ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL
Using the 16 day MODIS (aboard the EOS Terra satellite) 250m NDVI and ground biophysical and spectral measurements we established simple relationships between these parameters and the canopy cover. The canopy cover is used in water erosion models to estimate the amount of soil loss under precipitati...
Guardado en:
Autores principales: | , , , |
---|---|
Lenguaje: | English |
Publicado: |
Facultad de Ciencias Naturales y Oceanográficas, Universidad de Concepción
2004
|
Materias: | |
Acceso en línea: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-65382004000200043 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:scielo:S0717-65382004000200043 |
---|---|
record_format |
dspace |
spelling |
oai:scielo:S0717-653820040002000432005-05-16ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODELGonzález Lanteri,DavidHuete,AlfredoKim,HoJinDidan,Kamel Canopy cover MODIS Soil erosion Semi arid environment Using the 16 day MODIS (aboard the EOS Terra satellite) 250m NDVI and ground biophysical and spectral measurements we established simple relationships between these parameters and the canopy cover. The canopy cover is used in water erosion models to estimate the amount of soil loss under precipitation events and specific geographic conditions. Two transects, in the grassland part of the Walnut Gulch Experimental Watershed (WGEW) located near the town of Tombstone in Arizona, were established for ground data collection. Ground measurements were performed every 16 days, to coincide with the Terra Satellite overpass. Erosion, in desert environment is a contributing factor to soil degradation and subsequently desertification. Erosion is strongly related with canopy cover, soil parameters, topography, and climate variables. Although ground point estimates of canopy cover are usually used in erosion models, their temporal and spatial variability need to be accounted for. Using MODIS NDVI data, calibrated with field measurements, we were able to estimate the canopy cover using regression analysis. This technique is very simple and properly accounts for the spatial and temporal variability of the canopy cover. We tested this technique with the WEPP erosion model and we found it to be very valuableinfo:eu-repo/semantics/openAccessFacultad de Ciencias Naturales y Oceanográficas, Universidad de ConcepciónGayana (Concepción) v.68 n.2 suppl.TIProc 20042004-01-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-65382004000200043en10.4067/S0717-65382004000200043 |
institution |
Scielo Chile |
collection |
Scielo Chile |
language |
English |
topic |
Canopy cover MODIS Soil erosion Semi arid environment |
spellingShingle |
Canopy cover MODIS Soil erosion Semi arid environment González Lanteri,David Huete,Alfredo Kim,HoJin Didan,Kamel ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL |
description |
Using the 16 day MODIS (aboard the EOS Terra satellite) 250m NDVI and ground biophysical and spectral measurements we established simple relationships between these parameters and the canopy cover. The canopy cover is used in water erosion models to estimate the amount of soil loss under precipitation events and specific geographic conditions. Two transects, in the grassland part of the Walnut Gulch Experimental Watershed (WGEW) located near the town of Tombstone in Arizona, were established for ground data collection. Ground measurements were performed every 16 days, to coincide with the Terra Satellite overpass. Erosion, in desert environment is a contributing factor to soil degradation and subsequently desertification. Erosion is strongly related with canopy cover, soil parameters, topography, and climate variables. Although ground point estimates of canopy cover are usually used in erosion models, their temporal and spatial variability need to be accounted for. Using MODIS NDVI data, calibrated with field measurements, we were able to estimate the canopy cover using regression analysis. This technique is very simple and properly accounts for the spatial and temporal variability of the canopy cover. We tested this technique with the WEPP erosion model and we found it to be very valuable |
author |
González Lanteri,David Huete,Alfredo Kim,HoJin Didan,Kamel |
author_facet |
González Lanteri,David Huete,Alfredo Kim,HoJin Didan,Kamel |
author_sort |
González Lanteri,David |
title |
ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL |
title_short |
ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL |
title_full |
ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL |
title_fullStr |
ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL |
title_full_unstemmed |
ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL |
title_sort |
estimation of the fraction of canopy cover from multispectral data to be used in a water soil erosion prediction model |
publisher |
Facultad de Ciencias Naturales y Oceanográficas, Universidad de Concepción |
publishDate |
2004 |
url |
http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-65382004000200043 |
work_keys_str_mv |
AT gonzalezlanteridavid estimationofthefractionofcanopycoverfrommultispectraldatatobeusedinawatersoilerosionpredictionmodel AT huetealfredo estimationofthefractionofcanopycoverfrommultispectraldatatobeusedinawatersoilerosionpredictionmodel AT kimhojin estimationofthefractionofcanopycoverfrommultispectraldatatobeusedinawatersoilerosionpredictionmodel AT didankamel estimationofthefractionofcanopycoverfrommultispectraldatatobeusedinawatersoilerosionpredictionmodel |
_version_ |
1718442068234207232 |