AN AUTOMATIC PROCEDURE FOR ESTIMATING SPRING SMALL GRAINS ACREAGE FROM LANDSAT DATA

The development and testing of a computerized technique for utilizing multitemporal Landsat multispectral scanner data to estimate spring small grains acreage are described. The Kauth-Thomas green number transformation is applied to the data prior to application of the pixel-level standardized logic. Four years of data from the U.S. and Canada are used in testing. A comparison of the test results to those of the analyst-intensive procedures indicates a potential for increase in near-harvest estimation efficiency with little sacrifice in accuracy.     

WyomingView: No-Cost Remotely Sensed Data for Geographic Education

Abstract

Learning enhanced by visual examples and remotely sensed imagery is a valuable classroom resource for teaching students geographic concepts in a meaningful context. Barriers to the use of imagery include difficulty finding appropriate imagery and the cost of moderate resolution satellite imagery. A program in Wyoming called WyomingView and analogous programs in other states are providing no-cost, preprocessed satellite imagery delivered over the Internet that can help teachers better communicate geospatial knowledge to their students.     

The influence of bottom vegetation on remote sensing bathymetry: A case study using Landsat Thematic Mapper data in the Zanzibar Channel

By using echo-sounding data and considerable local knowledge of the environment the possibility to use data from Landsat TM for bathymetric mapping is analysed in the vicinity of Zanzibar. Different TM band combinations and basic image processing techniques are evaluated against the known water depths. The limitations of remote sensing techniques for bathymetric mapping are discussed, with emphasis on the problem of differences in reflective properties of the sea bottom. A recommendation for an optimal empirical method is given.     

基于ETM＋遥感影像反演不同土地利用类型地表温度的研究

采用Landsat7 ETM＋为基本数据源,运用3种算法（大气辐射传输方程RTE、Qin等单窗算法和Jimenez—Munoz＆Sobrino普适性单通道算法）定量反演了黄河三角洲部分地区的地表温度（land surface temperature,LST）,并进行了不同算法反演结果的差值比较：以RTE反演结果为标准,在大气水汽含量较低时,Qin等单窗算法和JM＆S普适性单通道算法精度较高,与RTE的反演结果相差均在1K以内;在大气水汽含量较高时,Qin等单窗算法在采用地面气象资料估算水汽含量条件下仍保持较高的精度,比RTE反演结果平均偏小0．95K;而根据估算的大气水汽含量进行反演的JM＆S普适性单通道算法的反演偏差比Qin等单窗算法要大,达到1．94K,但JM＆S普适性单通道算法根据实测的大气水汽含量得到的反演结果要略优于Qin等单窗算法,比RTE结果偏大0．67K。同时计算了经过6s模式校正后归一化植被指数（INDV）,然后利用GIS中的空间分析功能,分析LST、INDV在不同土地利用类型之间的差异以及二者之间的定量关系。发现研究区内,就所有土地利用类型而言,平均LST和INDV之间存在显著的负相关关系;对于各种土地利用类型,这种相关关系也存在．但相关程度不同。     

单窗算法的大气参数估计方法

根据地表热辐射传导方程,提出了一个简单可行且精度较高的专门用于从TM6数据中演算地表温度的方法——单窗算法.这一算法把大气和地表状态对地表热传导的影响直接包括在演算公式中.该方法需要两个大气参数进行地表温度的演算,即大气平均作用温度和大气透射率.本文论述这两个大气参数的估计方法:根据大气水分含量或地表附近空气湿度来估计大气透射率;通过分析标准大气剖面资料,尤其是大气水分和气温随高程的变化规律,根据地表温度推算大气平均作用温度.     

