Annual Mean Leaf Area Index dataset at 1km Resolution in the Belt and Road and Surround Region (2015)
LI Jing1LIU Qinhuo1ZHAO Jing1LIN Shangrong1ZHONG Bo1WU Shanlong1
1 State Key Laboratory of Remote Sensing Science，Institute of Remote Sensing and Digital Earth，Chinese Academy of Sciences
DOI:10.3974/geodb.2017.04.02.V1
Published:Nov. 2017
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Key Words：
the Belt and Road and Surround Region,Leaf area index (LAI),annual mean leaf area index (AMLAI),2015
Abstract：
Leaf area index (LAI) is defined as half the total foliage area per unit ground surface area, and is a critical structural variable for quantifying the exchange processes of energy and matter between the land surface and atmosphere. The Annual Mean Leaf Area Index Dataset covering R&B and Adjacent Area in 1km Resolution (2015) was developed based on the 1 km/5 day LAI data product, which was integrated based on the concurrent use of multiple sensors (including Terra/MODIS, Aqua/MODIS, FY3A/VIRR, FY3B/VIRR, FY-3A/MERSI, and FY-3B/MERSI), as well as DEM and land-cover and land-use maps. The annual mean LAI of 2015, i.e. AMLAI is the mean values of LAI within the year of 2015 after the time series reconstruction from the 1 km/5 day LAI products. The AMLAI ranges from 0 to 10, and the higher value of AMLAI presents a better growth conditions of vegetation. The spatial distribution pattern of AMLAI is related to the vegetation types. AMLAI of the tropical rainforest near the equator is close to 6; AMLAI of the subtropical forest and shrub is between 3 and 5; AMLAI of the farmland with multi-season crops is between 2 and 3; AMLAI of coniferous forest near the 40°N is about 2; and AMLAI of the other grassland and farmland is generally lower than 2. The AMLAI dataset was archived as .tif data format with the compressed data size of 138 MB.
Foundation Item：
Ministry of Science and Technology of P. R. China (2012AA12A304; 2012AA12A305; 2013AA12A301)
Data Citation：
LI Jing, LIU Qinhuo, ZHAO Jing, LIN Shangrong, ZHONG Bo, WU Shanlong. Annual Mean Leaf Area Index dataset at 1km Resolution in the Belt and Road and Surround Region (2015)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2017. https://doi.org/10.3974/geodb.2017.04.02.V1.
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MuSyQ-AMLAI-1km-2015.rar |
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