Perspectives on combining ecological process models and remotely sensed data

Ecological Modelling

Volumn 129, Issue 2-3, 2000, Pages 169-186

  Plummer, S E ^a  

^a CENTRE FOR ECOLOGY AND HYDROLOGY   (United Kingdom)

Author keywords

Ecological process model; Remote sensing; Strategies

Indexed keywords

ECOLOGICAL MODELING; REMOTE SENSING;

EID: 0034732860     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-3800(00)00233-7     Document Type: Article

References (90)

1. Barber J., Horler D.N.H. Fundamental Relationships Between Plant Spectra and Geobotanical Stress Phenomena. 1981;NASA, Washington, DC. NASA Technical Reports I-IV on contract No. NAS5-25 738.
2. Baret F., Guyot G. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens. Environ. 35:1991;161-173.
3. Barton C.V.M., Plummer S.E. Modelling the physiological basis for assessing stress using remote sensing. Ceulemans R.J.M., Veroustraete F., Gond V., Van Rensburgen J. Forest Ecosystem Modelling, Upscaling and Remote Sensing. 2000;197-200 SPB Academic Publishing, The Hague.
4. Beerling D.J., Woodward F.I. 400 Million Years of Plant Biogeography. 2000;Cambridge University Press, Cambridge.
5. Bergen K.M., Dobson M.C. Integration of remotely sensed radar imagery in modeling and mapping forest biomass and net primary production. Ecol. Model. 122:1999;257-274.
6. Betts A.K., Viterbo P., Beljaars A., Pan H.L., Hong S.Y., Goulden M., Wofsy S. Evaluation of land-surface interaction in ECMWF and NCEP/NCAR reanalysis models over grassland (FIFE) and boreal forest (BOREAS). J. Geophys. Res. D18:1998;23079-23085.
7. Bicheron P., Leroy M. A method of biophysical parameter retrieval at global scale by inversion of a vegetation reflectance model. Remote Sens. Environ. 67:1999;251-266.
8. Bonan G. Importance of leaf area index and forest type when estimating photosynthesis in boreal forests. Remote Sens. Environ. 43:1993;303-314.
9. Bonan G. A Land Surface Model (LSM v1.0) for Ecological, Hydrological and Atmospheric Studies: Technical Description and User's Guide. 1996;National Centre for Atmospheric Research, Boulder, CO. NCAR Technical Note TN-417+STR.
10. Bouman B.A.M., Goudriaan J. Estimation of crop growth from optical and microwave soil cover. Int. J. Remote Sens. 10:1989;1843-1855.
11. Brenneman J. Long-Term Ecological Research in the United States. A Network of Research Sites 1989. 1989;Long-Term Ecological Research Network Office, College of Forestry Resources, University of Washington, Seattle, WA. AR-10.
12. Burke E.P., Gurney R.J., Simmonds L.P., O'Neill P.E. Using a modelling approach to predict soil hydraulic properties from passive microwave measurements. IEEE Trans. Geosci. Remote Sens. 36:1998;454-462.
13. Ciret C., Henderson-Sellers A. Sensitivity of ecosystem models to the spatial resolution of the NCAR Community Climate Model CCM2. Climate Dynam. 14:1998;409-429.
14. Clevers J.G.P.W., van Leeuwen H.J.C. Combined use of optical and microwave remote sensing data for crop growth monitoring. Remote Sens. Environ. 56:1996;42-51.
15. Coughlan J.C., Dungan J.L. Combining remote sensing and forest ecosystem modelling: an example using the Regional HydroEcological Simulation System (RHESSys). Gholz H.L., Nakane K., Shimoda H. The Use of Remote Sensing in the Modelling of Forest Productivity. 1996;135-158 Kluwer, Dordrecht.
16. Curran P.J., Dungan J.L., Macler B.A., Plummer S.E. The effect of a red leaf pigment on the relationship between red edge and chlorophyll concentration. Remote Sens. Environ. 35:1991;69-76.
17. Derrien M., Farki B., Harang L., LeGléau H., Noyalet A., Pochic D., Sairouni A. Automatic cloud detection applied to NOAA-11/AVHRR imagery. Remote Sens. Environ. 46:1993;246-267.
18. Eastwood J., Plummer S.E., Wyatt B.K., Stocks B. The potential of SPOT-VEGETATION data for fire scar detection in boreal forests. Int. J. Remote Sens. 19:1998;3681-3687.
19. Ellingson R.G. Surface longwave fluxes from satellite observations: a critical review. Remote Sens. Environ. 51:1995;89-97.
20. Field C.B., Randerson J.T., Malmström C.M. Global net primary production: combining ecology and remote sensing. Remote Sens. Environ. 51:1995;75-88.
