Google Earth Engine ——数据全解析专辑（COPERNICUS/S1_GRD）20154至今哨兵-1号合成孔径雷达 (SAR) 数据集

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发布于 2024-02-02 11:12:32

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发布于 2024-02-02 11:12:32

文章被收录于专栏：GEE数据专栏，GEE学习专栏，GEE错误集等专栏GEE数据专栏，GEE学习专栏，GEE错误集等专栏

The Sentinel-1 mission provides data from a dual-polarization C-band Synthetic Aperture Radar (SAR) instrument at 5.405GHz (C band). This collection includes the S1 Ground Range Detected (GRD) scenes, processed using the Sentinel-1 Toolbox to generate a calibrated, ortho-corrected product. The collection is updated daily. New assets are ingested within two days after they become available.

This collection contains all of the GRD scenes. Each scene has one of 3 resolutions (10, 25 or 40 meters), 4 band combinations (corresponding to scene polarization) and 3 instrument modes. Use of the collection in a mosaic context will likely require filtering down to a homogeneous set of bands and parameters. See this article for details of collection use and preprocessing. Each scene contains either 1 or 2 out of 4 possible polarization bands, depending on the instrument's polarization settings. The possible combinations are single band VV or HH, and dual band VV+VH and HH+HV:

VV: single co-polarization, vertical transmit/vertical receive
HH: single co-polarization, horizontal transmit/horizontal receive
VV + VH: dual-band cross-polarization, vertical transmit/horizontal receive
HH + HV: dual-band cross-polarization, horizontal transmit/vertical receive

Each scene also includes an additional 'angle' band that contains the approximate incidence angle from ellipsoid in degrees at every point. This band is generated by interpolating the 'incidenceAngle' property of the 'geolocationGridPoint' gridded field provided with each asset.

Each scene was pre-processed with Sentinel-1 Toolbox using the following steps:

Thermal noise removal
Radiometric calibration
Terrain correction using SRTM 30 or ASTER DEM for areas greater than 60 degrees latitude, where SRTM is not available. The final terrain-corrected values are converted to decibels via log scaling (10*log10(x)).

For more information about these pre-processing steps, please refer to the Sentinel-1 Pre-processing article. For further advice on working with Sentinel-1 imagery, see Guido Lemoine's tutorial on SAR basics and Mort Canty's tutorial on SAR change detection.

This collection is computed on-the-fly. If you want to use the underlying collection with raw power values (which is updated faster), see COPERNICUS/S1_GRD_FLOAT.

Sentinel-1 任务提供来自双极化 C 波段合成孔径雷达 (SAR) 仪器的数据，频率为 5.405GHz（C 波段）。该集合包括 S1 地面范围检测 (GRD) 场景，使用 Sentinel-1 工具箱处理以生成校准的正射校正产品。该系列每天更新。新资产在可用后的两天内被摄取。

此集合包含所有 GRD 场景。每个场景具有 3 种分辨率（10、25 或 40 米）、4 种波段组合（对应于场景极化）和 3 种仪器模式之一。在镶嵌上下文中使用集合可能需要过滤到一组同质的波段和参数。有关集合使用和预处理的详细信息，请参阅本文。每个场景包含 4 个可能的极化波段中的 1 个或 2 个，具体取决于仪器的极化设置。可能的组合是单频段 VV 或 HH，以及双频段 VV+VH 和 HH+HV：

VV：单共极化，垂直发射/垂直接收 HH：单共极化，水平发射/水平接收 VV + VH：双频交叉极化，垂直发射/水平接收 HH + HV：双频交叉极化，水平发射/垂直接收每个场景还包括一个附加的“角度”带，其中包含从椭球每个点的近似入射角（以度为单位）。该波段是通过插入每个资产提供的“geolocationGridPoint”网格字段的“incidenceAngle”属性来生成的。

