Satellites observe forests, wetlands, coasts and the ocean surface repeatedly and across borders, which field surveys cannot. Earth observation maps ecosystem extent, change and some aspects of condition, and it gives a consistent record for places where no one monitors on the ground.
What earth observation and remote sensing does here.
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 biodiversity and nature, climate and hazards and oceans and coasts, 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 onSTEM Commons.
Forest loss and disturbance alerts
Landsat, Sentinel-2 and Sentinel-1 time series are classified to map annual loss and near-real-time disturbance, with radar used where cloud blocks optical sensors.
Wetland and mangrove dynamics
Radar and optical time series track flooding regimes, wetland extent and mangrove change, separating seasonal variation from conversion.
Vegetation structure and condition
Spaceborne lidar and radar estimate canopy height and biomass, and spectral indices track phenology and stress as proxies for ecosystem condition.
03جوگرافیا
Habitat condition in the Amazon Basin.
Land cover, vegetation and plant growth over the Amazon Basin, from NASA GIBS. Each layer carries its own date.
نەخشە کارلێککارەکە JavaScript پێویستە؛ لیستی چینەکان و سەرچاوەکان لە خوارەوەن.
چینەکان 3
دۆخی شوێنی ژیان، بۆ ئەم لاپەڕەیە
دەربارەی ئەم چینە
بەڵگە
مۆدێلکراو (دوایین ساڵ کە GIBS بڵاوی دەکاتەوە)
سەرچاوە
داپۆشراوی زەوی MODIS Terra و Aqua (MCD12Q1) (NASA LP DAAC)
Habitat condition, framed on the Amazon Basin.بەرهەمی ماهەوارە و مۆدێل وەک NASA بڵاوی دەکاتەوە، هەر یەکەیان بە بەرواری خۆی. نیشاندەرن، نەک هەڵسەنگاندنی هیچ شوێنێک.
We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified).داتای کراوەی NASA
We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified).داتای کراوەی NASA
بەرهەمەکانی زەویی MODIS (ئیندێکسی ڕووەک، بەرهەمی سەرەتایی گشتی، داپۆشراوی زەوی)، NASA LP DAAC و LANCE؛ وێنەکان لە ڕێگەی NASA GIBS. ڕەنگەکان لە نەخشەڕەنگی بڵاوکراو دووبارە کێشراونەتەوە؛ بەهاکان لە خانە شەشگۆشەییەکاندا تێکڕا کراون کاتێک پیشان دراون (دەستکاریکراو). داتای کراوەی NASA
NASA Fire Information for Resource Management System (FIRMS)، بەرهەمی ئاگری چالاکی VIIRS 375 m، NASA LANCE؛ تایلی ڤێکتەر لە ڕێگەی NASA GIBS. ڕەنگەکان لە نەخشەڕەنگی بڵاوکراو دووبارە کێشراونەتەوە؛ بەهاکان لە خانە شەشگۆشەییەکاندا تێکڕا کراون کاتێک پیشان دراون (دەستکاریکراو). داتای کراوەی NASA
Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. ڕەنگەکان لە نەخشەڕەنگی بڵاوکراو دووبارە کێشراونەتەوە؛ بەهاکان لە خانە شەشگۆشەییەکاندا تێکڕا کراون کاتێک پیشان دراون (دەستکاریکراو). doi:10.7927/H49C6VHW. CC BY 4.0
ASTER GDEM بەرهەمی METI و NASA ە (ASTER Global Digital Elevation Model V003، NASA LP DAAC)؛ وێنەکان لە ڕێگەی NASA GIBS. ڕەنگەکان لە نەخشەڕەنگی بڵاوکراو دووبارە کێشراونەتەوە؛ بەهاکان لە خانە شەشگۆشەییەکاندا تێکڕا کراون کاتێک پیشان دراون (دەستکاریکراو). ناوهێنان بەم شێوەیە: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. داتای کراوەی NASA
ڕووداوە ڕاستەوخۆکان: NASA Earth Observatory Natural Event Tracker (EONET)؛ ڕووداوەکان نیشانەدەرن و بەستەری سەرچاوەی ڕەسەنی خۆیان دەهێڵنەوە.
ڕاستەوخۆ: NASA EONET ڕووداوەکان نیشانەدەرن، نەک ئاگادارکردنەوەی دەسەڵات.
Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
Optional layers (6 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
چینەکان و بەروارەکان
جۆری داپۆشەری زەوی (IGBP)، ساڵانە: داپۆشەری زەویی MODIS Terra و Aqua (MCD12Q1)، NASA LP DAAC · 2024
ئیندێکسی ڕووەکی باشترکراو، 8 ڕۆژی بزۆک: MODIS Terra EVI، NASA LANCE · 13ی تشرینی یەکەمی 2026
ئاگرە چالاکەکان و نائاسایی گەرمایی: VIIRS NOAA-20 375 m (FIRMS)، NASA LANCE FIRMS · 13ی تشرینی یەکەمی 2026
بەرهەمی سەرەتایی گشتی، کۆی 8 ڕۆژ: MODIS Aqua GPP (MYD17)، NASA LP DAAC · 30ی ئەیلوولی 2026
چڕی دانیشتووان، 2020: دانیشتووان: CIESIN، زانکۆی کۆلۆمبیا، Gridded Population of the World v4.11 (2018)، NASA SEDAC، CC BY 4.0 · جێگیر
04داتا
What the method consumes.
