RefDoc
Haut

Faire une nouvelle recherche
Make a new search
Lancer la recherche


Titre du document / Document title

A new crop yield forecasting model based on satellite measurements applied across the Indus Basin, Pakistan

Auteur(s) / Author(s)

BASTIAANSSEN Wim G. M. (1) ; ALI Samia (2) ;

Affiliation(s) du ou des auteurs / Author(s) Affiliation(s)

(1) International Water Management Institute (IWMI), P.O. Box 2075, Colombo, SRI LANKA
(2) International Water Management Institute (IWMI), 12 km Multan Road, Chowk Thokar Niaz Baig, Lahore 53700, PAKISTAN

Résumé / Abstract

Three existing models are coupled to assess crop development and forecast yield in the largest contiguous irrigation network in the world: the Indus Basin in Pakistan. Monteith's model is used for the calculation of absorbed photosynthetically active radiation (APAR), the Carnegie Institution Stanford model is used for determining the light use efficiency, and the surface energy balance algorithm for land (SEBAL) is used to describe the spatio-temporal variability in land wetness conditions. The new model requires a crop identification map and some standard meteorological measurements as inputs. The conversion of above ground dry biomass into crop yield has been calibrated through harvest indices and the values obtained are compared with the international literature. The computations were executed in a GIS environment using 20 satellite measurements of the advanced very high resolution radiometer (AVHRR) to cover an annual crop rotation cycle. The validation with district data revealed a root mean square error of 525, 616, 551 and 13,484 kg ha-l for wheat, rice, cotton and sugarcane yield, respectively. The model performs satisfactorily for wheat, rice and sugarcane, and poorly for cotton. It is expected that the accuracy of the model applied to I . 1 km pixels decreases with the increasing number of crops occurring within a given pixel. Although AVHRR is basically too coarse a resolution for field scale crop yield estimations, the results provides yield predictions to policy makers in Pakistan with a spatial detail that is better than the traditional district level data. The gaps between the average and the maximum yield are 1075 and] 246kg ha-l for wheat and rice, respectively. Future work should rely on the integration of high and low resolution images to estimate field scale crop yields.

Revue / Journal Title

Agriculture, ecosystems & environment    ISSN  0167-8809   CODEN AEENDO 

Source / Source

2003, vol. 94, no3, pp. 321-340 [20 page(s) (article)] (2 p.)

Langue / Language

Anglais

Editeur / Publisher

Elsevier, Oxford, ROYAUME-UNI  (1983) (Revue)

Mots-clés anglais / English Keywords

Indian Peninsula

;

Cereal crop

;

Environmental factor

;

Light effect

;

Asia

;

Spermatophyta

;

Angiospermae

;

Monocotyledones

;

Gramineae

;

Pakistan

;

Triticum aestivum

;

Oryza sativa

;

Biomass

;

Meteorological variable

;

Geographic information system

;

Radiation use efficiency

;

Photosynthesis

;

Measurement method

;

Remote sensing

;

Yield component

;

Forecast model

;

Mots-clés français / French Keywords

Péninsule Indienne

;

Plante céréalière

;

Facteur milieu

;

Facteur photique

;

Asie

;

Spermatophyta

;

Angiospermae

;

Monocotyledones

;

Gramineae

;

Pakistan

;

Triticum aestivum

;

Oryza sativa

;

Biomasse

;

Elément météorologique

;

Système information géographique

;

Efficacité utilisation rayonnement

;

Photosynthèse

;

Méthode mesure

;

Télédétection

;

Composante rendement

;

Modèle prévision

;

Mots-clés espagnols / Spanish Keywords

Península India

;

Planta cerealista

;

Factor medio

;

Factor fótico

;

Asia

;

Spermatophyta

;

Angiospermae

;

Monocotyledones

;

Gramineae

;

Pakistan

;

Triticum aestivum

;

Oryza sativa

;

Biomasa

;

Elemento meteorológico

;

Sistema información geográfica

;

Eficacia utilización radiación

;

Fotosíntesis

;

Método medida

;

Teledetección

;

Componente rendimiento

;

Modelo previsión

;

Mots-clés d'auteur / Author Keywords

Crop yield forecast

;

Early warning

;

Photosynthesis

;

Light use efficiency

;

NOAA-AVHRR

;

Localisation / Location

INIST-CNRS, Cote INIST : 16535, 35400010989920.0070

Nº notice refdoc (ud4) : 14656164



Faire une nouvelle recherche
Make a new search
Lancer la recherche
Bas