【记录】CALIPSO Lidar Level 1B产品介绍

2023-11-11 15:20

本文主要是介绍【记录】CALIPSO Lidar Level 1B产品介绍,希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!

目录

CALIPSO Quality Statements Lidar Level 1B Profile Products Version Releases: 3.01, 3.02, 3.30

Attenuated Backscatter Profiles

Total Attenuated Backscatter 532

Perpendicular Attenuated Backscatter 532

Attenuated Backscatter 1064

Calibration Coefficients and Uncertainties

Column Reflectance

Geolocation and Altitude Registration

Latitude

Longitude

Lidar Data Altitude

Number Bins Shift

Surface Altitude Shift

Orbit Number

Path Number

Meteorological Data

Time Parameters

Profile Identification

Ancillary Data

Day Night Flag

IGBP Surface Type

Land Water Mask

NSIDC Surface Type

Surface Elevation

CALIPSO Quality Statements Lidar Level 1B Profile Products Version Releases: 2.01, 2.02


CALIPSO Quality Statements Lidar Level 1B Profile Products Version Releases: 3.01, 3.02, 3.30

CALIOP_L1ProfileProducts_3-01-v02.pdf

Attenuated Backscatter Profiles

Total Attenuated Backscatter 532

The total attenuated backscatter at 532 nm,β’532n Section 6.2.2 of the Lidar Level I ATBD (PDF),是主要的激光雷达一级数据产品之一。β’532是是532nm体积后向散射系数和532nm处的双向光学透射的乘积。Lidar Level I ATBD (PDF)第6节详细描述了来自两个组成偏振分量的532nm总衰减后向散射的构造。衰减的反向散射剖面是从校准的(除以校准常数)、距离校正的、激光能量归一化的、基线减去激光雷达返回信号中得到的。

532nm衰减后向散射系数被记录在每个激光脉冲的对应的583个元素的阵列中,对应于由激光雷达数据高度字段定义的恒定高度网格(元数据中Lidar Data Altitudes字段中记录)。(https://blog.csdn.net/wokaowokaowokao12345/article/details/79790675)

为了减少下行链路数据量,对不同的高度范围使用不同的水平和垂直分辨率,如下表所示。

The total attenuated backscatter at 532 nm, β'532 in Section 6.2.2 of the Lidar Level I ATBD (PDF), is one of the primary lidar Level 1 data products. β'532 is the product of the 532 nm volume backscatter coefficient and the two-way optical transmission at 532 nm from the lidar to the sample volume. The construction of the 532 nm total attenuated backscatter from the two constituent polarization components is described in detail in Section 6 of the Lidar Level I ATBD (PDF). The attenuated backscatter profiles are derived from the calibrated (divided by calibration constant), range-corrected, laser energy normalized, baseline subtracted lidar return signal.

The 532 nm attenuated backscatter coefficients are reported for each laser pulse as an array of 583 elements that have been registered to a constant altitude grid defined by the Lidar Data Altitude field.

Note that to reduce the downlink data volume, an on-board averaging scheme is applied using different horizontal and vertical resolutions for different altitude regimes, as shown in the following table.

Uncertainties for the attenuated backscatter are not explicitly reported in the CALIOP Level 1 data products to save data volume, which would otherwise approximately double the Level 1 data volume. If needed, users can compute random errors for the attenuated backscatter products as described in Uncertainties for Attenuated Backscatter (PDF). IDL code for computing the attenuated backscatter uncertainties is contained in IDL Code for Uncertainty Calculations (PDF).

Perpendicular Attenuated Backscatter 532

532nm总衰减后向散射的垂直分量。垂直通道532nm衰减后向散射的轮廓以与532nm总后向散射的轮廓相同的方式记录。反向散射的平行分量的轮廓可以通过从总量中简单地减去垂直分量来获得。

This field reports the perpendicular component of the 532 nm total attenuated backscatter, as described in section 6 of the CALIPSO Lidar Level I ATBD (PDF). Profiles of the perpendicular channel 532 nm attenuated backscatter are reported in the same manner as are profiles of the 532 nm total backscatter. Profiles of the parallel component of the backscatter can be obtained by simple subtraction of the perpendicular component from the total.

Attenuated Backscatter 1064

The attenuated backscatter at 1064 nm, β'1064, is computed according to equation 7.23 in section 7.2 of the Lidar Level I ATBD (PDF). Like β'532, β'1064 is one of the primary lidar Level 1 data products. β'1064 is the product of the 1064 nm volume backscatter coefficient and the two-way optical transmission at 1064 nm from the lidar to the sample volume. Profiles of the 1064 nm attenuated backscatter are reported in the same manner as are profiles of the 532 nm total backscatter. However, the first 34 bins of each profile contain fill values (-9999), because no 1064 nm data is downlinked from the 30.1 - 40 km altitude range.

