NDLI: Views on the application of MODIS image in forest mapping and forest type identification

Content Provider	IEEE Xplore Digital Library
Author	Liming Bai
Copyright Year	2013
Description	Author affiliation: Coll. of Bus. Adm., Guangxi Univ. of Finance & Econ., Nanning, China (Liming Bai)
Abstract	The Moderate-resolution Imaging Spectroradiometer (MODIS) is an important sensor on board the Aqua satellite and the Terra satellite in the Earth Observation System (EOS). In remotely sensed mapping of the complex forest vegetation with low-resolution satellite data as MODIS, how to improve the accuracy of information extraction and enhance the effectiveness of data mining have become aroused general interest in forestry. Based on analyzing the current application status of MODIS data in forest mapping, this paper suggests several spectral bands and products which are used relatively rare at present but valuable for future research, and proposes some critical issues in MODIS forest mapping and forest type identification, namely, mixed pixel decomposition, reconstruction of vegetation index time-series dataset, auxiliary application of biophysical parameters, forest type identification based on the bidirectional reflectance distribution function (BRDF) model and coupling or process imitation of hyperspectral remote sensing data. Holistic and integrated utilization of spectral, temporal, biophysical and angle information has great potential in vegetation mapping.
Sponsorship	Dar Al-Uloom Univ.
Starting Page	1
Ending Page	4
File Size	240262
Page Count	4
File Format	PDF
ISBN	9781467352840
e-ISBN	9781467352857
DOI	10.1109/ICCAT.2013.6522060
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-20
Publisher Place	Tunisia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Satellites Vegetation mapping Forest mapping Biophisical parameters Bidirectional reflectance distribution function model Indexes MODIS Hyperspectral remote sensing Hyperspectral imaging
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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