard_3-2-1_105075_2023-06-03_final.stac-item
2023-06-21 10:35:10	ga_ls9c_ard_3-2-1_103072_2023-06-21_final.stac-item
2023-08-14 09:56:33	ga_ls9c_ard_3-2-1_097067_2023-08-14_final.stac-item
2023-09-15 09:56:51	ga_ls9c_ard_3-2-1_097067_2023-09-15_final.stac-item
2023-09-21 09:22:33	ga_ls9c_ard_3-2-1_091074_2023-09-20_final.stac-item
2023-09-21 09:27:44	ga_ls9c_ard_3-2-1_091087_2023-09-20_final.stac-item
2023-10-01 10:04:00	ga_ls9c_ard_3-2-1_097085_2023-10-01_final.stac-item
2023-10-15 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-10-15_final.stac-item
2023-10-21 09:34:42	ga_ls9c_ard_3-2-1_093073_2023-10-21_final.stac-item
2023-11-08 11:05:08	ga_ls9c_ard_3-2-1_107083_2023-11-08_final.stac-item
2023-11-09 10:05:07	ga_ls9c_ard_3-2-1_098072_2023-11-09_final.stac-item
2023-11-15 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-11-14_final.stac-item
2023-12-09 10:17:08	ga_ls9c_ard_3-2-1_100071_2023-12-09_final.stac-item
2023-12-19 09:21:02	ga_ls9c_ard_3-2-1_090085_2023-12-18_final.stac-item
2023-12-31 11:20:36	ga_ls9c_ard_3-2-1_110075_2023-12-31_final.stac-item
2024-01-07 11:26:19	ga_ls9c_ard_3-2-1_111074_2024-01-07_final.stac-item
2024-01-12 10:07:37	ga_ls9c_ard_3-2-1_098078_2024-01-12_final.stac-item
2024-01-26 10:17:08	ga_ls9c_ard_3-2-1_100071_2024-01-26_final.stac-item
2024-02-07 09:07:03	ga_ls9c_ard_3-2-1_088081_2024-02-06_final.stac-item
2024-02-09 10:28:47	ga_ls9c_ard_3-2-1_102069_2024-02-09_final.stac-item
2024-02-20 10:12:52	ga_ls9c_ard_3-2-1_099076_2024-02-20_final.stac-item
2024-02-24 09:52:28	ga_ls9c_ard_3-2-1_095087_2024-02-24_final.stac-item
2024-03-06 09:29:15	ga_ls9c_ard_3-2-1_092075_2024-03-05_final.stac-item
2024-03-14 10:18:15	ga_ls9c_ard_3-2-1_100074_2024-03-14_final.stac-item
2024-03-17 10:49:10	ga_ls9c_ard_3-2-1_105074_2024-03-17_final.stac-item
2024-04-16 09:22:21	ga_ls9c_ard_3-2-1_091074_2024-04-15_final.stac-item
2024-05-10 10:13:31	ga_ls9c_ard_3-2-1_099079_2024-05-10_final.stac-item
2024-05-19 11:44:06	ga_ls9c_ard_3-2-1_114074_2024-05-19_nrt.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