Set data ALOS Landform menyediakan kelas bentang alam yang dibuat dengan menggabungkan
set data Continuous Heat-Insolation Load Index (CHILI) dan
multi-scale Topographic Position Index (mTPI). Data ini didasarkan pada DEM NED 10 m USGS (tersedia di EE sebagai USGS/NED).
Kumpulan Data Geomorphology (ERGo) yang Relevan secara Ekologis, Bentuk Lahan, dan Fisiografi dari Conservation Science Partners (CSP) berisi data multi-skala yang mendetail tentang bentuk lahan dan pola fisiografi (alias aspek lahan). Meskipun ada banyak potensi penggunaan data ini, tujuan awal data ini adalah untuk mengembangkan klasifikasi dan peta bentuk lahan dan kelas fisiografi yang relevan secara ekologis yang sesuai untuk perencanaan adaptasi iklim. Karena ada ketidakpastian besar yang terkait dengan kondisi iklim di masa mendatang dan bahkan lebih banyak ketidakpastian seputar respons ekologis, memberikan informasi tentang apa yang tidak mungkin berubah akan memberikan dasar yang kuat bagi pengelola untuk menyusun rencana adaptasi iklim yang kuat. Kuantifikasi fitur lanskap ini sensitif terhadap resolusi, jadi kami memberikan resolusi tertinggi yang mungkin mengingat cakupan dan karakteristik indeks tertentu.
Theobald, D. M., Harrison-Atlas, D., Monahan, W. B., & Albano, C. M.
(2015). Peta bentuk lahan dan keanekaragaman fisiografi yang relevan secara ekologis untuk perencanaan adaptasi iklim. PloS one, 10(12),
e0143619
Set data ALOS Landform menyediakan kelas bentukan lahan yang dibuat dengan menggabungkan set data Continuous Heat-Insolation Load Index (CHILI) dan multi-scale Topographic Position Index (mTPI). Data ini didasarkan pada DEM NED 10 m USGS (tersedia di EE sebagai USGS/NED). Kumpulan Data, Bentuk Lahan, dan … Geomorphology yang Relevan secara Ekologis (ERGo) dari Conservation Science Partners (CSP)
[null,null,[],[[["\u003cp\u003eThe ALOS Landform dataset provides landform classes by combining CHILI and mTPI datasets, based on the USGS's 10m NED DEM.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset was developed for climate adaptation planning by classifying landforms and physiographic patterns.\u003c/p\u003e\n"],["\u003cp\u003eIt offers 10-meter resolution and includes 15 distinct landform classes, such as peaks, ridges, slopes, and valleys.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is provided by Conservation Science Partners and is licensed under CC-BY-NC-SA-4.0.\u003c/p\u003e\n"],["\u003cp\u003eIt covers the United States and is available in Google Earth Engine for analysis and visualization.\u003c/p\u003e\n"]]],[],null,["# US NED Landforms\n\nDataset Availability\n: 2006-01-24T00:00:00Z--2011-05-13T00:00:00Z\n\nDataset Provider\n:\n\n\n [Conservation Science Partners](https://www.csp-inc.org/)\n\nTags\n:\n[aspect](/earth-engine/datasets/tags/aspect) [csp](/earth-engine/datasets/tags/csp) [elevation](/earth-engine/datasets/tags/elevation) [elevation-topography](/earth-engine/datasets/tags/elevation-topography) [ergo](/earth-engine/datasets/tags/ergo) [geophysical](/earth-engine/datasets/tags/geophysical) [landforms](/earth-engine/datasets/tags/landforms) [slope](/earth-engine/datasets/tags/slope) [topography](/earth-engine/datasets/tags/topography) [us](/earth-engine/datasets/tags/us) \n\n#### Description\n\nThe ALOS Landform dataset provides landform classes created by combining\nthe Continuous Heat-Insolation Load Index (CHILI) and the\nmulti-scale Topographic Position Index (mTPI) datasets. It is\nbased on the USGS's 10m NED DEM (available in EE as USGS/NED).