More accurate estimation of crop evapotranspiration(ET_c)in a regional scale has always been one of the most important challenges.Temporal and spatial monitoring of ET_(c )using satellite images can help to enhance ac...More accurate estimation of crop evapotranspiration(ET_c)in a regional scale has always been one of the most important challenges.Temporal and spatial monitoring of ET_(c )using satellite images can help to enhance accuracy of estimations.In this study,the(ET_c)_(rice) maps were produced by using statistical/experimental methods based on crop coefficient(K_c)maps derived from vegetation index(Ⅵ).K_c was estimated using four methods,including linear relationship between K_c and Ⅵ(K_c-Ⅵ),calibrated model of K_c-Ⅵ,linear relationship between K_(cb)(the basal crop coefficient)and Ⅵ(K_(cb)-Ⅵ),and calibrated model of K_(cb)-Ⅵ.The results showed that calibrated model of K_c-Ⅵ had a better performance compared to the other methods,with normalized root mean square errors(NRMSE),mean absolute error and root mean square error being 5.7%,0.05 mm/d and 0.06mm/d,respectively.(ET_c)_(rice) maps were produced by using calibrated model of K_c-Ⅵ and reference evapotranspiration(ET_0)from FAO Penman-Monteith method.The NRMSE was 21.3%for using FAO Penman-Monteith method.Therefore,calibrated K_c-Ⅵ model in combining with ET_0 based on the Landsat 7 ETM+images could be provided a good estimation of(ET_c)_(rice) in regional scale,and can be applied to estimate water requirement due to the free and facilitate access.展开更多
This paper presents a lineament detection method using multi-band remote sensing images. The main objective of this work is to design an automatic image processing tool for lineament mapping from Landsat-7 ETM + satel...This paper presents a lineament detection method using multi-band remote sensing images. The main objective of this work is to design an automatic image processing tool for lineament mapping from Landsat-7 ETM + satellite data. Five procedures were involved: 1) The Principal Component Analysis;2) image enhancement using histogram equalization technique 3) directional Sobel filters of the original data;4) histogram segmentation and 5) binary image generation. The applied methodology was contributed in identifying several known large-scale faults in the Northeast of Tunisia. The statistical and spatial analyses of lineament map indicate a difference of morphological appearance of lineaments in the satellite image. Indeed, all the lineaments present a specific organization. Five groups were classified based on three orientations: NE-SW, E-W and NW-SE. The overlapping of lineament map with the geologic map confirms that these lineaments of diverse directions can be identified and recognized on the field as a fault. The identified lineaments were linked to a deep faults caused by tectonic movements in Tunisia. This study shows the performance of the satellite image processing in the analysis and mapping of the accidents in the northern Atlas.展开更多
文摘More accurate estimation of crop evapotranspiration(ET_c)in a regional scale has always been one of the most important challenges.Temporal and spatial monitoring of ET_(c )using satellite images can help to enhance accuracy of estimations.In this study,the(ET_c)_(rice) maps were produced by using statistical/experimental methods based on crop coefficient(K_c)maps derived from vegetation index(Ⅵ).K_c was estimated using four methods,including linear relationship between K_c and Ⅵ(K_c-Ⅵ),calibrated model of K_c-Ⅵ,linear relationship between K_(cb)(the basal crop coefficient)and Ⅵ(K_(cb)-Ⅵ),and calibrated model of K_(cb)-Ⅵ.The results showed that calibrated model of K_c-Ⅵ had a better performance compared to the other methods,with normalized root mean square errors(NRMSE),mean absolute error and root mean square error being 5.7%,0.05 mm/d and 0.06mm/d,respectively.(ET_c)_(rice) maps were produced by using calibrated model of K_c-Ⅵ and reference evapotranspiration(ET_0)from FAO Penman-Monteith method.The NRMSE was 21.3%for using FAO Penman-Monteith method.Therefore,calibrated K_c-Ⅵ model in combining with ET_0 based on the Landsat 7 ETM+images could be provided a good estimation of(ET_c)_(rice) in regional scale,and can be applied to estimate water requirement due to the free and facilitate access.
文摘This paper presents a lineament detection method using multi-band remote sensing images. The main objective of this work is to design an automatic image processing tool for lineament mapping from Landsat-7 ETM + satellite data. Five procedures were involved: 1) The Principal Component Analysis;2) image enhancement using histogram equalization technique 3) directional Sobel filters of the original data;4) histogram segmentation and 5) binary image generation. The applied methodology was contributed in identifying several known large-scale faults in the Northeast of Tunisia. The statistical and spatial analyses of lineament map indicate a difference of morphological appearance of lineaments in the satellite image. Indeed, all the lineaments present a specific organization. Five groups were classified based on three orientations: NE-SW, E-W and NW-SE. The overlapping of lineament map with the geologic map confirms that these lineaments of diverse directions can be identified and recognized on the field as a fault. The identified lineaments were linked to a deep faults caused by tectonic movements in Tunisia. This study shows the performance of the satellite image processing in the analysis and mapping of the accidents in the northern Atlas.
