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

94 results

Time (local)	Label
2021-12-04 09:24:05	ga_ls9c_ard_3-2-1_091077_2021-12-03_final.stac-item
2021-12-04 09:29:17	ga_ls9c_ard_3-2-1_091090_2021-12-03_final.stac-item
2021-12-07 09:57:45	ga_ls9c_ard_3-2-1_096084_2021-12-07_final.stac-item
2021-12-09 11:21:04	ga_ls9c_ard_3-2-1_110076_2021-12-09_final.stac-item
2021-12-22 10:49:17	ga_ls9c_ard_3-2-1_105074_2021-12-22_final.stac-item
2022-01-19 09:39:29	ga_ls9c_ard_3-2-1_093085_2022-01-19_final.stac-item
2022-01-24 09:58:03	ga_ls9c_ard_3-2-1_096085_2022-01-24_final.stac-item
2022-02-04 11:12:24	ga_ls9c_ard_3-2-1_109070_2022-02-04_final.stac-item
2022-02-15 10:53:47	ga_ls9c_ard_3-2-1_106070_2022-02-15_final.stac-item
2022-03-08 09:34:04	ga_ls9c_ard_3-2-1_093072_2022-03-08_final.stac-item
2022-03-09 10:16:56	ga_ls9c_ard_3-2-1_100071_2022-03-09_final.stac-item
2022-03-27 10:09:40	ga_ls9c_ard_3-2-1_098084_2022-03-27_final.stac-item
2022-04-03 11:51:33	ga_ls9c_ard_3-2-1_115076_2022-04-03_final.stac-item
2022-04-25 11:13:53	ga_ls9c_ard_3-2-1_109075_2022-04-25_final.stac-item
2022-04-28 10:07:29	ga_ls9c_ard_3-2-1_098079_2022-04-28_final.stac-item
2022-05-04 09:33:10	ga_ls9c_ard_3-2-1_092086_2022-05-04_final.stac-item
2022-05-14 10:02:33	ga_ls9c_ard_3-2-1_098067_2022-05-14_final.stac-item
2022-05-18 11:23:02	ga_ls9c_ard_3-2-1_110083_2022-05-18_final.stac-item
2022-05-24 09:06:15	ga_ls9c_ard_3-2-1_088081_2022-05-23_final.stac-item
2022-06-05 09:27:24	ga_ls9c_ard_3-2-1_092072_2022-06-04_final.stac-item
2022-06-08 09:56:42	ga_ls9c_ard_3-2-1_097068_2022-06-08_final.stac-item
2022-07-12 09:46:37	ga_ls9c_ard_3-2-1_095073_2022-07-12_final.stac-item
2022-08-01 10:59:50	ga_ls9c_ard_3-2-1_107070_2022-08-01_final.stac-item
2022-08-07 10:27:36	ga_ls9c_ard_3-2-1_101082_2022-08-07_final.stac-item
2022-08-16 10:17:06	ga_ls9c_ard_3-2-1_100071_2022-08-16_final.stac-item
2022-08-16 10:19:06	ga_ls9c_ard_3-2-1_100076_2022-08-16_final.stac-item
2022-08-19 09:12:20	ga_ls9c_ard_3-2-1_089079_2022-08-18_final.stac-item
2022-08-26 09:22:55	ga_ls9c_ard_3-2-1_090090_2022-08-25_final.stac-item
2022-08-31 09:39:04	ga_ls9c_ard_3-2-1_093084_2022-08-31_final.stac-item
2022-09-11 09:22:56	ga_ls9c_ard_3-2-1_090090_2022-09-10_final.stac-item
2022-09-11 10:53:26	ga_ls9c_ard_3-2-1_106069_2022-09-11_final.stac-item
2022-09-19 10:04:04	ga_ls9c_ard_3-2-1_098069_2022-09-19_final.stac-item
2022-10-25 09:46:16	ga_ls9c_ard_3-2-1_094086_2022-10-25_final.stac-item
2022-11-01 11:24:55	ga_ls9c_ard_3-2-1_111070_2022-11-01_final.stac-item
2022-11-01 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-11-01_final.stac-item
2022-11-09 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-11-09_final.stac-item
2022-11-14 09:21:34	ga_ls9c_ard_3-2-1_090086_2022-11-13_final.stac-item
2022-11-19 09:35:19	ga_ls9c_ard_3-2-1_093074_2022-11-19_final.stac-item
2022-11-19 11:18:11	ga_ls9c_ard_3-2-1_109084_2022-11-19_final.stac-item
2022-11-23 09:12:58	ga_ls9c_ard_3-2-1_089080_2022-11-22_final.stac-item
2022-11-27 10:28:19	ga_ls9c_ard_3-2-1_101083_2022-11-27_final.stac-item
2022-12-11 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-12-11_final.stac-item
2022-12-15 10:11:34	ga_ls9c_ard_3-2-1_099072_2022-12-15_final.stac-item
2022-12-21 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-12-21_final.stac-item
2022-12-29 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-12-29_final.stac-item
2023-01-15 11:05:56	ga_ls9c_ard_3-2-1_108069_2023-01-15_final.stac-item
