@inbook{4505815643544957b1c8ac209ed420b3,
title = "Integrating Landsat with MODIS Products for Vegetation Monitoring",
abstract = "Satellite imagery provides a valuable data source for monitoring vegetation from space. In order to monitor vegetation dynamic and changes, high spatial resolution satellite imagery with frequent acquisition is required. However, current satellite systems cannot satisfy these requirements due to either technical or fiscal difficulties. In recent years, studies have been focused on integrating high spatial resolution Landsat and high temporal resolution MODIS data for vegetation monitoring. This chapter describes three categories of approach to integrate two data sources. The first category approach adopts MODIS algorithms for Landsat data processing. The second category approach blends Landsat and MODIS data through a data fusion approach. The third category approach normalizes Landsat data using standard MODIS data products. This chapter presents examples and recent applications on the integration of Landsat and MODIS data. Their advantages and limitations are discussed.",
keywords = "leaf area index, land cover type, surface reflectance, aerosol optical thickness, landsat data",
author = "Feng Gao",
year = "2015",
month = apr,
day = "9",
doi = "10.1007/978-94-007-5872-8_16",
language = "English",
isbn = "9789400758711",
series = "Springer Atmospheric Sciences",
publisher = "Springer Netherlands",
pages = "247--261",
editor = "Qu, {John J.} and {Powell, Jr.}, {Alfred M.} and Sivakumar, {M. V. K.}",
booktitle = "Satellite-Based Applications on Climate Change",
address = "Netherlands",
edition = "2013",
}