Spatial statistics estimate social conditions for small areas and map how vulnerability and hazards overlap. In this field they produce poverty and vulnerability maps for places surveys barely cover, always with uncertainty shown.
What spatial statistics and geostatistics does here.
Spatial statistics and geostatistics analyse data that vary across space, accounting for spatial dependence. They estimate values at unsampled locations and test for spatial patterns. In society and human development and information and public trust, spatial statistics produce continuous hazard and exposure surfaces with uncertainty. They reveal geographic clustering of risks and vulnerabilities across sectors. The canonical description is onSTEM Commons.
Small-area poverty estimation
Survey data are combined with census and satellite covariates to estimate poverty for districts and neighbourhoods, with uncertainty mapped beside estimates.
Vulnerability and hazard overlay
Social vulnerability estimates are overlaid with hazard maps to identify places where exposure and limitedتوانای مامەڵەکردنcoincide.
Spatial clustering of deprivation
Statistical tests identify clusters of deprivation that are unlikely to arise by chance, guiding targeted programmes.
03جوگرافیا
خەڵک و ڕووبەڕووبوون لە ئەمریکای لاتین و کارائیب.
چڕیی دانیشتووان، ڕووناکیی شەو و گەرمیی ڕووی زەوی لە ڕۆژدا لەسەر ئەمریکای لاتین و کەریبی، لە NASA GIBS. هەر چینێک ڕێکەوتی خۆی هەڵدەگرێت.
نەخشە کارلێککارەکە JavaScript پێویستە؛ لیستی چینەکان و سەرچاوەکان لە خوارەوەن.
چینەکان 3
خەڵک و ڕووبەڕووبوون، بۆ ئەم لاپەڕەیە
دەربارەی ئەم چینە
بەڵگە
مەزەندەکراو
سەرچاوە
Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
خەڵک و ڕووبەڕووبوون، لەسەر ئەمریکای لاتین و کارائیب.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
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
ڕووناکیی شەوی VIIRS Black Marble، NASA Goddard Space Flight Center؛ بڵاودەکرێتەوە لەلایەن NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC)؛ وێنەکان لە ڕێگەی NASA GIBS. ڕەنگەکان لە نەخشەڕەنگی بڵاوکراو دووبارە کێشراونەتەوە؛ بەهاکان لە خانە شەشگۆشەییەکاندا تێکڕا کراون کاتێک پیشان دراون (دەستکاریکراو). 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
دووانە ئۆکسیدی نایترۆجینی OMI (Aura) و ئیندێکسی ئەیرۆسۆڵی OMPS (Suomi NPP)، NASA؛ بڵاودەکرێتەوە لەلایەن NASA GES DISC؛ وێنەکان لە ڕێگەی NASA GIBS. ڕەنگەکان لە نەخشەڕەنگی بڵاوکراو دووبارە کێشراونەتەوە؛ بەهاکان لە خانە شەشگۆشەییەکاندا تێکڕا کراون کاتێک پیشان دراون (دەستکاریکراو). داتای کراوەی NASA
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.
Context: CIESIN/Columbia, NASA SEDAC HBASE. Center for International Earth Science Information Network (CIESIN), Columbia University, and NASA Socioeconomic Data and Applications Center (SEDAC): Global Human Built-up And Settlement Extent (HBASE) 2010; Seto, Guneralp and Hutyra 2012, Global Grid of Probabilities of Urban Expansion to 2030; Global Urban Heat Island (UHI) Data Set, 2013.
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).
پێشبینی کوالیتی هەوا، 5 ڕۆژ، PM2.5 (CAMS لە ڕێگەی Open-Meteo): Contains modified Copernicus Atmosphere Monitoring Service information 2026.
داتای کەشناسی لە Open-Meteo.com (https://open-meteo.com/), بە مۆڵەتی CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
چینە ئارەزوومەندانەکان (9 سەرچاوە لە لیستی چینەکان: ڕاستەوخۆ، پێشبینی، چاودێریکراو و ناوەڕۆک) کاتێک دەکرێنەوە ناوی دابینکەرەکەیان لەسەر نەخشە و لێرەدا پیشان دەدەن؛ پێشبینییەکان دەرچووی مۆدێلن و نیشاندەرە وەرگیراوەکان مەزەندەن.
