基于长时间序列Landsat影像的嘎龙错冰湖变化特征分析及溃决风险评估

冰湖溃决灾害是我国青藏高原地区最严重的自然灾害之一。作为聂拉木县最大的冰川终碛湖,嘎龙错冰湖溃决风险直接威胁着下游居民的生产生活。利用1991—2011年Landsat-5/TM、2012年Landsat-7/ETM+、2013—2017年Landsat-8/OLI近27年的遥感影像、降水量和气温资料对嘎龙错冰湖变化特征进行了研究,对其溃决风险作出评估。结果表明:嘎龙错冰湖明显扩张,面积呈现显著增长趋势,由1991年的2.209 4 km^2增长到2017年的5.465 7 km^2,增幅为147.38%;同时,发现聂拉木气象站年平均气温和年降水量在波动中上升,其中气温上升较为显著,气温和降水量的增加对冰湖扩张有重要影响,特别是气温上升导致的冰川融水增多是造成冰湖面积增加的重要原因。嘎龙错冰湖在遇到冰崩或者冰湖面积持续扩张情况下,湖水会瞬间大规模外泄,形成山洪、泥石流灾害,给下游造成严重的人员伤亡和财产损失。     

二维大地电磁资料频域逆散射反演

逆散射反演是由已知散射波场反演地下介质中散射体各参数了分布的方法，本文从这一思想出发，针对二维大地电磁资料，在BORN近似的前提下，提出了一种新的反地下电导率参数的方法，经模型试算与实际资料的反演验证正确，这一方法特别适于地下无强电性分界面的地区。     

Determination of regional land surface heat fluxes over a heterogeneous landscape of the Jiddah area of Saudi Arabia by using Landsat‐7 ETM data

In this study, a parameterization method based on Landsat‐7 Enhanced Thematic Mapper (ETM) data and field observations is presented and tested for deriving the regional land surface variables, vegetation variables and land surface heat fluxes over a heterogeneous landscape. As a case study, the method and two Landsat‐7 ETM images are applied to the Jiddah area of Saudi Arabia. The regional distribution maps of surface reflectance, normalized difference vegetation index, modified soil adjusted vegetation index (MSAVI), vegetation coverage, leaf area index, surface temperature, net radiation flux, soil heat flux, sensible heat flux and latent heat flux have been determined over the Jiddah area. The derived results have been validated by using the ‘ground truth’. The results show that the more reasonable regional distributions of land surface variables (surface reflectance, surface temperature), vegetation variables (MSAVI and vegetation coverage), net radiation, soil heat flux and sensible heat flux can be obtained by using the method proposed in this study. Further improvement of the method is also discussed. Copyright © 2006 John Wiley & Sons, Ltd.     

Mapping rubber trees based on phenological analysis of Landsat time series data-sets

This study proposes a strategy for accurate mapping of rubber trees through the analysis of Landsat time series datasets. The phenological dynamics of rubber trees were derived from the Normalized Difference Vegetation Index (NDVI) to verify the three important phenological metrics of rubber trees; defoliation, foliation and their growing stages. A decade (2006–2015) ago, Landsat time series NDVIs were used to study the strength of relationship between rubber trees, evergreen trees and oil palm trees. Two important results that could discriminate these three types of vegetation were found; firstly, a weak relationship of NDVIs between rubber trees and evergreen trees during the defoliation period (r² = 0.1358) and secondly between rubber trees and oil palm trees during the growing period (r² = 0.2029). This analysis was verified using Support Vector Machine to map the distribution of the three types of vegetation. An accurate mapping strategy of rubber trees was successfully formulated.     

新疆北山地区侵入岩遥感识别方法

基于ASTER数据、Landsat 8数据及WorldView-2数据,采用波段组合法、最小噪声分离法、主成分分析法以及波段比值法,结合岩石光谱曲线,综合提取了新疆北山地区侵入岩的岩性特征。对WorldView-2进行主成分分析和最小噪声分离,并将R(PCA2)G(PCA1)B(PCA4)、R(MNF2)G(MNF1)B(PCA1)、OLI数据R(B7)G(B6)B(B5)进行假彩色合成,利用OLI数据中的B5/B2、B2/B1突出花岗岩。这些方法解决了复杂岩性的影像色调差异较小、细节不清晰等问题,降低了岩性划分及解译的难度,使各种岩性界线更加明晰。结合前人的区域地质调查成果,对研究区侵入岩岩性进行了系统解译及分析。多源遥感数据的综合利用,有助于更有效地识别复杂岩性并进行更详细的岩性分类,提高遥感岩性识别的正确率。     

Detecting and mapping annual newly-burned plots (NBP) of swiddening using historical Landsat data in Montane Mainland Southeast Asia (MMSEA) during 1988–2016