21. Fischer A., Kergoat L., Mougin E. Understanding the ecosystem dynamic behaviour. What is the potential for satellite data assimilation into functional models? Proceedings of the Sixth Symposium on Spectral Signatures and Physical Measurements in Remote Sensing, Val d'Isere. 1994;971-980.
22. Friend A.D., Schugart H.H., Running S.W. A physiology-based gap model of forest dynamics. Ecology. 74:1993;792-797.
23. Frouin R., Pinker R.T. Estimating photosynthetically active radiation (PAR) at the Earth's surface from satellite observations. Remote Sens. Environ. 51:1995;98-107.
24. Fung A.K. Microwave Scattering and Emission Models and Their Applications. 1994;451-525 Artech, Boston, MA.
25. Goel N.S. Models of vegetation canopy reflectance and their use in the estimation of biophysical parameters from reflectance data. Remote Sens. Rev. 4:1988;1-222.
26. Goetz S.J., Prince S.D., Goward S.N., Thawley M.M., Small J. Satellite remote sensing of primary production: an improved production efficiency modelling approach. Ecol. Model. 122:1999;239-255.
27. Gopal S., Woodcock C.E., Strahler A.H. Fuzzy neural network classification of global land cover from a 1 degree AVHRR dataset. Remote Sens. Environ. 67:1999;230-243.
28. Goward S.N., Waring R.H., Dye D.G., Yang J. Ecological remote sensing at Otter: satellite macroscale observations. Ecol. Appl. 4:1994;322-343.
29. Graetz R.D. Remote sensing of terrestrial ecosystem structure: an ecologists pragmatic view. Hobbs R.J., Mooney H.A. Remote Sensing of Biosphere Functioning. 1990;5-30 Springer, New York.
30. Hall F.G., Townshend J.R., Engman E.T. Status of remote sensing algorithms for estimation of land surface state parameters. Remote Sens. Environ. 51:1995;138-156.
31. Harrell P.A., Bourgeau-Chavez L.L., Kasischke E.S., French N.H.F., Christensen N.L. Sensitivity of ERS-1 and JERS-1 radar data to biomass and stand structure in Alaskan boreal forest. Remote Sens. Environ. 54:1995;247-260.
32. Huffman G.J., Adler R.F., Arkin P., Chang A., Ferraro R., Gruber A., Janowiak J., McNab A., Rudolph B., Schneider U. The Global Precipitation Climatology Project (GPCP) combined precipitation dataset. Bull. Am. Meteorol. Soc. 78:1997;5-20.
33. 2 concentrations predicted by an ecosystem process model and three-dimensional atmospheric transport model. Global Biogeochemical Cycles. 10:1996;431-456.
34. Hutchison K.D., Choe N.J. Application of 1.38 μm imagery for thin cirrus detection in daytime imagery collected over land surfaces. Int. J. Remote Sens. 17:1996;3325-3342.
35. Jacquemoud S., Baret F., Andrieu B., Danson F.M., Jaggard K. Extraction of vegetation biophysical parameters by inversion of the PROSPECT+SAIL models on sugar beet canopy reflectance data: application to TM and AVIRIS sensors. Remote Sens. Environ. 52:1995;163-172.
36. Jørgensen S.E. Fundamentals of Ecological Modelling. 1994;Elsevier, Amsterdam.
37. Kasischke E.S., French N.H.F. Locating and estimating the areal extent of wildfires in Alaskan boreal forests using multiple-season AVHRR NDVI composite data. Remote Sens. Environ. 51:1995;263-275.
38. Kergoat L., Dedieu G. Towards assimilation of satellite measurements in a generic vegetation process model. Proceedings of the Sixth Symposium on Spectral Signatures and Physical Measurements in Remote Sensing, Val d'Isere. 1994;1085-1092.
39. Kergoat L., Fischer A., Moulin S., Dedieu G. Satellite measurements as a constraint on estimates of vegetation carbon budget. Tellus. 47B:1995;251-263.
40. Kimes D.S., Harrison P.R., Ratcliffe P.A. A knowledge-based expert system for inferring vegetation characteristics. Int. J. Remote Sens. 12:1991;1987-2020.
41. Kimes D.S., Ranson K.J., Sun G. Inversion of a forest backscatter model using neural networks. Int. J. Remote Sens. 18:1997;2181-2199.
42. Kimes D.S., Nelson R.F., Manry M.T., Fung A.K. Attributes of neural networks for extracting continuous vegetation variables from optical and radar measurements. Int. J. Remote Sens. 19:1998;2639-2663.
43. King, M.D., 1999. EOS Science Plan, National Aeronautics and Space Administration, Report No. NP-1998-12-069-GSFC.
44. Kurth W. Morphological models of plant growth: possibilities and ecological relevance. Ecol. Model. 75-76:1994;299-308.
45. Landsberg J.J., Prince S.D., Jarvis P.G., McMurtrie R.E., Luxmoore R., Medlyn B.E. Energy conversion and use in forests: an analysis of forest production in terms of radiation utilisation efficiency (ε). Gholz H.L., Nakane K., Shimoda H. The Use of Remote Sensing in the Modelling of Forest Productivity. 1996;273-298 Kluwer, Dordrecht.