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 inthe source register.
داتا
ڕۆڵ
ناونیشان
Landsat and Sentinel-2 optical imagery
Land cover and change
چاودێریکراو
Sentinel-1 and ALOS PALSAR radar
Forest and wetland mapping through cloud
چاودێریکراو
GEDI spaceborne lidar
Canopy height and structure
چاودێریکراو
Copernicus Marine ocean colour and temperature
Marine productivity and heat stress
چاودێریکراو
ESA WorldCover
Land cover baseline
مۆدێلکراو
05چاودێری
Earth observation run.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Earth observation run
Biodiversity · Earth observation for biodiversity · Run R-8579
Scene processingGCRI · Biodiversity Nexus
Acquisition
revisit and swath
Accuracy assessment
stratified sample
ئاو
91
97
96
Cropland
89
87
287
Built-up
82
79
124
Forest
91
88
103
Processing chain
بەدەستهێنانL1
Calibrateradiometric
ڕاست بکەرەوەatmospheric
Maskcloud · shadow
Classifyچاودێریی زەوی
پشتڕاستکردنەوەground truth
Earth observation run: the screen’s structure, terms and states for Biodiversity.ناو و بەهای نموونەیی؛ دیزاینێکە، نەک تۆمار یان سیستەمی ڕاستەوخۆ.
06پشتڕاستکردنەوە
How results are checked.
Products are assessed against ground reference data using accuracy matrices and independent samples. Cross-calibration between sensors checks consistency over time.
بپشکنە
How it is done
Accuracy assessment with area estimation
Maps are scored against a probability sample of reference points, and areas are adjusted for classification error
Cross-sensor consistency
Trends are checked across sensors and processing versions before they are reported
Field calibration
Structure and condition proxies are calibrated against inventory plots
Coverage reporting
Cloud, revisit gaps and missing scenes are reported as no data, not as no change
Clouds, revisit gaps and mixed pixels limit what can be observed. Changes in sensors and processing can create artificial trends.
07شبیهسازی دووانە و زنجیرەیی
Model earth observation for biodiversity as a system. Run the cascade.
Assembled from theNexus Standardsarea profileستانداردەکانی مەترسیی فرەجۆریی زیندەوەری و سروشت: the hazards it names, theسیستەمەand 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 fullSystem Builder.
پرەنسیپە ڕێنماییەکانی FAIR · GO FAIR و FORCE11W3C PROV · World Wide Web Consortiumڕێنمایی بۆ مامەڵەی یەکسان لەگەڵ نادڵنیاییەکان · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
Earth observation for biodiversity: Earth observation processing chain
9 steps·4 قۆناغ·1 gate
پرۆسە
Earth observation for biodiversity: Earth observation processing chain
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.
01 Ground segment
01بەدەستهێنانسەرچاوەSensors acquire optical or radar data. For Sentinel-2 the Level-0 product is raw image data in Instrument Source Packet format.
03Level-1 radiometric and geometric processingهەنگاوLevel-1B gives calibrated top-of-atmosphere radiance. Level-1C adds geometric corrections, including orthorectification, for reflectance.
02 Pre-processing
04Level-2 atmospheric correctionهەنگاوLevel-2A applies an atmospheric correction to the Level-1C orthoimage. Its main output is a surface reflectance product.
05Scene classification and masksهەنگاوLevel-2A includes scene classification, and Level-1C also makes cloud, cirrus and snow or ice masks. Quality flags travel with the product.
06Analysis-ready dataDatasetCEOS Analysis Ready Data meet minimum processing requirements and are organised for immediate analysis and interoperability.
03 Analytics
02Reference dataDatasetField samples or other independent reference data are used to check the product.
07Change analysisمۆدێلClassification and time-series methods detect change in the analysis-ready data. The method is chosen by the analyst.
08پشتڕاستکردنەوەدەروازەThe product is compared with reference data and accuracy is reported, for example with a confusion matrix.
04 Delivery
09Product to the userDecision · Protected area authorityThe producer releases the product with its limits stated.
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.
14پرسیارەکان
پرسیار و وەڵام.
What are the limits of earth observation and remote sensing in this field?
Clouds, revisit gaps and mixed pixels limit what can be observed. Changes in sensors and processing can create artificial trends.
How are results checked?
Products are assessed against ground reference data using accuracy matrices and independent samples. Cross-calibration between sensors checks consistency over time.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Reportsis 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.
GCRIBiodiversity Nexusمەترسی و خۆڕاگریی کەرتی جیهانیئاماژەی چاودێرگە
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