The Tidal Marsh Inundation Index (TMII): An inundation filter to flag flooded pixels and improve MODIS tidal marsh vegetation time-series analysis

Remote Sensing of Environment

Volumn 201, Issue , 2017, Pages 34-46

  O'Connell, Jessica L ^a   Mishra, Deepak R ^a   Cotten, David L ^a   Wang, Li ^a   Alber, Merryl ^a  

^a UNIVERSITY OF GEORGIA   (United States)

Author keywords

Bayou Sauvage National Wildlife Refuge; Coastal wetlands; Georgia Coastal Ecosystems Long Term Ecological Research site; Grand Bay National Estuarine Research Reserve; Juncus roemerianus; Moderate Resolution Imagery Spectroradiometer (MODIS); PhenoCam; Phenology; Plum Island Ecosystems Long Term Ecological Research site; Salt and brackish marsh; Sapelo Island National Estuarine Research Reserve; Spartina alterniflora; Spartina patens

Indexed keywords

BANDPASS FILTERS; BIOLOGY; CALIBRATION; DIGITAL STORAGE; ECOLOGY; ECOSYSTEMS; FLOODS; FORESTRY; IMAGE PROCESSING; IMAGE RECONSTRUCTION; INFRARED DEVICES; INFRARED RADIATION; PIXELS; RADIOMETERS; REFLECTION; REMOTE SENSING; SATELLITE IMAGERY; SPECTROMETERS; TIDES; TIME SERIES ANALYSIS; VEGETATION;

COASTAL ECOSYSTEMS; COASTAL WETLANDS; GRAND BAY NATIONAL ESTUARINE RESEARCH RESERVE; JUNCUS ROEMERIANUS; LONG-TERM ECOLOGICAL RESEARCH; PHENOCAM; PHENOLOGY; SAPELO ISLAND NATIONAL ESTUARINE RESEARCH RESERVE; SPARTINA ALTERNIFLORA; SPARTINA PATENS; SPECTRO-RADIOMETERS; WILDLIFE REFUGE;

WETLANDS;

ANGIOSPERM; CARBON SEQUESTRATION; COASTAL WETLAND; FLOOD; GRASS; INDEX METHOD; INSTRUMENTATION; MODIS; NDVI; PHENOLOGY; PIXEL; PRIMARY PRODUCTION; REMOTE SENSING; SATELLITE IMAGERY; SPECTRAL REFLECTANCE; TIDAL RANGE; TIME SERIES ANALYSIS; VEGETATION COVER;

GEORGIA; GRAND BAY NATIONAL ESTUARINE RESEARCH RESERVE; GULF COAST [UNITED STATES]; MASSACHUSETTS; MISSISSIPPI; PLUM ISLAND; SAPELO ISLAND; SEA ISLANDS; UNITED STATES;

JUNCUS ROEMERIANUS; PRUNUS DOMESTICA; SPARTINA ALTERNIFLORA; SPARTINA PATENS;

EID: 85028911430     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2017.08.008     Document Type: Article

References (45)

