| 000 | 00000nam 2200000zi 4500 |
| 001 | 9.946308 |
| 003 | CaOODSP |
| 005 | 20250916101457 |
| 006 | m o d f |
| 007 | cr cn||||||||| |
| 008 | 241218t20252025oncbd ob f000 0 eng d |
| 020 | |a9780660749969 |
| 040 | |aCaOODSP|beng|erda|cCaOODSP |
| 043 | |an-cnh-- |
| 086 | 1 |aM103-3/93-2024E-PDF |
| 100 | 1 |aHong, G. |q(Gang)|eauthor. |
| 245 | 10|aMonthly vegetation essential climate variable maps for the Hudson Bay Lowland using the LEAF-toolbox implementation of the SL2P algorithm / |cG. Hong, R.A. Fernandes, L. Sun, and N. Djamai. |
| 264 | 1|a[Ottawa] : |bGeomatics Canada, |c2025. |
| 264 | 4|c©2025 |
| 300 | |a1 online resource (iii, 18 pages) : |bmaps, graphs. |
| 336 | |atext|btxt|2rdacontent |
| 337 | |acomputer|bc|2rdamedia |
| 338 | |aonline resource|bcr|2rdacarrier |
| 490 | 1 |aOpen file, |x2292-7875 ; |v93 |
| 504 | |aIncludes bibliographical references (pages 17-18). |
| 520 | 3 |a"Leaf area index (LAI), fraction of canopy cover (fCOVER), and fraction of absorbed photosynthetically active radiation (FAPAR) are essential climate variables and widely used in monitoring, understanding, and modeling activities related to land surfaces. Landscape Evolution and Forecasting (LEAF) which includes the Simplified Level 2 Product Prototype Processor (SL2P) algorithm provides an efficient way to produce biophysical parameters in a regional level using Sentinel 2 or Landsat 8. This study applies LEAF to produce monthly LAI, fCOVER and FAPAR for supporting permafrost modeling in Hudson Bay Lowland. The limited field samples were used to assess the thematic performance of those products"--Abstract, page 1. |
| 650 | 0|aVegetation and climate|zHudson Bay. |
| 650 | 0|aVegetation mapping|zHudson Bay. |
| 650 | 0|aAlgorithms. |
| 650 | 6|aVégétation et climat|zHudson, Baie d'. |
| 650 | 6|aCartographie de la végétation|zHudson, Baie d'. |
| 650 | 6|aAlgorithmes. |
| 710 | 2 |aGeomatics Canada, |eissuing body. |
| 830 | #0|aOpen file (Geomatics Canada)|x2292-7875 ; |v93.|w(CaOODSP)9.821474 |
| 856 | 40|qPDF|s8.37 MB|uhttps://publications.gc.ca/collections/collection_2025/rncan-nrcan/m103-3/M103-3-93-2024-eng.pdf |
| 856 | 40|qHTML|sN/A|uhttps://doi.org/10.4095/pbvvgcknc5 |