A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia

The areal extent and spatial distribution of evergreen forests in the tropical zones are important for the study of climate, carbon cycle and biodiversity. However, frequent cloud cover in the tropical regions makes mapping evergreen forests a challenging task. In this study we developed a simple an...

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Main Authors: Tunrayo Alabi, Michael Keller, Christina Czarnecki, Chandrashekhar M. Biradar, Xiangming Xiao
Format: Article
Language:English
Published: MDPI AG 2009-08-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/1/3/355/
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author Tunrayo Alabi
Michael Keller
Christina Czarnecki
Chandrashekhar M. Biradar
Xiangming Xiao
author_facet Tunrayo Alabi
Michael Keller
Christina Czarnecki
Chandrashekhar M. Biradar
Xiangming Xiao
author_sort Tunrayo Alabi
collection DOAJ
description The areal extent and spatial distribution of evergreen forests in the tropical zones are important for the study of climate, carbon cycle and biodiversity. However, frequent cloud cover in the tropical regions makes mapping evergreen forests a challenging task. In this study we developed a simple and novel mapping algorithm that is based on the temporal profile analysis of Land Surface Water Index (LSWI), which is calculated as a normalized ratio between near infrared and shortwave infrared spectral bands. The 8-day composites of MODIS Land Surface Reflectance data (MOD09A1) in 2001 at 500-m spatial resolution were used to calculate LSWI. The LSWI-based mapping algorithm was applied to map evergreen forests in tropical Africa, America and Asia (30°N–30°S). The resultant maps of evergreen forests in the tropical zone in 2001, as estimated by the LSWI-based algorithm, are compared to the three global forest datasets [FAO FRA 2000, GLC2000 and the standard MODIS Land Cover Product (MOD12Q1) produced by the MODIS Land Science Team] that are developed through complex algorithms and processes. The inter-comparison of the four datasets shows that the area estimate of evergreen forest from the LSWI-based algorithm fall within the range of forest area estimates from the FAO FRA 2000, GLC2000 and MOD12Q1 at a country level. The area and spatial distribution of evergreen forests from the LSWI-based algorithm is to a large degree similar to those of the MOD12Q1 produced by complex mapping algorithms. The results from this study demonstrate the potential of the LSWI-based mapping algorithm for large-scale mapping of evergreen forests in the tropical zone at moderate spatial resolution.
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spelling doaj.art-8a617e7425254eaa80d92bd18124b2752022-12-21T19:46:13ZengMDPI AGRemote Sensing2072-42922009-08-011335537410.3390/rs1030355A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and AsiaTunrayo AlabiMichael KellerChristina CzarneckiChandrashekhar M. BiradarXiangming XiaoThe areal extent and spatial distribution of evergreen forests in the tropical zones are important for the study of climate, carbon cycle and biodiversity. However, frequent cloud cover in the tropical regions makes mapping evergreen forests a challenging task. In this study we developed a simple and novel mapping algorithm that is based on the temporal profile analysis of Land Surface Water Index (LSWI), which is calculated as a normalized ratio between near infrared and shortwave infrared spectral bands. The 8-day composites of MODIS Land Surface Reflectance data (MOD09A1) in 2001 at 500-m spatial resolution were used to calculate LSWI. The LSWI-based mapping algorithm was applied to map evergreen forests in tropical Africa, America and Asia (30°N–30°S). The resultant maps of evergreen forests in the tropical zone in 2001, as estimated by the LSWI-based algorithm, are compared to the three global forest datasets [FAO FRA 2000, GLC2000 and the standard MODIS Land Cover Product (MOD12Q1) produced by the MODIS Land Science Team] that are developed through complex algorithms and processes. The inter-comparison of the four datasets shows that the area estimate of evergreen forest from the LSWI-based algorithm fall within the range of forest area estimates from the FAO FRA 2000, GLC2000 and MOD12Q1 at a country level. The area and spatial distribution of evergreen forests from the LSWI-based algorithm is to a large degree similar to those of the MOD12Q1 produced by complex mapping algorithms. The results from this study demonstrate the potential of the LSWI-based mapping algorithm for large-scale mapping of evergreen forests in the tropical zone at moderate spatial resolution.http://www.mdpi.com/2072-4292/1/3/355/MODIS imageland surface water indextemporal profile analysisevergreen forests
spellingShingle Tunrayo Alabi
Michael Keller
Christina Czarnecki
Chandrashekhar M. Biradar
Xiangming Xiao
A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia
Remote Sensing
MODIS image
land surface water index
temporal profile analysis
evergreen forests
title A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia
title_full A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia
title_fullStr A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia
title_full_unstemmed A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia
title_short A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia
title_sort simple algorithm for large scale mapping of evergreen forests in tropical america africa and asia
topic MODIS image
land surface water index
temporal profile analysis
evergreen forests
url http://www.mdpi.com/2072-4292/1/3/355/
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