This case study evaluates the seasonal variability of the Pearson's linear correlation coefficient of land surface temperature(LST)with some spectral indices like NDVI,NDWI,NDBI,and NDBaI by using a series of Land...This case study evaluates the seasonal variability of the Pearson's linear correlation coefficient of land surface temperature(LST)with some spectral indices like NDVI,NDWI,NDBI,and NDBaI by using a series of Landsat images for 1991-92,1995-96,1999-00,2004-05,2009-10,2014-15,and 2018-19.The results from the average correlation of the entire period of all-season show that the LST builds a positive correlation with NDBI(0.71)and NDBaI(0.52)while it builds a negative correlation with NDVI(-0.44).The LST-NDWI correlation is insignificant.The best correlation is noticed in the post-monsoon period,while the least correlation is observed in the winter season.This study can support the environmental planning to build a sustainable city under a similar environment.展开更多
In this paper, the theory of plausible and paradoxical reasoning of Dezert- Smarandache (DSmT) is used to take into account the paradoxical charac-ter through the intersections of vegetation, aquatic and mineral surfa...In this paper, the theory of plausible and paradoxical reasoning of Dezert- Smarandache (DSmT) is used to take into account the paradoxical charac-ter through the intersections of vegetation, aquatic and mineral surfaces. In order to do this, we developed a classification model of pixels by aggregating information using the DSmT theory based on the PCR5 rule using the ∩NDVI, ∩MNDWI and ∩NDBaI spectral indices obtained from the ASTER satellite images. On the qualitative level, the model produced three simple classes for certain knowledge (E, V, M) and eight composite classes including two union classes characterizing partial ignorance ({E,V}, {M,V}) and six classes of intersection of which three classes of simple intersection (E∩V, M∩V, E∩M) and three classes of composite intersection (E∩{M,V}, M∩{E,V}, V∩{E,M}), which represent paradoxes. This model was validated with an average rate of 93.34% for the well-classified pixels and a compliance rate of the entities in the field of 96.37%. Thus, the model 1 retained provides 84.98% for the simple classes against 15.02% for the composite classes.展开更多
Degradation of vegetation cover and expansion of barren land are remained the leading environmental problem at global level.Land surface temperature(LST),Normalized Difference Vegetation Index(NDVI),Normalized Differe...Degradation of vegetation cover and expansion of barren land are remained the leading environmental problem at global level.Land surface temperature(LST),Normalized Difference Vegetation Index(NDVI),Normalized Difference Barren Index(NDBaI),and Modified Normalized Difference Water Index(MNDWI)were used to quantify the changing relationships using correlation analysis.This study attempted to analyze the relationship between LST and NDVI,NDBaI,and MNDWI using Geospatial technologies in Gida Kiremu,Limu,and Amuru districts in Western Ethiopia.All indices were estimated by using thermal bands and multispectral bands from Landsat TM 1990,Landsat ETM+2003,and Landsat OLI/TIRS 2020.The correlation of LST with NDVI,NDBaI and MNDWI were analyzed by using scatter plot.Accordingly,the NDBaI was positive correlation with LST(R 2=0.96).However,NDVI and MNDWI were substantially negative relationship with LST(R 2=0.99,0.95),respectively.The result shows that,LST was increased by 5℃due to decline of vegetation cover and increasing of bare land over the study periods.Finally,our result recommended that,decision-makers and environmental analysts should give attention on the importance of vegetation cover,water bodies and wetland in climate change mitigation,particularly,LST in the study area.展开更多
文摘This case study evaluates the seasonal variability of the Pearson's linear correlation coefficient of land surface temperature(LST)with some spectral indices like NDVI,NDWI,NDBI,and NDBaI by using a series of Landsat images for 1991-92,1995-96,1999-00,2004-05,2009-10,2014-15,and 2018-19.The results from the average correlation of the entire period of all-season show that the LST builds a positive correlation with NDBI(0.71)and NDBaI(0.52)while it builds a negative correlation with NDVI(-0.44).The LST-NDWI correlation is insignificant.The best correlation is noticed in the post-monsoon period,while the least correlation is observed in the winter season.This study can support the environmental planning to build a sustainable city under a similar environment.
文摘In this paper, the theory of plausible and paradoxical reasoning of Dezert- Smarandache (DSmT) is used to take into account the paradoxical charac-ter through the intersections of vegetation, aquatic and mineral surfaces. In order to do this, we developed a classification model of pixels by aggregating information using the DSmT theory based on the PCR5 rule using the ∩NDVI, ∩MNDWI and ∩NDBaI spectral indices obtained from the ASTER satellite images. On the qualitative level, the model produced three simple classes for certain knowledge (E, V, M) and eight composite classes including two union classes characterizing partial ignorance ({E,V}, {M,V}) and six classes of intersection of which three classes of simple intersection (E∩V, M∩V, E∩M) and three classes of composite intersection (E∩{M,V}, M∩{E,V}, V∩{E,M}), which represent paradoxes. This model was validated with an average rate of 93.34% for the well-classified pixels and a compliance rate of the entities in the field of 96.37%. Thus, the model 1 retained provides 84.98% for the simple classes against 15.02% for the composite classes.
文摘Degradation of vegetation cover and expansion of barren land are remained the leading environmental problem at global level.Land surface temperature(LST),Normalized Difference Vegetation Index(NDVI),Normalized Difference Barren Index(NDBaI),and Modified Normalized Difference Water Index(MNDWI)were used to quantify the changing relationships using correlation analysis.This study attempted to analyze the relationship between LST and NDVI,NDBaI,and MNDWI using Geospatial technologies in Gida Kiremu,Limu,and Amuru districts in Western Ethiopia.All indices were estimated by using thermal bands and multispectral bands from Landsat TM 1990,Landsat ETM+2003,and Landsat OLI/TIRS 2020.The correlation of LST with NDVI,NDBaI and MNDWI were analyzed by using scatter plot.Accordingly,the NDBaI was positive correlation with LST(R 2=0.96).However,NDVI and MNDWI were substantially negative relationship with LST(R 2=0.99,0.95),respectively.The result shows that,LST was increased by 5℃due to decline of vegetation cover and increasing of bare land over the study periods.Finally,our result recommended that,decision-makers and environmental analysts should give attention on the importance of vegetation cover,water bodies and wetland in climate change mitigation,particularly,LST in the study area.