2023-01-18 09:57:30	ga_ls9c_ard_3-2-1_097068_2023-01-18_final.stac-item
2023-01-18 11:39:11	ga_ls9c_ard_3-2-1_113075_2023-01-18_final.stac-item
2023-02-20 09:07:06	ga_ls9c_ard_3-2-1_088081_2023-02-19_final.stac-item
2023-02-27 09:15:11	ga_ls9c_ard_3-2-1_089086_2023-02-26_final.stac-item
2023-03-15 09:16:16	ga_ls9c_ard_3-2-1_089089_2023-03-14_final.stac-item
2023-03-20 09:33:58	ga_ls9c_ard_3-2-1_092087_2023-03-20_final.stac-item
2023-03-27 11:16:56	ga_ls9c_ard_3-2-1_109082_2023-03-27_final.stac-item
2023-04-28 09:33:49	ga_ls9c_ard_3-2-1_093072_2023-04-28_final.stac-item
2023-05-05 11:23:32	ga_ls9c_ard_3-2-1_110084_2023-05-05_final.stac-item
2023-05-11 09:06:47	ga_ls9c_ard_3-2-1_088082_2023-05-10_final.stac-item
2023-05-19 11:31:02	ga_ls9c_ard_3-2-1_112072_2023-05-19_final.stac-item
2023-06-01 09:22:21	ga_ls9c_ard_3-2-1_091075_2023-05-31_final.stac-item
2023-07-05 09:12:50	ga_ls9c_ard_3-2-1_089082_2023-07-04_final.stac-item
2023-07-21 09:15:42	ga_ls9c_ard_3-2-1_089089_2023-07-20_final.stac-item
2023-07-22 11:31:52	ga_ls9c_ard_3-2-1_112074_2023-07-22_final.stac-item
2023-08-10 10:25:15	ga_ls9c_ard_3-2-1_101077_2023-08-10_final.stac-item
2023-08-19 11:57:10	ga_ls9c_ard_3-2-1_116075_2023-08-19_final.stac-item
2023-08-19 11:57:34	ga_ls9c_ard_3-2-1_116076_2023-08-19_final.stac-item
2023-08-23 09:57:13	ga_ls9c_ard_3-2-1_096084_2023-08-23_final.stac-item
2023-08-28 10:09:26	ga_ls9c_ard_3-2-1_099068_2023-08-28_final.stac-item
2023-09-05 09:22:04	ga_ls9c_ard_3-2-1_091073_2023-09-04_final.stac-item
2023-09-06 11:47:01	ga_ls9c_ard_3-2-1_114080_2023-09-06_final.stac-item
2023-09-21 09:28:56	ga_ls9c_ard_3-2-1_091090_2023-09-20_final.stac-item
2023-09-30 10:55:37	ga_ls9c_ard_3-2-1_106075_2023-09-30_final.stac-item
2023-10-16 09:22:07	ga_ls9c_ard_3-2-1_090088_2023-10-15_final.stac-item
2023-10-16 09:22:55	ga_ls9c_ard_3-2-1_090090_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 09:22:15	ga_ls9c_ard_3-2-1_091073_2023-11-07_final.stac-item
2023-11-13 09:40:00	ga_ls9c_ard_3-2-1_094071_2023-11-13_final.stac-item
2023-11-15 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-11-14_final.stac-item
2023-11-17 10:53:23	ga_ls9c_ard_3-2-1_106069_2023-11-17_final.stac-item
2023-11-22 09:39:30	ga_ls9c_ard_3-2-1_093085_2023-11-22_final.stac-item
2023-11-26 09:11:38	ga_ls9c_ard_3-2-1_089077_2023-11-25_final.stac-item
2023-12-23 10:30:25	ga_ls9c_ard_3-2-1_102073_2023-12-23_final.stac-item
2023-12-26 09:22:25	ga_ls9c_ard_3-2-1_091073_2023-12-25_final.stac-item
2024-01-02 11:06:37	ga_ls9c_ard_3-2-1_108071_2024-01-02_final.stac-item
2024-01-04 10:53:02	ga_ls9c_ard_3-2-1_106068_2024-01-04_final.stac-item
2024-01-07 09:49:26	ga_ls9c_ard_3-2-1_095079_2024-01-07_final.stac-item
2024-01-18 09:29:20	ga_ls9c_ard_3-2-1_092075_2024-01-17_final.stac-item
2024-01-26 10:18:20	ga_ls9c_ard_3-2-1_100074_2024-01-26_final.stac-item
2024-02-07 10:42:44	ga_ls9c_ard_3-2-1_104073_2024-02-07_final.stac-item
2024-03-08 09:22:04	ga_ls9c_ard_3-2-1_090088_2024-03-07_final.stac-item
2024-03-13 09:33:48	ga_ls9c_ard_3-2-1_093071_2024-03-13_final.stac-item
2024-03-24 09:21:36	ga_ls9c_ard_3-2-1_090087_2024-03-23_final.stac-item
2024-04-04 10:34:39	ga_ls9c_ard_3-2-1_103069_2024-04-04_final.stac-item
2024-04-22 10:27:34	ga_ls9c_ard_3-2-1_101083_2024-04-22_final.stac-item
2024-04-30 09:34:03	ga_ls9c_ard_3-2-1_093073_2024-04-30_final.stac-item
2024-05-11 09:16:18	ga_ls9c_ard_3-2-1_090075_2024-05-10_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