Calibration Coefficients and Uncertainties

Column Reflectance

Geolocation and Altitude Registration

Latitude

Geodetic latitude, in degrees, of the laser footprint on the Earth's surface.

Longitude

Longitude, in degrees, of the laser footprint on the Earth's surface.

Lidar Data Altitude

这是一个HDF元数据字段,定义激光雷达1级剖面产品注册到的583个距离仓的高度(请参考表1:下行链路数据的不同高度范围的距离分辨率)。

This is an HDF metadata field that defines the altitudes of the 583 range bins (refer to Table 1: Range Resolutions of Different Altitude Ranges for Downlinked Data) to which lidar Level 1 profile products are registered.

Number Bins Shift

Number bins shift contains the number of 30 meter bins the profile specific 30 meter array elements are shifted to match the lowest altitude bin of the fixed 30 meter altitude array. Profile specific altitude arrays are computed as a function of the actual spacecraft offnadir angle, which varies slightly from the commanded spacecraft off-nadir angle. The fixed altitude array is computed using the commanded spacecraft off-nadir angle (0.3 or 3.0 degrees). The profile specific array elements may be shifted up or down.

Surface Altitude Shift

Surface altitude shift contains the altitude difference between the profile specific 30 meter altitude array and the fixed 30 meter altitude array at the array element that includes mean sea level. Profile specific altitude arrays are computed as a function of the actual spacecraft off-nadir angle, which varies slightly from the commanded spacecraft off-nadir angle. The fixed altitude array is computed using the commanded spacecraft off-nadir angle (0.3 or 3.0 degrees). The units are in kilometers and the values may be positive or negative. The difference is calculated as: Surface_Altitude_Shift = altitude (profile specific 30 meter mean sea level bin) - altitude (fixed 30 meter mean sea level bin).

Orbit Number

Orbit Number consists of three HDF metadata fields that define the number of revolutions by the CALIPSO spacecraft around the Earth and is incremented as the spacecraft passes the equator at the ascending node. To maintain consistency between the CALIPSO and CloudSat orbit parameters, the Orbit Number is keyed to the Cloudsat orbit 2121 at 23:00:47 on 2006/09/20. Because the CALIPSO data granules are organized according to day and night conditions, day/night boundaries do not coincide with transition points for defining orbit number. As such, three parameters are needed to describe the orbit number for each granule as:

  • Orbit Number at Granule Start: orbit number at the granule start time
  • Orbit Number at Granule End: orbit number at the granule stop time
  • Orbit Number Change Time: time at which the orbit number changes in the granule

Path Number

Orbit Number Path Number consists of three HDF metadata fields that define an index ranging from 1-233 that references orbits to the Worldwide Reference System (WRS). This global grid system was developed to support scene identification for LandSat imagery. Since the A-Train is maintained to the WRS grid within +/- 10 km, the Path Number provides a convenient index to support data searches, instead of having to define complex latitude and longitude regions along the orbit track. The Path Number is incremented after the maximum latitude in the orbit is realized and changes by a value of 16 between successive orbits. Because the CALIPSO data granules are organized according to day and night conditions, day/night boundaries do not coincide with transition points for defining path number. As such, three parameters are needed to describe the path number for each granule as:

  • Path Number at Granule Start: path number at the granule start time
  • Path Number at Granule End: path number at the granule stop time
  • Path Number Change Time: time at which the path number changes in the granule

Meteorological Data

Time Parameters

Profile Identification

Ancillary Data

Day Night Flag

This field indicates the lighting conditions at an altitude of ~24 km above mean sea level;

0 = day,

1 = night.

IGBP Surface Type

International Geosphere/Biosphere Programme (IGBP) classification of the surface type at the laser footprint. The IGBP surface types reported by CALIPSO are the same as those used in the CERES/SARB surface map.

Land Water Mask

This is an 8-bit integer indicating the surface type at the laser footprint, with

  • 0 = shallow ocean;
  • 1 = land;
  • 2 = coastlines;
  • 3 = shallow inland water;
  • 4 = intermittent water;
  • 5 = deep inland water;
  • 6 = continental ocean;
  • 7 = deep ocean.

NSIDC Surface Type

Snow and ice coverage for the surface at the laser footprint; data obtained from the National Snow and Ice Data Center (NSIDC).

Surface Elevation

这是从GTOPO30数字高程图(DEM)获得的激光足迹的表面高程,以高于当地平均海平面的公里为单位。

This is the surface elevation at the laser footprint, in kilometers above local mean sea level, obtained from the GTOPO30 digital elevation map (DEM).

