​CARVE: L1 Airborne Forward Looking Infrared Radiance Counts, Alaska, 2013-2015

简介

该数据集提供了 2013 年 4 月至 2015 年 11 月期间 CARVE 飞机上的前视红外（FLIR）热像仪为北极碳库脆弱性实验（CARVE）测量的地球参考辐射计数。FLIR 热像仪记录地表温度图像，同时测量大气中的二氧化碳、甲烷和臭氧浓度。FLIR 热像仪的热图像将用于表征冻融循环特定阶段中永久冻土覆盖的地表。该数据集中包含的测量数据对于理解北极碳循环的变化以及北极永久冻土融化带来的潜在威胁至关重要。这些测量结果是 CARVE 活动所搭载的创新型多仪器遥感有效载荷的一部分。

摘要

Table 1. CARVE file naming convention. Example file name: carve_FLIR_L1A_b23_20130403_000011_20160304004404124.nc

* Data from a single flight is spread across multiple files.

** Files are numbered in order that the data were collected

Table 2. Global metadata attributes for NetCDF files

Data variables

Each file contains 14 geolocation variables and 1 science measurement variable described in Table 3. Metadata attributes for the radiance variable, including polynomial conversion coefficients for converting digital numbers to standard units, are described in Table 4. 

Table 3. Data variables in each netCDF file. Fill value or missing data were set to -999.9 for all variables. 

Table 4. Metadata attributes for the radiance variable in the NetCDF files.

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"
df = pd.read_csv(url, sep="\t")
df
 
leafmap.nasa_data_login()
 
 
results, gdf = leafmap.nasa_data_search(
    short_name="CARVE_L1_Infrared_1428",
    cloud_hosted=True,
    bounding_box=(-168.07, 58.84, -132.24, 71.36),
    temporal=("2013-04-03", "2015-11-13"),
    count=-1,  # use -1 to return all datasets
    return_gdf=True,
)
 
 
gdf.explore()
 
#leafmap.nasa_data_download(results[:5], out_dir="data")