{"title":"利用NDVI和LAI监测小麦和向日葵半干旱种植系统不同生育期土地覆盖变化","authors":"Melise Pinar, G. Erpul","doi":"10.1109/Agro-Geoinformatics.2019.8820423","DOIUrl":null,"url":null,"abstract":"Evaluation indicators and parameters of land use and cover change have been drawing a significant attention as approaches for Sustainable Land Management (SLM), Sustainable Soil Management (SSM), Land Degradation Neutrality (LDN), Conservation Agriculture (CA), Climate Smart Agriculture (CSA) etc. increasingly progress to sustain and promote above and below-ground ecosystem services for human wellbeing. Most of the relevant models duly strive to improve their capability and propriety of assessing temporal-spatial cover change trend using remote sensing tools. Exclusively, from the perspective of different earth surface hydrological and erosional processes, not only over a period of years, rotational management systems of agricultural land require understanding of variations but within a year, as well. In this study, two different NDVI(Normalized Different Vegetation Index) metrics derived from satellite images of Pleiades 1A-1B and Spot-7 (NDVIsat and NDVIgm, respectively) and ground-measurements by hand-held crop sensor to obtain LAI (Leaf Area Index) were used to determine within a year variations occurred at different crop-stages of wheat and sunflower plots in semi-arid cropping systems in Turkey. Rough Fallow (Period F), Seedbed (Period SB), Establishment (Period 1 for sunflower), Development (Period 2 for wheat) and Maturing (Period 3) constituted measurement stages. In general, correlation analysis showed results from all three methodologies (NDVIsat, NDVIgm and LAI) were highly correlated one another at each growth stage. Exceptionally, NDVIsat, NDVIgm and LAI were poorly correlated at Period 1 and Period 3, respectively, for sunflower and wheat. To a great extent this was ascribed to the fact that wheat photosynthetic activity inversely varied with its leaf area index at Period 3 and the fact that vegetation cover rate of sunflower showed kind of fluctuations that hindered a clear gradient to emerge in Period 1. Also, the means of measurements of different growth stages for each research method were compared by ANOVA test, and all three methodologies statistically detected differences as the photosynthetic activity either increased or decreased among the wheat and sunflower growth stages with few exceptions. For instance, the LAI could not mark any significant difference between Period F and Period SB in wheat plots while NDVI-sat showed no statistically significant difference between Period F and Period 3 in sunflower. For either crops it was clearly observable from both satellite and ground measurements that the NDVI values increased as photosynthetic activity was approaching its maximum level, after which it decreased with the start of maturement; on the other hand, rather than photosynthetic activity, the LAI reached maximum values as the number and periphery of leave layers increased, which was much more notable for sunflowers. Consequently, study methods led to much clearer results for horizontally growing sunflower plots than those of wheat for all growth stages, suggesting that NDVI's can be used in combination with LAI to have cumulative totals of differences stemming from variances in both photosynthetic activity and leave periphery by growth stages.","PeriodicalId":143731,"journal":{"name":"2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Monitoring land cover changes during different growth stages of semi-arid cropping systems of wheat and sunflower by NDVI and LAI\",\"authors\":\"Melise Pinar, G. Erpul\",\"doi\":\"10.1109/Agro-Geoinformatics.2019.8820423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Evaluation indicators and parameters of land use and cover change have been drawing a significant attention as approaches for Sustainable Land Management (SLM), Sustainable Soil Management (SSM), Land Degradation Neutrality (LDN), Conservation Agriculture (CA), Climate Smart Agriculture (CSA) etc. increasingly progress to sustain and promote above and below-ground ecosystem services for human wellbeing. Most of the relevant models duly strive to improve their capability and propriety of assessing temporal-spatial cover change trend using remote sensing tools. Exclusively, from the perspective of different earth surface hydrological and erosional processes, not only over a period of years, rotational management systems of agricultural land require understanding of variations but within a year, as well. In this study, two different NDVI(Normalized Different Vegetation Index) metrics derived from satellite images of Pleiades 1A-1B and Spot-7 (NDVIsat and NDVIgm, respectively) and ground-measurements by hand-held crop sensor to obtain LAI (Leaf Area Index) were used to determine within a year variations occurred at different crop-stages of wheat and sunflower plots in semi-arid cropping systems in Turkey. Rough Fallow (Period F), Seedbed (Period