1. Adam, E., Mutanga, O., Rugege, D., Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review. Wetl. Ecol. Manag. 18 (2010), 281–296, 10.1007/s11273-009-9169-z.
2. 2 eddy covariance. Biogeosciences 10 (2013), 2145–2158, 10.5194/bg-10-2145-2013.
3. Bennett, N.D., Croke, B.F.W., Guariso, G., Guillaume, J.H.A., Hamilton, S.H., Jakeman, A.J., Marsili-Libelli, S., Newham, L.T.H., Norton, J.P., Perrin, C., Pierce, S.A., Robson, B., Seppelt, R., Voinov, A.A., Fath, B.D., Andreassian, V., Characterising performance of environmental models. Environ. Model Softw. 40 (2013), 1–20, 10.1016/j.envsoft.2012.09.011.
4. Byrd, K.B., O'Connell, J.L., Di Tommaso, S., Kelly, M., Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation. Remote Sens. Environ. 149 (2014), 166–180, 10.1016/j.rse.2014.04.003.
5. Cho, H.J., Kirui, P., Natarajan, H., Test of multi-spectral vegetation index for floating and canopy-forming submerged vegetation. Int. J. Environ. Res. Public Health 5 (2008), 477–483, 10.3390/ijerph5050477.
6. DeLong, E.R., DeLong, D.M., Clarke-Pearson, D.L., Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44 (1988), 837–845, 10.2307/2531595.
7. von Fischer, J.C., Tieszen, L.L., Schimel, D.S., Climate controls on C3 vs. C4 productivity in North American grasslands from carbon isotope composition of soil organic matter. Glob. Chang. Biol. 14 (2008), 1141–1155, 10.1111/j.1365-2486.2008.01552.x.
8. Gamon, J.A., Field, C.B., Goulden, M.L., Griffin, K.L., Hartley, A.E., Joel, G., Penuelas, J., Valentini, R., Relationships between NDVI, canopy structure, and photosynthesis in three Californian vegetation types. Ecol. Appl. 5 (1995), 28–41, 10.2307/1942049.
9. Gao, B.-C., NDWI normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens. Environ. 58 (1996), 257–266, 10.1016/S0034-4257(96)00067-3.
10. Ghosh, S., Mishra, D.R., Gitelson, A.A., Long-term monitoring of biophysical characteristics of tidal wetlands in the northern Gulf of Mexico methodological approach using MODIS. Remote Sens. Environ. 173 (2016), 39–58, 10.1016/j.rse.2015.11.015.
11. Giurgevich, J.R., Dunn, E.L., Seasonal patterns of daily net photosynthesis, transpiration and net primary productivity of Juncus roemerianus and Spartina alterniflora in a Georgia salt marsh. Oecologia 52 (1982), 404–410.
12. Goetz, S.J., Baccini, A., Laporte, N.T., Johns, T., Walker, W., Kellndorfer, J., Houghton, R.A., Sun, M., Mapping and monitoring carbon stocks with satellite observations: a comparison of methods. Carbon Balance Manag., 4, 2009, 10.1186/1750-0680-4-2.
13. Han, L., Rundquist, D.C., Liu, L.L., Fraser, R.N., Schalles, J.F., The spectral responses of algal chlorophyll in water with varying levels of suspended sediment. Int. J. Remote Sens. 15 (1994), 3707–3718, 10.1080/01431169408954353.
14. Hanley, J.A., McNeil, B.J., The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143 (1982), 29–36, 10.1148/radiology.143.1.7063747.
15. Hladik, C., Schalles, J., Alber, M., Salt marsh elevation and habitat mapping using hyperspectral and LIDAR data. Remote Sens. Environ. 139 (2013), 318–330, 10.1016/j.rse.2013.08.003.
16. Holbert, K., Solar energy calulations. Zobaa, A.F., Bansal, R.C., (eds.) Handbook of Renewable Energy Technology, 2011, World Scientific, Singapore, Hackensack, N.J., 193.
17. Huete, A.R., Justice, K., Leeuwen, W.V., MODIS Vegetation Index (MOD 13) Algorithm Theoretical Basis Document: Version 3.0. 1999.
18. Hughes, Z.J., FitzGerald, D.M., Wilson, C.A., Pennings, S.C., Wiski, K., Mahadevan, A., Rapid headward erosion of marsh creeks in response to relative sea level rise. Geophys. Res. Lett., 36, 2009, L03602, 10.1029/2008GL036000.
19. Hyndman, R.J., Koehler, A.B., Another look at measures of forecast accuracy. Int. J. Forecast. 22 (2006), 679–688, 10.1016/j.ijforecast.2006.03.001.
20. Ji, L., Zhang, L., Wylie, B., Analysis of dynamic thresholds for the normalized difference water index. Photogramm. Eng. Remote Sens. 75 (2009), 1307–1317, 10.14358/PERS.75.11.1307.
21. Kearney, M.S., Stutzer, D., Turpie, K., Stevenson, J.C., The effects of tidal inundation on the reflectance characteristics of coastal marsh vegetation. J. Coast. Res. 256 (2009), 1177–1186, 10.2112/08-1080.1.
22. Klemas, V., Remote sensing of wetlands: case studies comparing practical techniques. J. Coast. Res. 27 (2011), 418–427, 10.2112/JCOASTRES-D-10-00174.1.
23. Knight, J.F., Lunetta, R.S., Ediriwickrema, J., Khorram, S., Regional scale land cover characterization using MODIS-NDVIi 250 m multi-temporal imagery: a phenology-based approach. GISci. Remote Sens. 43 (2006), 1–23, 10.2747/1548-1603.43.1.1.
