Long-term coastal erosion assessment along the coast of Karnataka,west coast of India

Coastal areas are always under frequent threat from various natural processes and man-induced activities. Coastal erosion is recognized as the permanent loss of land along the shoreline resulting in the transformation of the coast. The current study focuses on long-term coastal erosion analysis of the entire Karnataka coast using Remote Sensing, Geographical Information System (GIS), Linear Regression Rate (LRR), and End Point Rate (EPR) techniques. Analysis of 26 (1990 to 2016) years of erosion using Landsat images by the use of the Digital Shoreline Analysis System (DSAS) tool has been done. The results show a high erosion rate at Ullal during this period (LRR -1.3m/yr) and accretion at Devbagh (LRR 3.2 m/yr). The southern Karnataka coast faces severe erosion especially at Ullal, where the settlement is high. At Thanirbhavi, Mukka, Kota, and Om Beaches erosion also is noticed. Both anthropogenic activities like ports, seawalls, breakwaters, etc. and natural processes like long shore drift, seasonal variation, etc. are factors affecting the shoreline change along the Karnataka coast.     

基于遥感的长沙市城市热岛与土地利用/覆盖变化研究

基于多时相Landsat TM/ETM+影像,首先计算长沙市地表亮度温度,然后利用NDVI(归一化植被指数)、MNDWI(改进 的归一化水体指数)、NDBI(归一化建筑指数)和NDBaI(归一化裸土指数)4个指数,采用决策树分类方法对长沙市影像进行 土地利用/覆盖分类。在此基础上,对长沙市城市热岛的空间分布特征、时空演变特征以及城市热岛与土地利用/覆盖变化和各种影 响因子之间的关系进行研究。结果表明,随着长沙市城区范围的不断扩张,城市热岛范围也不断增大; 土地利用/覆盖类型的变化 会改变地表温度的空间分布,城市用地和裸地是城市热岛强度的主要贡献因素,水体和林地具有较好的降温作用。地表温度与4种 归一化指数的回归分析表明,它们之间存在明显的相关性,不同土地利用/覆盖类型的地表温度存在较大差异。     

The response of vegetation cover and dune activity to rainfall,drought and fire observed by multitemporal satellite imagery

The stable longitudinal dunes in the northern Simpson Desert, Australia, were observed in satellite imagery to become more active after vegetation cover was reduced by fire and drought. Subsequent rainfall events also resulted in significant vegetation regrowth and dune stabilization. These switches between more active and stable conditions have not been previously described in the largely vegetated dune fields of central Australia. The observations, made on 12 dune sites, relied on high spatial resolution satellite imagery to observe dune crest activity, and seasonal Landsat fractional cover imagery to observe vegetation cover changes. The non-photosynthetic vegetation (NPV) component of the fractional vegetation cover images revealed significant changes in hummock grass cover on the dunes between 1988 and 2018, with a positive relationship with the three-year cumulative rainfall, disrupted by two periods of patchy burning. Only those sites that had burnt became active, and only after vegetation cover had remained low (NPV < 16%) during the ‘Millennium Drought’. There is no threshold in vegetation cover, below which dune crests become active, but active dune features require four-years of low NPV cover (< 16%) to develop. The large rainfall event that ended the drought increased NPV cover, stabilizing the dunes. Similar hummock grass covered dunes are present across large areas of the arid zone, and are likely to respond in similar ways, given that fire and drought are common occurrences in Australia. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd.     

