Globe Land 30是全球首套30 m分辨率地表覆盖数据产品,分为10种类型,包括耕地、森林、草地、灌木地等,分类精度经过多方验证达83.51%,Kappa系数0.78,耕地的分类精度达83.06%。由于Globe Land 30耕地图层没有更加详细的耕地亚类信息,限...Globe Land 30是全球首套30 m分辨率地表覆盖数据产品,分为10种类型,包括耕地、森林、草地、灌木地等,分类精度经过多方验证达83.51%,Kappa系数0.78,耕地的分类精度达83.06%。由于Globe Land 30耕地图层没有更加详细的耕地亚类信息,限制了其广泛应用。本文试图基于Globe Land 30耕地数据探索一种快速提取水田信息的方法,进而为获取全球范围的水田分布信息提供技术支持。该方法基于TM影像的归一化植被指数NDVI、地表水分指数LSWI、近红外波段的反射率ρnir和短波红外波段的反射率ρwir,通过Google Earth选取的水田样本,统计水田的光谱特征和空间特征,建立水田提取的知识规则,然后结合多尺度的分割对象图斑自动化识别水田信息。文中选取了江苏省高邮市实验区进行水田提取试验,结果表明:采用该方法分类精度比基于像素的决策树方法提升大约6%,并能有效地消除椒盐误差,图斑完整性较好。展开更多
Moderate resolution imaging spectroradiometer (MODIS) time series (TS) have been widely applied for flood monitoring in large tropical wetlands. However, little systematic work is available on the influence of pixel q...Moderate resolution imaging spectroradiometer (MODIS) time series (TS) have been widely applied for flood monitoring in large tropical wetlands. However, little systematic work is available on the influence of pixel quality, vegetation cover, and the annual hydroclimatic cycle on classification performance. In this study, this issue is examined based on a six-year, 250 m resolution MOD13Q1 TS underpinned by extensive in situ measurements. The most parsimonious logistic regression model was obtained for land surface water index (LSWI) and enhanced vegetation index (EVI). The inclusion of the 500 m MCD12Q1 land cover Type 2 product improves accuracy. Performance markedly decreases for subsets that include pixels with a VI quality assurance (QA) level poorer than 0110 and/or a pixel reliability (PR) of three. When a Savitzky-Golay filter was used for TS reconstitution, performance is slightly lower than those obtained in a classification of a VI QA 0001 or PR = 0 level strata;moreover, these have the advantage of gap-free flood monitoring. The overall accuracy (OA) of the PR = 0 subset is better for grasslands, and slightly lower for Savannah, and for woodland and forests. The average OA is highest for the dry season, intermediate for the rainy/flooded season, and lowest for the transitional seasons, when the wetland becomes flooded or dries. Comparisons of internal, k-fold, and external validations indicate that only external validation enables a realistic assessment of flood-mapping performance. The complete substitution of PR = 3 pixels by filled-in values is recommended for operational flood monitoring, and it is concluded that the use of the simplified PR metrics as filtering criteria for gap filling and smoothing is sufficient for flood monitoring in the Pantanal. Classification metrics vary more strongly as a function of the hydrological period than by vegetation cover. MOD13Q1 users should be aware that OA in forest stands during the transition seasons are, on average, 25 p.p. lower than the average OAs obtained for the entire series.展开更多
Forest fires often result in varying degrees of canopy loss in forested landscapes. The subsequent trajectory of vegetation canopy recovery is important for ecosystem processes because the canopy controls photosynthes...Forest fires often result in varying degrees of canopy loss in forested landscapes. The subsequent trajectory of vegetation canopy recovery is important for ecosystem processes because the canopy controls photosynthesis and evapotranspiration. The loss and recovery of a canopy is often measured by leaf area index （LAD and other vegetation indices that are related to canopy photosynthetic capacity. In this study we used time series imagery from the Moderate Resolution Imaging Spectroradiometer （MODIS） sensor onboard the Terra satellite over the period of 2000-2009 to track the recovery of the vegetation canopy after fire. The Black Hills National Forest, South Dakota, USA experienced an extensive wildfire starting on August 24, 2000 that burned a total area of 33 785 ha, most of which was ponderosa pine forest. The MODIS data show that canopy photosynthetic capacity, as measured by IL,AI, recovered within 3 years （2001-2003）. This recovery was attributed to rapid emergence of understory grass species after the fire event. Satellite-based Normalized Difference Vegetation Index （NDVI） and Enhanced Vegetation Index （EVI） at the burned sites also recovered within 3 years （2001-2003）. Rapid recovery of LAI, NDVI, and EVI at the burned sites makes it difficult to use these variables for identifying and mapping burned sites several years after the fire event. However, the Land Surface Water Index （LSWI）, calculated as a normalized ratio between near infrared and shortwave infrared bands （band 2 and band 6 （1628 1652 nm） in MODIS sensor）, was able to identify and track the burned sites over the entire period of 2000 2009. This fmding opens a window of opportunity to identify and map disturbances using imagery from those sensors with both NIR and SWIR bands, including Landsat 5 TM （dating back to 1984）; furthermore, a longer record of disturbance and recovery helps to improve our understanding of disturbance regimes, simulations of forest succession, and the carbon cycle.展开更多
