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南京师范大学地理科学学院地图与遥感研究所所长倪绍祥教授在国家自然科学基金的支持下 ,率领他的研究集体对环青海湖地区草地蝗虫的发生与生态因素和环境条件的关系及其遥感监测与预测进行了系统研究。在多年的实地考察与研究中 ,借助于陆地卫星遥感图象与地理信息系统 ,划分了草地蝗虫的生境类型、评估了潜在的发生与成灾的可能性并初步建立了预测预报模型 ,提出了草地蝗虫样区研究方案和蝗虫密度与植被生境的定量指标。在总结研究成果的基础上 ,撰写了《环青海湖地区草地蝗虫遥感监测与预测》专著。全书分上、下篇 ,上篇 :环青海湖地区草… 相似文献
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蝗虫生境评价信息系统的设计与实现 总被引:1,自引:0,他引:1
主要论述了蝗虫生境评价信息系统的设计目标、数据流程及结构设计、数据库设计、模型库设计及功能设计,并简要说明了所建系统的实现。研究表明,基于GIS技术所建立的蝗虫生境评价信息系统,可对影响蝗虫发生的生境因子进行综合分析以及针对蝗虫潜在发生可能性对蝗虫生境进行定量评价,从而为蝗虫发生和成灾的监测和防治提供强有力的技术手段。蝗虫生境评价信息系统除了应具备信息系统的基本功能和一般统计分析功能外,还应重点加强其生境评价功能,如评价因子选择和权重管理,评价指标量化,评价等级划分,评价指标的加权求和,以及总分值的划分。 相似文献
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环青海湖地区草地生境的蝗虫潜在发生可能性评价 总被引:4,自引:2,他引:2
环青海湖地区是青海省草地蝗虫最集中的区域,主要有10种,它们对草地造成了很大危害,草地蝗虫的发生与由植被、地形、土壤等组成的生境类型存在密切的关系。论述了草地蝗虫生境类型划分的原因,并提出了生境分类方案,在此基础上,提出了各类生境针对草地蝗虫潜在发生可能性的评价原理,方法和评价指标体系,并据其对野外实地调查样点进行了评价,结果表明,草地蝗虫潜在发生可能性指数与草地蝗虫密度间的相关系数高达0.90,研究区受草地蝗虫严重危害或较严重危害的生境类型是芨芨草草原,克氏针茅草原及紫花针草原,高寒草甸属一般危害,高寒灌丛草甸则不发生危害。 相似文献
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以内蒙古草地蝗虫产卵期、越冬期和孵化期的关键气象影响因子作为草地蝗虫气象适宜度指数构建的主要因子,对内蒙古镶黄旗2010年草地蝗虫潜在发生的气象适宜性进行评价;根据当年7月上中旬在镶黄旗的实地调查资料,选取海拔、坡向、土壤类型、土壤含砂量、植被类型、植被盖度、土地覆被类型7个相对稳定的生境因子,用模糊评判方法和3S(GIS、RS、GPS)技术对该旗草地蝗虫潜在发生的生境适宜性进行评价;最后通过构建气象-生境适宜性综合评价模型,得到该旗2010年草地蝗虫潜在发生可能性(POG)等级,并用2010年实测数据和2001-2010年历史数据对模型模拟的蝗虫发生位置和蝗灾发生面积进行验证.结果表明:用本文所建气象-生境适宜性综合评价模型对镶黄旗POG等级的评价结果是可靠的.该旗草地蝗虫潜在发生的气象适宜性等级非常一致,绝大多数为适宜等级;蝗虫潜在发生源地的空间异质性主要与生境因子有关,在海拔1300~1400 m的平地/东坡/南坡、植被盖度30%~50%的温带丛生禾草草原、土壤含砂量60%~80%的典型栗钙土的生境条件下,草地蝗虫潜在发生的可能性最高. 相似文献
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内蒙古镶黄旗草地蝗虫潜在发生可能性评价 总被引:1,自引:0,他引:1
以内蒙古草地蝗虫产卵期、越冬期和孵化期的关键气象影响因子作为草地蝗虫气象适宜度指数构建的主要因子,对内蒙古镶黄旗2010年草地蝗虫潜在发生的气象适宜性进行评价;根据当年7月上中旬在镶黄旗的实地调查资料,选取海拔、坡向、土壤类型、土壤含砂量、植被类型、植被盖度、土地覆被类型7个相对稳定的生境因子,用模糊评判方法和3S(GIS、RS、GPS)技术对该旗草地蝗虫潜在发生的生境适宜性进行评价;最后通过构建气象-生境适宜性综合评价模型,得到该旗2010年草地蝗虫潜在发生可能性(POG)等级,并用2010年实测数据和2001-2010年历史数据对模型模拟的蝗虫发生位置和蝗灾发生面积进行验证.结果表明:用本文所建气象-生境适宜性综合评价模型对镶黄旗POG等级的评价结果是可靠的.该旗草地蝗虫潜在发生的气象适宜性等级非常一致,绝大多数为适宜等级;蝗虫潜在发生源地的空间异质性主要与生境因子有关,在海拔1300~1400 m的平地/东坡/南坡、植被盖度30% ~ 50%的温带丛生禾草草原、土壤含砂量60%~80%的典型栗钙土的生境条件下,草地蝗虫潜在发生的可能性最高. 相似文献
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内蒙古锡林河流域不同生境中蝗虫种类组成的分析 总被引:8,自引:0,他引:8
本文对内蒙古锡林河流域不同生境中蝗虫种类发生的情况进行了分析。经过系统取样和大面积扫网调查,共采集到蝗虫21种,这些种类在各生境中出现的情况,与生境的复杂程度存在很大的关系。在复杂的生境中,蝗虫种类最丰富。根据锡林河流域不同生境中蝗虫种类发生的情况,经过比较分析,我们认为在该区域存在的沙带生境是典型草原的“蝗虫库”。“蝗虫库”的存在,对牧业生产构成一定的潜在威胁。经存在度分析表明,一些常见的种类,生态分布幅度宽,同时,它们又是当地的优势种害虫,为害大,是重点防治对象。 相似文献
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应用种-多度分布模型、多样性指数、相似性分析、主成分(PCA)分析及多元逐步回归等方法比较了洛河流域不同生境的蝗虫群落结构。结果显示:洛河流域各生境的蝗虫分布基本上服从Preston对数正态分布,其中以森林拟合的最好。各多样性指数的变化趋势均为森林>森林草原>河滩和农田>典型草原。在相似性分析中,典型草原、森林草原和森林这3种生境相似性很高,而河滩和农田则是完全不同的另一种生境。对各生境植被因素和蝗虫群落所进行的主成分分析,结果非常理想,两维主成分的累计方差贡献率分别达到了92.558%和78.566%。通过多元逐步回归发现,影响蝗虫种类和数量变化的植被因有草本植物高度多样性、树木盖度、豆科优势度、禾本科优势度和其他科优势度等。 相似文献
