Google Earth Engine(GEE)—— 全球生态系统动态调查(GEDI)综合数据集(高程、森林覆盖、城市占比)

The Global Ecosystem Dynamics Investigation (GEDI) mission aims to characterize ecosystem structure and dynamics to enable radically improved quantification and understanding of the Earth's carbon cycle and biodiversity. The GEDI instrument, attached to the International Space Station (ISS), collects data globally between 51.6° N and 51.6° S latitudes at the highest resolution and densest sampling of the 3-dimensional structure of the Earth.

GEDI's Level 2A Geolocated Elevation and Height Metrics Product (GEDI02_A) is primarily composed of 100 Relative Height (RH) metrics, which collectively describe the waveform collected by GEDI.

The original GEDI02_A product is a table of point with a spatial resolution (average footprint) of 25 meters. The dataset LARSE/GEDI/GEDI02_A_002_MONTHLY is a raster version of the original GEDI02_A product. The raster images are organized as monthly composites of individual orbits in the corresponding month. Only root-level RH values and their associated quality flags and metadata are preserved as raster bands. Each GEDI02_A_002 raster has 136 bands.

See User Guide for more information.

全球生态系统动态调查(GEDI)任务的目的是描述生态系统的结构和动态,以便从根本上改善对地球碳循环和生物多样性的量化和理解。附属于国际空间站(ISS)的GEDI仪器在全球范围内收集北纬51.6°和南纬51.6°之间的数据,对地球的三维结构进行最高分辨率和最密集的采样。

GEDI的2A级地理位置海拔和高度指标产品(GEDI02_A)主要由100个相对高度(RH)指标组成,它们共同描述了GEDI收集的波形。

原始的GEDI02_A产品是一个点的表格,空间分辨率(平均足迹)为25米。数据集LARSE/GEDI/GEDI02_A_002_MONTHLY是原始GEDI02_A产品的栅格版本。光栅图像被组织为相应月份的单个轨道的月度合成。只有根级相对湿度值及其相关的质量标志和元数据被保留为栅格带。每个GEDI02_A_002栅格有136个波段。

 GEDI L2A Canopy Top Height (Version 2)

Dataset Availability

2019-03-25T00:00:00Z - 2021-09-01T00:00:00

Dataset Provider

NASA GEDI mission, accessed through the USGS LP DAAC Rasterization: Google and USFS Laboratory for Applications of Remote Sensing in Ecology (LARSE)

Earth Engine Snippet

ee.ImageCollection("LARSE/GEDI/GEDI02_A_002_MONTHLY") open_in_new

波段:

Resolution
25 meters

Bands

Name Description
beam

Beam identifier

degrade_flag

Flag indicating degraded state of pointing and/or positioning information.

  • 3X - ADF CHU solution unavailable (ST-2)
  • 4X - Platform attitude
  • 5X - Poor solution (filter covariance large)
  • 6X - Data outage (platform attitude gap also)
  • 7X - ST 1+2 unavailable (similar boresight FOV)
  • 8X - ST 1+2+3 unavailable
  • 9X - ST 1+2+3 and ISS unavailable
  • X1 - Maneuver
  • X2 - GPS data gap
  • X3 - ST blinding
  • X4 - Other
  • X5 - GPS receiver clock drift
  • X6 - Maneuver & GPS receiver clock drift
  • X7 - GPS data gap & GPS receiver clock drift
  • X8 - ST blinding & GPS receiver clock drift
  • X9 - Other & GPS receiver clock drift
delta_time

Time delta since Jan 1 00:00 2018

digital_elevation_model

TanDEM-X elevation at GEDI footprint location

digital_elevation_model_srtm

STRM elevation at GEDI footprint location

elev_highestreturn

Elevation of highest detected return relative to reference ellipsoid

elev_lowestmode

Elevation of center of lowest mode relative to reference ellipsoid

elevation_bias_flag

Elevations potentially affected by 4bin (~60 cm) ranging error

landsat_treecover

Tree cover in the year 2010, defined as canopy closure for all vegetation taller than 5 m in height as a percentage per output grid cell

landsat_water_persistence

Percent UMD GLAD Landsat observations with classified surface water

lat_highestreturn

Latitude of highest detected return

leaf_off_doy

GEDI 1 km EASE 2.0 grid leaf-off start day-of-year

leaf_off_flag

GEDI 1 km EASE 2.0 grid flag

leaf_on_cycle

Flag that indicates the vegetation growing cycle for leaf-on observations

leaf_on_doy

GEDI 1 km EASE 2.0 grid leaf-on start day-of-year

lon_highestreturn

Longitude of highest detected return

modis_nonvegetated

Percent non-vegetated from MODIS MOD44B V6 data

modis_nonvegetated_sd

Percent non-vegetated standard deviation from MODIS MOD44B V6 data

modis_treecover

Percent tree cover from MODIS MOD44B V6 data

modis_treecover_sd

Percent tree cover standard deviation from MODIS MOD44B V6 data

num_detectedmodes

Number of detected modes in rxwaveform

pft_class

GEDI 1 km EASE 2.0 grid Plant Functional Type (PFT)

quality_flag

Flag indicating likely invalid waveform (1=valid, 0=invalid)

region_class

GEDI 1 km EASE 2.0 grid world continental regions

selected_algorithm

Identifier of algorithm selected as identifying the lowest non-noise mode

selected_mode

Identifier of mode selected as lowest non-noise mode

selected_mode_flag

Flag indicating status of selected_mode

sensitivity

Maxmimum canopy cover that can be penetrated

shot_number

Shot number, a unique identifier. This field is truncated on some images that are being reprocessed to properly show it (as of March 2022).

