S-NPP及VIIRS在林火监测中的应用

S-NPP是最新一代地球环境观测卫星,可见光红外成像辐射仪(VIIRS)是其携带的重要仪器之一。VIIRS比MODIS具有更高的空间分辨率和数据质量。VIIRS作为新一代对地观测设备在林火监测中比以往设备更具优势,将在全球林火监测中发挥重要作用。     

Forest Fire Burnt Area Assessment in the Biodiversity Rich Regions Using Geospatial Technology: Uttarakhand Forest Fire Event 2016

The hills of Uttarakhand witness forest fire every year during the summer season and the number of these fire events is reported to have increased due to increased anthropogenic disturbances as well as changes in climate. These fires cause significant damage to the natural resources which can be mapped and monitored using satellite images by virtue of its synoptic coverage of the landscape and near real time monitoring. This study presents burnt area assessment caused by the fire episode of April 2016 to the forest vegetation. Digital classification of satellite images was done to extract the burnt area which was found to be 3774.14 km², representing 15.28% of the total forest area of the state. It also gives an account of cumulative progression of forest fire in Uttarakhand using satellite images of three dates viz. 23rd, 27th May and 2nd June, 2016. Results were analyzed at district, administrative and forest division level using overlay analysis. Separate area statistics were given for different categories of biological richness, forest types and protected areas affected by forest fire. The burnt area assessment can be used in mitigation planning to prevent drastic ecological impacts of the forest fire on the landscape.     

Using GIS in Areawide Pest Management: A Case Study in South Dakota

Infestations of corn rootworms (Coleoptera: Chrysomelidae) create economic and environmental concerns in the Corn Belt region of the United States. To supplement the population control tactics of areawide pest management programs, we believe that a better understanding of the spatial relationships between biotic and abiotic or physical factors at the landscape scale is needed. Our research used several geographical information systems (GIS) and spatial analytical techniques to examine relationships between corn rootworm metapopulation dynamics, soil texture, and elevation. Within GIS, several spatially explicit procedures were used that include an interpolation technique, spatial autocorrelation analysis, and contingency analysis. Corn rootworm metapopulation distributions were found to be aggregated and related to soil texture and elevation. We review techniques and discuss our preferences for using particular spatially explicit procedures. The information derived from the spatial analyses demonstrates how GIS can be used in areawide pest management to provide inputs for spatially explicit models to predict future pest populations and formulate more well‐informed pest management decisions. The techniques described in this paper could easily be extended to study the spatial dynamics between other pest populations in agricultural landscapes.     

森林防火地理信息系统的设计与开发

将GIS技术应用于森林防火,实现了C/S与B/S相混合的森林防火信息监测模式。以湖北森林防火系统为例,给出了系统软件结构、功能实现及数据库的设计,为实现基于GIS的森林防火系统提供参考。通过系统运行过程中的数据采集、历史数据累积,可以实现森林防火数据的分析、挖掘,为有效防治森林火灾提供重要途径。     

Spatiotemporal characteristics of white mold and impacts on yield in soybean fields in South Dakota

ABSTRACT

White mold of soybeans is one of the most important fungal diseases that affect soybean production in South Dakota. However, there is a lack of information on the spatial characteristics of the disease and relationship with soybean yield. This relationship can be explored with the Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 and a fusion of Landsat 8 and the Moderate Resolution Imaging Spectroradiometer (MODIS) images. This study investigated the patterns of yield in two soybean fields infected with white mold between 2016 and 2017, and estimated yield loss caused by white mold. Results show evidence of clustering in the spatial distribution of yield (Moran’s I = 0.38; p < 0.05 in 2016 and Moran’s I = 0.45; p < 0.05 in 2017) that can be explained by the spatial distribution of white mold in the observed fields. Yield loss caused by white mold was estimated at 36% in 2016 and 56% in 2017 for the worse disease pixels, with the most accurate period for estimating this loss on 21 August and 8 September for 2016 field and 2017 field, respectively. This study shows the potential of free remotely sensed satellite data in estimating yield loss caused by white mold.     

