Satellite-based investigation of flood-affected rice cultivation areas in Chao Phraya River Delta,Thailand     

《ISPRS Journal of Photogrammetry and Remote Sensing》2013

The occurrence of catastrophic floods in Thailand in 2011 caused significant damage to rice agriculture. This study investigated flood-affected rice cultivation areas in the Chao Phraya River Delta (CRD) rice bowl, Thailand using time-series moderate resolution imaging spectroradiometer (MODIS) data. The data were processed for 2008 (normal flood year) and 2011, comprising four main steps: (1) data pre-processing to construct time-series MODIS vegetation indices (VIs), to filter noise from the time-series VIs by the empirical mode decomposition (EMD), and to mask out non-agricultural areas in respect to water-related cropping areas; (2) flood-affected area classification using the unsupervised linear mixture model (ULMM); (3) rice crop classification using the support vector machines (SVM); and (4) accuracy assessment of flood and rice crop mapping results. The comparisons between the flood mapping results and the ground reference data indicated an overall accuracy of 97.9% and Kappa coefficient of 0.62 achieved for 2008, and 95.7% and 0.77 for 2011, respectively. These results were reaffirmed by close agreement (R² > 0.8) between comparisons of the two datasets at the provincial level. The crop mapping results compared with the ground reference data revealed that the overall accuracies and Kappa coefficients obtained for 2008 were 88.5% and 0.82, and for 2011 were 84.1% and 0.76, respectively. A strong correlation was also found between MODIS-derived rice area and rice area statistics at the provincial level (R² > 0.7). Rice crop maps overlaid on the flood-affected area maps showed that approximately 16.8% of the rice cultivation area was affected by floods in 2011 compared to 4.9% in 2008. A majority of the flood-expanded area was observed for the double-cropped rice (10.5%), probably due to flood-induced effects to the autumn–summer and rainy season crops. Information achieved from this study could be useful for agricultural planners to mitigate possible impacts of floods on rice production.  相似文献   

Plume and bloom: effect of the Mississippi River diversion on the water quality of Lake Pontchartrain     

Deepak R. Mishra  Sachidananda Mishra 《国际地球制图》2013,28(7):555-568

The opening of the Bonnet Carré spillway to prevent flood threat to New Orleans in April 2008 created a sediment plume in the Lake Pontchartrain. The nutrient rich plume triggered a massive algal bloom in the lake. In this article, we have quantified the spatio-temporal distribution of the plume (suspended solids) and the bloom (chlorophyll-a (chl-a)) in the lake using remotely-sensed data. We processed the Moderate-resolution Imaging Spectroradiometer satellite data for mapping the total suspended solids (TSS) and chl-a concentrations. An existing algorithm was used for estimating TSS whereas a novel slope model was developed to predict the per-pixel chl-a concentration. Both algorithms were successful in capturing the spatio-temporal trend of TSS and chl-a concentrations, respectively. Algal growth was found to be inversely related to TSS concentrations and a time lag of ～45 days existed between the spillway opening and the appearance of the first algal bloom at an observation location.  相似文献   

Atmospheric correction to IRS-P6 AWiFS data and its validation with ground measurements: A study over the semi-arid region     

Anu Rani Sharma  Shailesh Kumar Kharol 《国际地球制图》2013,28(7):581-594

In this study, we have implemented a fast atmospheric correction algorithm to IRS-P6 advanced wide field sensor (AWiFS) satellite data for retrieving surface reflectance under different atmospheric and surface conditions. The algorithm is based on MODIS climatology products and simplified use of Second Simulation of Satellite Signal in Solar Spectrum (6S) radiative transfer code. The algorithm requires information on aerosol optical depth (AOD) for correcting the satellite dataset. The atmospheric correction algorithm has been tested for IRS-P6 AWiFS False colour composites covering the International Crops Research Institute for the Semi-Arid Tropics Farm, Patancheru, Hyderabad, India, under varying atmospheric conditions. Ground measurements of surface reflectance representing different land use/land cover, i.e. red soil, chick pea, groundnut and pigeon pea crops were conducted to validate the algorithm. Terra MODIS AOD₅₅₀ validated with Microtops-II sun photometer–derived AOD₅₀₀ over the urban region of Hyderabad exhibited very good correlation of ～0.92, suggesting possible use of satellite-derived AOD for atmospheric correction.  相似文献   

