Village level crop inventory using remote sensing and field survey data

This paper presents results of a pilot study in six villages located in the states of Haryana, Rajasthan and Madhya Pradesh, to evaluate accuracy of crop area at village level estimated by IRS - LISS-I1I data with respect to detailed field survey carried out by National Sample Survey Organization. T...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of the Indian Society of Remote Sensing 2005-03, Vol.33 (1), p.93-98
Hauptverfasser: Singh, R. P., Sridhar, V. N., Dadhwal, V. K., Jaishankar, R., Neelkanthan, M., Srivastava, A. K., Bairagi, G. D., Sharma, N. K., Raza, S. A., Sharma, Rajesh, Yadav, Manoj, Joshi, F. K., Purohit, N. L.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper presents results of a pilot study in six villages located in the states of Haryana, Rajasthan and Madhya Pradesh, to evaluate accuracy of crop area at village level estimated by IRS - LISS-I1I data with respect to detailed field survey carried out by National Sample Survey Organization. The selected villages were located in Karnal, Kota and Bhopal districts which represented single dominant wheat crop as well as wheat-mustard and wheat-gram situation, respectively. Accuracy assessment of remote sensing based estimate with field survey of NSSO showed relative deviation in wheat estimate ranging from 3.72 percent for Mainmati village in Karnal district in Haryana to 22.65 percent fo Ranpur village in Kota district of Rajasthan. It was found that relative deviation in area estimation is inversely poportional to the crop proportion in that village. Observations of over estimation at low crop proportion and underestimation at higher crop proportion was explained by simple budgeting of relative proportion of ommision and commision errors. The study demonstrates that on the average, 90 percent crop area accuracy is possible with LISS-II1 data and the adopted approach.
ISSN:0255-660X
0974-3006
DOI:10.1007/BF02989996