The Shuttle Radar Technology Mission (SRTM) was used to gather data for digital elevation.New Millennium era: The new millennium era (Bailey et al., 2001) refers to highly advanced ��test-of concept�� satellites sent into orbit around the same time as EOS era, but the concepts 1|]# and ideas are different. These are basically satellites and sensors for the next generation. These include Earth Observing-1 carrying the first spaceborne hyperspectral data. The idea of Advanced Land Imager (ALI) as a cheaper, technologically better replacement for Landsat is also very attractive.Private industry era: The private industry era began at the end of the last millennium and beginning of this millennium (see Stoney, 2005).

This era consists of a number of innovations. First, collection of data in very high resolution (<10 meter).

This is typified by IKONOS and Quickbird satellites. Second, a revolutionary means of data collection. This is typified by Rapideye satellite constellation of 5 satellites, having almost daily coverage of any spot on earth at 6.5 meter resolution in 5 spectral bands including a red-edge band. Third, is the introduction of micro satellites, some under disaster monitoring constellation (DMC), which are designed and launched by surrey satellite technology Ltd. for Turkey, Nigeria, China, USGS, UK, and others. Fourth, is the innovation by Google Earth (http://earth.google.

com) in making rapid data access of VHRI for any part of the World through streaming technology that makes it easy for even a non-specialist to zoom and pan remote sensing data.Table 1.

Satellite sensor data characteristics1.2. Summary of sensors in environmental modelingA state-of-art of satellite sensors widely used in environmental applications and natural resources management are given in Table 1. These sensors provide data in a wide range of scales (or Entinostat pixel resolutions), radiometry, band numbers, and band widths and provides distinct advantage of consistency of data, synoptic coverage, global reach, cost per unit area, repeatability, precision, and accuracy. Added to this is the long-time series of archives and pathfinder datasets (e.g.

, Tucker, 2005, Agbu and James, 1994) that have global coverage. Much of this data is also free and accessible online.Many applications (e.g., Thenkabail et al., 2006) in environmental monitoring require frequent coverage of the same area. This can be maximized by using data from multiple sensors (Table 1). However, since data from these sensors are acquired Cilengitide in multiple resolution (spatial, spectral, radiometric), multiple bandwidth, and in varying conditions, they need to be harmonized and synthesized before being used (Thenkabail et al., 2004).