ACT-America:美国东部 L2 机载激光雷达遥感柱状平均二氧化碳
ACT-America: L2 Remotely Sensed Column-average CO2 by Airborne Lidar, Eastern USA
简介
该数据集提供了二级(L2)遥感柱状平均二氧化碳(CO2)浓度,这些浓度是在 2016 年夏季、2017 年冬季、2017 年秋季和 2018 年春季为大气碳和输送(ACT-America)项目在美国中部和东部地区开展的空中观测活动中测得的。柱状平均二氧化碳浓度是在 C-130 大力神运输机飞行高度高达 8 公里时,使用多功能光纤激光雷达(MFLL;哈里斯公司)以 0.1 秒的频率测量的。 MFLL 是一组连续波 (CW) 激光雷达仪器,由工作在 1571 nm 的强度调制多频单光束同步检测激光吸收光谱仪 (LAS) 组成,用于测量 CO2 数密度的柱量以及飞机与地面或云顶之间的范围以及表面反射率,以及工作在 1596 nm 的伪随机噪声 (PN) 高度计,用于测量从飞机到散射表面和/或云顶的路径长度。除 2019 年夏季外,所有 ACT-America 季节性活动都配备了 MFLL。完整的飞机飞行信息(插值到 0.1 秒的 CO2 柱报告频率)包括但不限于纬度、经度、高度和姿态。此 2 级 (L2) 产品的处理包括本文档中描述的附加处理和校准程序,用于从 L1 MFLL 数据中检索 CO2 柱。数据用户应该使用此 L2 数据,除非优先考虑不同的 CO2 检索标准。
ACT-America 的总体任务持续了五年,包括覆盖美国中部和东部地区所有四个季节的实地活动。ACT-America 的目标是研究大气中二氧化碳和甲烷的输送和通量。两架仪器飞机平台,即美国宇航局兰利比奇 B-200 空中国王和美国宇航局瓦洛普斯飞行设施的 C-130 大力神,用于收集各种大陆表面和大气条件下的高质量现场测量数据。有时,它们直接飞过轨道碳观测站-2 (OCO-2) 立交桥,以评估 OCO-2 观测高分辨率大气二氧化碳变化的能力。C-130 飞机还配备了主动遥感仪器,用于行星边界层高度探测和柱状温室气体测量。
摘要
Variable name | Units | Description |
---|---|---|
Derived Measurements | ||
Column_CO2 | ppm | CO2 column mole fraction in parts per million (see XCO2 Calculation in Section 5) |
Range_nadir | meters | Range at nadir |
OD_nadir | NA | Optical depth at nadir |
OD_bias_corr | NA | Optical depth at nadir with bias corrections |
Native Measurements | ||
Amplitude_ref_ch1 | count | Channel 1 reference amplitude |
Amplitude_ref_ch2 | count | Channel 2 reference amplitude |
Amplitude_ref_ch3 | count | Channel 3 reference amplitude |
Amplitude_sci_ch1 | count | Channel 1 processed amplitude for the primary scatterer |
Amplitude_sci_ch2 | count | Channel 2 processed amplitude for the primary scatterer |
Amplitude_sci_ch3 | count | Channel 3 processed amplitude for the primary scatterer |
Range_ref_ch1 | meter | Channel 1 reference range |
Range_ref_ch2 | meter | Channel 2 reference range |
Range_ref_ch3 | meter | Channel 3 reference range |
Range_sci_ch1 | meter | Channel 1 processed range for the primary scatterer |
Range_sci_ch2 | meter | Channel 2 processed range for the primary scatterer |
Range_sci_ch3 | meter | Channel 3 processed range for the primary scatterer |
Amplitude_2nd_scatter | count | Amplitude for secondary the scatterer |
Range_2nd_scatter | meter | Range for secondary the scatterer |
Processing Parameters | ||
Range_offset | meter | Range offset |
Calibration_coeff | Zero-path calibration coefficient | |
Ancillary Data * | ||
time | seconds | UTC time in seconds since 2016-01-01 00:00:00 |
Latitude | decimal degrees north | Latitude |
Longitude | decimal degrees east | Longitude |
Mask | Mask flag values indicate if the measured sample had any quality issues. Users can screen data to quickly remove questionable Column_CO2 values. Mask values: “1” indicates a good Column_CO2 value; “0” indicates that the Column_CO2 value may not be of good quality. | |
GPS_Altitude | meter | GPS altitude of aircraft |
Pitch | degree | Pitch angle of aircraft |
Roll | degree | Roll angle of aircraft |
Ground_elevation | meter | Ground elevation |
Wavelength_ch1 | nanometer | Channel 1 (on-line) signal wavelength |
Wavelength_ch2 | nanometer | Channel 2 (off-line) signal wavelength off-short at -50 pm |
Wavelength_ch3 | nanometer | Channel 3 (off-line signal wavelength off-long at +50 pm |
Flags | ||
Data_quality_flag | see Table 2 | Data quality flag |
Cloud_Ground_flag | see Table 3 | Cloud-ground flag |
Flag_2nd_scatter | see Table 4 | Second backscatter flag |
代码
!pip install leafmap
!pip install pandas
!pip install folium
!pip install matplotlib
!pip install mapclassify
import pandas as pd
import leafmap
url = "https://github.com/opengeos/NASA-Earth-Data/raw"
df = pd.read_csv(url, sep="\t")
df
leafmap.nasa_data_login()
results, gdf = leafmap.nasa_data_search(
short_name="ACTAMERICA_MFFLL_1649",
cloud_hosted=True,
bounding_box=(-106.05, 27.23, -71.91, 49.11),
temporal=("2016-05-27", "2018-05-20"),
count=-1, # use -1 to return all datasets
return_gdf=True,
)
gdf.explore()
#leafmap.nasa_data_download(results[:5], out_dir="data")
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