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
行业研究员20 小时前
AI原生的商城智能经营平台合作商推荐:腾讯云Mall
云计算·腾讯云·ai-native
故乡de云21 小时前
AWS 更换信用卡完整教程:绑定新卡、切换默认支付方式与扣款失败排查
云计算·aws
酷可达拉斯1 天前
Linux操作系统-shell编程(0)
linux·运维·服务器·python·云计算
AI小译1 天前
ShareGPT 数据集格式
数据集·sharegpt
国科安芯1 天前
空间机电一体化:AS32S601型抗辐射MCU在卫星推进与执行机构控制中的关键技术研究
单片机·嵌入式硬件·物联网·机器人·云计算
前网易架构师-高司机1 天前
带标注的移动通信基站信号塔,可识别塔架和塔身数据集,识别率93.5%,1008张图,支持yolo,coco json,voc xml,文末有模型训练代码
yolo·数据集·通信基站·信号塔·塔架·塔身
Qianyunzhiyun2 天前
AWS根用户MFA怎么设置?新账号安全教程
安全·云计算·aws
2601_955759412 天前
AWS 账单支付失败会怎样?NiceCloud 说明影响与补救
云计算·aws
全云在线allcloudonline2 天前
北京阿里云代理商怎么选?本地服务与企业采购判断指南
阿里云·云计算·企业上云