Evaluating a thermal image sharpening model over a mixed agricultural landscape in India     

C. Jeganathan  N.A.S. Hamm  S. Mukherjee  P.M. Atkinson  P.L.N. Raju  V.K. Dadhwal 《International Journal of Applied Earth Observation and Geoinformation》2011

Fine spatial resolution (e.g., <300 m) thermal data are needed regularly to characterise the temporal pattern of surface moisture status, water stress, and to forecast agriculture drought and famine. However, current optical sensors do not provide frequent thermal data at a fine spatial resolution. The TsHARP model provides a possibility to generate fine spatial resolution thermal data from coarse spatial resolution (≥1 km) data on the basis of an anticipated inverse linear relationship between the normalised difference vegetation index (NDVI) at fine spatial resolution and land surface temperature at coarse spatial resolution. The current study utilised the TsHARP model over a mixed agricultural landscape in the northern part of India. Five variants of the model were analysed, including the original model, for their efficiency. Those five variants were the global model (original); the resolution-adjusted global model; the piecewise regression model; the stratified model; and the local model. The models were first evaluated using Advanced Space-borne Thermal Emission Reflection Radiometer (ASTER) thermal data (90 m) aggregated to the following spatial resolutions: 180 m, 270 m, 450 m, 630 m, 810 m and 990 m. Although sharpening was undertaken for spatial resolutions from 990 m to 90 m, root mean square error (RMSE) of <2 K could, on average, be achieved only for 990–270 m in the ASTER data. The RMSE of the sharpened images at 270 m, using ASTER data, from the global, resolution-adjusted global, piecewise regression, stratification and local models were 1.91, 1.89, 1.96, 1.91, 1.70 K, respectively. The global model, resolution-adjusted global model and local model yielded higher accuracy, and were applied to sharpen MODIS thermal data (1 km) to the target spatial resolutions. Aggregated ASTER thermal data were considered as a reference at the respective target spatial resolutions to assess the prediction results from MODIS data. The RMSE of the predicted sharpened image from MODIS using the global, resolution-adjusted global and local models at 250 m were 3.08, 2.92 and 1.98 K, respectively. The local model consistently led to more accurate sharpened predictions by comparison to other variants.  相似文献   

基于典型物候特征的MODIS-EVI时间序列数据 农作物种植面积提取方法 —小区域冬小麦实验研究   总被引：11，自引：1，他引：10  

潘耀忠  李乐  张锦水  梁顺林  侯东 《遥感学报》2011,15(3):578-594

利用MODIS植被指数时间序列这一特性,以北京市通州及周边为实验区,冬小麦种植面积为研究对象,提出 了农作物种植面积指数模型(Pan-CPI模型)的概念,并构造了冬小麦特征物候期植被指数与种植面积的定量函数关系, 通过样区TM影像求解关键参数,对研究区冬小麦种植面积测量方法进行了试验研究。研究结果表明：(1)Pan-CPI模 型能够很好地反映特定目标农作物种植面积状况,为基于植被指数时间序列影像识别农作物种植面积提供了新方法; (2)精度分析结果表明：Pan-CPI模型具有很高的稳定性,且不受样本变化的影响,只要达到满足模型计算的样本量(如： 5%),多次测量结果间具有很好的一致性。选取MODIS 6×6像元大小的窗口时,TM样本的复相关系数(R2)稳定在0.85 左右,与TM结果比较,窗口相对精度稳定在95%左右,区域精度稳定在92%以上,经调整的区域精度高达96%以上; (3)对于种植结构复杂、目标作物种植破碎的地区,Pan-CPI模型可以充分利用MODIS植被指数时间序列的优势,有效改 善TM单时相和多时相提取信息因时相缺失无法表征作物变化的不足。  相似文献   

