利用多时相MODIS NDVI数据进行土地利用/覆被分类和变化监测（英文）

编号 zgly0001584856

文献类型 期刊论文

文献题名 利用多时相MODIS NDVI数据进行土地利用/覆被分类和变化监测（英文）

作者 MUSMAN  RLIEDL  MASHAHID  AABBAS 

作者单位 InstituteforGroundwaterManagement  UniversityofAgriculture  LeibnizCentreforAgriculturalLandscapeResearch(ZALF) 

母体文献 Journal of Geographical Sciences 

年卷期 2015年12期

年份 2015 

分类号 P237  P901 

关键词 landuse/landcover  remotesensing  normalizeddifferencevegetationindex  accuracyassessment  changedetection  hydrologicalmodeling 

文摘内容 Detailed analysis of Land Use/Land Cover(LULC) using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this study provides detailed land use maps of the Lower Chenab Canal irrigated region of Pakistan from 2005 to 2012 for LULC change detection. Major crop types are demarcated by identifying temporal profiles of NDVI using MODIS 250 m ? 250 m spatial resolution data. Wheat and rice are found to be major crops in rabi and kharif seasons, respectively. Accuracy assessment of prepared maps is performed using three different techniques: error matrix approach, comparison with ancillary data and with previous study. Producer and user accuracies for each class are calculated along with kappa coefficients(K). The average overall accuracies for rabi and kharif are 82.83% and 78.21%, respectively. Producer and user accuracies for individual class range respectively between 72.5% to 77% and 70.1% to 84.3% for rabi and 76.6% to 90.2% and 72% to 84.7% for kharif. The K values range between 0.66 to 0.77 for rabi with average of 0.73, and from 0.69 to 0.74 with average of 0.71 for kharif. LULC change detection indicates that wheat and rice have less volatility of change in comparison with both rabi and kharif fodders. Transformation between cotton and rice is less common due to their completely different cropping conditions. Results of spatial and temporal LULC distributions and their seasonal variations provide useful insights for establishing realistic LULC scenarios for hydrological studies.