The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer(MODIS) data in China.Paddy rice fields were extracted by identify...The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer(MODIS) data in China.Paddy rice fields were extracted by identifying the unique char-acteristic of high soil moisture in the flooding and transplanting period with improved algorithms based on rice growth calendar regionalization.The characteristic could be reflected by the enhanced vegetation index(EVI) and the land surface water index(LSWI) derived from MODIS sensor data.Algorithms for single,early,and late rice identification were obtained from selected typical test sites.The algorithms could not only separate early rice and late rice planted in the same fields,but also reduce the uncertainties.The areal accuracy of the MODIS-derived results was validated by comparison with agricultural statistics,and the spatial matching was examined by ETM+(enhanced thematic mapper plus) images in a test region.Major factors that might cause errors,such as the coarse spatial resolution and noises in the MODIS data,were discussed.Although not suitable for monitoring the inter-annual variations due to some inevitable factors,the MODIS-derived results were useful for obtaining spatial distribution maps of paddy rice on a large scale,and they might provide reference for further studies.展开更多
Timely and accurate mapping of rice planting areas is crucial under China's current cropping structure. This study proposes a new paddy rice mapping method by combining phenological parameters and a decision tree ...Timely and accurate mapping of rice planting areas is crucial under China's current cropping structure. This study proposes a new paddy rice mapping method by combining phenological parameters and a decision tree model.Six phenological parameters were developed to identify paddy rice areas based on the analysis of the Moderate Resolution Imaging Spectroradiometer (MODIS)Enhanced Vegetation Index (EVI)time series and the Land Surface Water Index (LSWI)time series.The six phenological parameters considered the performance of different land cover types during specific phenological phases (EVI1 and EVI2),one-half of or the entire rice growing cycle (LSWI1 and LSWI2),and the shape of the LSWI time series (KurtosisLSWI and SkewnessLSWI).A hierarchical decision tree model was designed to classify paddy rice areas according to the potential separability of different land cover types in paired phenological parameter spaces.Results showed that the decision tree model was more sensitive to LSWI1,LSWI2,and SkewnessLswi than the other phenological parameters.A paddy rice map of Jiangsu Province for 2015 was generated with an optimal threshold set of(0.4,0.42,9,19,1.5,-1.7,0.0)with a total accuracy of 93.9%.The MODIS-derived paddy rice map generally agreed with the paddy land fraction map from the National Land Cover Dataset project,but there were regional discrepancies because of their different definitions of land use and the inability of MODIS to map paddy rice at a fragmental level.The MODIS-derived paddy rice map showed high correlation (R^2=0.85)with county-level agricultural statistics.The results of this study indicate that the phenological parameter-based paddy rice mapping algorithm could be applied at larger spatial scales.展开更多
One of the promising and emerging enhanced oil recovery techniques in both sandstones and carbonates is engineered water injection(EWI).However,few studies discussed the field-scale applications of this technique in h...One of the promising and emerging enhanced oil recovery techniques in both sandstones and carbonates is engineered water injection(EWI).However,few studies discussed the field-scale applications of this technique in heterogeneous carbonate formations.This paper is an extension of our previous work of the EWI technology at core-scale.This research numerically investigates heterogeneity effect on EWI technique in carbonates at field-scale using five-spot models.Three synthetic five-spot sector models were considered including homogeneous,heterogeneous with permeability channeling,and heterogeneous with gravity underride.The results showed that EWI improves both volumetric and displacement sweep efficiencies compared to conventional formation water injection(FWI)for all models investigated.Also,tracer method is recommended for better estimation of volumetric sweep efficiency as opposed to fractional flow method.Moreover,secondary EWI outperforms other techniques including secondary FW and tertiary EWI.In addition,the observed delay in tertiary EWI can be reduced by increasing well injection pressure and sulfate concentration in the engineered water.An optimum sulfate concentration of 25,000 ppm is recommended for achieving the highest oil recovery by EWI.This study gives more insight into understanding the performance of the EWI technique at field-scale.Recommendations for boosting the performance of this technique have been discussed,which assure more certainty and lower risk.展开更多
