Landsats Aff

Bio-D – Landsat Key – Data Continuity

Landsat is key to our long-term heritage – consistent data continuity
Leimgruber et al 5 (Peter, Conservation and Research Center, National Zoological Park, Smithsonian Institution, Catherine A. Christen, same, and Alison Laborderie, Durrell Institute of Conservation and Ecology at U Kent, Environmental Monitoring and Assessment 106: p. 81–101, http://nationalzoo.si.edu/Publications/ScientificPublications/pdfs/E48D1034-C95B-4400-ABB5-66A1E5A32EC8.pdf, accessed 7-6-11, JMB)

Concluding from these observations, we suggest there is a justified need for global satellite monitoring of Earth resources that provides rapid, inexpensive and consistent access to this type of information. Existing data, already increasingly accessible via the Internet, represent historical records of our natural heritage and should be made even more easily available to the public just as is being done with the holdings of major libraries and archival collections. Maintaining such accessible data repositories will not only be invaluable for short- and mid-term environmental policy decisions; by complementing other varieties of historical records, including natural history museum collections and land tenure data, these satellite-derived data repositories will provide future generations with accurate evidence of changes in human culture and value systems. Ongoing satellite monitoring programs need to be developed to create a consistently comparable record extending indefinitely the lineage of this historical resource. Data continuity should always be a major consideration in the development of future programs. Much of the Landsat program’s success can be attributed to a) its 30-m spatial resolution that allows for enough detail to detect land use changes; b) its long data continuity, providing records of how the Earth’s land has changed over two to three decades, and c) recent Landsat data acquisition strategies permitting cloud-free images and seasonal assessments while providing global coverage. Calls for a new Landsat satellite should be formulated as calls for a guaranteed continued operational Earth resource satellite program with similar or even improved attributes. New, and different, satellites and sensors launched since the late 1990s, as components of NASA’s new Earth Observing System (EOS), may provide data continuity fulfilling the basic requirements for such a program. However, so far these data are not as accessible as Landsat data. The imagery comes from newly developed and hence still largely experimental sensors. Currently most of these data seem not to be collected with the goal of global environmental monitoring. Although it may be technically possible, regular and complete coverage of Earth is not presently achieved by these satellite-based monitoring systems. In those cases where coverage is global, the spatial resolution is much lower than with Landsat. For example, the Moderate-Resolution Imaging Spectroradiometer (MODIS) offers only a spatial resolution of between 250 and 1,000 m. No clear plans have been communicated to a broader user community detailing a) how these sensors may fill the Landsat gap; b) whether the data acquired will adequately cover the entire globe and c) how, and at what cost, the data will be provided to end-users or archived for future use.

Bio-D – Landsat Key – AT: Need Higher Res

Landsat comparatively better at monitoring bio-d than higher resolution imagery
Nagendra et al 10 (Harini Nagendra 1,2, Duccio Rocchini 3 , Rucha Ghate 4 , Bhawna Sharma 1 and Sajid Pareeth 1; 1 Ashoka Trust for Research in Ecology and the Environment (B.S.); (S.P.) 2 Center for the Study of Institutions, Population, and Environmental Change (CIPEC), Indiana University, 3 IASMA Research and Innovation Centre, Fondazione Edmund Mach, Environment and Natural Resources Area, (D.R.) 4 SHODH: The Institute for Research and Development, Feb. 2, Remote Sens., 2, p. 478-496, http://www.mdpi.com/2072-4292/2/2/478/pdf, accessed 7-6-11, JMB)

High resolution satellite imagery, with pixel sizes of the size of 2–5 m, corresponding well to the size of individual tree crowns, has been declared as having much greater potential for mapping vegetation diversity and distributions [2,4,13,14]. In the past decade, the launch of very high spatial resolution satellite sensors like IKONOS, QuickBird, OrbView-3 and the Panchromatic band of IRS LISS-3 have provided researchers with the opportunity to study ecological systems at far greater detail than previously possible. These data have been used in multiple studies for plant diversity assessment in habitats with a smaller number of tree species, such as mangroves, temperate forests and boreal forests (e.g., [15-18]). Yet the fine spatial resolution provided by these sensors can lead to problems. When pixel dimensions shrink to a point where individual pixels are smaller than the size of individual tree crowns, then pixel-pixel variability increases dramatically. For instance, some pixels may cover a leaf in sunshine while others cover a leaf of the same tree in shade, in gaps between leaves, or even on tree bark—making it hard to handle relatively simple tasks like delineating tree canopies, let alone assigning signatures to different species [11]. Further, in comparison to hyperspatial data, medium resolution sensors such as Landsat have a greater number of bands and are able to record additional information in the middle infrared range, which relates to a range of critical plant properties including leaf pigment, water content, and chemical composition, and can be very useful for discriminating tree species [19-22]. Landsat also provides data over a longer period of time than most other remote sensing platforms, which makes it of great use for monitoring programs [14,23].
Even if hyperspatial imagery is good, combining it with Landsat is key
Olson et al 2 (David M., Eric Dinerstein, George V. N. Powell, and Er D. Wikramanayake, Conservation Science Program, World Wildlife Fund, Conservation Biology, p. 1-3, Vol. 16, No. 1, Feb, EBSCO, JMB)

Table 1 describes the spatial and spectral resolution, the geographic coverage, temporal frequency and cost of the satellite sensors and platforms routinely used for biodiversity studies and vegetation mapping today. While hyperspectral data are generated at medium spatial resolutions of 20–30 m at best, hyperspatial data are usually multispectral, spanning 4–5 bands. The increased cost of these data limits their use in scientific studies (Gillespie et al. 2008). Further, unlike older satellite programs such as Landsat, hyperspectral and hyperspatial sensors, whether airborne or satellite borne, do not routinely cover all areas of the globe at repeated intervals of time (Loarie et al. 2007). Instead, they collect images when commissioned. Thus, obtaining archival data for a specific area and time period is a matter of chance, even if one has the money available for such research. Given the relatively recent arrival of these instruments, and their limited geographic spread, their utility will only be realized to the full when they will be coupled with existing large scale monitoring systems that currently utilize moderate resolution multispectral data like SPOT, ASTER, and Landsat TM/ETM+ to great effect (Duro et al. 2007)