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IMPACTS OF IMAGERY TEMPORAL FREQUENCES ON LAND-COVER CHANGE DETECTION MONITORING
Citation:
Lunetta, R S., D. M. Johnson, J G. Lyon, AND J. Crotwell. IMPACTS OF IMAGERY TEMPORAL FREQUENCES ON LAND-COVER CHANGE DETECTION MONITORING. REMOTE SENSING OF ENVIRONMENT 89(4):444-454, (2004).
Impact/Purpose:
Our research objectives are to: (a) develop new methods using satellite remote sensor data for the rapid characterization of LC condition and change at regional to national scales; (b) evaluate the utility of the new NASA-EOS MODIS (Moderate Resolution Imaging Spectrometer) leaf area index (LAI) measurements for regional scale application with landscape process models (e.g., biogenic emissions and atmospheric deposition); (c) provide remote sensor derived measurement data to advance the development of the next generation of distributed landscape process-based models to provide a predictive modeling capability for important ecosystem processes (e.g., nutrients, sedimentation, pathogens, etc.); and (d) integrate in situ monitoring measurement networks with UAV and satellite based remote sensor data to provide a continuous environmental monitoring capability.
Description:
An important consideration for monitoring land~cover (LC) change is the nominal temporal frequency of remote sensor data acquisitions required to adequately characterize change events, Ecosystem specific regeneration rates are an important consideration for determining the required frequency of data collections to minimize change omission errors. Clear-cut forested areas in north central North Carolina undergo rapid colonization from pioneer (replacement) vegetation that is often difficult to differentiate spectrally from that previously present. This study compared change detection results for temporal frequencies corresponding to three, seven, and ten-year time intervals for !1ear-anniversary date Landsat 5 Thematic Mapper (TM) data acquisitions corresponding to a single path/row. Change detection was performed using an identical change vector analysis (:cy .l\.) technique tor all imagery dates. Although the accuracy of the three-year analysis was acceptable (86.3%, Kappa=O.55), a significant level of change omission errors resulted (51.7~-0). Accuracies associated with both the seven~year (43.6%, Kappa=O.l 0) a.'ld ten-year (37.2%, Kappa.:a.O5) temporal frequency analyses performed poorly, with excessive change omission errors of 84.8% and 86.3%, respectfully. The average rate of LC change observed over the study area tor the 13- year index period (1987- 2000) was approximately 1.0~/o per a.IU1Ul1l, .Overall results indicated that a minimum of three-four year temporal data acquisition frequency is required to monitor LC change events in north central North Carolina. Reductions in change omission errors could probably best be achieved by further increasing temporal data acquisition frequencies to a one-two year time interval.