每个场景都使用 Sentinel-1 Toolbox 进行预处理，步骤如下：

热噪声去除辐射校准使用 SRTM 30 或 ASTER DEM 对纬度大于 60 度的区域进行地形校正，其中 SRTM 不可用。最终的地形校正值通过对数缩放 (10*log10(x)) 转换为分贝。有关这些预处理步骤的更多信息，请参阅 Sentinel-1 预处理文章。有关使用 Sentinel-1 影像的进一步建议，请参阅 Guido Lemoine 的 SAR 基础教程和 Mort Canty 的 SAR 变化检测教程。

该集合是即时计算的。如果要使用具有原始功率值（更新速度更快）的基础集合，请参阅 COPERNICUS/S1_GRD_FLOAT。

Dataset Availability

2014-10-03T00:00:00 - 2021-09-04T00:00:00

Dataset Provider

European Union/ESA/Copernicus

Collection Snippet

ee.ImageCollection("COPERNICUS/S1_GRD")

Bands Table

Name	Description	Min*	Max*	Resolution	Units
HH	Single co-polarization, horizontal transmit/horizontal receive	-50	1	10 meters
HV	Dual-band cross-polarization, horizontal transmit/vertical receive	-50	1	10 meters
VV	Single co-polarization, vertical transmit/vertical receive	-50	1	10 meters
VH	Dual-band cross-polarization, vertical transmit/horizontal receive	-50	1	10 meters
angle	Approximate incidence angle from ellipsoid	0	90	-1 meters	Degrees