Swidden agriculture is by far the dominant land use system in the uplands of Southeast Asia (SEA), as well as other tropical regions, which plays an important role in the implementation of Reducing Emissions from Deforestation and Forest Degradation (REDD) of United Nations. To our knowledge, the long-term inter-annual area of newly burned plots (NBP) of swidden agriculture in mainland Southeast Asia is still not available, let alone in the whole tropics. With the strengthening regional geo-economic cooperation in SEA, swidden agriculture has experienced and/or is still experiencing extensive and drastic transformations into other diverse market-oriented land use types since the 1990s. In this study, high-level surface reflectance products of Landsat 4/5/7/8 family sensors including Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) acquired in March, April and May of each year between 1988 and 2016 were firstly utilized to detect and monitor the extent and area of NBP of swidden agriculture with multiple thresholds of four commonly-used vegetation indices, namely the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Burn Ratio (NBR) and Soil Adjusted Vegetation Index (SAVI), in combination with local phenological features of swiddening and topographical data. The results showed that: (1) an annual average of 6.08×10⁴ km² of NBP of swidden agriculture, or 3.15% of the total land area of MSEA, were estimated in the past nearly three decades. (2) Annual NBP were primarily distributed in four major geomorphic units including the Central Range of Hills, Northern Mountainous Region, Western Myanmar Hills, and Annamite Chain. (3) A decadal average analysis indicated that the NBP of swidden agriculture opened year by year declined as a whole, especially after 2010, merely with an average of 5.23×10⁴ km². (4) The top ten provincial administrative units in Cambodia, Laos, Myanmar, Thailand and Vietnam, which consistently accounted for over 90% of the newly opened swiddens of each country, showed distinct fluctuations in using slash-and-burn practices in the last decades. The Landsat-based (30 m) reconstructed 29-year longitudinal updated maps (including extent and area) of the NBP of swidden agriculture may contribute to REDD and local livelihood related studies in Continental Southeast Asia. Our study further demonstrated that the multiple vegetative indices thresholds approach holds great potential in detecting swidden agriculture in tropical mountainous regions.     

遥感影像用于城市扩展监测的研究

通过焦作市城市扩展监测的实践,对以多时相遥感影像监测城市扩展进行了研究,阐述了以地形图及TM遥感影像为数据源,利用RS和GIS软件进行图像处理,提取城区扩展的变化信息,并对其扩张变化的主要方向、速度及规律进行监测和分析;论述了交通建设、政策法规、经济投资区的建设和当地的自然地理环境对城市的扩展速度和方向的影响。     

微机TM图象的主成分变换与彩色变换及其信息提取实验

遥感图像处理向微机化发展是遥感技术引人注目的发展趋势之一，本文采用ＬＡＮＤＳＡＴ－５ＴＭ数字图象借助适用于微机的软件系统，驿ＴＭ图象分别进行了主成分变换和彩色空间变换了这两种变换的意义及其相互结合的优势。这项试验研究在遥感图象微机应用处理、区域资源和环境调查，监测以及研究中有一定的实际意义。     

Inventory of Glaciers in Mongolia,Derived from Landsat Imagery from 1989 to 2011

Glaciers in the Altai Mountains of Mongolia provide an estimated 11% of the total water resources within the country. Yet, their number and area in inconsistent. Using satellite imagery acquired from Landsat 4, 5, and 7, and SRTM digital elevation model (DEM) data, we present here an intuitive, robust, and inexpensive methodology to map the exposed ice of glaciers in the Altai Mountains for the period 1989 to 2011. The total glacierized area was 515 km² in 1989/1991, 428 km² in 1998/2001, and 372 km² in 2010/2011; it decreased by 17% from 1989/1991 to 1998/2001, 13% from 1998/2001 to 2010/2011, and 28% for the entire period 1989/1991 to 2010/2011. In analyzing a sub‐sample of 260 glaciers, 6% advanced, 11% were stable, and 83% receded from 1989 to 2011. The glacier dataset is available to the public free of charge at the Global Land Ice Measurements from Space (GLIMS) website.     

Optical and radar remote sensing data for forest cover mapping in Peninsular Malaysia

This study aims to map forest cover in Peninsular Malaysia using satellite images as deforestation is of concern in the recent decades, and is an important environmental issue for the future too. The Carnegie Landsat Analysis System‐Lite (CLASlite) program was used in this study to detect forest cover in Peninsular Malaysia using Landsat satellite data. The results of the study show that CLASlite algorithm misclassified some oil palm, rubber and urban areas as forest vegetation. A reliable forest cover map was produced by first combining Landsat and ALOS PALSAR images to identify oil palm, rubber and urban areas, and then subsequently removing them. The HH and HV polarization data of ALOS PALSAR (threshold method) could detect oil palm plantations with 85.26 per cent of overall accuracy. For urban area detection, Enhance Build up Index (EBBI) using spectral bands from Landsat provided higher overall accuracy of 94 per cent. These methods produced a forest cover reading of 5 914 421 ha with an overall classification accuracy of 94.5 per cent. The forest cover (including rubber areas) detected in this study is 0.38 per cent higher than the percentage of 2010 forest cover detected by the Forestry Department of Peninsular Malaysia. The technique described in this paper presents an alternative and viable approach for updating forest cover maps in Malaysia.