地形抹平与半经验模型的Landsat TM/ETM+地形校正方法

地形校正可以减小地形起伏对地物光谱的影响,提高计算机分类在山区的精度。设计了针对全球土地覆盖分类的Landsat TM/ETM+数据地形校正方法 SCOS(Smoothed COS余弦),首先对地形的坡度角进行抹平处理,很大程度上削弱了地表非朗伯性对地形校正的影响,然后利用简单有效的余弦校正去除地形效应。该方法与其他常用地形校正算法的对比分析是通过对全球不同区域、不同地表覆盖的有代表性的6景Landsat TM/ETM+数据的试验,采用统计分析与目视判读的方式,从过度校正和类内均一性两个方面进行的。结果表明,该方法在目视效果和统计结果上优于常规方法,并且更加简单有效,无需复杂的大气参数及传感器参数,满足全球地表覆盖分类对地形校正的需求。     

集成Landsat OLI和机载LiDAR条带数据的亚热带森林生物量制图

以亚热带天然次生林为研究对象,借助一个条带的少量LiDAR点云数据和覆盖整个研究区的免费Landsat OLI多光谱数据,并结合地面实测数据,探索森林生物量低成本高精度制图方法。首先,提取了OLI和LiDAR特征变量,并与地上和地下生物量进行相关分析以筛选变量;然后,借助LiDAR数据覆盖区的样地和条带LiDAR数据构建"LiDAR生物量模型";再从LiDAR反演生物量的结果中进行采样,结合OLI特征变量构建"LiDAR-OLI模型";最后,与单独使用OLI多光谱数据建立的"OLI估算模型"结果进行比较,分析精度并验证新方法的效果。结果表明,"LiDAR-OLI模型"对地上和地下生物量的模型拟合效果较好且均优于"OLI模型",且其交叉验证的精度也较高并优于"OLI模型",从而证明了新方法的可靠性及有效性。本研究为主、被动遥感技术在中小尺度上协同反演森林参数提供了实验基础,也为基于全覆盖免费OLI多光谱数据及条带LiDAR数据的低成本森林生物量制图探索了技术路线。     

Mapping mineralogy in evaporite basins through time using multispectral Landsat data: Examples from the Bonneville basin,Utah, USA

The Bonneville basin, located in north-western Utah, is a vast evaporite basin which is home to the world-renowned Bonneville Salt Flats international speedway and is a highly valued landscape undergoing rapid change and anthropogenic influence. Air quality, snowpack, the local hydrological system, and state tourism are all impacted by the nature of the surface sediments exposed in the Bonneville basin. Mapping the Bonneville basin over time with remote sensing methods provides insight into the dynamics and impacts of the changing surface landscape. Utilizing the Landsat-5 Thematic Mapper (TM) and Landsat-8 Operational Land Imager (OLI) sensors, a set of band math indices are empirically established to map the predominant halite, gypsum, and carbonates mineralogical zones of the Bonneville basin. Spectral comparisons of representative samples from the study area and image-derived spectra indicate the halite of the Bonneville basin is wet and that gypsum deposits are slightly mixed with halite. The established indices are assessed in four ways, all of which support the ability of the indices to accentuate the associated mineralogical endmembers. Two study areas within the Bonneville basin are investigated temporally from 1986, 1995, 2005, and 2016 and show changing patterns in mineral distribution that align with surface processes active through these timescales. These indices provide a resource for mapping mineralogy though time in evaporite basins globally with diverse applications for questions about land use and environmental change.     

油砂的光谱反射特征及其遥感应用

油砂作为21世纪以来世界能源的重要组成部分,已经有大量的地质工作者对其形成的地质特征、成矿带分布特征等进行了详细研究,并取得一定成果,但是对于遥感在油砂勘探中的应用少有研究。遥感技术识别不同地物的理论基础是同一波长位置处的反射率差异及反射率随波长的变化规律,因此本文通过分析油砂的实测光谱数据,得到其反射光谱的特征及规律。为实现在Landsat 8OLI卫星遥感影像上对油砂的识别,根据油砂实测光谱的研究,分别提出基于油砂光谱特征和相关性分析的Landsat 8遥感影像油砂识别模式,并将其应用在柴达木盆地冷湖和马海两个研究区。结果表明:利用遥感影像进行油砂找矿靶区圈定是可行的;本文总结出的基于相关性分析的油砂提取模式优于光谱特征分析模式;冷湖地区用比值方法进行油砂遥感信息增强效果较好,马海地区则差值方法较好。