This is the main drawing-board repository for the 'Understanding Land-System Change in Myanmar' project. The repository is organised into a series of studies or papers (i.e., planned, ongoing, and completed) that seek to explore and understand the land-system change dynamics in Myanmar, a country experiencing profound social-economic-political transitions. Each study/paper is organised and contained in a folder, which contains relevant working files, data, scripts, outputs, development notes, as well as project boards (where available) for the specific study topic. Note that this main repository contains the working versions of files at varying stages of progress. Completed studies are noted and links are provided to a separate repository that contains the final versions.
This study explored the synergy of optical and L-band SAR data for mapping and monitoring land/forest cover change in Tanintharyi Region, Myanmar over a twenty-year period. Landsat (5/8) and L-band SAR (JERS-1/PALSAR-2) data were combined to generate land cover maps at two time points, specifically 1995 and 2015. Image processing and analysis tasks for this study were carried out using Google Earth Engine, ESA SNAP Toolbox, Quantum GIS, and R Software for Statistical Computing, among others. Land cover transitions over the 20-year period, such as forest conversion into tree-based agricultural plantations like oil palm and rubber, were analysed.
The study has been completed and published as an open-access paper entitled, Combined Landsat and L-band SAR data improves land cover classification and change detection in dynamic tropical landscapes, in Remote Sensing journal on February 2018. Also, please head over to the GitHub repository ms-remote-sens-2018 for the final versions of the materials used in the published paper.
This study investigated the occurrence of a broad-scale land-cover regime shift in the dynamic landscape of Tanintharyi Region, southern Myanmar through the integration of complementary analytical frameworks. The 24-year annual time-series ESA CCI global land cover product coupled with extensive literature review and expert observations were used to explore the dynamics of the land-cover regime shift.
The study has been completed and published as an open-access paper entitled, Integrating analytical frameworks to investigate land-cover regime shifts in dynamic landscapes, in Sustainability journal on February 2019. Please head over to the GitHub repository ms-sustainability-2019 for the final versions of the materials used in the published paper.
This study analyses the land cover change transitions and the underlying drivers of these changes in Myanmar over a twenty-year period. Using the approach developed from a previous study (see item 1 above), this country- and subnational-scale analyses utilises combined Landsat (5/7/8) and L-band SAR (JERS-1/PALSAR-1/PALSAR-2) data, including ancillary data layers, to generate historical land cover maps at three time-points: 1996, 2007, and 2016. The patterns of land cover transitions over two time-intervals, 1996-2007 and 2007-2016, are analysed using the Intensity Analysis framework, among other approaches.
One of the studies under this topic has been completed and published as an open-access paper entitled, Improved estimates of mangrove cover and change reveal catastrophic deforestation in Myanmar, in Environmental Research Letters journal on March 2020. Also, please head over to the GitHub repository ms-environ-res-lett-2020 for the final versions of the materials used in the published paper.
This study analyses the patterns of land cover change in Tanintharyi Region, particularly (a) investigating various spatial determinants (or locational factors) of land cover change such as biophysical and socio-economic predictors, and (b) characterising the landscape patterns in terms of land cover composition and configuration–all of which aim to contribute to explaining the driving processes of land cover change in the region.
This study intends to develop spatially explicit models of future land cover change in Myanmar based on various policy and development scenarios in the region. Two land cover datasets are being used for developing the predictive models: the combined Landsat + L-band SAR data (30m, 1995-2015); and the global ESA CCI annual land cover product (300m, 1992-2015).