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为了寻求有害蝗虫的防治对策,深入研究蝗虫生物多样性,用多样性指数、相似性分析等方法比较分析了延安北洛河流域不同生境中蝗虫群落组成。结果表明:草地中占有的属种数量均最高,灌草丛和农田中蝗虫的科属种都相对较低。不同生境蝗虫多样性指数的排列顺序为草地>河滩>灌草丛>农田,草地的多样性指数最高,农田的多样性指数最低。丰富度指数的变化趋势与多样性指数一致,而优势度指数却恰好与二者的顺序相反。在相似性分析中,草地和河滩相似性系数最大,说明草地和河滩这两种生境蝗虫种类组成的相似性较大,具有更多的共同种,从而可以推知草地和河滩的生境条件有一定的相似性,而农田和草地是两种完全不同的生境。 相似文献
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延安北部丘陵沟壑区退耕还林(草)成效的遥感监测 总被引:2,自引:0,他引:2
将延安北部丘陵沟壑区的吴起、志丹、安塞、子长、延川、延长和宝塔等7县区做为一个整体,利用GIS综合解译分析SPOTVGT、NOAA/AVHRR、EOS/MODIS、TM和DEM数据,揭示该区域退耕还林(草)生态建设工程所取得的实效。1998-2009年NOAA/AVHRR和EOS/MODIS遥感监测表明,该区域在遥感影像图上凸现,在其北部和西部形成一条明显的与行政区边界相吻合的分界线,表明退耕还林后植被覆盖状况正在逐年改善,而且植被恢复情况明显好于其北部和西部。1999-2007年SPOTVGTNDVI演变表明,该区域NDVI正处于快速上升阶段,线性趋势值为0.0078,与其南部次生林区的NDVI差值在明显减小,与北部粮食种植区的NDVI差值在逐渐加大。退耕前后的TM影像解译结果对比分析说明,延安北部近年来退耕还林(草)的成绩是显著的,生态环境有了明显的改善。与1997年相比,到2007年延安北部有68.37%耕地不再耕种,而大于35°的坡耕地91.45%实现了退耕,25-35°的坡耕地有74.70%退耕,绝大部分高坡度耕地实现了退耕,而较低坡度的坡耕地退耕幅度也很大,达到了50%-70%。退出的耕地主要变为草地、林地和果园。TM影像解译结果表明,林草覆盖度增加非常显著,达到65.3%,增加24.3%,以草的面积增加最为明显。低植被覆盖度的土地面积在大幅度减少,植被覆盖度小于10%的面积减少了83.42%;中植被覆盖度面积在显著增加,到2007年,植被覆盖度在30%-50%的面积最大,占总面积的47.2%,将近一半;高植被覆盖度面积也明显增加,由1997年的6%增加到2007年22%。TM影像与DEM数据叠加分析表明,土壤侵蚀强度总体上降低,强度、极强度和剧烈等级土壤侵蚀的土地面积减少50%以上,但极强度和剧烈的高等级土壤侵蚀面积仍占2007年国土总面积的13.3%,土壤侵蚀状况仍然严重。植被以灌木和草为主,乔木面积较低,森林覆盖率只有22.4%,因此需要继续加强治理。 相似文献
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Remote sensing of sea surface and coastal features in the area of the Golfe d'Arguin,Mauritania 总被引:2,自引:2,他引:0
F. Cuq 《Hydrobiologia》1993,258(1-3):33-40
The analysis of a series of NOAA AVHRR satellite data recorded between July and September 1986 shows the interaction between northerly and southerly water masses during summer as well as the northern limit of the northward advance of water masses originating from the South Equatorial Current. Two upwelling situations analysed by means of NOAA data show the intrusion of suspended matter from the ocean into the Golfe d'Arguin and illustrate the water circulation within the coastal zone. This circulation pattern is detailed by LANDSAT and SPOT data. A SPOT picture from October 1987 shows the structure of the intertidal and coastal geomorphology. 相似文献
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植物叶绿素含量的遥感模型及用陆地卫星数据所作的二维分布图 总被引:6,自引:0,他引:6
为了确定全球和区域尺度的植物叶绿素含量的多少和分布,遥感方法是一种很好的途径。有些遥感科学家直接利用归一化植被指数(NDVI)等植被指数推算叶绿素含量。实践表明,这种做法的缺点有:1.植被指数NDVI中的近红外波段反射率与叶绿素含量基本无关,这样NDVI中的主信息并没有表达叶绿素含量,其信噪比显著降低;2.存在明显的信息不确定性,同一个植被指数NDVI可能有两种状态:较高叶面积指数伴有较低叶绿素含量或者是较低叶面积指数伴有较高叶绿素含量。通过实践,作者推导出可用LANDSAT和NOAA影像图灰度值推算植被叶绿素含量遥感模型。并在中国科学院禹城遥感实验场实际应用中得到验证:用其模型推算植被叶绿素含量的精度比NDVI有较明显提高,不确定性有明显的降低。 相似文献
