with 4.88 km, 39 km, or 1 degree mapping units compiled over daily, weekly,
monthly and yearly intervals (Esias et al., 1998). Products are available from
the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC,
http://daac.gsfc.nasa.gov/MODIS/) At the time of this writing, ocean color products
from the SeaWiFS (Sea-viewing Wide Field-of-view Sensor) and calibration of MODIS
ocean color products are in flux, with new products to be designated soon. In addition,
the number of MODIS products and distribution protocol and gateways are also under
review.
Another area of active ongoing research is how best to combine other data
available from ocean satellites, including wind, currents, cloud cover, and solar
radiation with sea surface temperature and degree-heating-weeks models to improve
prediction of the biological response that causes coral bleaching (e.g. Wooldridge and
Done, 2004). Mumby et al. (2004) point out that global map products of ultraviolet and
photosynthetically active radiation could be combined with water column attenuation
coefficients to estimate the solar radiation received by marine organisms. The potential
for integrating sea surface temperature data with data on reef geomorphology, coastal
habitats and adjacent land cover remains to be explored (cf., Andréfouët et al., 2004).
3.3 MODERATE SPATIAL RESOLUTION (20-100 METER) GLOBAL LAND
(COASTAL) PRODUCTS
Landsat Multispectral Scanner (MSS), Thematic Mapper (TM) and Enhanced
Thematic Mapper (ETM+) have been global workhorses for moderate resolution (30 m)
multispectral remote sensing. There are currently several free or low-cost sources of
archival data that make it easy to add Landsat information into management
http://glcf.
data provides
data circa
1980s, 1990s and 2000, orthorectified to facilitate comparisons
of change over
time (Tucker et al., 2004). Other moderate resolution sensors such as SPOT (Système
pour l’Observation de la Terre), HRV (High Resolution Visible ), and ASTER
(Advanced Spaceborne Thermal Emission and Reflection Radiometer), are also available.
Most multispectral optical sensors use bands selected to respond to vegetation
signals in the red and near infrared, so multispectral data are well-suited to the detection
of wetland vegetation and mangroves. Spatial scale is a key factor in using different
data sources (e.g. Ramsey and Laine, 1997). For example, marsh vegetation becomes
increasingly sparse as the habitat degrades. Subpixel analysis of the amount of water,
soil and vegetation can help to monitor “health” of a marsh (Kearney et al., 1995). The
detection of different levels of habitat loss or degradation can be dependent on the scale
of the source data. In temperate marshes, seasonal changes in vegetation (senescence
and regrowth) are also important considerations. The more complex and heterogeneous
the marsh, the more challenging it can be to get good classifications of wetland
vegetation types and accurate estimates of change (Ramsey and Laine, 1997). As a
class of coastal vegetation, coastal mangroves exhibit a strong multispectral signal and
are well-suited to mapping from most multispectral satellite sensors, but discrimination
of mangrove types can also be more challenging (Green et al., 1998).
Although numerous regional studies have mapping data that could be used for
synthesis, there is only one nearly global classified landcover product at moderate
resolution, the Geocover-LC product produced by Earthsat Corporation.
analyses (especially the University of Maryland’s Global Land Cover Facility,
umiacs.umd.edu). NASA’s “Geocover” set of global orthorectified Landsat
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Data Synthesis for Management
monthly and yearly intervals (Esias et al., 1998). Products are available from
the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC,
http://daac.gsfc.nasa.gov/MODIS/) At the time of this writing, ocean color products
from the SeaWiFS (Sea-viewing Wide Field-of-view Sensor) and calibration of MODIS
ocean color products are in flux, with new products to be designated soon. In addition,
the number of MODIS products and distribution protocol and gateways are also under
review.
Another area of active ongoing research is how best to combine other data
available from ocean satellites, including wind, currents, cloud cover, and solar
radiation with sea surface temperature and degree-heating-weeks models to improve
prediction of the biological response that causes coral bleaching (e.g. Wooldridge and
Done, 2004). Mumby et al. (2004) point out that global map products of ultraviolet and
photosynthetically active radiation could be combined with water column attenuation
coefficients to estimate the solar radiation received by marine organisms. The potential
for integrating sea surface temperature data with data on reef geomorphology, coastal
habitats and adjacent land cover remains to be explored (cf., Andréfouët et al., 2004).
3.3 MODERATE SPATIAL RESOLUTION (20-100 METER) GLOBAL LAND
(COASTAL) PRODUCTS
Landsat Multispectral Scanner (MSS), Thematic Mapper (TM) and Enhanced
Thematic Mapper (ETM+) have been global workhorses for moderate resolution (30 m)
multispectral remote sensing. There are currently several free or low-cost sources of
archival data that make it easy to add Landsat information into management
http://glcf.
data provides
data circa
1980s, 1990s and 2000, orthorectified to facilitate comparisons
of change over
time (Tucker et al., 2004). Other moderate resolution sensors such as SPOT (Système
pour l’Observation de la Terre), HRV (High Resolution Visible ), and ASTER
(Advanced Spaceborne Thermal Emission and Reflection Radiometer), are also available.
Most multispectral optical sensors use bands selected to respond to vegetation
signals in the red and near infrared, so multispectral data are well-suited to the detection
of wetland vegetation and mangroves. Spatial scale is a key factor in using different
data sources (e.g. Ramsey and Laine, 1997). For example, marsh vegetation becomes
increasingly sparse as the habitat degrades. Subpixel analysis of the amount of water,
soil and vegetation can help to monitor “health” of a marsh (Kearney et al., 1995). The
detection of different levels of habitat loss or degradation can be dependent on the scale
of the source data. In temperate marshes, seasonal changes in vegetation (senescence
and regrowth) are also important considerations. The more complex and heterogeneous
the marsh, the more challenging it can be to get good classifications of wetland
vegetation types and accurate estimates of change (Ramsey and Laine, 1997). As a
class of coastal vegetation, coastal mangroves exhibit a strong multispectral signal and
are well-suited to mapping from most multispectral satellite sensors, but discrimination
of mangrove types can also be more challenging (Green et al., 1998).
Although numerous regional studies have mapping data that could be used for
synthesis, there is only one nearly global classified landcover product at moderate
resolution, the Geocover-LC product produced by Earthsat Corporation.
analyses (especially the University of Maryland’s Global Land Cover Facility,
umiacs.umd.edu). NASA’s “Geocover” set of global orthorectified Landsat
291
Data Synthesis for Management