46. Leemans R., Cramer W.P. The IIASA database for mean monthly values of temperature, precipitation and cloudiness on a global terrestrial grid. 1990;International Institute for Applied Systems Analysis, Laxenburg, Austria. IIASA WP-90-41.
47. Legovic T. Ecological modelling internet resources. Ecol. Model. 100:1997;163-169.
48. Liu J., Chen J.M., Cihlar J., Park W.M. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens. Environ. 62:1997;158-175.
49. Lo Seen D., Mougin E., Rambal S., Gaston A., Hiernaux P. A regional Sahelian grassland model to be coupled with multispectral satellite data. II: toward the control of its simulations by remotely sensed indices. Remote Sens. Environ. 52:1995;194-206.
50. Luckman A.J., Baker J., Kuplich T.M., Yanasse C.C.F., Frery A.C. A study of the relationship between radar backscatter and regenerating forest biomass for space-borne SAR instruments. Remote Sens. Environ. 60:1997;1-13.
51. Luckman A.J., Baker J., Honzák M., Lucas R. Tropical forest biomass density estimation using JERS-1 SAR: seasonal variation, confidence limits, and application to image mosaics. Remote Sens. Environ. 63:1998;127-139.
52. Luker-Brown, M., 1998. Simulating the Interactions between Canopy Microclimate and Vegetation Physiology, Ph.D Thesis, University of Sheffield.
53. Maas S.J. Use of remotely sensed information in agricultural crop growth models. Ecol. Model. 41:1988;247-268.
54. Maisongrande P., Ruimy A., Dedieu G., Saugier B. Monitoring seasonal and interannual variations of gross primary productivity, net primary productivity and net ecosystem productivity using a diagnostic model and remotely sensed data. Tellus. 47B:1995;178-190.
55. McNaughton D.J., Vet R.J. Eulerian model evaluation field study (EMEFS): a summary of surface network measurements and data quality. Atmos. Environ. 30:(2):1996;227-238.
56. Meinander O., Somersalo S., Holopainen T., Strasser R.J. Scots pines after exposure to elevated ozone and carbon dioxide probed by reflectance spectra and chlorophyll-a fluorescence transients. J. Plant Physiol. 148:1996;229-236.
57. Mougin E., Lo Seen D., Rambal S., Gaston A., Hiernaux P. A regional Sahelian grassland model to be coupled with multispectral satellite data. I: model description and validation. Remote Sens. Environ. 52:1995;181-193.
58. Moulin S., Fischer A., Delécolle R. Assimilation of satellite measurements in short wavelengths into production model. Test of several radiative transfer models. Proceedings of the Sixth Symposium on Spectral Signatures and Physical Measurements in Remote Sensing, Val d'Isere. 1994;1127-1134.
59. Moulin S., Fischer A., Dedieu G., Delécolle R. Temporal variations in satellite reflectances at field and regional scales compared with values simulated by linking crop growth and SAIL models. Remote Sens. Environ. 54:1995;261-272.
60. Moulin S., Bondeau A., Delécolle R. Combining agricultural crop models and satellite observations: from field to regional scales. Int. J. Remote Sens. 19:1998;1021-1036.
61. Muchoney D., Strahler A., Hodges J., LoCAstro J. The IGBP DISCover Confidence Sites and the System for Terrestrial Ecosystem Parameterisation: Tools for validating global land cover data. Photogram. Eng. Remote Sens. 65:(9):1999;1061-1066.
62. Myneni R.B., Ross J.K., Asrar G. A review on the theory of photon transport in leaf canopies in slab geometry. Agric. For. Meteorol. 45:1989;1-153.
63. Myneni R.B., Maggion S., Iaquinta J., Privette J.L., Gobron N., Pinty B., Kimes D.S., Verstraete M.M., Williams D.L. Optical remote sensing of vegetation: modelling, caveats, and algorithms. Remote Sens. Environ. 51:1995;169-188.
64. Nemani R., Pierce L., Running S., Band L. Forest ecosystem processes at the water shed scale: sensitivity to remotely sensed leaf area index estimates. Int. J. Remote Sens. 14:1993;2519-2534.
65. North P.R.J. Three-dimensional forest light interaction model using a Monte Carlo method. IEEE Trans. Geosci. Remote Sens. 34:1996;946-956.
66. Perttunen J., Sievänen R., Nikinmaa E. LIGNUM: a model combining the structure and the functioning of trees. Ecol. Model. 108:1998;189-198.