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利用遥感光谱法进行农田土壤水分遥感动态监测 总被引:14,自引:1,他引:14
自 1 997年 4月至 1 998年 1 0月 ,在甘肃省定西县进行了大面积 0~ 5 0 cm土层农田土壤水分按每 1 5 d本底资料实际观测 ,对此间收到的 5幅 TM与 7幅 NOAA卫片数据资料进行了加工处理 ,并对地面光谱资料也进行了观测。在光谱反演与光谱和土壤水分相关性分析基础上 ,利用遥感技术和地理信息系统 ,初步建立了典型试验区 ( 3× 3km2 )遥感信息与土壤含水量之间的遥感光谱相关监测模型 ,做出了观测区土壤水分含量分布图和得到了大面积农田土壤水分宏观动态监测结果 ,并同地面实测土壤水分进行了精度校正。研究结果表明 ,文中提出的“光学植被盖度”概念 ,对土壤水分遥感监测研究是有益的 ,利用遥感光谱法和数学统计方法求出了有关物理参数 ,初步建立了 TM与 NOAA光谱水分监测模型 ,其模型监测 0~2 0 cm土层含水量的精度达到 90 %以上 ,实际监测土壤水分精度达到 72 .3% ;在遥感监测 2 0~ 5 0 cm土层土壤含水量中 ,利用遥感模型监测土壤水分精度达到 80 %以上 ,实际遥感监测精度达到 60 %左右 ,其结果可有效指导干旱半干旱雨养农业区春耕时间和动态监测大面积土壤墒情 ,可为农业生产提供科学依据。另外 ,经地面大量观测表明 ,一般来说 ,当土壤含水量为田间最大持水量的 5 5 %~ 85 %时 ,从生长状况和经济 相似文献
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应用NOAA/AVHRR资料监测松毛虫危害研究初探 总被引:1,自引:0,他引:1
探讨了利用气象卫星定量监测松毛虫危害程度的可能性.以针叶被害率代表松毛虫的危害程度,轻度、中度、重度危害分别定义为针叶被害率<30%、30%~60%和>60%.根据地面光谱观测资料,建立了归一化植被指数与针叶被害率的相关方程,无松毛虫危害时NDVI为0.8823;为了消除大气等因子影响,利用松毛虫危害与未被危害的植被指数相对值表示松毛虫轻、中、重危害程度的遥感监测指标,无危害为1,0.78~1为轻度危害,0.57~0.78为中度危害,<0.57为重度危害.监测危害面积时,利用线性可加垂直植被指数进行混合象元分解.并分别对严重、中度、轻度3种类型发生年进行了定量监测分析,结果表明,AVHRR资料对中等以上松毛虫危害可进行定量监测分析,监测受灾面积比用同期的陆地卫星TM资料监测的受灾面积小12.1%~14.3%;对于轻度危害区域,采用气象卫星不易分辨,主要是由于不同下垫面和大气影响的差异,以及气象卫星空间分辨率较低. 相似文献
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Satellite remote sensing of wetlands 总被引:20,自引:0,他引:20
To conserve and manage wetland resources, it is important to inventoryand monitor wetlands and their adjacent uplands. Satellite remote sensing hasseveral advantages for monitoring wetland resources, especially for largegeographic areas. This review summarizes the literature on satellite remotesensing of wetlands, including what classification techniques were mostsuccessful in identifying wetlands and separating them from other land covertypes. All types of wetlands have been studied with satellite remote sensing.Landsat MSS, Landsat TM, and SPOT are the major satellite systems that have beenused to study wetlands; other systems are NOAA AVHRR, IRS-1B LISS-II and radarsystems, including JERS-1, ERS-1 and RADARSAT. Early work with satellite imageryused visual interpretation for classification. The most commonly used computerclassification method to map wetlands is unsupervised classification orclustering. Maximum likelihood is the most common supervised classificationmethod. Wetland classification is difficult because of spectral confusion withother landcover classes and among different types of wetlands. However,multi-temporal data usually improves the classification of wetlands, as doesancillary data such as soil data, elevation or topography data. Classifiedsatellite imagery and maps derived from