Before and after hurricane topographic lidar surveys were compared of the Chandeleur Islands, Louisiana to detect the magnitude and pattern of extreme coastal changes. These changes have significant implications to the reconstruction of coastal Louisiana after Hurricane Katrina, the most costly storm in United States history. The coastal impact of extreme storms was examined with airborne topographic lidar and aerial photography to survey the Chandeleur Islands before and after the landfall of Hurricane Katrina. This project is part of a cooperative research program between NASA and the USGS. Pre-Katrina: Chandeleur Islands had a 32 km reach Consists of 40 individual islands (Averaging .79 km in length) 89% of reach were sandy barriers Only 3.5 km of reach was water Post-Katrina: 40 individual islands became 85 march islets (Averaging .15 km in length) 3.5 km reach of water became 21 km reach of water We assume that the bulk of the observed changes are attributable to Hurricane Katrina. However, the observed changes are cumulative between the “before” and “after” surveys. Natural recovery of the island beaches is problematic. In general, sand stored offshore in bars will, over weeks and months, be driven back to the shore by shoaling waves, potentially re-establishing beaches. However, offshore sand bars may not have developed. The storm surge of approximately 3 m was sufficient to completely submerge the islands, at least during the latter stages of the storm when the islands’ elevation was reduced and not allow for the re-establishment of Gulf-side beaches. In coastal Louisiana, barrier islands have long been considered natural breakwaters, protecting the mainland wetland environment and human developments from the marine environment. As plans for reconstructing New Orleans and coastal Louisiana evolve, the degree to which the degraded barrier islands serve as protectors of environment and development needs to be determined and verified. Terms: Lidar -describing systems that use a light beam in place of conventional microwave beams for atmospheric monitoring, tracking and detection functions Topographic -a graphic representation of elevations and landmarks in an area Islets -very small islands Hurricane Katrina Forced Extreme Changes in Barrier Islands
Transcript
Before and after hurricane topographic lidar surveys were compared of the Chandeleur Islands, Louisiana to detect the magnitude and pattern of extreme coastal changes. These changes have significant implications to the reconstruction of coastal Louisiana after Hurricane Katrina, the most costly storm in United States history.
The coastal impact of extreme storms was examined with airborne topographic lidar and aerial photography to survey the Chandeleur Islands before and after the landfall of Hurricane Katrina. This project is part of a cooperative research program between NASA and the USGS.
Pre-Katrina:Chandeleur Islands had a 32 km reachConsists of 40 individual islands (Averaging .79 km in length)89% of reach were sandy barriersOnly 3.5 km of reach was water
Post-Katrina:40 individual islands became 85 march islets (Averaging .15 km in length)3.5 km reach of water became 21 km reach of water
We assume that the bulk of the observed changes are attributable to Hurricane Katrina. However, the observed changes are cumulative between the “before” and “after” surveys.
Natural recovery of the island beaches is problematic. In general, sand stored offshore in bars will, over weeks and months, be driven back to the shore by shoaling waves, potentially re-establishing beaches. However, offshore sand bars may not have developed. The storm surge of approximately 3 m was sufficient to completely submerge the islands, at least during the latter stages of the storm when the islands’ elevation was reduced and not allow for the re-establishment of Gulf-side beaches.
In coastal Louisiana, barrier islands have long been considered natural breakwaters, protecting the mainland wetland environment and human developments from the marine environment. As plans for reconstructing New Orleans and coastal Louisiana evolve, the degree to which the degraded barrier islands serve as protectors of environment and development needs to be determined and verified.
Terms:Lidar-describing systems that use a light beam in place of conventional microwave beams for atmospheric monitoring, tracking and detection functionsTopographic-a graphic representation of elevations and landmarks in an area Islets-very small islands
Hurricane Katrina Forced Extreme Changes in Barrier Islands
Hurricane Katrina Forced Extreme Changes in Barrier Islands Charles W. Wright/GSFC 614.6
Development of global snow water equivalent (SWE) and snow depth products from AMSR-ERichard Kelly (614.3/UMBC) and James Foster (614.3)
A five-day minimum snow water equivalent (SWE) estimate for the period ending 20 January 2005. The blue colors represent the SWE over an Earth-shaded relief map taken with Version 4 AMSR-E
Version 5 AMSR-E:In Implementation phaseEnhanced snowpack parameterization (grain size and density)Enhanced resolution implementationEnhanced Use of lower frequency measurements
April 2005 monthly maximum SWE from Aqua AMSR-E standard productshows a reduction in snow volume compared with mid season estimates
Use of 10-36 GHz AMSR-E channel difference increases sensitivity to SWE compared with 18-36 GHz channel difference: mid-season snow
Three-dimensional histogramsof AMSR-E Tb combinations of low frequency (10 & 18 GHz) Tb measurements and high frequency Tb measurements for both vertical (V) and horizontal (H) polarizations.