SB), Establishment (Period 1 for sunflower), Development (Period 2 for wheat) and Maturing (Period 3) constituted measurement stages. In general, correlation analysis showed results from all three methodologies (NDVIsat, NDVIgm and LAI) were highly correlated one another at each growth stage. Exceptionally, NDVIsat, NDVIgm and LAI were poorly correlated at Period 1 and Period 3, respectively, for sunflower and wheat. To a great extent this was ascribed to the fact that wheat photosynthetic activity inversely varied with its leaf area index at Period 3 and the fact that vegetation cover rate of sunflower showed kind of fluctuations that hindered a clear gradient to emerge in Period 1. Also, the means of measurements of different growth stages for each research method were compared by ANOVA test, and all three methodologies statistically detected differences as the photosynthetic activity either increased or decreased among the wheat and sunflower growth stages with few exceptions. For instance, the LAI could not mark any significant difference between Period F and Period SB in wheat plots while NDVI-sat showed no statistically significant difference between Period F and Period 3 in sunflower. For either crops it was clearly observable from both satellite and ground measurements that the NDVI values increased as photosynthetic activity was approaching its maximum level, after which it decreased with the start of maturement; on the other hand, rather than photosynthetic activity, the LAI reached maximum values as the number and periphery of leave layers increased, which was much more notable for sunflowers. 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Monitoring land cover changes during different growth stages of semi-arid cropping systems of wheat and sunflower by NDVI and LAI
Evaluation indicators and parameters of land use and cover change have been drawing a significant attention as approaches for Sustainable Land Management (SLM), Sustainable Soil Management (SSM), Land Degradation Neutrality (LDN), Conservation Agriculture (CA), Climate Smart Agriculture (CSA) etc. increasingly progress to sustain and promote above and below-ground ecosystem services for human wellbeing. Most of the relevant models duly strive to improve their capability and propriety of assessing temporal-spatial cover change trend using remote sensing tools. Exclusively, from the perspective of different earth surface hydrological and erosional processes, not only over a period of years, rotational management systems of agricultural land require understanding of variations but within a year, as well. In this study, two different NDVI(Normalized Different Vegetation Index) metrics derived from satellite images of Pleiades 1A-1B and Spot-7 (NDVIsat and NDVIgm, respectively) and ground-measurements by hand-held crop sensor to obtain LAI (Leaf Area Index) were used to determine within a year variations occurred at different crop-stages of wheat and sunflower plots in semi-arid cropping systems in Turkey. Rough Fallow (Period F), Seedbed (Period SB), Establishment (Period 1 for sunflower), Development (Period 2 for wheat) and Maturing (Period 3) constituted measurement stages. In general, correlation analysis showed results from all three methodologies (NDVIsat, NDVIgm and LAI) were highly correlated one another at each growth stage. Exceptionally, NDVIsat, NDVIgm and LAI were poorly correlated at Period 1 and Period 3, respectively, for sunflower and wheat. To a great extent this was ascribed to the fact that wheat photosynthetic activity inversely varied with its leaf area index at Period 3 and the fact that vegetation cover rate of sunflower showed kind of fluctuations that hindered a clear gradient to emerge in Period 1. Also, the means of measurements of different growth stages for each research method were compared by ANOVA test, and all three methodologies statistically detected differences as the photosynthetic activity either increased or decreased among the wheat and sunflower growth stages with few exceptions. For instance, the LAI could not mark any significant difference between Period F and Period SB in wheat plots while NDVI-sat showed no statistically significant difference between Period F and Period 3 in sunflower. For either crops it was clearly observable from both satellite and ground measurements that the NDVI values increased as photosynthetic activity was approaching its maximum level, after which it decreased with the start of maturement; on the other hand, rather than photosynthetic activity, the LAI reached maximum values as the number and periphery of leave layers increased, which was much more notable for sunflowers. Consequently, study methods led to much clearer results for horizontally growing sunflower plots than those of wheat for all growth stages, suggesting that NDVI's can be used in combination with LAI to have cumulative totals of differences stemming from variances in both photosynthetic activity and leave periphery by growth stages.