TY - JOUR
T1 - Spatiotemporal Variation in Land Use Land Cover in the Response to Local Climate Change Using Multispectral Remote Sensing Data
AU - Hussain, Sajjad
AU - Lu, Linlin
AU - Mubeen, Muhammad
AU - Nasim, Wajid
AU - Karuppannan, Shankar
AU - Fahad, Shah
AU - Tariq, Aqil
AU - Mousa, B. G.
AU - Mumtaz, Faisal
AU - Aslam, Muhammad
N1 - Funding Information:
Funding: This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (grant numbers XDA19090130) and the National Natural Science Foundation of China (grant number 42071321).
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/4/19
Y1 - 2022/4/19
N2 - Climate change is likely to have serious social, economic, and environmental impacts on farmers whose subsistence depends on nature. Land Use Land Cover (LULC) changes were examined as a significant tool for assessing changes at diverse temporal and spatial scales. Normalized Difference Vegetation Index (NDVI) has the potential ability to signify the vegetation structures of various eco-regions and provide valuable information as a remote sensing tool in studying vegetation phenology cycles. In this study, we used remote sensing and Geographical Information System (GIS) techniques with Maximum Likelihood Classification (MLC) to identify the LULC changes for 40 years in the Sahiwal District. Later, we conducted 120 questionnaires administered to local farmers which were used to correlate climate changes with NDVI. The LULC maps were prepared using MLC and training sites for the years 1981, 2001, and 2021. Regression analysis (R2) was performed to identify the relationship between temperature and vegetation cover (NDVI) in the study area. Results indicate that the build-up area was increased from 7203.76 ha (2.25%) to 31,081.3 ha (9.70%), while the vegetation area decreased by 14,427.1 ha (4.5%) from 1981 to 2021 in Sahiwal District. The mean NDVI values showed that overall NDVI values decreased from 0.24 to 0.20 from 1981 to 2021. Almost 78% of farmers stated that the climate has been changing during the last few years, 72% of farmers stated that climate change had affected agriculture, and 53% of farmers thought that rainfall intensity had also decreased. The R2 tendency showed that temperature and NDVI were negatively connected to each other. This study will integrate and apply the best and most suitable methods, tools, and approaches for equitable local adaptation and governance of agricultural systems in changing climate conditions. Therefore, this research outcome will also meaningfully help policymakers and urban planners for sustainable LULC management and strategies at the local level.
AB - Climate change is likely to have serious social, economic, and environmental impacts on farmers whose subsistence depends on nature. Land Use Land Cover (LULC) changes were examined as a significant tool for assessing changes at diverse temporal and spatial scales. Normalized Difference Vegetation Index (NDVI) has the potential ability to signify the vegetation structures of various eco-regions and provide valuable information as a remote sensing tool in studying vegetation phenology cycles. In this study, we used remote sensing and Geographical Information System (GIS) techniques with Maximum Likelihood Classification (MLC) to identify the LULC changes for 40 years in the Sahiwal District. Later, we conducted 120 questionnaires administered to local farmers which were used to correlate climate changes with NDVI. The LULC maps were prepared using MLC and training sites for the years 1981, 2001, and 2021. Regression analysis (R2) was performed to identify the relationship between temperature and vegetation cover (NDVI) in the study area. Results indicate that the build-up area was increased from 7203.76 ha (2.25%) to 31,081.3 ha (9.70%), while the vegetation area decreased by 14,427.1 ha (4.5%) from 1981 to 2021 in Sahiwal District. The mean NDVI values showed that overall NDVI values decreased from 0.24 to 0.20 from 1981 to 2021. Almost 78% of farmers stated that the climate has been changing during the last few years, 72% of farmers stated that climate change had affected agriculture, and 53% of farmers thought that rainfall intensity had also decreased. The R2 tendency showed that temperature and NDVI were negatively connected to each other. This study will integrate and apply the best and most suitable methods, tools, and approaches for equitable local adaptation and governance of agricultural systems in changing climate conditions. Therefore, this research outcome will also meaningfully help policymakers and urban planners for sustainable LULC management and strategies at the local level.
KW - climate change
KW - Land Use Land Cover (LULC)
KW - Maximum Likelihood Classification (MLC)
KW - NDVI
KW - remote sensing and GIS
UR - http://www.scopus.com/inward/record.url?scp=85129210476&partnerID=8YFLogxK
U2 - 10.3390/land11050595
DO - 10.3390/land11050595
M3 - Article
VL - 11
JO - Land
JF - Land
IS - 5
M1 - 595
ER -
