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The recent rise in global demand for natural rubber ( Hevea brasiliensis ) has led to expansive areas of natural forest being transformed into monoculture plantations. This paper explores the utility of annual Landsat time series for monitoring forest disturbance and the role of natural rubber in mainland Southeast Asia from 2000 to 2012. A region on the Cambodian–Vietnamese border was chosen for this study considering four primary questions: 1) how accurately can annual Landsat time series map the location and timing of forest disturbances in evergreen and seasonal tropical forests, 2) are there cross-border differences in frontier and non-frontier forest disturbance rates between Cambodia and Vietnam, 3) what proportion of disturbances in frontier and non-frontier forests can be accounted for by the impact of rubber plantations, and 4) is there a relationship between global market prices for natural rubber and the annual rate of frontier forest clearing for rubber plantations on both sides of the border. We used LandTrendr (Landsat-based detection of trends in disturbance and recovery) for temporal segmentation of the Landsat time series and disturbance mapping. Our results show that this approach can provide accurate forest disturbance maps but that accuracy is affected by forest type. Highest accuracies were found in evergreen forest (91%), with lower accuracies in mixed (82%) and dry-deciduous forest types (86%). Our final map considering all forest types yielded an overall accuracy of 86%. Forest disturbance rates were generally higher on the Cambodian side of the border. Frontier forest disturbance rates averaged 3.8%/year in Cambodia compared to 2.5%/year in Vietnam. Conversion to rubber was the dominant form of frontier forest change in both countries (42% in Cambodia and 84% in Vietnam). Non-frontier forest disturbances averaged 4.0% and 2.5% in Cambodia and Vietnam, respectively, with most disturbances likewise linked with rubber plantations. Although rates of frontier forest disturbance differed in both countries, they each displayed similar correlations between disturbance rates related to rubber plantation expansion and price fluctuations of natural rubber. This suggests links between localized land cover/use change and international market forces, irrespective of differing political and socioeconomic backgrounds. Our study underlines the value of using dense Landsat time series when exploring the dynamics of human-induced land cover change. [ABSTRACT FROM AUTHOR]

As a way to understand vegetation changes, trend analysis on NDVI (normalized difference vegetation index) time series data have been widely performed at regional to global scales. However, most long-term NDVI datasets are based upon multiple sensor systems and unsuccessful corrections related to sensor shifts potentially introduce substantial uncertainties and artifacts in the analysis of trends. The temporal consistency of NDVI datasets should therefore be evaluated before performing trend analysis to obtain reliable results. In this study we analyze the temporal consistency of multi-sensor NDVI time series by analyzing the co-occurrence between breaks in the NDVI time series and sensor shifts from GIMMS3g (Global Inventory Modeling and Mapping Studies 3rd generation), VIP3 (Vegetation Index and Phenology version 3), LTDR4 (Long Term Data Record version 4) and SPOT-VGT (Système Pour l'Observation de la Terre VEGETATION). Single sensor time series from MODIS (MODerate Resolution Imaging Spectroradiometer) Terra and Aqua are used as reference datasets. The global land surface is divided into six regions according to the world humidity zones and averaged NDVI time series in each region are analyzed separately using a multiple structural change detection approach. We find that artifacts exist in the VIP3 and LTDR4 NDVI datasets with an abrupt shift detected in all humidity zones coinciding with the shift from NOAA-9 to NOAA-11 in 1988 and that orbital drift effects are evident in arid regions, potentially introducing uncertainties in NDVI trend analysis. Platform/sensor change from VGT-1 to VGT-2 is found to cause a significant positive break in the SPOT-VGT NDVI time series. Potential artifacts exist in humid, dry-subhumid, semi-arid and hyper-arid regions of GIMMS3g NDVI, whereas no signs of artifacts are found in the arid region. Although temporal consistency throughout all examined datasets increases after 2000 due to the usage of advanced platforms and sensors, variations in NDVI values from 2010 to 2011 still result in different trends at global and regional scales. [ABSTRACT FROM AUTHOR]