Abstract:
In this paper, we show that MODIS NDVI and AMSR-E microwave vegetation indexes (MVI) data can be used to monitor land surface phenology in the Bermejo River Basin. For this purpose, the statistical nature of the study area's NDVI and MVI time series was analyzed. For NDVI, widely known time series models were tested and modified. NDVI temporal variation trends show functional forms that originate from the general annual performance of land surface phenology. Using these functional forms, a classification scheme is proposed. Furthermore, we also explored the possibility to use MVIs in order to improve the classification using assumptions about canopy structure that influence vegetation emissivity and opacity. © 2012 IEEE.
Registro:
| Documento: |
Conferencia
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| Título: | Monitoring and modeling land surface dynamics in Bermejo River Basin, Argentina: Time series analysis of MODIS and AMSR-E data |
| Autor: | Barraza, V.; Grings, F.; Perna, P.; Salvia, M.; Carbajo, A.E.; Ferrazzoli, P.; Karszenbaum, H. |
| Ciudad: | Munich |
| Filiación: | Grupo de Teledetección Cuantitativa, Instituto de Astronomía y Física Del Espacio (IAFE-CONICET-UBA), Buenos Aires, Argentina
Ecología de Enfermedades Transmitidas Por Vectores, 3iA, UNSAM, CONICET, Prov. Buenos Aires, Argentina
Tor Vergata University, Ingegneria - DISP, Via del Politecnico 1, 00133 Roma, Italy
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| Palabras clave: | land surface phenology; microwave vegetation indexes; NDVI; Argentina; Canopy structure; Classification scheme; Functional forms; Land surface; Land surface phenology; NDVI; River basins; Study areas; Temporal variation; Time series models; Vegetation index; Biology; Geology; Phenols; Radiometers; Remote sensing; Time series analysis; Vegetation; Watersheds; Surface measurement |
| Año: | 2012
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| Página de inicio: | 6408
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| Página de fin: | 6411
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| DOI: |
http://dx.doi.org/10.1109/IGARSS.2012.6352726 |
| Título revista: | 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
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| Título revista abreviado: | Dig Int Geosci Remote Sens Symp (IGARSS)
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| CODEN: | IGRSE
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| Registro: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_NIS23308_v_n_p6408_Barraza |
Referencias:
- Lhermitte, S., Verbesselt, J., Verstraeten, W.W., Coppin, P., A comparison of time series similarity measures for classification and change detection of ecosystem dynamics (2011) Remote Sensing of Environment, 115, pp. 3129-3152. , Dic
- Shi, J., Jackson, T., Tao, J., Bindlish, R., Lu, L., Chen, K.S., Microwave vegetation indices for short vegetation covers from satellite passive microwave sensor AMSR-E (2008) Remote Sensing of Environment, 112 (12), pp. 4285-4300. , Dic
- Tan, B., Morisette, J.T., Wolfe, R.E., Gao, F., Ederer, G.A., Nightingale, J., Pedelty, J.A., An enhanced TIMESAT algorithm for estimating vegetation phenology metrics from MODIS data (2011) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4, pp. 361-371. , Jun
- Alhamad, M.N., Stuth, J., Vannucci, M., Biophysical modelling and NDVI time series to project near-term forage supply: Spectral analysis aided by wavelet denoising and ARIMA modelling (2007) International Journal of Remote Sensing, 28, pp. 2513-2548. , Jun
- Jones, M.O., Jones, L.A., Kimball, J.S., McDonald, K.C., Satellite passive microwave remote sensing for monitoring global land surface phenology (2011) Remote Sensing of Environment, 115 (4), pp. 1102-1114. , Abr
- Huete, A., Justice, C., Leeuwen, W.V., (1999) EOS MODIS Vegetation Index (MOD 13) Theoretical Basis Document, p. 115. , University of Virginia, NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
- De Beurs, K.M., Henebry, G.M., A statistical framework for the analysis of long image time series (2005) International Journal of Remote Sensing, 26 (8), pp. 1551-1573A4 - Geoscience and Remote Sensing Society (GRS)
Citas:
---------- APA ----------
Barraza, V., Grings, F., Perna, P., Salvia, M., Carbajo, A.E., Ferrazzoli, P. & Karszenbaum, H.
(2012)
. Monitoring and modeling land surface dynamics in Bermejo River Basin, Argentina: Time series analysis of MODIS and AMSR-E data. 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012, 6408-6411.
http://dx.doi.org/10.1109/IGARSS.2012.6352726---------- CHICAGO ----------
Barraza, V., Grings, F., Perna, P., Salvia, M., Carbajo, A.E., Ferrazzoli, P., et al.
"Monitoring and modeling land surface dynamics in Bermejo River Basin, Argentina: Time series analysis of MODIS and AMSR-E data"
. 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
(2012) : 6408-6411.
http://dx.doi.org/10.1109/IGARSS.2012.6352726---------- MLA ----------
Barraza, V., Grings, F., Perna, P., Salvia, M., Carbajo, A.E., Ferrazzoli, P., et al.
"Monitoring and modeling land surface dynamics in Bermejo River Basin, Argentina: Time series analysis of MODIS and AMSR-E data"
. 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012, 2012, pp. 6408-6411.
http://dx.doi.org/10.1109/IGARSS.2012.6352726---------- VANCOUVER ----------
Barraza, V., Grings, F., Perna, P., Salvia, M., Carbajo, A.E., Ferrazzoli, P., et al. Monitoring and modeling land surface dynamics in Bermejo River Basin, Argentina: Time series analysis of MODIS and AMSR-E data. Dig Int Geosci Remote Sens Symp (IGARSS). 2012:6408-6411.
http://dx.doi.org/10.1109/IGARSS.2012.6352726