MOD14A1 V6.1 ডেটাসেট MODIS 4- এবং 11-মাইক্রোমিটার রেডিয়েন্স থেকে প্রাপ্ত 1km রেজোলিউশনে দৈনিক ফায়ার মাস্ক কম্পোজিট সরবরাহ করে। আগুন সনাক্তকরণ কৌশলটি আগুনের নিখুঁত সনাক্তকরণের উপর ভিত্তি করে (যখন আগুনের শক্তি শনাক্ত করার জন্য যথেষ্ট) এবং এর পটভূমির সাথে সম্পর্কিত সনাক্তকরণের উপর ভিত্তি করে (পৃষ্ঠের তাপমাত্রার পরিবর্তনশীলতা এবং সূর্যালোকের প্রতিফলনের জন্য)। পণ্য আগুন, কোন আগুন এবং কোন পর্যবেক্ষণ মধ্যে পার্থক্য. এই তথ্যটি বিভিন্ন বাস্তুতন্ত্রে আগুনের স্থানিক এবং অস্থায়ী বন্টন নিরীক্ষণ, আগুন বিতরণে পরিবর্তন সনাক্তকরণ এবং নতুন অগ্নি সীমান্ত, বন্য আগুন, এবং আগুনের ফ্রিকোয়েন্সি বা তাদের আপেক্ষিক শক্তির পরিবর্তন সনাক্ত করতে ব্যবহৃত হয়।
MOD14A1 V6.1 ডেটাসেট MODIS 4- এবং 11-মাইক্রোমিটার রেডিয়েন্স থেকে প্রাপ্ত 1km রেজোলিউশনে দৈনিক ফায়ার মাস্ক কম্পোজিট সরবরাহ করে। অগ্নি সনাক্তকরণ কৌশলটি আগুনের নিখুঁত সনাক্তকরণের উপর ভিত্তি করে (যখন আগুনের শক্তি সনাক্ত করার জন্য যথেষ্ট), এবং এর পটভূমির সাথে সম্পর্কিত সনাক্তকরণের উপর ভিত্তি করে (উত্তর হিসাবে ...
[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)"]]
