LBA-ECO CD-04 CO2 Profiles, km 83 Tower Site, Tapajos National Forest
简介
在巴西帕拉州圣塔伦市塔帕若斯国家森林，83公里长的伐木塔点，测量了高达64米，12个高度的大气二氧化碳浓度剖面。数据收集于2000年6月至2004年3月的三年半期间。红外气体分析仪每48分钟连续测量一次塔上12个高度（距地面0.1、0.35、0.7、1.4、3、6、10.7、20、35、40、50、64米）的二氧化碳浓度。数据以30分钟为间隔报告，并保存在一个逗号分隔的文件中。
摘要
File Contents / Variable Descriptions:
Column # Heading Units/format Description
1 exp_day experiment day (0 = January 1, 2000, 00:00 hours)
2 year yyyy year
3 month mm month
4 day dd day
5 hour hh hour at start of sampling period (GMT:24 hour clock)
6 minute mm minute at start of sampling period (GMT)
7 CO2_10cm ppm atmospheric CO2 concentration at 10 cm height
8 CO2_35cm ppm atmospheric CO2 concentration at 35 cm height
9 CO2_70cm ppm atmospheric CO2 concentration at 70 cm height
10 CO2_1_4m ppm atmospheric CO2 concentration at 1.4 m height
11 CO2_3m ppm atmospheric CO2 concentration at 3 m height
12 CO2_6m ppm atmospheric CO2 concentration at 6 m height
13 CO2_10_7m ppm atmospheric CO2 concentration at 10.7 m height
14 CO2_20m ppm atmospheric CO2 concentration at 20 m height
15 CO2_35m ppm atmospheric CO2 concentration at 35 m height
16 CO2_40m ppm atmospheric CO2 concentration at 40 m height
17 CO2_50m ppm atmospheric CO2 concentration at 50 m height
18 CO2_64m ppm atmospheric CO2 concentration at 64 m height
19 fstor_64m micromoles/m2/s CO2 storage flux below 64 m
This data set is not gap-filled.
Missing data are represented by -999
Site (Region) Westernmost Longitude Easternmost Longitude Northernmost Latitude Southernmost Latitude Geodetic Datum
Para Western (Santarem) - km 83 Logged Forest Tower (Para Western (Santarem)) -54.96889 -54.96889 -3.01806 -3.01806 World Geodetic System, 1984 (WGS-84)
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="CD04_CO2_Profiles_947",
cloud_hosted=True,
bounding_box=(-54.97, -3.02, -54.89, -3.02),
temporal=("2000-07-01", "2004-03-12"),
count=-1, # use -1 to return all datasets
return_gdf=True,
)
gdf.explore()
