(preferably at least weekly but every 2–3 days is better), appropriate spectral bands
(discussed further below), and images that are inexpensive or available for free. As
Table 1 indicates, all current sensors fail to meet one or more of these criteria. The
Medium Resolution Imaging Spectrometer (MERIS) sensor on the European satellite Envisat came closest to meeting the above criteria, but it has not been operational since 2012, and its pixel size (300 m
2 ) limited it to moderately large lakes
(> 150 ha [~370 ac]). For Minnesota, its spatial resolution provided measurements
for only ~8 % of the state’s lakes [1].
This situation leaves Landsat and related satellites (Table 1) as the current
“default systems” for inland lake monitoring by ORS. The Landsat series was
designed primarily for land features and has been hugely important for land
use/land cover analyses, vegetation condition, and agricultural applications, but
Landsat sensors also have been used for over 30 years to estimate some water
quality variables on inland lakes [71–76]. The biggest drawback of the Landsat
sensors, aside from low temporal resolution (repeat coverage every 16 days), is
their limited and coarse spectral resolution (only 3–4 bands in the visible range
(e.g., for Landsat 5 and 7: band 1, 450–520 nm; band 2, 520–600 nm; band 3, 630–
690 nm; Landsat 8 added a new band 1, 430–450 nm, and slightly narrowed the
ranges for the earlier three bands, which now are designated band 2 through band
4). As described in Sect. 2.2.5, this may hinder the accurate retrieval of data on
important variables like chlorophyll in waters with complex optical properties and
also limits the types of algorithms applicable to Landsat data.
A class of multispectral sensors with high spatial resolution (Table 1) could be
used for more locally based regions, such as city-scale projects. This imagery can
be fairly expensive, but for important areas and projects, it has the advantage of
being able to monitor smaller water bodies than Landsat can. For example, Sawaya
et al. [21] found that IKONOS imagery worked as well as Landsat for water clarity
(SD) assessment, and a single image was able to assess the clarity of 236 lakes and
ponds as small as 0.08 ha in the City of Eagan, Minnesota. In contrast, Landsat
imagery was able to assess only 48 of the water bodies (minimum size of 1.5 ha).
The spatial resolution of IKONOS and QuickBird images has made them particularly useful for aquatic plant surveys [21, 22]. Several high-resolution systems
are now operational (Table 1), but WorldView-2 and WorldView-3 with 8 and
28 spectral bands, respectively, may be particularly useful for water quality
assessments.
Launched in February 2013 with a new Operational Land Imager (OLI) sensor,
Landsat 8 has several improvements over the Thematic Mapper (TM) and
Enhanced Thematic Mapper (ETM+) instruments on previous Landsat satellites.
The OLI sensor has improved signal-to-noise ratio, radiometric resolution (12-bit
vs. 8-bit for Landsat 5 and 7), and two new spectral bands—a shorter wavelength
blue band (see above) and a shortwave infrared band positioned to detect cirrus
clouds. These advancements should improve the ability to map variables like water
clarity and CDOM but may not improve the discrimination of chlorophyll from
SS min . Landsat 7 launched in 1999 continues to collect imagery and can be used for
water clarity assessments.
US government agencies have made significant investments in systems like the
Coastal Zone Color Scanner (CZCS), Sea-viewing Wide Field-of-view Sensor
Remote Sensing for Regional Lake Water Quality Assessment: Capabilities and. . .
129
(discussed further below), and images that are inexpensive or available for free. As
Table 1 indicates, all current sensors fail to meet one or more of these criteria. The
Medium Resolution Imaging Spectrometer (MERIS) sensor on the European satellite Envisat came closest to meeting the above criteria, but it has not been operational since 2012, and its pixel size (300 m
2 ) limited it to moderately large lakes
(> 150 ha [~370 ac]). For Minnesota, its spatial resolution provided measurements
for only ~8 % of the state’s lakes [1].
This situation leaves Landsat and related satellites (Table 1) as the current
“default systems” for inland lake monitoring by ORS. The Landsat series was
designed primarily for land features and has been hugely important for land
use/land cover analyses, vegetation condition, and agricultural applications, but
Landsat sensors also have been used for over 30 years to estimate some water
quality variables on inland lakes [71–76]. The biggest drawback of the Landsat
sensors, aside from low temporal resolution (repeat coverage every 16 days), is
their limited and coarse spectral resolution (only 3–4 bands in the visible range
(e.g., for Landsat 5 and 7: band 1, 450–520 nm; band 2, 520–600 nm; band 3, 630–
690 nm; Landsat 8 added a new band 1, 430–450 nm, and slightly narrowed the
ranges for the earlier three bands, which now are designated band 2 through band
4). As described in Sect. 2.2.5, this may hinder the accurate retrieval of data on
important variables like chlorophyll in waters with complex optical properties and
also limits the types of algorithms applicable to Landsat data.
A class of multispectral sensors with high spatial resolution (Table 1) could be
used for more locally based regions, such as city-scale projects. This imagery can
be fairly expensive, but for important areas and projects, it has the advantage of
being able to monitor smaller water bodies than Landsat can. For example, Sawaya
et al. [21] found that IKONOS imagery worked as well as Landsat for water clarity
(SD) assessment, and a single image was able to assess the clarity of 236 lakes and
ponds as small as 0.08 ha in the City of Eagan, Minnesota. In contrast, Landsat
imagery was able to assess only 48 of the water bodies (minimum size of 1.5 ha).
The spatial resolution of IKONOS and QuickBird images has made them particularly useful for aquatic plant surveys [21, 22]. Several high-resolution systems
are now operational (Table 1), but WorldView-2 and WorldView-3 with 8 and
28 spectral bands, respectively, may be particularly useful for water quality
assessments.
Launched in February 2013 with a new Operational Land Imager (OLI) sensor,
Landsat 8 has several improvements over the Thematic Mapper (TM) and
Enhanced Thematic Mapper (ETM+) instruments on previous Landsat satellites.
The OLI sensor has improved signal-to-noise ratio, radiometric resolution (12-bit
vs. 8-bit for Landsat 5 and 7), and two new spectral bands—a shorter wavelength
blue band (see above) and a shortwave infrared band positioned to detect cirrus
clouds. These advancements should improve the ability to map variables like water
clarity and CDOM but may not improve the discrimination of chlorophyll from
SS min . Landsat 7 launched in 1999 continues to collect imagery and can be used for
water clarity assessments.
US government agencies have made significant investments in systems like the
Coastal Zone Color Scanner (CZCS), Sea-viewing Wide Field-of-view Sensor
Remote Sensing for Regional Lake Water Quality Assessment: Capabilities and. . .
129