用环境小卫星遥感数据分析攀枝花市苏保区植被覆盖变化情况

利用环境小卫星遥感数据,可以计算特定区域的归一化植被指数,进而定量分析其植被覆盖情况。以"四川攀枝花苏铁国家级自然保护区"为研究对象,选取下载了相应区域2009年和2015年的环境小卫星遥感数据,经过辐射定标、图像校准等预处理后,计算得到归一化植被指数和植被覆盖度,通过对植被覆盖度数据进行统计和分析比较,结果表明该自然保护区及周边区域2015年植被覆盖度比2009年有明显增加。     

基于RS和GIS技术的重庆市主城区扩展分析

采用重庆市主城区2000年和2010年两个时相的TM影像提取城市扩展信息,对影像数据的归一化建筑指数（NDBI）、归一化植被指数（NDVI）和归一化水体指数（NDWI）进行RGB组合增强,再进行决策树分类和减法运算获取研究区扩展信息,发现建筑区面积增加了1.62倍,大部分是由植被区转变而来。其扩张方向受地理影响,南北方向为外延型,东西方向为飞地型。借助统计资料进行精度验证和城市扩展的驱动因素分析发现,区域发展政策、经济增长和人口扩张是主要的影响因素,探讨了对经济增长、城市扩张和人口增长的关系。研究结果表明,以遥感手段监测与研究城市发展变化的趋势是可行和高效的。     

利用遥感影像软件ENVI提取植被指数

在遥感影像处理中，植被指数提取广泛应用于定性和定量评价植被覆盖及其生长活力。主要介绍了在ENVI遥感图像处理软件对遥感影像进行植被指数。对植被指数提取的关键部分进行分析，并给出植被指数提取的技术关键。     

基于MODIS的济南市气溶胶反演及影响机制研究

选取2015年3月6日济南市MODIS卫星遥感影像数据,以ENVI5.3为平台,利用改进的暗像元算法,进行气溶胶光学厚度(AOD)反演,并分析其空间分布特征和影响机制,得到以下结论:济南市平均AOD为0.454,南部山区处于低浓度梯度,西部地区处于高浓度梯度,东部地区介于二者之间;济南市AOD与其地势(DEM)、归一化植被指数(NDVI)呈负相关,与人类活动呈正相关。依据分析结果,提出了分区分层治理、建立生态廊道、转移污染企业、提高植被覆盖的治理策略。     

基于ETM影像多种特征的CART决策树分类——以延边州为例

分类回归树(CART)是一种非参数化的分类与回归方法,在用于遥感影像自动分类时,可方便地应用多源知识,提高分类精度.以延边州试验区土地利用/覆被分类为例,利用分类回归树分析从训练样本中集中发现分类规则,集成遥感影像的光谱特征、纹理特征和辅助地学特征进行分类试验,并与传统的最大似然分类方法进行比较.结果表明,基于CART的决策树分类结果的总精度和Kappa系数分别为90.37%和0.8863,分类精度比MLC监督分类方法有明显提高.     

利用数码相片对冬小麦生物量的试算

数码相片属于地面遥感资料的一种,被广泛应用于实地调查中.然而,目前利用数码相片对植被生物量进行推算的研究很少.利用数码相片提取小麦生长期的小麦覆盖度,结合地面实测叶面积指数(LAI)、归一化植被指数(NDVI)和小麦生物量,分析小麦覆盖度与LAI,NDVI,生物量与小麦覆盖度、LAI,NDVI各自的相关系数,建立各自合适的回归模型推算冬小麦的生物量.结果表明,在小麦生长期,小麦覆盖度与LAI,NDVI的相关系数R2分别达到0.765,0.896,生物量与小麦覆盖度、LAI,NDVI的相关系数R2分别为0.774,0.876,0.712,生物量与其小麦覆盖度、LAI,NDVI之间具有很高的相关性,多元回归分析效果更好,系数R2达0.891.结果说明,在不破坏植被生长状态的情况下,基于数码相片可有效地推算小麦的生物量,这为大面积实地测量和遥感监测作物长势及其生物量估算提供了理论参考依据.     

