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This spatial 
(0.4 ha) of Landsat MSS data. This fact was the 
single most difficult problem in making an 
inventory of boro using Landsat. However, it was 
expected that in regions of 
production the chances of boro 
adjacent to or near each other 
hence they might be detected, 
clustering is a result of the use of mechanical 
pumps which can each irrigate from 4 to 16 
hectares. 
However, in Bangladesh there are likely to be 
many pixels in which the amount of boro present is 
so small that it is insufficient to be 
distinguished from bare soil and other categories. 
This is particularly true for boro fields 
irrigated by traditional (non-mechanical pump) 
methods. Thus, it was expected that a boro map 
based on the amount of green vegetation present 
would produce an underestimate of total boro. 
Boro acreages collected by local agricultural 
officers were available for several administrative 
units near Dhaka. For those political units, the 
Landsat pixel and line numbers were obtained for 
the vertices of the boundary of each area and the 
Landsat data for each political unit processed 
independently. Registration points were located 
on Landsat produced gray maps and available base 
maps and a regreseion relationship obtained 
between the latitude and longitude coordinates and 
the Landsat pixel-row locations. 
Initial examinations of several political units 
indicated that the Landsat recognized acreage of 
boro was less than the reported amount. This was 
not unexpected and may be the result of several 
factors. Some of the boro fields, particularly 
those irrigated by traditional methods, are too 
small to be recognized by Landsat and will be 
confused with homestead or other categories. This 
situation was indicated in some of the initial 
processing efforts and led to a decision to 
produce maps which identified the large contiguous 
boro fields but not necessarily the scattered, 
small fields. That decison produced accurate maps 
of the major boro areas, but underestimated the 
total extent. In addition, because of the 
variable transplanting date of the boro, not all 
of it may be at a sufficient stage of development 
to be identifed on the early March Landsat data. 
It is also possible that the ground statistics 
consistently overestimated the true boro amount, 
but there was no way of verifying this. Current 
aerial photography and ground work during the time 
of Landsat acquisiton would be useful to produce 
better field statistics. 
A census and double-sampling approach was 
implemented to make an estimate of boro over a 
fairly large area in Bangladesh. In this 
procedure, the entire area of interest is 
inventoried using Landsat data to obtain an 
estimate. Then, Landsat estimates and field 
estimates are made for identical sampling units 
within the area of interest. Finally, the Landsat 
total census is corrected by the relationship 
between Landsat and field data in the double- 
sampled areas (Gilmer, 1980; Colwell, 1978). 
For ten small political units called unions for 
which field estimates of boro area were available, 
the double-sample relationship between Landsat 
indicated boro area and field estimates of area 
were determined. Those results are in Table 1. 
When a regression between the two estimates was 
performed, the slope of the regression equation 
was found to be statistically significant, but the 
constant term was not statistically significant. 
Therefore, a zero intercept for the relation was 
assumed, and a correlation found between the two 
estimates of 0.98. Figure 2 is a scatter plot of 
the double-sample results. The average ratio of 
Landsat to field estimates of boro area was 
determined to be 0.52. A Landsat census of boro 
for another area for which reported field acreages 
Table 1. Boro rice digital processing double 
sampling results. 
Union Reported acreage 
Digitally identified 
Aminpur 
Baradi and 
182 
141 
Baidya Bazar 
610 
269 
Jampur 
570 
278 
Kachpur 
1140 
733 
Mograpara 
330 
195 
Noagaon 
580 
199 
Pirijpur 
1190 
562 
Sadipur 
420 
160 
Sambhupura 
1410 
813 
Sanmandi 
855 
430 
Acreage 
Reported 
1410 
1128 
0 162 325 488 650 813 
Landsat Digitally Identified Acreage 
Figure 2. Scatter plot of boro reported and 
Landsat digitally identified acreage for ten 
unions. 
were available was then made and adjusted by the 
average correction factor. That area, a portion 
of Rubganj Thana and the Dhaka-Narayangonj-Demra 
project, had a reported boro area or 27,546 acres 
and an adjusted Landsat estimate of 26,528 acres; 
these are considered excellent results. 
The validity and expected accuracy of employing 
a correction factor to Landsat recognitions to 
obtain an estimate of actual ground conditions is 
a function of the reasons for the discrepency 
between Landsat recognition and actual conditions. 
If the reasons for the discrepency are fairly 
uniformly applicable throughout the study area, 
then such a procedure is valid. However, if the 
discrepency is spatially nonuniform then such a 
procedure may be invalid unless the sampling 
strategy for the census and double sampling is 
well stratified, or if the estimate is for a 
sufficiently large area that there will be 
compensating errors. 
The reported areas available in this study and 
their reliability were not sufficient to provide a 
good test of these considerations. However, the 
use of a census and double-sampling method with 
Landsat data appears to be promising for boro rice 
acreage estimates. In a future application of 
this method, the field data should be available 
for a wider spectrum of ground conditions and more 
spatially separated. The ground data should also 
have a high degree of accuracy. This could be 
accomplished by utlizing aerial photography at the 
time of Landsat overflight with field checks to 
supply the actual field statistics.