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Timber Volume Estimation by Double Sampling Using High Resolution Satellite Data


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1 North Eastern Space Applications Centre Dept. of Space, Umiam 793103 Meghalaya, India
     

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Double sampling or two-phase sampling design offers a variety of possibilities for effective use of auxiliary information such as those from high resolution remote sensing data. This study has been made to examine the possibilities of different forms of auxiliary information derived from remote sensing data in double sampling design and suggest an appropriate estimator for forest timber volume estimation in the context of preparing forest working plan inputs. A regression-cum-ratio estimator has been derived for double sampling using information on two auxiliary variables derived from high resolution satellite data. The estimator has been adopted for forest timber volume estimation utilizing tree crown diameter (x) and NDVI (z) as auxiliary variables. Relationship between timber volume (y) and 2 2 average crown diameter (x) has a higher value of R (0.733) as compared to that with NDVI (z), where R =0.528. It is shown that combination of these two auxiliary variables under doubling sampling design has significantly reduce the standard error of the timber volume estimate (CV of SE=11.49%) against estimates brought out by common sampling design (31% for simple random sampling, 22.34% for systematic sampling and 18.69% for stratified random sampling). This indicates that the estimator can be employed in a variety of conditions where there is good correlation of satellite derived auxiliary information with sample based ground measurements and when the cost of ground measurements is relatively high.

Keywords

Double Sampling, Regression-cum-ratio Estimator, High Resolution Satellite Data, Timber Volume Estimation, Mean Square Error.
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About The Authors

B. K. Handique
North Eastern Space Applications Centre Dept. of Space, Umiam 793103 Meghalaya
India

S. Sudhakar
North Eastern Space Applications Centre Dept. of Space, Umiam 793103 Meghalaya
India


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  • Timber Volume Estimation by Double Sampling Using High Resolution Satellite Data

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Authors

B. K. Handique
North Eastern Space Applications Centre Dept. of Space, Umiam 793103 Meghalaya, India
S. Sudhakar
North Eastern Space Applications Centre Dept. of Space, Umiam 793103 Meghalaya, India

Abstract


Double sampling or two-phase sampling design offers a variety of possibilities for effective use of auxiliary information such as those from high resolution remote sensing data. This study has been made to examine the possibilities of different forms of auxiliary information derived from remote sensing data in double sampling design and suggest an appropriate estimator for forest timber volume estimation in the context of preparing forest working plan inputs. A regression-cum-ratio estimator has been derived for double sampling using information on two auxiliary variables derived from high resolution satellite data. The estimator has been adopted for forest timber volume estimation utilizing tree crown diameter (x) and NDVI (z) as auxiliary variables. Relationship between timber volume (y) and 2 2 average crown diameter (x) has a higher value of R (0.733) as compared to that with NDVI (z), where R =0.528. It is shown that combination of these two auxiliary variables under doubling sampling design has significantly reduce the standard error of the timber volume estimate (CV of SE=11.49%) against estimates brought out by common sampling design (31% for simple random sampling, 22.34% for systematic sampling and 18.69% for stratified random sampling). This indicates that the estimator can be employed in a variety of conditions where there is good correlation of satellite derived auxiliary information with sample based ground measurements and when the cost of ground measurements is relatively high.

Keywords


Double Sampling, Regression-cum-ratio Estimator, High Resolution Satellite Data, Timber Volume Estimation, Mean Square Error.

References