缅甸土地覆被遥感制图和空间格局分析

在“一带一路”倡议框架下，中缅经济走廊逐步从概念转入实质规划建设阶段，了解和掌握缅甸土地覆被的空间格局和分布特征对于合理开发利用资源、制定务实的经济廊道建设规划具有重要的战略意义。利用Landsat-8 OLI遥感影像数据，基于多分类器集成的面向对象迭代分类方法（OIC-MCE），生产了缅甸2015年30 m分辨率土地覆被产品（MyanmarLC-2015）。采用Google Earth高分辨率影像获取验证样本用于产品精度验证，验证结果表明：MyanmarLC-2015产品的总体分类精度为89.05%,Kappa系数为0.87，各类别的用户精度和制图精度均超过72%，能够准确地反映缅甸土地覆被类型的空间格局。根据产品统计，林地是缅甸面积最大的土地覆被类型，占国土面积56.15%，以常绿阔叶林为主，占林地面积83.57%。耕地面积次之，占国土面积27.01%。地形因子对缅甸土地覆被类型空间分布格局有显著的影响，随着海拔升高，呈现出按如下顺序的垂直地带性特征：森林湿地、水田、旱地、落叶灌木林、落叶阔叶林、常绿灌木林、常绿阔叶林、常绿针叶林。从植被生产力的角度来看，缅甸东部、东北部和东南部植...

Land Cover Mapping and Spatial Pattern Analysis with Remote Sensing in Myanmar

Under the framework of the "Belt and Road" initiative， the China-Myanmar Economic Corridor has gradually moved from planning to substantive construction. Understanding the spatial pattern and distribution characteristics of land cover in Myanmar is of great strategic significance for the rational exploitation and utilization of resources and the planning of economic corridor construction. In this paper， a 30m resolution land cover product of Myanmar in 2015 （hereinafter referred to as the MyanmarLC-2015） was produced using Landsat8 OLI remote sensing images， based on the Object-oriented Iterative Classification method based on Multiple Classifiers Ensemble （OIC-MCE）. Besides， the accuracy validation of the MyanmarLC-2015 was conducted by using samples obtained from high-resolution Google Earth imagery. The verification results show that the overall classification accuracy of MyanmarLC-2015 product is 89.05%， the Kappa coefficient is 0.87， which can accurately reflect the spatial distribution characteristics of land cover in Myanmar. According to statistics， forest is the major land cover class in Myanmar， accounting for 56.15% of the total land area of Myanmar. The cultivated land area followed， accounting for 27.01% of the total land area. Combined with topographic factors， we know that with the increase of altitude， the appearance pattern of the typical land cover classes is tree wetlands， paddy fields， dry lands， deciduous shrublands， deciduous broadleaf forests， evergreen shrublands， evergreen broadleaf forests， and evergreen needleleaf forests. From the perspective of vegetation productivity， the NPP of vegetation is the largest in the eastern， northeastern and southeastern parts of Myanmar， while it is lower of vegetation in the central arid region and the southern Irrawaddy Delta. In 2015， the average of Net Primary Productivity for vegetation in Myanmar was higher in evergreen forest than deciduous forest， broad-leaved forest higher than shrub forest， and the productivity of dry land in cultivated land higher than paddy field.