TY - JOUR
T1 - Assessing the impact of urbanization on net primary productivity using multi-scale remote sensing data
T2 - a case study of Xuzhou, China
AU - Tan, Kun
AU - Zhou, Songyang
AU - Li, Erzhu
AU - Du, Peijun
N1 - Publisher Copyright:
© 2015, Higher Education Press and Springer-Verlag Berlin Heidelberg.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - An improved Carnegie Ames Stanford Approach (CASA) model based on two kinds of remote sensing (RS) data, Landsat Enhanced Thematic Mapper Plus (ETM +) and Moderate Resolution Imaging Spectro-radiometer (MODIS), and climate variables were applied to estimate the Net Primary Productivity (NPP) of Xuzhou in June of each year from 2001 to 2010. The NPP of the study area decreased as the spatial scale increased. The average NPP of terrestrial vegetation in Xuzhou showed a decreasing trend in recent years, likely due to changes in climate and environment. The study area was divided into four sub-regions, designated as highest, moderately high, moderately low, and lowest in NPP. The area designated as the lowest sub-region in NPP increased with expanding scale, indicating that the NPP distribution varied with different spatial scales. The NPP of different vegetation types was also significantly influenced by scale. In particular, the NPP of urban woodland produced lower estimates because of mixed pixels. Similar trends in NPP were observed with different RS data. In addition, expansion of residential areas and reduction of vegetated areas were the major reasons for NPP change. Land cover changes in urban areas reduced NPP, which could chiefly be attributed to human-induced disturbance.
AB - An improved Carnegie Ames Stanford Approach (CASA) model based on two kinds of remote sensing (RS) data, Landsat Enhanced Thematic Mapper Plus (ETM +) and Moderate Resolution Imaging Spectro-radiometer (MODIS), and climate variables were applied to estimate the Net Primary Productivity (NPP) of Xuzhou in June of each year from 2001 to 2010. The NPP of the study area decreased as the spatial scale increased. The average NPP of terrestrial vegetation in Xuzhou showed a decreasing trend in recent years, likely due to changes in climate and environment. The study area was divided into four sub-regions, designated as highest, moderately high, moderately low, and lowest in NPP. The area designated as the lowest sub-region in NPP increased with expanding scale, indicating that the NPP distribution varied with different spatial scales. The NPP of different vegetation types was also significantly influenced by scale. In particular, the NPP of urban woodland produced lower estimates because of mixed pixels. Similar trends in NPP were observed with different RS data. In addition, expansion of residential areas and reduction of vegetated areas were the major reasons for NPP change. Land cover changes in urban areas reduced NPP, which could chiefly be attributed to human-induced disturbance.
KW - improved Carnegie Ames Stanford approach model
KW - multi-scale remote sensing
KW - net primary productivity
KW - urbanization
UR - https://www.scopus.com/pages/publications/84946180128
U2 - 10.1007/s11707-014-0454-7
DO - 10.1007/s11707-014-0454-7
M3 - 文章
AN - SCOPUS:84946180128
SN - 2095-0195
VL - 9
SP - 319
EP - 329
JO - Frontiers of Earth Science
JF - Frontiers of Earth Science
IS - 2
ER -