基于遥感技术的土地利用/土地覆盖现状信息提取研究——以艾比湖湿地保护区为例

艾比湖地区是中国沙尘暴的起源地之一,而且对该区域的生态环境变化具有指征作用。利用中巴资源卫星影像,结合Modis数据,采用遥感数据分类与实地验证相结合的方法。利用植被指数模型,建立解译标志,采用无监和有监相结合的分类方法,提取了艾比湖湿地保护区LUCC的现状信息,为进一步研究提供了基础性数据。     

基于决策树技术的城市建设用地信息提取方法研究

以2006年中巴多波段遥感影像为数据源,采用决策树分类技术对济南市城市建设用地信息进行提取.在建立研究区先验知识的基础上,对城市建设用地及不同类型背景地物的光谱响应特征进行了统计,建立了基于地物光谱特征的决策树分类模型与分类知识库,然后进行图像分类,最后经过精度评价,发现该方法能有效地将城市建设用地信息提取出来并具有较高的分类精度与效率.     

彩色合成法在新疆地表植被覆盖变化中的应用--以多时相NOAA-AVHRR影像为例

以NOAA—AVHRR遥感数据为基础，使用彩色合成法对新疆地表植被变化进行分析。结果证明，利用不同时相的NDVI影像进行彩色合成可以直观地反映地表植被的变化趋势，通过遥感软件对彩色图像处理，还可以对地表植被变化进行定量分析。     

1998~2008年川西北若尔盖高原NDVI变化趋势分析

本文利用Mann-Kendall非参数检验方法对川西北若尔盖高原1998~2008年10年逐旬共372景的SPOT-VEGITATION归一化植被指数(NDVI)进行变化趋势检验。结果表明:川西北若尔盖高原1998~2008十年来的NDVI变化趋势以衰减为主导,其中衰减区域的面积比例为47.8%,而增长区域的面积比例仅为22.0%。若尔盖高原植被衰减区主要分布在海拔3500~4000米的高程带上,气候变化和人类活动是导致NDVI变化的主要因素。     

Emergence of Indigenous Vegetation Classifications Through Integration of Traditional Ecological Knowledge and Remote Sensing Analyses

Traditional ecological knowledge (TEK) can play an important role in the understanding of ecological systems. Although TEK has complemented scientific and managerial programs in a variety of contexts, its formal incorporation into remote sensing exercises has to date been limited. Here, we show that the vegetation classifications of the Ache, an indigenous hunter-gatherer tribe of the Mbaracayu Forest Reserve in Paraguay, are reflected in a supervised classification of satellite imagery of the reserve. Accuracy of classification was toward the low end of the range of published values, but was reasonable given the difficult nature of separating forest classes from satellite images. Comparison of the resultant map with a more traditionally elaborated vegetation map highlights differences between the two approaches and the gain in information obtained by considering TEK classifications. We suggest that integration of TEK and remote sensing may provide alternative insights into the ecology of vegetation communities and land cover, particularly in remote and densely forested areas where ecological field research is often limited by roads and/or trail systems.     

地震勘探引起植被棋盘式分布分析

通过高分辨率卫星遥感数据和实地调研,发现黄河三角洲的很多区域因胜利油田地震勘探而引起植被棋盘式分布。地震勘探引起植被群落斑块扩展,就其生态作用来说,与当前黄河三角洲生态恢复、保护和重建植被这一目标相吻合。此种植被群落的扩展,无须额外经费投入,对此进行深入研究,寻找使其从自发状态转变为通过人工协调可在适宜区域最大限度扩展的对策,将有助于更好地协调油田开发和湿地生态保护之间的矛盾。     

An introduction to digital methods in remote sensing of forested ecosystems: Focus on the Pacific Northwest,USA

Aerial photography has been routinely used for several decades by natural resource scientists and managers to map and monitor the condition of forested landscapes. Recently, along with the emergence of concepts in managing forests as ecosystems, has come a significant shift in emphasis from smaller to larger spatial scales and the widespread use of geographic information systems. These developments have precipitated an increasing need for vegetation information derived from other remote sensing imagery, especially digital data acquired from high-elevation aircraft and satellite platforms. This paper introduces fundamental concepts in digital remote sensing and describes numerous applications of the technology. The intent is to provide a balanced, nontechnical view, discussing the shortcomings, successes, and future potential for digital remote sensing of forested ecosystems.     

基于NDVI的大同煤田植被覆盖度动态变化研究

利用大同煤田地区1987年9月10日、2000年9月2日和2010年9月6日的TM遥感影像数据,采用基于NDVI的像元二分模型法反演了植被覆盖度,获取了该地区3个时期的植被覆盖度等级图,定量分析了该地区在大规模煤炭开采影响下的植被覆盖度的动态变化情况.研究结果表明1987年～2010年近24年以来,大同煤田地区植被覆盖度呈较明显的下降趋势,植被退化较严重.     

