GEE数据集——汉森全球森林变化数据集Hansen Global Forest Change v1.11 (2000-2023)

Hansen Global Forest Change v1.11 (2000-2023)

对大地遥感卫星图像进行时间序列分析以确定全球森林范围和变化特征的结果。

第一个 "和 "最后一个 "波段是大地遥感卫星光谱波段(红、近红外、SWIR1 和 SWIR2)的第一个和最后一个可用年份的参考多光谱图像。参考复合图像代表了这些波段中每个波段的生长季节质量评估观测数据集的中值观测数据。

请参阅 1.11 版更新的用户说明以及相关期刊文章:Hansen、Potapov、Moore、Hancher 等:"21 世纪森林覆盖变化的高分辨率全球地图"。科学》342.6160 (2013):850-853.

Dataset Availability

2000-01-01T00:00:00 - 2023-12-31T00:00:00

Dataset Provider

Hansen/UMD/Google/USGS/NASA

Collection Snippet

Copied

ee.Image("UMD/hansen/global_forest_change_2023_v1_11")

Resolution

30.92 meters

Bands Table
Name Description Min Max Units Wavelength
treecover2000 Tree canopy cover for year 2000, defined as canopy closure for all vegetation taller than 5m in height. 0 100 %
loss Forest loss during the study period, defined as a stand-replacement disturbance (a change from a forest to non-forest state).
loss Bitmask * Bit 0: Forest loss during the study period. * 0: Not loss * 1: Loss
gain Forest gain during the period 2000-2012, defined as the inverse of loss (a non-forest to forest change entirely within the study period). Note that this has not been updated in subsequent versions.
gain Bitmask * Bit 0: Forest gain during the period 2000-2012. * 0: No gain * 1: Gain
first_b30 Landsat Red cloud-free image composite (corresponding to Landsat 5/7 band 3 and Landsat 8/9 band 4). Reference multispectral imagery from the first available year, typically 2000. 0.63-0.69µm
first_b40 Landsat NIR cloud-free image composite (corresponding to Landsat 5/7 band 4 and Landsat 8/9 band 5). Reference multispectral imagery from the first available year, typically 2000. 0.77-0.90µm
first_b50 Landsat SWIR1 cloud-free image composite (corresponding to Landsat 5/7 band 5 and Landsat 8/9 band 6). Reference multispectral imagery from the first available year, typically 2000. 1.55-1.75µm
first_b70 Landsat SWIR2 cloud-free image composite (corresponding to Landsat 5/7 band 7 and Landsat 8/9 band 7). Reference multispectral imagery from the first available year, typically 2000. 2.09-2.35µm
last_b30 Landsat Red cloud-free image composite (corresponding to Landsat 5/7 band 3 and Landsat 8/9 band 4). Reference multispectral imagery from the last available year, typically the last year of the study period. 0.63-0.69µm
last_b40 Landsat NIR cloud-free image composite (corresponding to Landsat 5/7 band 4 and Landsat 8/9 band 5). Reference multispectral imagery from the last available year, typically the last year of the study period. 0.77-0.90µm
last_b50 Landsat SWIR1 cloud-free image composite (corresponding to Landsat 5/7 band 5 and Landsat 8/9 band 6). Reference multispectral imagery from the last available year, typically the last year of the study period. 1.55-1.75µm
last_b70 Landsat SWIR2 cloud-free image composite (corresponding to Landsat 5/7 band 7 and Landsat 8/9 band 7). Reference multispectral imagery from the last available year, typically the last year of the study period. 2.09-2.35µm
datamask Three values representing areas of no data, mapped land surface, and permanent water bodies.
datamask Bitmask * Bits 0-1: Three values representing areas of no data, mapped land surface, and permanent water bodies. * 0: No data * 1: Mapped land surface * 2: Permanent water bodies
lossyear Year of gross forest cover loss event. Forest loss during the study period, defined as a stand-replacement disturbance, or a change from a forest to non-forest state. Encoded as either 0 (no loss) or else a value in the range 1-23, representing loss detected primarily in the year 2001-2023, respectively. 0 23

代码

javascript 复制代码
var geometry = 
    /* color: #d63000 */
    /* displayProperties: [
      {
        "type": "rectangle"
      }
    ] */
    ee.Geometry.Polygon(
        [[[-111.37186963558197, 41.621164801215464],
          [-111.37186963558197, 34.14087733236979],
          [-100.12186963558197, 34.14087733236979],
          [-100.12186963558197, 41.621164801215464]]], null, false);
var image = ee.Image("UMD/hansen/global_forest_change_2023_v1_11")
print(image)

Map.addLayer(image.clip(geometry),{},'sss')

数据引用

Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend.

  1. "High-Resolution Global Maps of 21st-Century Forest Cover Change." Science 342 (15 November): 850-53. 10.1126/science.1244693 Data available on-line at: Global Forest Change.

网址推荐

0代码在线构建地图应用

https://sso.mapmost.com/#/login?source_inviter=nClSZANO

机器学习

https://www.cbedai.net/xg

相关推荐
avoidaily3 小时前
使用Node.js分片上传大文件到阿里云OSS
阿里云·node.js·云计算
Elastic 中国社区官方博客7 小时前
Elastic 获得 AWS 教育 ISV 合作伙伴资质,进一步增强教育解决方案产品组合
大数据·人工智能·elasticsearch·搜索引擎·云计算·全文检索·aws
agenIT7 小时前
腾讯云 Python3.12.8 通过yum安装 并设置为默认版本
云计算·腾讯云
Johny_Zhao7 小时前
阿里云数据库Inventory Hint技术分析
linux·mysql·信息安全·云计算·系统运维
容器魔方7 小时前
议程一览 | KubeCon China 2025 华为云精彩前瞻
云原生·容器·云计算
FBI HackerHarry浩7 小时前
云计算 Linux Rocky day05【rpm、yum、history、date、du、zip、ln】
linux·运维·云计算·腾讯云
阿杆10 小时前
大故障,阿里云核心域名疑似被劫持
云计算·阿里巴巴
国际云15 小时前
腾讯云国际版和国内版账户通用吗?一样吗?为什么?
大数据·运维·阿里云·云计算
ZStack开发者社区16 小时前
全球化2.0|云轴科技ZStack助力香港服务机构VMware替代
运维·云计算·政务
BOB-wangbaohai16 小时前
阿里云ACP云计算备考笔记 (3)——云存储&RDS
阿里云·云计算·oss·块存储·rds