* = Values are estimated

影像属性：

Name	Type	Description
GRD_Post_Processing_facility_country	String	Name of the country where the facility is located. This element is configurable within the IPF.
GRD_Post_Processing_facility_name	String	Name of the facility where the processing step was performed. This element is configurable within the IPF.
GRD_Post_Processing_facility_organisation	String	Name of the organisation responsible for the facility. This element is configurable within the IPF.
GRD_Post_Processing_facility_site	String	Geographical location of the facility. This element is configurable within the IPF.
GRD_Post_Processing_software_name	String	Name of the software.
GRD_Post_Processing_software_version	String	Software version identification.
GRD_Post_Processing_start	Double	Processing start time.
GRD_Post_Processing_stop	Double	Processing stop time.
SLC_Processing_facility_country	String	Name of the country where the facility is located. This element is configurable within the IPF.
SLC_Processing_facility_name	String	Name of the facility where the processing step was performed. This element is configurable within the IPF.
SLC_Processing_facility_organisation	String	Name of the organisation responsible for the facility. This element is configurable within the IPF.
SLC_Processing_facility_site	String	Geographical location of the facility. This element is configurable within the IPF.
SLC_Processing_software_name	String	Name of the software.
SLC_Processing_software_version	String	Software version identification.
SLC_Processing_start	Double	Processing start time.
SLC_Processing_stop	Double	Processing stop time.
S1TBX_Calibration_Operator_version	String	Sentinel-1 Toolbox calibration tool version.
S1TBX_SAR_Processing_version	String	Sentinel-1 Toolbox SAR processing tool version.
SNAP_Graph_Processing_Framework_GPF_version	String	Sentinel Application Platform (SNAP) version.
startTimeANX	Double	Sensing start time of the input data relative to the ascending node crossing. This is a count of the time elapsed since the orbit ascending node crossing [ms].
stopTimeANX	Double	Sensing stop time of the input data relative to the ascending node crossing. This is a count of the time elapsed since the orbit ascending node crossing [ms].
nssdcIdentifier	String	Uniquely identifies the mission according to standards defined by the World Data Center for Satellite Information (WDC-SI), available [here](https://nssdc.gsfc.nasa.gov/nmc/SpacecraftQuery.jsp).
familyName	String	The full mission name. E.g. “SENTINEL-1”
platform_number	String	The alphanumeric identifier of the platform within the mission.
instrument	String	Information related to the instrument on the platform to which acquired the data.
instrumentMode	String	IW ([Interferometric Wide Swath](https://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/interferometric-wide-swath)), EW ([Extra Wide Swath](https://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/extra-wide-swath)) or SM ([Strip Map](https://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/stripmap))
instrumentSwath	String	List of the swaths contained within a product. Most products will contain only one swath, except for TOPS SLC products which include 3 or 5 swaths.
orbitNumber_start	Double	Absolute orbit number of the oldest line within the image data.
orbitNumber_stop	Double	Absolute orbit number of the most recent line within the image data.
relativeOrbitNumber_start	Double	Relative orbit number of the oldest line within the image data.
relativeOrbitNumber_stop	Double	Relative orbit number of the most recent line within the image data.
cycleNumber	Double	Absolute sequence number of the mission cycle to which the oldest image data applies.
phaseIdentifier	Double	Id of the mission phase to which the oldest image data applies.
orbitProperties_pass	String	Direction of the orbit ('ASCENDING' or 'DESCENDING') for the oldest image data in the product (the start of the product).
orbitProperties_ascendingNodeTime	Double	UTC time of the ascending node of the orbit. This element is present for all products except ASAR L2 OCN products which are generated from an ASAR L1 input.
resolution	String	H for high or M for medium.
resolution_meters	Double	Resolution in meters.
instrumentConfigurationID	Double	The instrument configuration ID (Radar database ID) for this data.
missionDataTakeID	Double	Unique ID of the datatake within the mission.
transmitterReceiverPolarisation	Double	Transmit/Receive polarisation for the data. There is one element for each Tx/Rx combination: ['VV'], ['HH'], ['VV', 'VH'], or ['HH', 'HV'].
productClass	String	Output product class “A” for Annotation or “S” for Standard.
productClassDescription	String	Textual description of the output product class.
productComposition	String	The composition type of this product: “Individual”, “Slice” or “Assembled”.
productType	String	The product type (correction level) of this product.
productTimelinessCategory	String	Describes the required timeliness of the processing. One of: NRT-10m, NRT-1h, NRT-3h, Fast-24h, Off-line, or Reprocessing
sliceProductFlag	String	True if this is a slice from a larger product or false if this is a complete product.
segmentStartTime	Double	Sensing start time of the segment to which this slice belongs. This field is only present if sliceProductFlag = true.
sliceNumber	Double	Absolute slice number of this slice starting at 1. This field is only present if sliceProductFlag = true.
totalSlices	Double	Total number of slices in the complete data take. This field is only present if sliceProductFlag = true.

代码：

var imgVV = ee.ImageCollection('COPERNICUS/S1_GRD')
        .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VV'))
        .filter(ee.Filter.eq('instrumentMode', 'IW'))
        .select('VV')
        .map(function(image) {
          var edge = image.lt(-30.0);
          var maskedImage = image.mask().and(edge.not());
          return image.updateMask(maskedImage);
        });

var desc = imgVV.filter(ee.Filter.eq('orbitProperties_pass', 'DESCENDING'));
var asc = imgVV.filter(ee.Filter.eq('orbitProperties_pass', 'ASCENDING'));

var spring = ee.Filter.date('2015-03-01', '2015-04-20');
var lateSpring = ee.Filter.date('2015-04-21', '2015-06-10');
var summer = ee.Filter.date('2015-06-11', '2015-08-31');

var descChange = ee.Image.cat(
        desc.filter(spring).mean(),
        desc.filter(lateSpring).mean(),
        desc.filter(summer).mean());

var ascChange = ee.Image.cat(
        asc.filter(spring).mean(),
        asc.filter(lateSpring).mean(),
        asc.filter(summer).mean());

Map.setCenter(5.2013, 47.3277, 12);
Map.addLayer(ascChange, {min: -25, max: 5}, 'Multi-T Mean ASC', true);
Map.addLayer(descChange, {min: -25, max: 5}, 'Multi-T Mean DESC', true);

影像