MODIS NDVI和AVHRR NDVI 对草原植被变化监测差异   总被引：5，自引：0，他引：5  

陈燕丽  龙步菊  潘学标  钟仕全  莫伟华 《遥感学报》2011,15(4):831-845

以草地作为研究载体,对比分析草原植被AVHRR NDVI和MODIS NDVI两种NDVI序列的年内、年际变化特征,讨论两种NDVI序列对降水量、平均气温和水汽压3种气候因子的响应差异,为合理选择NDVI序列对植被进行监测研究提供参考。结果表明：(1)两种NDVI序列所反映的草原植被年内变化趋势相似,但MODIS NDVI对各类草原的区分度优于AVHRR NDVI;(2)两种NDVI序列所反映的2000年—2003年草原植被年际变化差异明显。较之于MODIS NDVI,AVHRR NDVI变化趋势分类图表现出更强的植被改善趋势,植被改善面积在AVHRR NDVI变化趋势分类图中占94.25%,在MODIS NDVI中为83.33%;两种NDVI变化趋势分类图反映的植被变化趋势吻合度为52.88%。(3)两种NDVI序列与水汽压、降水量相关性差异显著。MODIS NDVI与各站点平均气温的相关系数均大于GIMMS NDVI;而MODIS NDVI与水汽压的相关系数83%(10个站点)小于GIMMS NDVI,与降水量的相关系数67%(8个站点)小于GIMMS NDVI。  相似文献   

NASA MODIS海冰产品评价分析——以辽东湾海冰监测为例     

马龙 《国土资源遥感》2011,22(1):115-117

NASA开发的MODIS海冰产品可提供全球范围的海冰分布和冰表温度信息,但将其直接用于局地和区域海冰监测时,其精度还有待进一步验证.以辽东湾冬季海冰监测为例,对MODIS海冰产品进行了分析,发现该产品将区域内绝大部分海冰标识为云.根据NASA的海冰算法,利用反射率和冰表温度(Ice Surface Temperatur...  相似文献   

星载激光雷达气溶胶数据辅助的近岸浑浊水体大气校正研究     

田礼乔  陈晓玲  邱凤  张伟 《武汉大学学报(信息科学版)》2011,(8):960-963,1009

提出了一种星载激光雷达CALIOP气溶胶数据辅助的MODIS/Aqua水色数据大气校正方法,并在长江口及其邻近浑浊水体区域进行了实验。通过与实测光谱数据的对比分析说明,本文方法能在一定程度上避免如近红外波段离水辐亮度为零的假设的不合理性,摆脱对实测数据的依赖,有效地反演离水辐亮度,修复SeaDAS软件中短波红外-近红外联合大气校正算法中短波红外波段引起的产品的条带问题。  相似文献   

应用MODIS数据对陕西地区土地利用/覆盖变化的监测     

樊艳伟  林超  吕国胜 《地理空间信息》2011,(4):136-139

应用MODIS数据监测陕西地区土地利用/覆盖变化。主要内容是利用陕西省MODIS影像辅助以ETM＋等数据进行最大似然法监督分类,根据分类的结果得到各个土地利用类型面积,然后与统计资料对比,进行土地利用/土地覆盖动态监测分析。  相似文献   

Application of snowmelt runoff model for water resource management   总被引：1，自引：0，他引：1  

Mohsin Jamil Butt  Muhammad Bilal 《水文研究》2011,25(24):3735-3747

Snow‐covered areas (SCAs) are the fundamental source of water for the hydrological cycle for some region. Accurate measurements of river discharge from snowmelt can help manage much needed water required for hydropower generation and irrigation purposes. This study aims to apply the snowmelt runoff model (SRM) in the Upper Indus basin by the Astore River in northern Pakistan for the years 2000 to 2006. The Shuttle Radar Topographic Mission (SRTM) data are used to generate the Digital Elevation Model (DEM) of the region. Various variables (snow cover depletion curves (SCDCs), temperature and precipitation) and parameters (degree‐day factor, recession coefficient, runoff coefficients, time lag, critical temperature and temperature lapse rate) are used as input in the SRM. However, snow cover data are direct and an important input to the SRM. Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate the SCA. Normalized difference snow index (NDSI) algorithm is applied for snow cover mapping and to differentiate snow from other land features. Nash–Sutcliffe coefficient of determination (R²) and volume difference (D_V) are used for quality assessment of the SRM. The results of the current research show that for the study years (2000–2006), the average value of R² is 0·87 and average volume difference D_V is 1·18%. The correlation coefficient between measured and computed runoff is 0·95. The results of the study further show that a high level of accuracy can be achieved during the snowmelt season. The simulation results endorse that the SRM in conjunction with MODIS snow cover product is very useful for water resource management in the Astore River and can be used for runoff forecasts in the Indus River basin in northern Pakistan. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献