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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the regeneration of floodplain forest. This dataset uses lidar derivatives to identify forest canopy gaps along select portions of the Mississippi River and Illinois River. USACE will use this dataset to select field sites to collect data in forest canopy gaps. This will also serve as the baseline for long-term forest canopy gap study.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the regeneration of floodplain forest. This dataset uses lidar derivatives to identify forest canopy gaps along select portions of the Mississippi River and Illinois River. USACE will use this dataset to select field sites to collect data in forest canopy gaps. This will also serve as the baseline for long-term forest canopy gap study.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the regeneration of floodplain forest. This dataset uses lidar derivatives to identify forest canopy gaps along select portions of the Mississippi River and Illinois River. USACE will use this dataset to select field sites to collect data in forest canopy gaps. This will also serve as the baseline for long-term forest canopy gap study.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the regeneration of floodplain forest. This dataset uses lidar derivatives to identify forest canopy gaps along select portions of the Mississippi River and Illinois River. USACE will use this dataset to select field sites to collect data in forest canopy gaps. This will also serve as the baseline for long-term forest canopy gap study.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the regeneration of floodplain forest. This dataset uses lidar derivatives to identify forest canopy gaps along select portions of the Mississippi River and Illinois River. USACE will use this dataset to select field sites to collect data in forest canopy gaps. This will also serve as the baseline for long-term forest canopy gap study.
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In 2007, the U.S Army Corps of Engineers’ Upper Mississippi River Restoration (UMRR) program partnered with the Iowa Department of Natural Resources (IDNR) to collect FEMA-grade, bluff-to-bluff lidar for Navigation Pools 8-24 of the UMRS. In 2009, with American Recovery and Reinvestment (ARRA) funds awarded to UMRR, the remaining lidar for the Upper Mississippi River, to the confluence with the Ohio River, and the Illinois River was contracted. Data acquisition was completed in 2011. Lidar data are remotely sensed, high-resolution elevation data collected by airplane. The Upper Midwest Environmental Sciences Center is processing these data to create Digital Elevation Models (DEMs), 0.5 meter contour lines, and pool-wide...
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In 2007, the U.S Army Corps of Engineers’ Upper Mississippi River Restoration (UMRR) program partnered with the Iowa Department of Natural Resources (IDNR) to collect FEMA-grade, bluff-to-bluff lidar for Navigation Pools 8-24 of the UMRS. In 2009, with American Recovery and Reinvestment (ARRA) funds awarded to UMRR, the remaining lidar for the Upper Mississippi River, to the confluence with the Ohio River, and the Illinois River was contracted. Data acquisition was completed in 2011. Lidar data are remotely sensed, high-resolution elevation data collected by airplane. The Upper Midwest Environmental Sciences Center is processing these data to create Digital Elevation Models (DEMs), 0.5 meter contour lines, and pool-wide...
thumbnail
As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the regeneration of floodplain forest. This dataset uses lidar derivatives to identify forest canopy gaps along select portions of the Mississippi River and Illinois River. USACE will use this dataset to select field sites to collect data in forest canopy gaps. This will also serve as the baseline for long-term forest canopy gap study.
As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
thumbnail
As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
    map background search result map search result map Forest Canopy Gaps Identified by Lidar for Navigational Pool 8 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 9 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 13 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 21 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 24 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 26 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 8 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 9 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 13 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 21 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 24 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 26 of the Mississippi River Illinois River, Alton the Reach from the Confluence of the Mississippi River to Kampsville, IL, Digital Elevation Model, First Return Mississippi River, Pool 8 Digital Elevation Model, First Return Forest Canopy Gaps Identified by Lidar for Navigational Pool 21 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 21 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 8 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 8 of the Mississippi River Mississippi River, Pool 8 Digital Elevation Model, First Return Illinois River, Alton the Reach from the Confluence of the Mississippi River to Kampsville, IL, Digital Elevation Model, First Return Forest Canopy Gaps Identified by Lidar for Navigational Pool 24 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 24 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 9 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 9 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 26 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 26 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 13 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 13 of the Mississippi River