aerial photography have been comparedwith the conclusion that they offer different but complimentary information.Change detection studies have taken advantage of the repeat coverage andarchival data available with satellite remote sensing. Detailed wetland maps canbe updated using satellite imagery. Given the spatial resolution of satelliteremote sensing systems, fuzzy classification, subpixel classification, spectralmixture analysis, and mixtures estimation may provide more detailed informationon wetlands. A layered, hybrid or rule-based approach may give better resultsthan more traditional methods. The combination of radar and optical data providethe most promise for improving wetland classification. 相似文献
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Landscape structure and locust swarming: a satellite's eye view 总被引:1,自引:0,他引:1
Desert locust Schistocerca gregaria outbreaks consistently start in the same places, suggesting that certain landscapes are particularly favourable for outbreaking. Outbreaks are generated by multiplication, concentration and gregarisation of locust populations. Previous research has shown how small-scale vegetation patterns in desert ecosystems influence locust gregarisation; the present study examines the effects of large-scale landscape structure on locust multiplication and concentration. NOAA/AVHRR satellite imagery was used to relate abundance and spatial distribution of resources at the landscape scale to the historical record of locust outbreaks. Threshold NDVI values were investigated to define what constitutes 'resource' for locusts. The first part of the study showed that abundance and spatial distribution of resource were not sufficient to distinguish between outbreak and non-outbreak areas in the western part of the locust distribution area. Thus, outbreak danger zones cannot be identified by landscape structure at this spatial resolution. The second analysis investigated spatio-temporal patterns of vegetation growth in two locust breeding areas with very different landscape structure; in both cases, the patterns differed significantly between outbreaking and non-outbreaking years. In Mauritania, a flat homogeneous desert landscape, both resource abundance and fragmentation were higher in outbreaking years. On the Red Sea coast, a fragmented landscape, resource spatial distribution was consistent between years, and abundance alone was a significant predictor of outbreaking. High resource abundance promotes locust multiplication, and contraction of resource into small patches increases locust concentration; these two mechanisms explain how landscape structure influences locust outbreaking. 相似文献
18.