چینەکان و بەروارەکان
چڕی دانیشتووان، 2020: دانیشتووان: CIESIN، زانکۆی کۆلۆمبیا، Gridded Population of the World v4.11 (2018)، NASA SEDAC، CC BY 4.0 · جێگیر
ڕووناکی شەو، ڕۆژانە: VIIRS Black Marble (VNP46A2)، NASA LAADS DAAC · 12ی تشرینی یەکەمی 2026
جۆری داپۆشەری زەوی (IGBP)، ساڵانە: داپۆشەری زەویی MODIS Terra و Aqua (MCD12Q1)، NASA LP DAAC · 2024
دووانە ئۆکسیدی نایترۆجین، ستوونی خوارەوەی کەشوهەوا: OMI Aura، NASA GES DISC · 10ی تشرینی یەکەمی 2026
04داتا
What the method consumes.
Datasets and records used by spatial statistics and geostatistics on this platform, with the role each plays and the label its values carry. Sources are listed inthe source register.
داتا
ڕۆڵ
ناونیشان
Household surveys with location
Indicator values
مەزەندەکراو
Census small-area data
Covariates
ئامارە بڵاوکراوەکان
Satellite-derived covariates
Covariates
چاودێریکراو
Hazard maps
ڕووبەڕووبوون
مۆدێلکراو
05چاودێری
Spatial model.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Spatial model: the screen’s structure, terms and states for Society and human development.ناو و بەهای نموونەیی؛ دیزاینێکە، نەک تۆمار یان سیستەمی ڕاستەوخۆ.
06پشتڕاستکردنەوە
How results are checked.
Predictions are tested using spatial cross-validation that respects dependence. Uncertainty maps are compared with independent observations.
بپشکنە
How it is done
Model validation
Small-area estimates are compared with direct estimates where samples are large
Uncertainty mapping
Every map is accompanied by uncertainty
Privacy protection
Maps are aggregated to avoid identifying households
Results depend on the scale and zoning of analysis. Sparse or clustered sampling limits prediction in unsampled areas.
07شبیهسازی دووانە و زنجیرەیی
Model spatial statistics for social data as a system. Run the cascade.
Assembled from theNexus Standardsarea profileSocietal and information risk standards: 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
10Stewardship
Who maintains the method.
فەزا و چاودێری زەویstewards spatial statistics and geostatistics for the Consortium and reviews how it is applied across platforms.
Spatial statistics for social data: Layers to published map
7 steps·4 قۆناغ·1 gate
پرۆسە
Spatial statistics for social data: Layers to published map
Layers enter with their rights, are aligned, analysed and checked for uncertainty, then released after public-safe review; a map is a governed spatial claim.
01 Data
01Source layers with their rightsDataset ·NXS-GRX(canonical data, provenance and risk)Spatial views of The Global Risks Index (NXS-GRX) products sit under the boundary licence gate. Rights classification sets how a layer may be used.
02 Harmonise
02Coordinate reference and boundary versionتۆمار · NXS-EOP(earth observation and digital twins)The area of interest preserves its coordinate reference system, polygon validity and observation support. Boundary versions are kept.
03Harmonise units, variables and timeهەنگاوUnit metadata, conversion records and transformation logs are required. Alignment is an evidence event, not hidden preprocessing.
03 Analyse and check
04Analyse with a recorded processing recipeModel · GIS teamA processing recipe records parameters, calibration, inputs and output lineage. The analysis methods are named in each product’s own record.
05Spatial uncertainty checkدەروازەSpatial uncertainty is recorded and affects downstream use. A high-uncertainty polygon may suit internal review, not public-safe release.
04 بڵاوکردنەوە
06Spatial metadata bundleتۆمارThe bundle records boundary type, jurisdiction, geometry version, projection, resolution, source, time window, uncertainty and access class.
07Public-safe release of the mapبڕیارThe output record names the redactions, uncertainty and public-safe reviewer. A map is a governed spatial claim, never merely a picture.
Spatio-temporal intelligence· Data protocols: semantic, jurisdictional and temporal intelligence · NXS-EOPDesigned programme process, not a record of operation. No cycle has run and every programme is at service level R0. A gate is a programme decision, never a public-authority approval, certification or deployment authorisation. The pages cited are design doctrine.
What are the limits of spatial statistics and geostatistics in this field?
Results depend on the scale and zoning of analysis. Sparse or clustered sampling limits prediction in unsampled areas.
How are results checked?
Predictions are tested using spatial cross-validation that respects dependence. Uncertainty maps are compared with independent observations.
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.
GCRIکۆمەڵگا و گەشەپێدانی مرۆییمەترسی و خۆڕاگریی سیستەمی وڵاتکورتەی بەڵگە
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