Google Earth Engine——多光谱/潘氏图像集包含了从原始12位数据上移的五个16位波段的图像。B、G、R和近红外波段的分辨率约为每像素2米,而Pan波段的分辨率约为0.8米

简介: Google Earth Engine——多光谱/潘氏图像集包含了从原始12位数据上移的五个16位波段的图像。B、G、R和近红外波段的分辨率约为每像素2米,而Pan波段的分辨率约为0.8米

This data from Planet labs Inc. SkySat satellites was collected for the experimental "Skybox for Good Beta" program in 2015, as well as for various crisis response events and a few other projects. The data is available in both a 5-band Multispectral/Pan collection, and a Pansharpened RGB collection.

 

Each image's asset ID contains the acquisition date and time, for example, image s01_20150304T080608Z was acquired on March 4, 2015 at 08:06 Zulu (UTC). For more information, please see the [Planet Imagery Product Specifications] (https://www.planet.com/products/satellite-imagery/files/Planet_Combined_Imagery_Product_Specs_December2017.pdf) and visit the [Planet Imagery and Archive] (Satellite Imagery and Archive | Planet) site.

This Multispectral/Pan collection contains images with five 16-bit bands shifted up from the original 12-bit data. The B, G, R, and Near-IR bands have a resolution of approximately 2m per pixel, while the Pan band is approximately 0.8m resolution (closer to 1m for off-nadir images).


这些数据来自Planet labs Inc. SkySat卫星在2015年为实验性的 "Skybox for Good Beta "项目,以及各种危机应对事件和其他一些项目收集的数据。这些数据有5个波段的多光谱/全景收集,以及一个全景锐化的RGB收集。

每张图片的资产ID包含了采集日期和时间,例如,图片s01_20150304T080608Z是在2015年3月4日08:06 Zulu(UTC)采集的。欲了解更多信息,请参见[行星图像产品规格](https://www.planet.com/products/satellite-imagery/files/Planet_Combined_Imagery_Product_Specs_December2017.pdf),并访问[行星图像和档案](https://www.planet.com/products/planet-imagery/)网站。

这套多光谱/潘氏图像集包含了从原始12位数据上移的五个16位波段的图像。B、G、R和近红外波段的分辨率约为每像素2米,而Pan波段的分辨率约为0.8米(离地图像则接近1米)。

Dataset Availability

2014-07-03T00:00:00 - 2016-12-24T00:00:00

Dataset Provider

Planet Labs Inc.

Collection Snippet

ee.ImageCollection("SKYSAT/GEN-A/PUBLIC/ORTHO/MULTISPECTRAL")

Bands Table

Name Description Min* Max* Resolution Wavelength
B Blue 878 62089 2 meters 450-515nm
G Green 341 62007 2 meters 515-595nm
R Red 107 63393 2 meters 605-695nm
N Near-IR 16 62874 2 meters 740-900nm
P Panchromatic 16 65520 0.8 meters 450-900nm


* = Values are estimated

影像属性:

Name Type Description
catalogID String Unique catalog ID corresponding to a single collection event; same across all three detectors.
collectionEndTime String ISO 8601 collection end time (UTC).
collectionStartTime String ISO 8601 collection start time (UTC).
collectionType String 'Strip', 'Point', 'Area', or 'Path'.
productType String Product type identifying the product level ('Orthorectified Imagery').
productionID String ID of this version of this product, generated by Singer/TileMill.
productionSystemVersion String N/A
resamplingMethod String The method used for interpolated pixel values.
satelliteAzimuthAngleMax Double Maximum satellite azimuth angle over the collection (degrees).
satelliteAzimuthAngleMean Double Mean satellite azimuth angle over the collection (degrees).
satelliteAzimuthAngleMin Double Minimum satellite azimuth angle over the collection (degrees).
satelliteElevationAngleMax Double Maximum satellite elevation angle over the collection (degrees).
satelliteElevationAngleMean Double Mean satellite elevation angle over the collection (degrees).
satelliteElevationAngleMin Double Minimum satellite elevation angle over the collection (degrees).
satelliteName String Unique name identifying the spacecraft.
snaptoAlignmentConfidence Double N/A
snaptoReferenceAssets String N/A
solarAzimuthAngle Double Solar azimuth angle at the time of collection.
solarElevationAngle Double Solar elevation angle at the time of collection.
terrainBlendEpoch Double N/A

代码:

var dataset = ee.ImageCollection('SKYSAT/GEN-A/PUBLIC/ORTHO/MULTISPECTRAL');
var falseColor = dataset.select(['N', 'G', 'B']);
var falseColorVis = {
  min: 200.0,
  max: 6000.0,
};
Map.setCenter(-70.892, 41.6555, 15);
Map.addLayer(falseColor, falseColorVis, 'False Color');


相关文章
|
7月前
|
数据可视化 定位技术 Sentinel
如何用Google Earth Engine快速、大量下载遥感影像数据?
【2月更文挑战第9天】本文介绍在谷歌地球引擎(Google Earth Engine,GEE)中,批量下载指定时间范围、空间范围的遥感影像数据(包括Landsat、Sentinel等)的方法~
2691 1
如何用Google Earth Engine快速、大量下载遥感影像数据?
|
7月前
|
编解码 人工智能 算法
Google Earth Engine——促进森林温室气体报告的全球时间序列数据集
Google Earth Engine——促进森林温室气体报告的全球时间序列数据集
101 0
|
7月前
|
机器学习/深度学习 算法 数据可视化
基于Google Earth Engine云平台构建的多源遥感数据森林地上生物量AGB估算模型含生物量模型应用APP
基于Google Earth Engine云平台构建的多源遥感数据森林地上生物量AGB估算模型含生物量模型应用APP
251 0
|
7月前
|
存储 编解码 数据可视化
Google Earth Engine获取随机抽样点并均匀分布在栅格的不同数值区中
【2月更文挑战第14天】本文介绍在谷歌地球引擎(Google Earth Engine,GEE)中,按照给定的地表分类数据,对每一种不同的地物类型,分别加以全球范围内随机抽样点自动批量选取的方法~
662 1
Google Earth Engine获取随机抽样点并均匀分布在栅格的不同数值区中
|
7月前
|
数据处理
Google Earth Engine(GEE)——sentinel-1数据处理过程中出现错误Dictionary does not contain key: bucketMeans
Google Earth Engine(GEE)——sentinel-1数据处理过程中出现错误Dictionary does not contain key: bucketMeans
124 0
|
7月前
|
编解码 人工智能 数据库
Google Earth Engine(GEE)——全球道路盘查项目全球道路数据库
Google Earth Engine(GEE)——全球道路盘查项目全球道路数据库
165 0
|
7月前
|
编解码
Open Google Earth Engine(OEEL)——matrixUnit(...)中产生常量影像
Open Google Earth Engine(OEEL)——matrixUnit(...)中产生常量影像
88 0
|
7月前
Google Earth Engine(GEE)——导出指定区域的河流和流域范围
Google Earth Engine(GEE)——导出指定区域的河流和流域范围
291 0
|
7月前
|
传感器 编解码 数据处理
Open Google Earth Engine(OEEL)——哨兵1号数据的黑边去除功能附链接和代码
Open Google Earth Engine(OEEL)——哨兵1号数据的黑边去除功能附链接和代码
148 0
|
7月前
Google Earth Engine(GEE)——当加载图表的时候出现错误No features contain non-null values of “system:time_start“.
Google Earth Engine(GEE)——当加载图表的时候出现错误No features contain non-null values of “system:time_start“.
136 0