Jos M. Paruelo Martín Oesterheld Carlos M. Di Bella Martín Arzadum Juan Lafontaine Miguel Cahuep Csar M. Rebella 《应用植被学》2000,3(2):189-195
Abstract. Above‐ground Net Primary Production (ANPP) is the main determinant of forage availability and hence of stocking density. A tool to track the seasonal and interannual changes in ANPP at the paddock level will be very important for livestock management. We studied the relationship between field ANPP data and the Normalized Difference Vegetation Index (NDVI) for rangelands of the Flooding Pampa of Argentina using spectral data provided by sensors on board of two satellites: NOAA/AVHRR and Landsat TM. The relationship between NDVI and ANPP was linear both for data derived from NOAA/AVHRR and Landsat TM. Changes in ANPP accounted for a large proportion of the temporal and spatial variation of NDVI: 71% of NOAA/AVHRR data and 74% of Landsat TM data. By inverting these models, ANPP may be inferred from NDVI data at a seasonal and paddock scale. NOAA/AVHRR data captured better the seasonal variation in ANPP and were less sensitive to local variations than Landsat TM data. In contrast, Landsat TM data were more sensitive to inter‐site differences in primary production, except for the winter months. Thus, combining information from these two sources offers a good alternative for monitoring rangeland production at high temporal and spatial resolution. 相似文献
19.
W. Müller 《International journal of biometeorology》1976,20(3):249-255
Images of satellite ERTS (LANDSAT)-1 taken during 1972/73 have been used for ecoclimatological mapping of optimum breeding habitats of the African migratory losusts (Locusta migratoria migratorioides R. & F.) in the middle Niger area. The seasonal shifting of the optimum area for locust (hopper) development both in space and time has been characterized by thermal (mean air temperatures of the months between 25 and about 33°C) and hydric (soil moisture for plants available, but below field capacity) criteria. Examples of the interpretation of favorable (very humid), tolerable (humid) and intolerable, (either flooded or very dry soil or soil without vegetation cover) conditions for development are given. The possibilities are discussed to forecast the chances of hopper development.Presented at the Seventh International Biometeorological Congress, 17–23 August 1975, College Park, Maryland, USA. 相似文献
20.
Climate and satellite-derived land cover for predicting breeding bird distribution in the Great Lakes Basin 总被引:5,自引:0,他引:5
L. A. Venier J. Pearce J. E. McKee D. W. McKenney G. J. Niemi 《Journal of Biogeography》2004,31(2):315-331
Aim We examined relationships between breeding bird distribution of 10 forest songbirds in the Great Lakes Basin, large‐scale climate and the distribution of land cover types as estimated by advanced very high resolution radiometer (AVHRR) and multi‐spectral scanner (MSS) land cover classifications. Our objective was to examine the ability of regional climate, AVHRR (1 km resolution) land cover and MSS (200 m resolution) land cover to predict the distribution of breeding forest birds at the scale of the Great Lakes Basin and at the resolution of Breeding Bird Atlas data (5–10 km2). Specifically we addressed the following questions. (1) How well do AVHRR or MSS classifications capture the variation in distribution of bird species? (2) Is one land cover classification more useful than the other for predicting distribution? (3) How do models based on climate compare with models based on land cover? (4) Can the combination of both climate and land cover improve the predictive ability of these models. Location Modelling was conducted over the area of the Great Lakes Basin including parts of Ontario, Canada and parts of Illinois, Indiana, Michigan, New York, Ohio, Pennsylvania Wisconsin, and Minnesota, USA. Methods We conducted single variable logistic regression with the forest classes of AVHRR and MSS land cover using evidence of breeding as the response variable. We conducted multiple logistic regression with stepwise selection to select models from five sets of explanatory variables (AVHRR, MSS, climate, AVHRR + climate, MSS + climate). Results Generally, species were related to both AVHRR and MSS land cover types in the direction expected based on the known local habitat use of the species. Neither land cover classification appeared to produce consistently more intuitive results. Good models were generated using each of the explanatory data sets examined here. And at least one but usually all five variable sets produced acceptable or excellent models for each species. Main conclusions Both climate and large scale land cover were effective predictors of the distribution of the 10 forest bird species examined here. Models generated from these data had good classification accuracy of independent validation data. Good models were produced from all explanatory data sets or combinations suggesting that the distribution of climate, AVHRR land cover, and MSS land cover all captured similar variance in the distribution of the birds. It is difficult to separate the effects of climate and vegetation on the species’ distributions at this scale. 相似文献