Do agrometeorological data improve optical satellite-based estimations of the herbaceous yield in Sahelian semi-arid ecosystems?

Abdoul Aziz Diouf; Pierre Hiernaux; Martin Stefan Brandt; Gayane Faye; Bakary Djaby; Mouhamadou Bamba Diop; Jacques André Ndione; Bernard Tychon

doi:10.3390/rs8080668

Do agrometeorological data improve optical satellite-based estimations of the herbaceous yield in Sahelian semi-arid ecosystems?

Abdoul Aziz Diouf^*, Pierre Hiernaux, Martin Stefan Brandt, Gayane Faye, Bakary Djaby, Mouhamadou Bamba Diop, Jacques André Ndione, Bernard Tychon

^*Corresponding author af dette arbejde

LUKKET: Geografi

14 Citationer (Scopus)

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Abstract

Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) have been widely used to assess Sahelian plant productivity for about 40 years. This study combines traditional FAPAR-based assessments with agrometeorological variables computed by the geospatial water balance program, GeoWRSI, using rainfall and potential evapotranspiration satellite gridded data to estimate the annual herbaceous yield in the semi-arid areas of Senegal. It showed that a machine-learning model combining FAPAR seasonal metrics with various agrometeorological data provided better estimations of the in situ annual herbaceous yield (R² = 0.69; RMSE = 483 kg·DM/ha) than models based exclusively on FAPAR metrics (R² = 0.63; RMSE = 550 kg·DM/ha) or agrometeorological variables (R² = 0.55; RMSE = 585 kg·DM/ha). All the models provided reasonable outputs and showed a decrease in the mean annual yield with increasing latitude, together with an increase in relative inter-annual variation. In particular, the additional use of agrometeorological information mitigated the saturation effects that characterize the plant indices of areas with high plant productivity. In addition, the date of the onset of the growing season derived from smoothed FAPAR seasonal dynamics showed no significant relationship (0.05 p-level) with the annual herbaceous yield across the whole studied area. The date of the onset of rainfall however, was significantly related to the herbaceous yield and its inclusion in fodder biomass models could constitute a significant improvement in forecasting risks of a mass herbaceous deficit at an early stage of the year.

Originalsprog	Engelsk
Artikelnummer	668
Tidsskrift	Remote Sensing
Vol/bind	8
Udgave nummer	8
ISSN	2072-4292
DOI	https://doi.org/10.3390/rs8080668
Status	Udgivet - 2016

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10.3390/rs8080668

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Citationsformater

@article{373cc29554414737987ea36150e2dd83,

title = "Do agrometeorological data improve optical satellite-based estimations of the herbaceous yield in Sahelian semi-arid ecosystems?",

abstract = "Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) have been widely used to assess Sahelian plant productivity for about 40 years. This study combines traditional FAPAR-based assessments with agrometeorological variables computed by the geospatial water balance program, GeoWRSI, using rainfall and potential evapotranspiration satellite gridded data to estimate the annual herbaceous yield in the semi-arid areas of Senegal. It showed that a machine-learning model combining FAPAR seasonal metrics with various agrometeorological data provided better estimations of the in situ annual herbaceous yield (R2 = 0.69; RMSE = 483 kg·DM/ha) than models based exclusively on FAPAR metrics (R2 = 0.63; RMSE = 550 kg·DM/ha) or agrometeorological variables (R2 = 0.55; RMSE = 585 kg·DM/ha). All the models provided reasonable outputs and showed a decrease in the mean annual yield with increasing latitude, together with an increase in relative inter-annual variation. In particular, the additional use of agrometeorological information mitigated the saturation effects that characterize the plant indices of areas with high plant productivity. In addition, the date of the onset of the growing season derived from smoothed FAPAR seasonal dynamics showed no significant relationship (0.05 p-level) with the annual herbaceous yield across the whole studied area. The date of the onset of rainfall however, was significantly related to the herbaceous yield and its inclusion in fodder biomass models could constitute a significant improvement in forecasting risks of a mass herbaceous deficit at an early stage of the year.",

keywords = "Cubist, FAPAR, GeoWRSI, Grasslands, Herbaceous annual yield, Land cover class, Sahel, Satellite remote sensing, Senegal, Start of season",

author = "Diouf, {Abdoul Aziz} and Pierre Hiernaux and Brandt, {Martin Stefan} and Gayane Faye and Bakary Djaby and Diop, {Mouhamadou Bamba} and Ndione, {Jacques Andr{\'e}} and Bernard Tychon",

year = "2016",

doi = "10.3390/rs8080668",

language = "English",

volume = "8",

journal = "Remote Sensing",

issn = "2072-4292",