\n\nThe Conservation Science Partners (CSP) Ecologically Relevant Geomorphology\n(ERGo) Datasets, Landforms and Physiography contain detailed, multi-scale\ndata on landforms and physiographic (aka land facet) patterns. Although\nthere are many potential uses of these data, the original purpose for these\ndata was to develop an ecologically relevant classification and map of\nlandforms and physiographic classes that are suitable for climate adaptation\nplanning. Because there is large uncertainty associated with future climate\nconditions and even more uncertainty around ecological responses, providing\ninformation about what is unlikely to change offers a strong foundation for\nmanagers to build robust climate adaptation plans. The quantification of\nthese features of the landscape is sensitive to the resolution, so we\nprovide the highest resolution possible given the extent and characteristics\nof a given index.\n\n### Bands\n\n\n**Pixel Size**\n\n10 meters\n\n**Bands**\n\n| Name | Pixel Size | Description |\n|------------|------------|------------------------------|\n| `constant` | meters | NED-derived landform classes |\n\n**constant Class Table**\n\n| Value | Color | Description |\n|-------|---------|--------------------|\n| 11 | #141414 | Peak/ridge (warm) |\n| 12 | #383838 | Peak/ridge |\n| 13 | #808080 | Peak/ridge (cool) |\n| 14 | #ebeb8f | Mountain/divide |\n| 15 | #f7d311 | Cliff |\n| 21 | #aa0000 | Upper slope (warm) |\n| 22 | #d89382 | Upper slope |\n| 23 | #ddc9c9 | Upper slope (cool) |\n| 24 | #dccdce | Upper slope (flat) |\n| 31 | #1c6330 | Lower slope (warm) |\n| 32 | #68aa63 | Lower slope |\n| 33 | #b5c98e | Lower slope (cool) |\n| 34 | #e1f0e5 | Lower slope (flat) |\n| 41 | #a975ba | Valley |\n| 42 | #6f198c | Valley (narrow) |\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-NC-SA-4.0](https://spdx.org/licenses/CC-BY-NC-SA-4.0.html)\n\n### Citations\n\nCitations:\n\n- Theobald, D. M., Harrison-Atlas, D., Monahan, W. B., \\& Albano, C. M.\n (2015). Ecologically-relevant maps of landforms and physiographic diversity\n for climate adaptation planning. PloS one, 10(12),\n [e0143619](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0143619)\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.Image('CSP/ERGo/1_0/US/landforms');\nvar landforms = dataset.select('constant');\nvar landformsVis = {\n min: 11.0,\n max: 42.0,\n palette: [\n '141414', '383838', '808080', 'ebeb8f', 'f7d311', 'aa0000', 'd89382',\n 'ddc9c9', 'dccdce', '1c6330', '68aa63', 'b5c98e', 'e1f0e5', 'a975ba',\n '6f198c'\n ],\n};\nMap.setCenter(-105.58, 40.5498, 11);\nMap.addLayer(landforms, landformsVis, 'Landforms');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/CSP/CSP_ERGo_1_0_US_landforms) \n[US NED Landforms](/earth-engine/datasets/catalog/CSP_ERGo_1_0_US_landforms) \nThe ALOS Landform dataset provides landform classes created by combining the Continuous Heat-Insolation Load Index (CHILI) and the multi-scale Topographic Position Index (mTPI) datasets. It is based on the USGS's 10m NED DEM (available in EE as USGS/NED). The Conservation Science Partners (CSP) Ecologically Relevant Geomorphology (ERGo) Datasets, Landforms and ... \nCSP/ERGo/1_0/US/landforms, aspect,csp,elevation,elevation-topography,ergo,geophysical,landforms,slope,topography,us \n2006-01-24T00:00:00Z/2011-05-13T00:00:00Z \n12.54 -132.09 56.21 -60.35 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://www.csp-inc.org/)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/CSP_ERGo_1_0_US_landforms)"]]