Identification and mapping of submerged plants in a shallow lake using Quickbird satellite data

Turkey is a country rich in lakes and wetlands--monitoring of all these will require advances in technology such as remote sensing. In this study, the aquatic plants of the large and shallow Lake Mogan, located in Central Anatolia were identified and mapped using high spatial resolution Quickbird imagery. As Lake Mogan is an important bird area the assessment of submerged plant species is of great value for ecosystem conservation and management. Quickbird multispectral image acquired on August 6, 2005 was geometrically corrected and a water mask was used based on strong absorption of Near Infrared (NIR) wavelengths by calm, clear and deep water. The water mask was applied using band reflectance values for a specific pixel satisfying the conditions of band decreasing property (Green>Red>NIR) and NIR相似文献   

SELECTING RECONNAISSANCE STRATEGIES FOR FLOODPLAIN SURVEYS1

ABSTRACT: Multispectral aircraft and satellite data over the West Branch of the Susquehanna River were analyzed to evaluate potential contributions of remote sensing to floodplain surveys. Multispectral digital classifications of land cover features indicative of floodplain areas were used by interpreters to locate various floodprone area boundaries. The boundaries thus obtained were found to be more striking and continuous in the Landsat data than in the low altitude aircraft data. The digital approach permitted satellite results to be displayed at 1:24,000 scale and aircraft results at even larger scales. Results indicate that remote sensing techniques can delineate floodprone areas more easily in agricultural and limited development areas than in areas covered by a heavy forest canopy. At this time it appears that the remote sensing data would be best used as a form of preliminary planning information or as an internal check on previous or ongoing floodplain studies. In addition, the remote sensing techniques can assist in effectively monitoring floodplain activities after a community enters into the National Flood Insurance Program.     

Cluster analysis of structural stage classes to map wildland fuels in a Madrean ecosystem

Geospatial information technology is changing the nature of fire mapping science and management. Geographic information systems (GIS) and global positioning system technology coupled with remotely sensed data provide powerful tools for mapping, assessing, and understanding the complex spatial phenomena of wildland fuels and fire hazard. The effectiveness of these technologies for fire management still depends on good baseline fuels data since techniques have yet to be developed to directly interrogate understory fuels with remotely sensed data. We couple field data collections with GIS, remote sensing, and hierarchical clustering to characterize and map the variability of wildland fuels within and across vegetation types. One hundred fifty six fuel plots were sampled in eight vegetation types ranging in elevation from 1150 to 2600 m surrounding a Madrean 'sky island' mountain range in the southwestern US. Fuel plots within individual vegetation types were divided into classes representing various stages of structural development with unique fuel load characteristics using a hierarchical clustering method. Two Landsat satellite images were then classified into vegetation/fuel classes using a hybrid unsupervised/supervised approach. A back-classification accuracy assessment, which uses the same pixels to test as used to train the classifier, produced an overall Kappa of 50% for the vegetation/fuels map. The map with fuel classes within vegetation type collapsed into single classes was verified with an independent dataset, yielding an overall Kappa of 80%.     

Decision-tree and rule-induction approach to integration of remotely sensed and GIS data in mapping vegetation in disturbed or hilly environments

The integration of Landsat TM and environmental GIS data sets using artificial intelligence rule-induction and decision-tree analysis is shown to facilitate the production of vegetation maps with both floristic and structural information. This technique is particularly suited to vegetation mapping in disturbed or hilly environments that are unsuited to either conventional remote sensing methods or GIS modeling using environmental data bases.     

REMOTE SENSING OF RIPARIAN BUFFERS: PAST PROGRESS AND FUTURE PROSPECTS1

Riparian buffer zone management is an area of increasing relevance as human modification of the landscape continues unabated. Land and water resource managers are continually challenged to maintain stream ecosystem integrity and water quality in the context of rapidly changing land use, which often offsets management gains. Approaches are needed not only to map vegetation cover in riparian zones, but also to monitor the changes taking place, target restoration activities, and assess the success of previous management actions. To date, these objectives have been difficult to meet using traditional techniques based on aerial photos and field visits, particularly over large areas. Recent advances in remote sensing have the potential to substantially aid buffer zone management. Very high resolution imagery is now available that allows detailed mapping and monitoring of buffer zone vegetation and provides a basis for consistent assessments using moderately high resolution remote sensing (e.g., Landsat). Laser‐based remote sensing is another advance that permits even more detailed information on buffer zone properties, such as refined topographic derivatives and multidimensional vegetation structure. These sources of image data and map information are reviewed in this paper, examples of their application to riparian buffer mapping and stream health assessment are provided, and future prospects for improved buffer monitoring are discussed.