TY - JOUR
T1 - Land surface temperature trends as indicator of land use changes in wetlands
AU - Muro, Javier
AU - Strauch, Adrian
AU - Heinemann, Sascha
AU - Steinbach, Stefanie
AU - Thonfeld, Frank
AU - Waske, Bjoern
AU - Diekkrüger, Bernd
PY - 2018/8
Y1 - 2018/8
N2 - The impacts of agricultural expansion on wetlands are diverse and complex. Land surface temperature (LST) has a great potential to act as a global indicator of the status of wetlands and changes in their hydrological and evapotranspiration regimes, which are often linked to land use and cover changes. We use the whole MODIS LST archive (2000–2017) to perform time series analysis in the Kilombero catchment, Tanzania; a large wetland that has experienced major land conversions to agriculture during the last two decades. We estimated pixel based trends using three models: a seasonal trend model, and aggregated time series using annual means and percentile 90. We characterized the trends found by using land cover change maps derived from Landsat imagery and a post-classification comparison. The relation between Normalized Difference Vegetation Index (NDVI) and LST trends was also studied (r =−0.56). The results given by the seasonal trend model and annual means were similar (r = 0.81). Fewer significant trends were found using the percentile 90, and these had larger magnitudes. Positive LST trends (i.e. increasing) corresponded to deforestation and farmland expansion into the floodplain, while forestation processes resulted in negative LST trends. Moderate increases of LST in natural wetlands suggest that the impacts of human activities extend also into non-cultivated areas. We provide evidence of how time series analysis of LST data can be successfully used to monitor and study changes in wetland ecosystems at regional and local scales.
AB - The impacts of agricultural expansion on wetlands are diverse and complex. Land surface temperature (LST) has a great potential to act as a global indicator of the status of wetlands and changes in their hydrological and evapotranspiration regimes, which are often linked to land use and cover changes. We use the whole MODIS LST archive (2000–2017) to perform time series analysis in the Kilombero catchment, Tanzania; a large wetland that has experienced major land conversions to agriculture during the last two decades. We estimated pixel based trends using three models: a seasonal trend model, and aggregated time series using annual means and percentile 90. We characterized the trends found by using land cover change maps derived from Landsat imagery and a post-classification comparison. The relation between Normalized Difference Vegetation Index (NDVI) and LST trends was also studied (r =−0.56). The results given by the seasonal trend model and annual means were similar (r = 0.81). Fewer significant trends were found using the percentile 90, and these had larger magnitudes. Positive LST trends (i.e. increasing) corresponded to deforestation and farmland expansion into the floodplain, while forestation processes resulted in negative LST trends. Moderate increases of LST in natural wetlands suggest that the impacts of human activities extend also into non-cultivated areas. We provide evidence of how time series analysis of LST data can be successfully used to monitor and study changes in wetland ecosystems at regional and local scales.
KW - Monitoring
KW - Wise use
KW - LST
KW - time series
KW - MODIS
KW - ITC-ISI-JOURNAL-ARTICLE
UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2018/isi/steinbach_lan.pdf
UR - https://ezproxy2.utwente.nl/login?url=https://doi.org/10.1016/j.jag.2018.02.002
U2 - 10.1016/j.jag.2018.02.002
DO - 10.1016/j.jag.2018.02.002
M3 - Article
VL - 70
SP - 62
EP - 71
JO - International Journal of Applied Earth Observation and Geoinformation (JAG)
JF - International Journal of Applied Earth Observation and Geoinformation (JAG)
SN - 1569-8432
ER -