CALIPSO Quality Statements Lidar Level 1B Profile Products Version Releases: 2.01, 2.02

CALIOP_L1ProfileProducts_2.01.pdf

这篇关于【记录】CALIPSO Lidar Level 1B产品介绍的文章就介绍到这儿,希望我们推荐的文章对编程师们有所帮助!



http://www.chinasem.cn/article/390988

相关文章

性能测试介绍

性能测试是一种测试方法,旨在评估系统、应用程序或组件在现实场景中的性能表现和可靠性。它通常用于衡量系统在不同负载条件下的响应时间、吞吐量、资源利用率、稳定性和可扩展性等关键指标。 为什么要进行性能测试 通过性能测试,可以确定系统是否能够满足预期的性能要求,找出性能瓶颈和潜在的问题,并进行优化和调整。 发现性能瓶颈:性能测试可以帮助发现系统的性能瓶颈,即系统在高负载或高并发情况下可能出现的问题

水位雨量在线监测系统概述及应用介绍

在当今社会,随着科技的飞速发展,各种智能监测系统已成为保障公共安全、促进资源管理和环境保护的重要工具。其中,水位雨量在线监测系统作为自然灾害预警、水资源管理及水利工程运行的关键技术,其重要性不言而喻。 一、水位雨量在线监测系统的基本原理 水位雨量在线监测系统主要由数据采集单元、数据传输网络、数据处理中心及用户终端四大部分构成,形成了一个完整的闭环系统。 数据采集单元:这是系统的“眼睛”,

Hadoop数据压缩使用介绍

一、压缩原则 (1)运算密集型的Job,少用压缩 (2)IO密集型的Job,多用压缩 二、压缩算法比较 三、压缩位置选择 四、压缩参数配置 1)为了支持多种压缩/解压缩算法,Hadoop引入了编码/解码器 2)要在Hadoop中启用压缩,可以配置如下参数

图神经网络模型介绍(1)

我们将图神经网络分为基于谱域的模型和基于空域的模型,并按照发展顺序详解每个类别中的重要模型。 1.1基于谱域的图神经网络         谱域上的图卷积在图学习迈向深度学习的发展历程中起到了关键的作用。本节主要介绍三个具有代表性的谱域图神经网络:谱图卷积网络、切比雪夫网络和图卷积网络。 (1)谱图卷积网络 卷积定理:函数卷积的傅里叶变换是函数傅里叶变换的乘积,即F{f*g}

Node.js学习记录(二)

目录 一、express 1、初识express 2、安装express 3、创建并启动web服务器 4、监听 GET&POST 请求、响应内容给客户端 5、获取URL中携带的查询参数 6、获取URL中动态参数 7、静态资源托管 二、工具nodemon 三、express路由 1、express中路由 2、路由的匹配 3、路由模块化 4、路由模块添加前缀 四、中间件

C++——stack、queue的实现及deque的介绍

目录 1.stack与queue的实现 1.1stack的实现  1.2 queue的实现 2.重温vector、list、stack、queue的介绍 2.1 STL标准库中stack和queue的底层结构  3.deque的简单介绍 3.1为什么选择deque作为stack和queue的底层默认容器  3.2 STL中对stack与queue的模拟实现 ①stack模拟实现

Mysql BLOB类型介绍

BLOB类型的字段用于存储二进制数据 在MySQL中,BLOB类型,包括:TinyBlob、Blob、MediumBlob、LongBlob,这几个类型之间的唯一区别是在存储的大小不同。 TinyBlob 最大 255 Blob 最大 65K MediumBlob 最大 16M LongBlob 最大 4G

记录每次更新到仓库 —— Git 学习笔记 10

记录每次更新到仓库 文章目录 文件的状态三个区域检查当前文件状态跟踪新文件取消跟踪(un-tracking)文件重新跟踪(re-tracking)文件暂存已修改文件忽略某些文件查看已暂存和未暂存的修改提交更新跳过暂存区删除文件移动文件参考资料 咱们接着很多天以前的 取得Git仓库 这篇文章继续说。 文件的状态 不管是通过哪种方法,现在我们已经有了一个仓库,并从这个仓

FreeRTOS-基本介绍和移植STM32

FreeRTOS-基本介绍和STM32移植 一、裸机开发和操作系统开发介绍二、任务调度和任务状态介绍2.1 任务调度2.1.1 抢占式调度2.1.2 时间片调度 2.2 任务状态 三、FreeRTOS源码和移植STM323.1 FreeRTOS源码3.2 FreeRTOS移植STM323.2.1 代码移植3.2.2 时钟中断配置 一、裸机开发和操作系统开发介绍 裸机:前后台系

nginx介绍及常用功能

什么是nginx nginx跟Apache一样,是一个web服务器(网站服务器),通过HTTP协议提供各种网络服务。 Apache:重量级的,不支持高并发的服务器。在Apache上运行数以万计的并发访问,会导致服务器消耗大量内存。操作系统对其进行进程或线程间的切换也消耗了大量的CPU资源,导致HTTP请求的平均响应速度降低。这些都决定了Apache不可能成为高性能WEB服务器  nginx: