Mapping vegetation cover change using geostatistical methods and bitemporal landsat TM images

Accurately mapping change in vegetation cover is difficult due to the need for permanent plots to collect field data of the change; errors from georeference, coregistration, and data analysis; a small coefficient of correlation between remote sensing and field data; and limitations of existing methods. In this study, four cosimulation procedures, two collocated cokriging procedures, and two regression procedures were compared. The results showed that with the same cosimulation or collocated cokriging methods, two postestimation procedures led to more accurate estimates than the corresponding two preestimation procedures. Among three postestimation procedures with the same image data, cosimulation resulted in the most accurate estimates and reliable variances, then regression modeling and collocated cokriging. Thus, cosimulation algorithms can be recommended for this purpose. Moreover, the accuracy by a joint cosimulation procedure of 1989 and 1992 vegetation cover was similar to that by a separate cosimulation procedure; however, the joint cosimulation overestimated the average change. In addition, adding more Thematic Mapper images increased the accuracy of mapping for the cosimulation procedures, and the increase was slight for the regression procedures.