67. Petty G.W. The status of satellite-based rainfall estimation over land. Remote Sens. Environ. 51:1995;125-137.
68. Pinker R.T., Frouin R., Li Z. A review of satellite methods to derive surface shortwave irradiance. Remote Sens. Environ. 51:1995;108-124.
69. Plummer, S.E., North, P., Eastwood, J.A., Wyatt, B., Lomas, M., Messeh, M., Quegan, S., Woodward, F.I., 1998. Validation of a global ecosystem model with SPOT-VEGETATION data, Technical Report to the Centre National d'Études Spatiales, Contract No: 95/CNES/0406.
70. Ranson K.J., Sun G., Weishampel J.F., Knox R.G. Forest biomass from combined ecosystem and radar backscatter modelling. Remote Sens. Environ. 59:1997;118-133.
71. Reiners W.A., Strong L.L., Matson P.A., Burke I.C., Ojima D.S. Estimating Biogeochemical Fluxes Across Sagebrush-Steppe Landscapes with Thematic Mapper Imagery. Remote Sens. Environ. 28:1989;121-129.
72. Rossow W.B., Garder L.C. Cloud detection using satellite measurements of infrared and visible radiances for ISCCP. J. Climate. 6:1993;2341-2369.
73. Running S.W., Coughlan J.C. A general model of forest ecosystem processes for regional applications I. Hydrologic balance, canopy gas exchange and primary production processes. Ecol. Model. 42:1988;125-154.
74. Running S.W., Nemani R.R. Relating seasonal patterns of AVHRR vegetation index to simulated photosynthesis and transpiration of forests in different climates. Remote Sens. Environ. 24:1988;347-367.
75. Running S.W., Loveland T.R., Pierce L.L. A vegetation classification logic based on remote sensing for use in global biogeochemical models. Ambio. 23:1994;77-81.
76. Running S.W. Testing FOREST-BGC ecosystem process simulations across a climatic gradient in Oregon. Ecol. Appl. 4:1994;238-247.
77. Sellers P.J., Mintz Y., Sud Y.C., Dalcher A. A simple biosphere model (SiB) for use with general circulation models. J. Atmos. Sci. 43:1986;505-531.
78. Sellers P.J., Meeson B.W., Hall F.G., Asrar G., Murphy R.E., Schiffer R.A., Bretherton F.P., Dickinson R.E., Ellingson R.G., Field C.B., Huemmrich K.F., Justice C.O., Melack J.M., Roulet N.T., Schimel D.S., Try P.D. Remote sensing of the land surface for studies of global change: models-algorithms-experiments. Remote Sens. Environ. 51:1995;3-26.
79. Sellers P.J., Hall F., Margolis H., et al. The Boreal Ecosystem Atmosphere Study (BOREAS): an overview and early results from the 1994 field year. Bull. Am. Meteorol. Soc. 76:1995;1549-1577.
80. Sellers P.J. Canopy reflectance, photosynthesis and transpiration. II. The role of biophysics in the linearity of their interdependence. Remote Sens. Environ. 21:1987;143-183.
81. Smith G.M., Fuller R.M., Amable G., Costa C., Devereux B.J. CLEVER-mapping: an implementation of a per parcel classification procedure within an integrated GIS environment. Proceedings of the 23rd Annual Conference of the Remote Sensing Society. 1997;21-26.
82. Van Cleve K., Martin S. Long-Term Ecological Research in the United States: A Network of Research Sites. sixth ed, revised :1991;Long-Term Ecological Research Network Office, Department of Biology, University of New Mexico, Albuquerque, NM. http://www.lternet.edu.
83. Verstraete M.M., Pinty B. Designing optimal spectral indexes for remote sensing applications. IEEE Trans. Geosci. Remote Sens. 34:1996;1254-1265.
84. Wan Z., Li Z.-L. A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data. IEEE Trans. Geosci. Remote Sens. 35:1997;980-996.
85. Wang Y.P., Jarvis P.G. Description and validation of an array model - MAESTRO. Agric. For. Met. 51:1990;257-280.
86. Waring D., Running S.W. Forest Ecosystems: Analysis at Multiple Scales. second ed :1998;Academic Press, San Diego.
87. Warner T.A., Shank M. An evaluation of the potential for fuzzy classification of multispectral data using artificial neural networks. Photogram. Eng. Remote Sens. 63:(11):1997;1285-1294.
88. Wessman C.A., Aber J.D., Peterson D.L., Melillo J.M. Remote sensing of canopy chemistry and nitrogen cycling in temperate forest ecosystems. Nature. 335:1988;154-156.
89. Woodward F.I., Smith T.M. Global photosynthesis and stomatal conductance-modelling the controls by soil and climate. Adv. Bot. Res. 20:1994;1-41.
90. Woodward F.I., Smith T.M., Emanuel W.R. A global land primary productivity and phytogeography model. Global Biogeochem. Cycles. 9:1995;471-490.