Flood extent mapping
Radar images, which see through cloud, are classified to map standing water during and after floods, and compared with optical images and field reports.
GCRI · 气候与灾害
Earth observation and remote sensing measure hazards and their footprints from space and the air: rainfall, soil moisture, vegetation, fire, flood extent and ground deformation. In this field it fills gaps between ground stations and gives consistent records across borders.
Earth observation and remote sensing gather information about the Earth’s surface and atmosphere from airborne and spaceborne sensors. They provide consistent, repeatable measurements over areas that are hard to monitor on the ground. In climate and hazards and disaster and crisis, earth observation maps exposure, damage and environmental change across borders and sectors. It supports rapid assessment after disasters and long-term monitoring of risk drivers. The canonical description is on STEM Commons.
Radar images, which see through cloud, are classified to map standing water during and after floods, and compared with optical images and field reports.
Vegetation indices and land surface temperature are compared with their seasonal norms to detect agricultural drought stress.
Thermal anomalies and post-fire reflectance changes map fire activity and burned area, with detection limits stated.
Active fires, flood water and land cover across the world, from NASA GIBS. Each layer carries its own date.
交互式地图需要JavaScript;图层列表和来源见下文。
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最新可用
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap贡献者 (ODbL) · Natural Earth
正在加载最新的NASA影像。
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Earth observation, framed on the world.NASA 发布的卫星和模型产品,各带自己的日期。它们是指标,而非对任何地点的评估。
图层与日期
Datasets and records used by earth observation and remote sensing on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.
| 数据 | 角色 | 标签 |
|---|---|---|
| Copernicus Sentinel-1 and Sentinel-2 | Radar and optical imagery | 观测 |
| NASA MODIS and VIIRS | Daily global observations | 观测 |
| GPM IMERG precipitation | Satellite rainfall estimates | 估算 |
| ESA CCI soil moisture | Long-term soil moisture records | 观测 |
团队遵循该方法时会使用的界面:其指标、状态与决策。名称为示例,数值仅作示意。
Climate and hazards · Earth observation for hazards · Run R-0133
revisit and swath
stratified sample
| 水 | 98 | 89 | 128 |
| Cropland | 87 | 75 | 261 |
| Built-up | 82 | 90 | 102 |
| Forest | 90 | 87 | 125 |
Products are assessed against ground reference data using accuracy matrices and independent samples. Cross-calibration between sensors checks consistency over time.
| 核查 | 如何开展 |
|---|---|
| 精度评估 | Maps are compared with independent reference data and accuracy reported by class |
| Cross-sensor consistency | Long records are checked for jumps when sensors change |
| Detection limits | Minimum detectable fire size, flood width or deformation is stated |
Clouds, revisit gaps and mixed pixels limit what can be observed. Changes in sensors and processing can create artificial trends.
Assembled from the Nexus Standards area profile 气候风险标准: the hazards it names, the 系统 and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
灾害
控制措施
NS-0 章程与原则NS-1 维持社会运转的 UNI 与制品目录(语法 v0.2:领域、部门、区域和环境分段)NS-3 风险记录 UNI(语法、旧编码对照、分配机构)NS-3b 数据集与产品元数据规范(STAC、DCAT、PROV-O)NS-9 情境 UNI(部署、实例、计划实例)NS-11 验证与监测(证据、证明、零信任符合性观测)NS-14 符合性及与外部标准的对照NRS-H65 危害类别:超越行星边界(NHS-1 planet.boundary)NRS-H62 危害类别:复合与多危害事件(NHS-1 sys.compound)NRS-H71 危害类别:深时与宇宙灾难(NHS-1 planet.deep-time)NRS-H79 危害类别:精神卫生危机(NHS-1 health.mental)NRS-H75 危害类别:气候敏感性疾病(NHS-1 health.climate-sensitive)NRS-H7 危害类别:大尺度环流异常(NHS-1 atmo.climate-mode)观测
示例地理范围
模型、其假设、数据和不确定性,以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意,不是研究发现。
How far the outlook for earth observation for hazards could spread, shown as ranges rather than a single line.
空间与地球观测 stewards earth observation and remote sensing for the Consortium and reviews how it is applied across platforms.
Process explorer · Process
9 steps·4 个阶段·1 gate
流程
Processing levels are mission specific; Sentinel-2 runs from Level-0 raw data to Level-2A, and CEOS Analysis Ready Data sets the minimum for analysis.
Neutral outline of a published external standard or method, from its issuing body. Not a record of operation. Nexus does not perform, certify or approve any step shown. A gate or decision belongs to the party the source names. Level-1B and Level-1C add corrections; Level-2A adds atmospheric correction and scene classification.
报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
切勿发送个人数据、敏感基础设施细节或您无权分享的任何内容。贡献在使用前会经过审查;发送贡献不赋予署名权或编辑权,赞助也绝不能换取研究结论。
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