文摘Globe Land 30是全球首套30 m分辨率地表覆盖数据产品,分为10种类型,包括耕地、森林、草地、灌木地等,分类精度经过多方验证达83.51%,Kappa系数0.78,耕地的分类精度达83.06%。由于Globe Land 30耕地图层没有更加详细的耕地亚类信息,限制了其广泛应用。本文试图基于Globe Land 30耕地数据探索一种快速提取水田信息的方法,进而为获取全球范围的水田分布信息提供技术支持。该方法基于TM影像的归一化植被指数NDVI、地表水分指数LSWI、近红外波段的反射率ρnir和短波红外波段的反射率ρwir,通过Google Earth选取的水田样本,统计水田的光谱特征和空间特征,建立水田提取的知识规则,然后结合多尺度的分割对象图斑自动化识别水田信息。文中选取了江苏省高邮市实验区进行水田提取试验,结果表明:采用该方法分类精度比基于像素的决策树方法提升大约6%,并能有效地消除椒盐误差,图斑完整性较好。
文摘Moderate resolution imaging spectroradiometer (MODIS) time series (TS) have been widely applied for flood monitoring in large tropical wetlands. However, little systematic work is available on the influence of pixel quality, vegetation cover, and the annual hydroclimatic cycle on classification performance. In this study, this issue is examined based on a six-year, 250 m resolution MOD13Q1 TS underpinned by extensive in situ measurements. The most parsimonious logistic regression model was obtained for land surface water index (LSWI) and enhanced vegetation index (EVI). The inclusion of the 500 m MCD12Q1 land cover Type 2 product improves accuracy. Performance markedly decreases for subsets that include pixels with a VI quality assurance (QA) level poorer than 0110 and/or a pixel reliability (PR) of three. When a Savitzky-Golay filter was used for TS reconstitution, performance is slightly lower than those obtained in a classification of a VI QA 0001 or PR = 0 level strata;moreover, these have the advantage of gap-free flood monitoring. The overall accuracy (OA) of the PR = 0 subset is better for grasslands, and slightly lower for Savannah, and for woodland and forests. The average OA is highest for the dry season, intermediate for the rainy/flooded season, and lowest for the transitional seasons, when the wetland becomes flooded or dries. Comparisons of internal, k-fold, and external validations indicate that only external validation enables a realistic assessment of flood-mapping performance. The complete substitution of PR = 3 pixels by filled-in values is recommended for operational flood monitoring, and it is concluded that the use of the simplified PR metrics as filtering criteria for gap filling and smoothing is sufficient for flood monitoring in the Pantanal. Classification metrics vary more strongly as a function of the hydrological period than by vegetation cover. MOD13Q1 users should be aware that OA in forest stands during the transition seasons are, on average, 25 p.p. lower than the average OAs obtained for the entire series.
基金supported by a grant from NASA Land Use and Land Cover Change program (NNX09AC39G)a grant from the National Science Foundation (NSF) EPSCoR program (NSF-0919466)
文摘Forest fires often result in varying degrees of canopy loss in forested landscapes. The subsequent trajectory of vegetation canopy recovery is important for ecosystem processes because the canopy controls photosynthesis and evapotranspiration. The loss and recovery of a canopy is often measured by leaf area index （LAD and other vegetation indices that are related to canopy photosynthetic capacity. In this study we used time series imagery from the Moderate Resolution Imaging Spectroradiometer （MODIS） sensor onboard the Terra satellite over the period of 2000-2009 to track the recovery of the vegetation canopy after fire. The Black Hills National Forest, South Dakota, USA experienced an extensive wildfire starting on August 24, 2000 that burned a total area of 33 785 ha, most of which was ponderosa pine forest. The MODIS data show that canopy photosynthetic capacity, as measured by IL,AI, recovered within 3 years （2001-2003）. This recovery was attributed to rapid emergence of understory grass species after the fire event. Satellite-based Normalized Difference Vegetation Index （NDVI） and Enhanced Vegetation Index （EVI） at the burned sites also recovered within 3 years （2001-2003）. Rapid recovery of LAI, NDVI, and EVI at the burned sites makes it difficult to use these variables for identifying and mapping burned sites several years after the fire event. However, the Land Surface Water Index （LSWI）, calculated as a normalized ratio between near infrared and shortwave infrared bands （band 2 and band 6 （1628 1652 nm） in MODIS sensor）, was able to identify and track the burned sites over the entire period of 2000 2009. This fmding opens a window of opportunity to identify and map disturbances using imagery from those sensors with both NIR and SWIR bands, including Landsat 5 TM （dating back to 1984）; furthermore, a longer record of disturbance and recovery helps to improve our understanding of disturbance regimes, simulations of forest succession, and the carbon cycle.