基于随机森林模型的太湖水生植被遥感信息提取

水生植被作为太湖湿地的重要组分,其数量和范围变化影响着湖泊生态系统的平衡,故利用遥感技术对水生植被的空间分布开展研究有助于太湖湿地生态系统的保护.以Landsat 8多光谱遥感影像为主要数据源,利用光谱指数和图像变换方法构建多个特征变量,结合随机森林(RF)模型,提取太湖水生植被的空间分布.结果表明:(1)通过对比分析训练样本特征值的平均值、标准差和变异系数,NDVI、NDWIF、SR等指数更易于区分开敞水域和沉水植被、浮叶植被和挺水植被;(2)当设置1000棵分类树和4个分割节点的随机变量时,RF分类模型的袋外误分率小于6%,误分主要受SR、MNDWI和NDVI等特征变量影响;(3)通过验证分析,基于RF模型获得的2014年7月太湖水生植被覆盖面积约为306.0km2,分类精度为88.56%(Kappa系数为0.88),主要分布在湖体的东部和南部,以沉水和浮叶植被为主,两者占水生植被覆盖总面积的84.9%.     

基于影象融合的干旱区城镇居民地信息提取研究

针对TM多波段图象中城镇居民地与裸地光谱特征相似难以准确提取城镇居民地信息的问题,利用雷达图象对居民地信息的敏感性,采用HIS变换方法,融合了2003年西安地区的Landsat TM和Radarsat SAR影象,并对融合影象做二类监督分类提取出城镇居民地信息,结果显示与TM图象监督分类相比,融合后的图象能很好地消除裸地对城镇居民地提取影响,其精度可达到84.21%,大大高于由TM多光谱影象监督分类所得到的精度71.79%,为提取干旱区城镇居民地信息提供一种新方法。     

长江口水域悬沙含量时空变化卫星遥感定量研究方法探讨

悬沙含量是反映细颗粒物质在水层中的输运和再悬浮过程的重要指标,对沉积环境和沉积过程的研究有着非常重要的作用,是联系动力作用和地貌演变的纽带[1].细颗粒物质是营养盐、有机物和重金属输送的载体,因此研究细颗粒物质的运移对河口和海洋环境及生态的影响有着重要的意义[2].由于河口地区同时受到河流径流和潮流的影响,径流的水沙输运、潮流和波浪等的动力都对悬浮泥沙含量有影响.河口地区悬沙含量既可以指示沉积物来源、输运量的变化,又可以显示沉积动力作用的变化,这两种影响因素的时间尺度不同,但它们会共同影响悬沙含量的大小和分布.在我国长江等大河每年的水沙输运量十分巨大.     

基于GF-5、Landsat8与GF-2遥感数据的蚀变信息提取研究——以四川宁南铅锌矿集区为例

四川宁南铅锌矿集区是中国重要的铅锌矿成矿区之一，区内铅锌矿床广泛分布，其围岩蚀变主要为白云岩化、方解石化、黏土矿化、硅化、黄铁矿化及赤铁矿化，是重要的找矿标志，同时也为遥感提取铁染、羟基、碳酸根离子蚀变信息提供了重要的理论依据。由于遥感卫星传感器类型的不同，同一研究区内不同种类影像所得到的数据会有所差异，且采用不同的提取方法所得到的蚀变信息结果也会有所不同，因此，对同一区域进行单一影像或单一提取方法的研究往往存在偶然性与不充分性。据此，文章基于对研究区内Landsat8与GF-5两种影像数据的详细解读，采用3种有效方法进行蚀变信息提取。①波段比值法，对影像数据采用波段比值计算，并对波段比值进行密度分割，从中突出铁染，羟基、碳酸根离子蚀变信息；②主成分分析法和主分量密度分割法对铁染蚀变信息，羟基、碳酸根离子蚀变信息进行提取并作分级处理，结合GF-2高空间分辨率影像以及依据同谱异物、同物异谱、混合像元等原理剔除伪异常，以得到有效的蚀变信息；③光谱角匹配法，通过提取GF-5高光谱影像数据的纯净端员，结合光谱角匹配技术提取有效的蚀变信息矿物。对2种影像数据分别用3种提取方法所得到的蚀变信息结果进行对比，讨论其差异性，并通过叠合已知矿产地信息的方法筛选出效果较好的蚀变信息，将选取出的结果进行综合比对，最终在宁南矿集区圈定出预测靶区，经过室内化探数据验证及野外实地工作验证，证实其真实性，同时也为该地区下一步工作提供真实可靠的资料。