This field has the format of OOOOOBBRRGNNNNNNNN, where:

  • OOOOO: Orbit number
  • BB: Beam number
  • RR: Reserved for future use
  • G: Sub-orbit granule number
  • NNNNNNNN: Shot index
solar_azimuth

Solar azimuth

solar_elevation

Solar elevation

surface_flag

Indicates elev_lowestmode is within 300 m of DEM or MSS

urban_focal_window_size

The focal window size used to calculate urban_proportion

urban_proportion

The percentage proportion of land area within a focal area surrounding each shot that is urban land cover.

rh0

Relative height metrics at 0%

rh1

Relative height metrics at 1%

rh2

Relative height metrics at 2%

rh3

Relative height metrics at 3%

rh4

Relative height metrics at 4%

rh5

Relative height metrics at 5%

rh6

Relative height metrics at 6%

rh7

Relative height metrics at 7%

rh8

Relative height metrics at 8%

rh9

Relative height metrics at 9%

rh10

Relative height metrics at 10%

rh11

Relative height metrics at 11%

rh12

Relative height metrics at 12%

rh13

Relative height metrics at 13%

rh14

Relative height metrics at 14%

rh15

Relative height metrics at 15%

rh16

Relative height metrics at 16%

rh17

Relative height metrics at 17%

rh18

Relative height metrics at 18%

rh19

Relative height metrics at 19%

rh20

Relative height metrics at 20%

rh21

Relative height metrics at 21%

rh22

Relative height metrics at 22%

rh23

Relative height metrics at 23%

rh24

Relative height metrics at 24%

rh25

Relative height metrics at 25%

rh26

Relative height metrics at 26%

rh27

Relative height metrics at 27%

rh28

Relative height metrics at 28%

rh29

Relative height metrics at 29%

rh30

Relative height metrics at 30%

rh31

Relative height metrics at 31%

rh32

Relative height metrics at 32%

rh33

Relative height metrics at 33%

rh34

Relative height metrics at 34%

rh35

Relative height metrics at 35%

rh36

Relative height metrics at 36%

rh37

Relative height metrics at 37%

rh38

Relative height metrics at 38%

rh39

Relative height metrics at 39%

rh40

Relative height metrics at 40%

rh41

Relative height metrics at 41%

rh42

Relative height metrics at 42%

rh43

Relative height metrics at 43%

rh44

Relative height metrics at 44%

rh45

Relative height metrics at 45%

rh46

Relative height metrics at 46%

rh47

Relative height metrics at 47%

rh48

Relative height metrics at 48%

rh49

Relative height metrics at 49%

rh50

Relative height metrics at 50%

rh51

Relative height metrics at 51%

rh52

Relative height metrics at 52%

rh53

Relative height metrics at 53%

rh54

Relative height metrics at 54%

rh55

Relative height metrics at 55%

rh56

Relative height metrics at 56%

rh57

Relative height metrics at 57%

rh58

Relative height metrics at 58%

rh59

Relative height metrics at 59%

rh60

Relative height metrics at 60%

rh61

Relative height metrics at 61%

rh62

Relative height metrics at 62%

rh63

Relative height metrics at 63%

rh64

Relative height metrics at 64%

rh65

Relative height metrics at 65%

rh66

Relative height metrics at 66%

rh67

Relative height metrics at 67%

rh68

Relative height metrics at 68%

rh69

Relative height metrics at 69%

rh70

Relative height metrics at 70%

rh71

Relative height metrics at 71%

rh72

Relative height metrics at 72%

rh73

Relative height metrics at 73%

rh74

Relative height metrics at 74%

rh75

Relative height metrics at 75%

rh76

Relative height metrics at 76%

rh77

Relative height metrics at 77%

rh78

Relative height metrics at 78%

rh79

Relative height metrics at 79%

rh80

Relative height metrics at 80%

rh81

Relative height metrics at 81%

rh82

Relative height metrics at 82%

rh83

Relative height metrics at 83%

rh84

Relative height metrics at 84%

rh85

Relative height metrics at 85%

rh86

Relative height metrics at 86%

rh87

Relative height metrics at 87%

rh88

Relative height metrics at 88%

rh89

Relative height metrics at 89%

rh90

Relative height metrics at 90%

rh91

Relative height metrics at 91%

rh92

Relative height metrics at 92%

rh93

Relative height metrics at 93%

rh94

Relative height metrics at 94%

rh95

Relative height metrics at 95%

rh96

Relative height metrics at 96%

rh97

Relative height metrics at 97%

rh98

Relative height metrics at 98%

rh99

Relative height metrics at 99%

rh100

Relative height metrics at 100%

代码:

var qualityMask = function(im) {
  return im.updateMask(im.select('quality_flag').eq(1))
      .updateMask(im.select('degrade_flag').eq(0));
};
var dataset = ee.ImageCollection('LARSE/GEDI/GEDI02_A_002_MONTHLY')
                  .map(qualityMask)
                  .select('rh98');

var gediVis = {
  min: 1,
  max: 60,
  palette: 'darkred,red,orange,green,darkgreen',
};
Map.setCenter(-74.803466, -9.342209, 10);
Map.addLayer(dataset, gediVis, 'rh98');

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转载自blog.csdn.net/qq_31988139/article/details/123355237#comments_24910838