24. Kuhn, M., Building predictive models in R using the caret package. J. Stat. Softw., 28, 2008, 10.18637/jss.v028.i05.
25. Lacaux, J.P., Tourre, Y.M., Vignolles, C., Ndione, J.A., Lafaye, M., Classification of ponds from high-spatial resolution remote sensing: application to Rift Valley fever epidemics in Senegal. Remote Sens. Environ. 106 (2007), 66–74, 10.1016/j.rse.2006.07.012.
26. McFeeters, S.K., The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. Int. J. Remote Sens. 17 (1996), 1425–1432, 10.1080/01431169608948714.
27. 2. Front. Ecol. Environ. 9 (2011), 552–560, 10.1890/110004.
28. Mishra, D., Ghosh, S., Using moderate resolution satellite sensors for monitoring the biophysical parameters and phenology of tidal wetlands. Tiner, R.W., Lang, M.W., Klemas, V.V., (eds.) Remote Sensing of Wetlands: Applications and Advances, 2015, CRC Press, Boca Raton FL, USA, 283–314.
29. Mishra, D.R., Cho, H.J., Ghosh, S., Fox, A., Downs, C., Merani, P.B., Kirui, P., Jackson, N., Mishra, S., Post-spill state of the marsh: remote estimation of the ecological impact of the Gulf of Mexico oil spill on Louisiana salt marshes. Remote Sens. Environ. 118 (2012), 176–185, 10.1016/j.rse.2011.11.007.
30. Mishra, D.R., Ghosh, S., Hladik, C., O'Connell, J.L., Cho, H.J., Wetland mapping methods and techniques using multi-sensor, multi-resolution remote sensing: successes and challenges. Thenkabail, P.S., (eds.) Remote Sensing of Water Resources, Disasters, and Urban Studies, 2015, Taylor and Francis Group, Boca Raton FL, USA, 712.
31. Mittenzwey, K.-H., Ullrich, S., Gitelson, A.A., Kondratiev, K.Y., Determination of chlorophyll a of inland waters on the basis of spectral reflectance. Limnol. Oceanogr. 37 (1992), 147–149, 10.4319/lo.1992.37.1.0147.
32. Mutanga, O., Skidmore, A.K., Narrow band vegetation indices overcome the saturation problem in biomass estimation. Int. J. Remote Sens. 25 (2004), 3999–4014, 10.1080/01431160310001654923.
33. O'Connell, J.L., Alber, M., A smart classifier for extracting environmental data from digital image time-series: applications for PhenoCam data in a tidal salt marsh. Environ. Model Softw. 84 (2016), 134–139, 10.1016/j.envsoft.2016.06.025.
34. O'Donnell, J.P.R., Schalles, J.F., Examination of abiotic drivers and their influence on Spartina alterniflora biomass over a twenty-eight year period using Landsat 5 TM satellite imagery of the central Georgia coast. Remote Sens., 8, 2016, 477, 10.3390/rs8060477.
35. Orson, R., Panageotou, W., Leatherman, S.P., Response of tidal salt marshes of the U.S. Atlantic and Gulf Coasts to rising sea levels. J. Coast. Res. 1 (1985), 29–37.
36. Pennings, S.C., Richards, C.L., Effects of wrack burial in salt-stressed habitats: Batis maritima in a southwest Atlantic salt marsh. Ecography 21 (1998), 630–638, 10.1111/j.1600-0587.1998.tb00556.x.
37. Perkins, N.J., Schisterman, E.F., The inconsistency of “optimal” cutpoints obtained using two criteria based on the receiver operating characteristic curve. Am. J. Epidemiol. 163 (2006), 670–675, 10.1093/aje/kwj063.
38. Redfield, A.C., Development of a New England salt marsh. Ecol. Monogr. 42 (1972), 201–237, 10.2307/1942263.
39. Rogers, A.S., Kearney, M.S., Reducing signature variability in unmixing coastal marsh thematic mapper scenes using spectral indices. Int. J. Remote Sens. 25 (2004), 2317–2335, 10.1080/01431160310001618103.
40. Stralberg, D., Brennan, M., Callaway, J.C., Wood, J.K., Schile, L.M., Jongsomjit, D., Kelly, M., Parker, V.T., Crooks, S., Evaluating tidal marsh sustainability in the face of sea-level rise: a hybrid modeling approach applied to San Francisco Bay. PLoS One, 6, 2011, e27388, 10.1371/journal.pone.0027388.
41. Turner, D.P., Ollinger, S.V., Kimball, J.S., Integrating remote sensing and ecosystem process models for landscape- to regional-scale analysis of the carbon cycle. Bioscience 54 (2004), 573–584.
42. Turpie, K.R., Explaining the spectral red-edge features of inundated marsh vegetation. J. Coast. Res. 290 (2013), 1111–1117, 10.2112/JCOASTRES-D-12-00209.1.
43. Wang, L., Dronova, I., Gong, P., Yang, W., Li, Y., Liu, Q., A new time series vegetationwater index of phenologicalhydrological trait across species and functional types for Poyang Lake wetland ecosystem. Remote Sens. Environ. 125 (2012), 49–63, 10.1016/j.rse.2012.07.003.
44. Xu, H., Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int. J. Remote Sens. 27 (2006), 3025–3033, 10.1080/01431160600589179.
45. Zuur, A., Ieno, E., Walker, N., Saveliev, A., Smith, G., Mixed Effects Models and Extensions in Ecology With R. 2009, Springer, New York, NY, USA.