Triangles represent dominant terrestrial snow spectral signatures in 10 GHz vs. 36 GHz feature space (green) and or 18 GHz vs. 36 GHz feature space (blue) . For 10 GHz combinations, (green) an increased dynamic range exists in the direction ofthe perpendicular arrow.
This channel combination now forms a key part of theAMSR-E SWE retrieval approach and is important because it increases the sensitivity of the algorithm to deeper snowpacks.
The PALS Program [Portable Airborne LiDAR System]
Program Objective: Develop a complete system of airborne LiDAR hardware, software, field procedures, and robust statistical techniques specifically designed to estimate above-ground forest carbon regionally, real-time, anywhere in the world.
- transportable, one operator, bolts onto aircraft found worldwide – Cessna, Bell JetRanger, Twin Otter
- LiDAR profiler, a sampling tool to collect sub-meter forest height, height variability, and crown closure measures along linear transects 10s – 1000s of kilometers long - assess counties, states, provinces, ecoregions
Dr. Ross NelsonBiospheric Sciences BranchCode 614.4, NASA-GSFC
PALS Profiler60k, GSFC-DDF, y2000
PALS Program:
Mapping Forest Fuels – NJ Pine Barrens -US Forest Service, Global Change Program,
25k + flight, 2004-2006
NJ Pine Barrens55 x 70 km
red – high fuel loadsQCLP – Quebec LiDAR Program -
develop variance estimators that includeground, PALS, and satellite laser errors
640k, NASA-HQ-Code Y, 2005-2007
Ehime Prefecture (SW Japan) Carbon Study -
Ehime University, Matsuyama -2005,2007 PALS overflights to estimate Prefecture carbon change, ~5000 km2.
travel+flights, 2005-2007
Circumpolar Boreal Forest Measurements - acquire 12-20 transboreal LiDAR flight linesglobally in 2005-2010 to estimate C amount and location. Establish “pre-climate change”
baseline (albeit a bit late).funding: piecemeal, w/Ehime University
and Norwegian University of Life Sciences
DOE STTR -Univ. Idaho & AquilaVision, Inc.
2004, not funded
DOE SBIR, Phase 2 –Zimmerman Associates, Inc.
PALS commercialized aspart of RaDAR/LiDAR biomass
estimation system
RaDAR/LiDAR Synergy –determine if BioSAR/PALS data,
national forest inventory870k, Skogforst (Norwegian Forestry Institute),2005-2008. NASA funding-TBD, currently 0
completed
ongoing
Real-time RegionalCarbon Measurement –
develop an on-the-flyC-estimation system
Texas A&M Univ.-PhD cand.87k, NASA-HQ-Code Y
2005-2007
statisticaldevelopment
fuels -fire risk
automation
carbon change
climate change
commercialization
sensor
fusion
national forest inventory
Terms:Transboreal-spanning or crossing the entire boreal forests (an almost continuous belt of coniferous trees amongst the subarctic)
Accomplishments – PALS Program
1. PALS built (30k) and flown over Delaware (30k); basic LiDAR sampling procedure developed to estimate forest volume, biomass, carbon, and impervious surface area. Results compared to USFS-Forest Inventory and Analysis estimates:
- PALS merchantable volume within 10% at county level, within 1% at state level.- PALS total dry biomass within 21% at county level, within 16% at state level.
2. Wildlife habitat assessment – Delmarva fox squirrel (DFS, an endangered species) habitat mapped. - 78% of areas mapped by PALS as >20m tall, >80% crown closure, >120m long were identified as suited to the DFS (blue and red dots); areal estimates of potential habitat and patch statistics reported.
3. QCLP: Quebec LiDAR Project – variance estimators tested, multiple sources of variability identified, regression error included in variance estimates.- Regression error adds 0 – 10% to variance of LiDAR-based C-estimates. Estimators tested and found to be nonconservative (the search continues).
4. USFS Pine Barrens Study – map forest fuels and identify areas in need of prescribed burning to mitigate risk of crown fire. Procedure developed to assess understory fuel load (1-4m above ground) using PALS.
