Landsats Aff

Water – Solvency – Accuracy

Landsats solve—atmospheric correction is crucial to accuracy.
Schroeder et al 6 (Todd A., Warren B. Cohen, Conghe Song, Morton J., Canty, Zhiquiang Yang, Dept. Forest Science, UO, Forest Science Lab, Dep. Geo @ North Carolina, Systems Analysis @ Munich, http://ddr.nal.usda.gov/bitstream/10113/38625/1/IND44322324.pdf, accessed 7/5/11) CJQ

Detecting and characterizing continuous changes in early forest succession using multi-temporal satellite imagery requires atmospheric correction procedures that are both operationally reliable, and that result in comparable units (e.g., surface reflectance). This paper presents a comparison of five atmospheric correction methods (2 relative, 3 absolute) used to correct a nearly continuous 20-year Landsat TM/ETM+ image data set (19-images) covering western Oregon (path/row 46/29). In theory, full absolute correction of individual images in a time-series should effectively minimize atmospheric effects resulting in a series of images that appears more similar in spectral response than the same set of uncorrected images. Contradicting this theory, evidence is presented that demonstrates how absolute correction methods such as Second Simulation of the Satellite Signal in the Solar Spectrum (6 s), Modified Dense Dark Vegetation (MDDV), and Dark Object Subtraction (DOS) actually make images in a time-series somewhat less spectrally similar to one another. Since the development of meaningful spectral reflectance trajectories is more dependant on consistent measurement of surface reflectance rather than on accurate estimation of true surface reflectance, correction using image pairs is also tested. The relative methods tested are variants of an approach referred to as “absolute-normalization”, which matches images in a time-series to an atmospherically corrected reference image using pseudo-invariant features and reduced major axis (RMA) regression. An advantage of “absolute-normalization” is that all images in the time-series are converted to units of surface reflectance while simultaneously being corrected for atmospheric effects. Of the two relative correction methods used for “absolute-normalization”, the first employed an automated ordination algorithm called multivariate alteration detection (MAD) to statistically locate pseudo-invariant pixels between each subject and reference image, while the second used analyst selected pseudo-invariant features (PIF) common to the entire image set. Overall, relative correction employed in the “absolute-normalization” context produced the most consistent temporal reflectance response, with the automated MAD algorithm performing equally as well as the handpicked PIFs. Although both relative methods performed nearly equally in terms of observed errors, several reasons emerged for preferring the MAD algorithm. The paper concludes by demonstrating how “absolutenormalization” improves (i.e., reduces scatter in) spectral reflectance trajectory models used for characterizing patterns of early forest succession.

Water – Landsats Key

Landsats are key—five reasons.
NASA 7 (http://landsat.gsfc.nasa.gov/pdf_archive/soc_0011.pdf, accessed 7/4/11)CJQ

The Landsat satellites have a number of characteristics that make them well suited for water-use mapping: (1) The spatial resolution of Landsat enables water managers to map water use for individual agricultural fields and thereby manage on a field-by-field basis. With coarser-resolution data this doesn't work. Landsat's “resolution helps us to resolve water consumption on the scales of anthropogenic interaction and land ownership,” Allen explains. (2) Landsat's spectral resolution includes a thermal infrared band. This thermal information is essential for water-use mapping because the mapping process is predicated on the fundamental principle that evaporating water absorbs energy, i.e. the more water fields are losing through ET, the cooler they are. (3) There is now an archive containing a quarter of a century worth of global Landsat data that has the spatial resolution, spectral coverage, and thermal imagery needed for water-use mapping. “Landsat provides continuity to assess change in ET over time and to document historical water consumption,” Allen says—an essential capability in the U.S. West, where water rights often are established by historical precedence. As Levitt puts it, “METRIC allows water resource administrators to go back in time and see consumptive use.” (4) The Landsat satellites' orbit place them overhead during morning hours, avoiding common afternoon cloud cover. (5) The entire Landsat archive is freely available. As Morse highlights, “all parties to a water dispute have equal access to a primary data source.”

Landsats successfully track water usage and are crucial to further water rights and management

NASA 7 (http://landsat.gsfc.nasa.gov/pdf_archive/soc_0011.pdf, accessed 7/4/11) CJQ

Detailed water consumption maps can be made quickly and easily with Landsat because of its 30 m spatial resolution and thermal imaging capability. Landsat has been proclaimed “the best and least expensive way to quantify and locate where water is used and in what quantity,” by Anthony Morse and Richard Allen, two water management specialists from Idaho. 11 Former World Bank economist, Dr. Chris Perry, predicts that, “We may expect significant improvements in the productivity of water—the crop per drop—by the analysis and debate facilitated by better data.” 12 Landsat data have been used successfully not only to quantify water consumed by irrigation, but also to establish water rights, to facilitate the transfer of water entitlements, and to estimate aquifer depletions and quantify net ground-water pumpage in areas where water extraction from underground is not measured. 13 A closer look at Landsat’s role Landsat data, including visible, near infrared, mid-infrared, and thermal information, for a particular geographic region are fed into a relatively sophisticated energy balance model that outputs evapotranspiration maps. 14 Evapotranspiration (ET) refers to the conversion of water into water vapor by the dual process of evaporation from the soil and transpiration (the escape of water though plant’s stomata). 15 For vegetated land, ET is synonymous with water consumption. 16 Maps of water consumption made with moderate resolution Landsat data enable water resources managers and administrators to determine how much water was consumed from individual fields. And, because the spatial nature of Landsat data lends itself to the monitoring of seasonal evapotranspiration trends, managers can use the information to determine which complex irrigation schedules should be pursued and how to time water releases from dams. “Remote sensing, applied to the measurement of ET over large areas, provides analysts of irrigation systems with extraordinary new tools for the objective assessment of consumption and production—constituting a quantum leap in the assessment of irrigation system performance,” Perry wrote in 2003. 17

Thermal band use is crucial to establishing water rights—multiple countries.

NASA 7 (http://landsat.gsfc.nasa.gov/pdf_archive/soc_0011.pdf, accessed 7/4/11)CJQ

“Satellite imagery, especially in the thermal bands, can and will revolutionize the establishment of water rights in the many parts of the world where they are insecure,” says Perry, who has worked on many water resources projects in developing countries. 24 Outside of the U.S., the contentious issue of securing water rights can be limited by data. “There are numerous aid programs from large donors such as the World Bank and Asian Development Bank that want to help manage water resources more effectively and productively, but nobody has the proper data,” Bastiaanssen says, but he continues, “with Landsat we can map out soil moisture, water consumption, water stress, crop yield.” 25 Increasingly, the World Bank must deal with the overdraft of aquifers. They have labeled the unsustainable water mining “critical” in the North China Plain, Jordan, Mexico, Northern India, Israel, Palestine and Yemen. 26 Meanwhile, Landsat has helped the World Bank successfully manage water projects in China, Mexico, and Yemen, as well as Egypt, Saudi Arabia, Uzbekistan, and Kazakhstan. 27 In Turkey, Pakistan, Sri Lanka, India and China remote sensing has been demonstrated as a key tool for the strategic planning of water productivity on a basin wide scale.