Набор данных MOD14A1 V6.1 предоставляет ежедневные композитные изображения пожарных масок с разрешением 1 км, полученные по данным MODIS с 4- и 11-микрометровой интенсивностью излучения. Стратегия обнаружения пожаров основана на абсолютном обнаружении пожара (когда интенсивность пожара достаточна для обнаружения) и на обнаружении относительно его фона (с учётом изменчивости температуры поверхности и отражения солнечного света). Продукт различает пожар, отсутствие пожара и отсутствие наблюдения. Эта информация используется для мониторинга пространственного и временного распределения пожаров в различных экосистемах, обнаружения изменений в их распространении и выявления новых границ пожаров, лесных пожаров, а также изменений частоты возникновения пожаров или их относительной интенсивности.
Набор данных MOD14A1 V6.1 предоставляет ежедневные композитные изображения пожаров с разрешением 1 км, полученные по данным MODIS с диапазоном излучений 4 и 11 микрометров. Стратегия обнаружения пожаров основана на абсолютном обнаружении пожара (когда интенсивность пожара достаточна для обнаружения) и на обнаружении относительно его фона (для учета…
[null,null,[],[[["\u003cp\u003eMOD14A1 V6.1 provides daily global fire mask composites at 1km resolution, derived from MODIS thermal radiances.\u003c/p\u003e\n"],["\u003cp\u003eThe fire detection strategy utilizes both absolute fire detection and detection relative to the background.\u003c/p\u003e\n"],["\u003cp\u003eData identifies fire occurrences with varying confidence levels and differentiates between fire, no fire, and no observation.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is useful for monitoring fire distribution, detecting fire frontiers, and analyzing fire frequency and strength changes.\u003c/p\u003e\n"],["\u003cp\u003eMODIS data acquired through the LP DAAC has no restrictions on subsequent use, sale, or redistribution.\u003c/p\u003e\n"]]],["The MOD14A1 V6.1 dataset from NASA LP DAAC provides daily 1km resolution fire mask composites from MODIS radiances, available from February 24, 2000, to February 17, 2025. It detects fires based on absolute strength and background relativity, distinguishing between fire, no fire, and no observation. Data bands include `FireMask`, `MaxFRP`, `sample`, and `QA`. Users can access and analyze this data via Google Earth Engine using the provided snippet and can acquire without any restriction.\n"],null,["# MOD14A1.061: Terra Thermal Anomalies & Fire Daily Global 1km\n\nDataset Availability\n: 2000-02-24T00:00:00Z--2025-08-20T00:00:00Z\n\nDataset Provider\n:\n\n\n [NASA LP DAAC at the USGS EROS Center](https://doi.org/10.5067/MODIS/MOD14A1.061)\n\nCadence\n: 1 Day\n\nTags\n:\n [daily](/earth-engine/datasets/tags/daily) [fire](/earth-engine/datasets/tags/fire) [global](/earth-engine/datasets/tags/global) [modis](/earth-engine/datasets/tags/modis) [nasa](/earth-engine/datasets/tags/nasa) [terra](/earth-engine/datasets/tags/terra) [usgs](/earth-engine/datasets/tags/usgs) \nmod14a1 \n\n#### Description\n\nThe MOD14A1 V6.1 dataset provides daily fire mask composites\nat 1km resolution derived from the MODIS 4- and 11-micrometer radiances.\nThe fire detection strategy is based on absolute detection of a\nfire (when the fire strength is sufficient to detect), and on detection\nrelative to its background (to account for variability of the surface\ntemperature and reflection by sunlight). The product distinguishes\nbetween fire, no fire and no observation. This information is used\nfor monitoring the spatial and temporal distribution of fires in\ndifferent ecosystems, detecting changes in fire distribution and\nidentifying new fire frontiers, wild fires, and changes in the\nfrequency of the fires or their relative strength.\n\nDocumentation:\n\n- [User's Guide](https://lpdaac.usgs.gov/documents/1005/MOD14_User_Guide_V61.pdf)\n\n- [Algorithm Theoretical Basis Document (ATBD)](https://lpdaac.usgs.gov/documents/87/MOD14_ATBD.pdf)\n\n- [General Documentation](https://ladsweb.modaps.eosdis.nasa.gov/filespec/MODIS/61/MOD14A1)\n\n### Bands\n\n\n**Pixel Size**\n\n1000 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Scale | Pixel Size | Description |\n|------------|-------|-----|--------|-------|------------|------------------------------------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| `FireMask` | | | | | meters | Confidence of fire |\n| Bitmask for FireMask - Bits 0-3: Fire mask pixel classes - 1: Not processed (obsolete; not used since Collection 1) - 2: Not processed (other reason) - 3: Non-fire water pixel - 4: Cloud (land or water) - 5: Non-fire land pixel - 6: Unknown (land or water) - 7: Fire (low confidence, land or water) - 8: Fire (nominal confidence, land or water) - 9: Fire (high confidence, land or water) ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n| `MaxFRP` | MW | 0 | 180000 | 0.1 | meters | Maximum fire radiative power |\n| `sample` | | 0 | 1353 | | meters | Position of fire pixel within scan |\n| `QA` | | | | | meters | Pixel quality indicators |\n| Bitmask for QA - Bits 0-1: Land/water state - 0: Water - 1: Coast - 2: Land - 3: Missing data - Bit 2: Night/day - 0: Night - 1: Day ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n\n### Terms of Use\n\n**Terms of Use**\n\nMODIS data and products acquired through the LP DAAC\nhave no restrictions on subsequent use, sale, or redistribution.\n\n### Citations\n\nCitations:\n\n- Please visit [LP DAAC 'Citing Our Data' page](https://lpdaac.usgs.gov/citing_our_data)\n for information on citing LP DAAC datasets.\n\n### DOIs\n\n- \u003chttps://doi.org/10.5067/MODIS/MOD14A1.061\u003e\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.ImageCollection('MODIS/061/MOD14A1')\n .filter(ee.Filter.date('2018-01-01', '2018-05-01'));\nvar fireMaskVis = {\n min: 0.0,\n max: 6000.0,\n bands: ['MaxFRP', 'FireMask', 'FireMask'],\n};\nMap.setCenter(6.746, 46.529, 2);\nMap.addLayer(dataset, fireMaskVis, 'Fire Mask');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/MODIS/MODIS_061_MOD14A1) \n[MOD14A1.061: Terra Thermal Anomalies \\& Fire Daily Global 1km](/earth-engine/datasets/catalog/MODIS_061_MOD14A1) \nThe MOD14A1 V6.1 dataset provides daily fire mask composites at 1km resolution derived from the MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of a fire (when the fire strength is sufficient to detect), and on detection relative to its background (to account for ... \nMODIS/061/MOD14A1, daily,fire,global,modis,nasa,terra,usgs \n2000-02-24T00:00:00Z/2025-08-20T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.5067/MODIS/MOD14A1.061](https://doi.org/https://doi.org/10.5067/MODIS/MOD14A1.061)\n- [https://doi.org/10.5067/MODIS/MOD14A1.061](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD14A1)"]]