5. RaDAR/LiDAR Synergy – BioSAR/PALS data collected over Weyerhaeuser stands 2003, 2005. Data analyzed to assess repeatability and utility for biomass/carbon estimation. - RaDAR/LiDAR results from Arizona ponderosa pine study – scanning LiDAR explained over 80% of
Evaluating UV-B Effects and EDU Protection in Soybean Leaves Evaluating UV-B Effects and EDU Protection in Soybean Leaves Using FluorescenceUsing Fluorescence
E.M. E.M. MiddletonMiddleton**, M.S. Kim, D.T. Krizek, and R. Bajwa, M.S. Kim, D.T. Krizek, and R. Bajwa The chemical ethylenediurea (EDU) has been widely used in plant studies to The chemical ethylenediurea (EDU) has been widely used in plant studies to
protect plants against air pollution injury caused by ozone. However, little was known protect plants against air pollution injury caused by ozone. However, little was known about its possible protective effects against ultraviolet radiation (UV-B) exposure in higher about its possible protective effects against ultraviolet radiation (UV-B) exposure in higher plants. The present study was conducted to determine the effects of treating soybean plants. The present study was conducted to determine the effects of treating soybean plants with either EDU or UV-B, or in combination (UV/EDU). Fluorescence measurements plants with either EDU or UV-B, or in combination (UV/EDU). Fluorescence measurements were used to test stress responses and EDU x UV-B interactions. By combined use of were used to test stress responses and EDU x UV-B interactions. By combined use of fluorescence imagery and emission spectra, we obtained the first evidence for EDU fluorescence imagery and emission spectra, we obtained the first evidence for EDU protection against UV-B damage to soybean leaves. With fluorescence imagery and protection against UV-B damage to soybean leaves. With fluorescence imagery and emission ratios at different regions of the spectrum, it was possible to distinguish among emission ratios at different regions of the spectrum, it was possible to distinguish among the four stress treatments. This work compliments research done earlier in our the four stress treatments. This work compliments research done earlier in our laboratories on cucumber and is only the second study that has been reported in the laboratories on cucumber and is only the second study that has been reported in the literature on EDU x UV-B interactions. This approach offers a non-destructive method to literature on EDU x UV-B interactions. This approach offers a non-destructive method to evaluate environmental stress effects in higher plants.evaluate environmental stress effects in higher plants.
The growth chamber experiment used a UV-B sensitive soybean cultivar The growth chamber experiment used a UV-B sensitive soybean cultivar (Roanoke) and four treatment groups: (Roanoke) and four treatment groups:
-Control-Control-EDU (500 umol/mol)-EDU (500 umol/mol)-UV-B (18 kJ/m-UV-B (18 kJ/m22/d);/d);-UV-B and EDU (UV/EDU). -UV-B and EDU (UV/EDU).
Results:Results:The FIS images additionally captured anatomical spatial patterns across the leaf surfaces The FIS images additionally captured anatomical spatial patterns across the leaf surfaces that differed markedly for UV-B versus EDU exposed leaves. These results will be useful in that differed markedly for UV-B versus EDU exposed leaves. These results will be useful in agricultural applications and could be relevant for crop growth in Moon-based facilities.agricultural applications and could be relevant for crop growth in Moon-based facilities.
Symposium-in-Print on the Effects of Ultraviolet Radiation on Terrestrial Ecosystems, Symposium-in-Print on the Effects of Ultraviolet Radiation on Terrestrial Ecosystems, Photochemistry and PhotobiologyPhotochemistry and Photobiology, 81: 1075-1085, 2005., 81: 1075-1085, 2005. * Code 614.4, Biospheric Sciences Branch* Code 614.4, Biospheric Sciences Branch
450 nmBlueband
550 nmGreenband680 nmRedband740 nmFar-redband
Low Fluorescence High Fluorescence
Fluorescence Emission ImagesFluorescence Emission ImagesImages in 4 bands (down) are shown for 4 Replicates (across). Within each replicate box, Images in 4 bands (down) are shown for 4 Replicates (across). Within each replicate box, 4 leaflets are shown, one per treatment. From the upper left hand corner, the treatments 4 leaflets are shown, one per treatment. From the upper left hand corner, the treatments are arranged clockwise: Controls, UV-B, UV-B/EDU, and EDU.are arranged clockwise: Controls, UV-B, UV-B/EDU, and EDU.
E.M. Middleton, 614.4E.M. Middleton, 614.4
Fluorescence Emission Ratios from SpectraFluorescence Emission Ratios from SpectraThe Four Treatments are separated by combining 280EX and The Four Treatments are separated by combining 280EX and