基金supported by the National High-Tech Research and Development Program (863) of China(No.2006AA120101)the National Natural Science Foundation of China(No.40871158/D0106)the Key Technologies Research and Development Program of China(No.2006BAD10A01)
文摘The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer(MODIS) data in China.Paddy rice fields were extracted by identifying the unique char-acteristic of high soil moisture in the flooding and transplanting period with improved algorithms based on rice growth calendar regionalization.The characteristic could be reflected by the enhanced vegetation index(EVI) and the land surface water index(LSWI) derived from MODIS sensor data.Algorithms for single,early,and late rice identification were obtained from selected typical test sites.The algorithms could not only separate early rice and late rice planted in the same fields,but also reduce the uncertainties.The areal accuracy of the MODIS-derived results was validated by comparison with agricultural statistics,and the spatial matching was examined by ETM+(enhanced thematic mapper plus) images in a test region.Major factors that might cause errors,such as the coarse spatial resolution and noises in the MODIS data,were discussed.Although not suitable for monitoring the inter-annual variations due to some inevitable factors,the MODIS-derived results were useful for obtaining spatial distribution maps of paddy rice on a large scale,and they might provide reference for further studies.
基金the National Natural Science Foundation of China (Grant No.41401494)China Postdoctoral Science Foundation (No.2014M552475)Foundation of Shaanxi Educational Committee (No.14JK1745).
文摘Timely and accurate mapping of rice planting areas is crucial under China's current cropping structure. This study proposes a new paddy rice mapping method by combining phenological parameters and a decision tree model.Six phenological parameters were developed to identify paddy rice areas based on the analysis of the Moderate Resolution Imaging Spectroradiometer (MODIS)Enhanced Vegetation Index (EVI)time series and the Land Surface Water Index (LSWI)time series.The six phenological parameters considered the performance of different land cover types during specific phenological phases (EVI1 and EVI2),one-half of or the entire rice growing cycle (LSWI1 and LSWI2),and the shape of the LSWI time series (KurtosisLSWI and SkewnessLSWI).A hierarchical decision tree model was designed to classify paddy rice areas according to the potential separability of different land cover types in paired phenological parameter spaces.Results showed that the decision tree model was more sensitive to LSWI1,LSWI2,and SkewnessLswi than the other phenological parameters.A paddy rice map of Jiangsu Province for 2015 was generated with an optimal threshold set of(0.4,0.42,9,19,1.5,-1.7,0.0)with a total accuracy of 93.9%.The MODIS-derived paddy rice map generally agreed with the paddy land fraction map from the National Land Cover Dataset project,but there were regional discrepancies because of their different definitions of land use and the inability of MODIS to map paddy rice at a fragmental level.The MODIS-derived paddy rice map showed high correlation (R^2=0.85)with county-level agricultural statistics.The results of this study indicate that the phenological parameter-based paddy rice mapping algorithm could be applied at larger spatial scales.
基金partially supported by Khalifa University under Award No.[FSU-2018-26].
文摘One of the promising and emerging enhanced oil recovery techniques in both sandstones and carbonates is engineered water injection(EWI).However,few studies discussed the field-scale applications of this technique in heterogeneous carbonate formations.This paper is an extension of our previous work of the EWI technology at core-scale.This research numerically investigates heterogeneity effect on EWI technique in carbonates at field-scale using five-spot models.Three synthetic five-spot sector models were considered including homogeneous,heterogeneous with permeability channeling,and heterogeneous with gravity underride.The results showed that EWI improves both volumetric and displacement sweep efficiencies compared to conventional formation water injection(FWI)for all models investigated.Also,tracer method is recommended for better estimation of volumetric sweep efficiency as opposed to fractional flow method.Moreover,secondary EWI outperforms other techniques including secondary FW and tertiary EWI.In addition,the observed delay in tertiary EWI can be reduced by increasing well injection pressure and sulfate concentration in the engineered water.An optimum sulfate concentration of 25,000 ppm is recommended for achieving the highest oil recovery by EWI.This study gives more insight into understanding the performance of the EWI technique at field-scale.Recommendations for boosting the performance of this technique have been discussed,which assure more certainty and lower risk.