应用TM图像监测及评估林火、虫灾和洪涝灾害的理论与实践

本文报导了在大兴安岭特大森林火灾实时监测与灾情分析、皖东孤山林场松毛虫害探测及江淮地区特大洪涝灾害灾情评估等工作中应用TM图像的成功实践,分析了TM图像用于监测及评估这些自然灾害的理论依据、关链技术及其优越性与局限性。     

一种改进的林火蔓延模型及其实现

为了研究林火蔓延的动态模拟问题,结合元胞自动机原理,对现有的林火蔓延数学模型进行改进,提出一种新的模拟林火蔓延模型。该模型充分表达了可燃物类型、温度、湿度、坡度、风速和风向等林火蔓延影响因子在元胞空间中的作用形式,通过求解出燃烧元胞向摩尔(Moore)型邻域中八个方向元胞的林火蔓延速度,来确定元胞状态演变规则函数。最后,利用地理信息系统二次开发技术将该模型表达成计算机算法,实现了不同条件下的林火行为的仿真模拟。     

我国森林植被遥感调查及建库研究

我国森林植被的覆盖程度受到土壤、气候、海拔、人为等各种因素的互相影响,为了能够遵循＂适地适树＂原则而更加精确在不同地区栽种适宜的树种从而提高我国森林覆被率,利用遥感技术对全国森林植被及其所生长的条件进行调查是重中之重。本文以全国范围为研究区域,利用MODIS数据对土壤、植被及气候数据进行提取,引入梯形网格,对全国进行等经纬度的网格划分,利用ArcGIS,ENVI等软件绘出我国土壤类型、N、P元素及有机质含量、年降雨量、年最高温度及最低温度的温度等值线,再利用数据挖掘技术提取与森林植被覆盖率相关的影响因子得出我国现阶段森林植被覆盖图,计算出我国现有林地面积并对影响森林植被覆盖的因子进行数据库的录入。     

皖南低山丘陵破碎带植被信息提取方法

以芜湖市繁昌县为例,利用多尺度多变量的面向对象影像分析方法,结合HJ1-CCD、Landsat5 TM以及DEM数据,研究了低山丘陵复杂背景下植被信息遥感提取方法。针对不同植被类型,选用适宜分割尺度进行影像分割,构建面向对象的分类规则集进行研究区植被信息分类,植被提取总体精度达到了80.8%。     

利用动态阈值的森林草原火灾火点检测算法

针对传统固定阈值的森林和草原火灾火点遥感检测算法因时空环境变化而导致的火点漏检和误检问题,提出了一种综合季节、地理位置和土地覆盖类型等影响因素的时空动态阈值火点检测算法。实验结果表明,时空动态阈值火点检测算法能有效改善火点检测结果,具有时空自适应性。     

粗糙神经网络在森林火灾预警中的应用

利用神经网络和粗糙集处理不确定性问题的优势，提出一种粗糙集结合神经网络进行森林火灾预测模型。通过与传统预测模型相比较，证明了该方法的有效性。     

基于PDA的森林防火GIS的研究与实现

目前,基于PDA的森林防火地理信息系统,以其自身独特的优势引起林业领域的广泛关注.本文从森林防hA-面,对基于PDA的嵌入式GIS系统进行探讨.首先介绍系统的开发环境和软件功能设计,然后分析系统实现的关键技术和方法,最后对基于PDA的森林防火GIS的应用前景进行了展望.     

基于AO技术的森林防火地理信息系统实例应用分析

ArcObjects完全基于COM架构,可以在任何符合COM标准的应用中嵌入,获得地理信息系统的功能.详细介绍AO技术在开发森林防火地理信息系统中的应用,同时也指出该系统在开发过程中的不足和缺陷.     

Seasonal Variation of MODIS Vegetation Indexes and Their Statistical Relationship With Climate Over the Subtropic Evergreen Forest in Zhejiang, China

Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day 1-km vegetation index products, daily temperature, photosynthetically active radiation (PAR), and precipitation from 2001 to 2004 were utilized to analyze the temporal variations of the MODIS normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), as well as their correlations with climate over the evergreen forested sites in Zhejiang-a humid subtropical region in the southeast of China. The results showed that both NDVI and EVI could discern the seasonal variation of the evergreen forests. Attributed to the sufficient precipitation in the study area, the growth of vegetation is mainly controlled by energy; as a result, NDVI, and especially EVI, is more correlated with temperature and PAR than precipitation. Compared with NDVI, EVI is more sensitive to climate condition and is a better indicator to study vegetation variations in the study region     

冲击指标应用于保安林地人为冲击之研究

保安林分布遍及全台湾省，但在自然与社会环境的变迁下，民众对土地资源需求日益迫切，区外保安林常遭非法使用，因此如何有效地订定经营决策，为经营者应注视之问题。本研究以垦丁公园辖区之区外保安林为研究范围，利用1993与2001年SPOT卫星遥测影像为材料，并用监督性分类法中之最大概似法进行影像分类，建立都市、森林、农耕地等3种土地利用类型，分类结果提供监测1993至2001年间保安林之土地变迁。此外保安林地受人为之冲击评估乃采用分类之结果与地理信息系统之空间分析技术，配合保安林地之开发地成长率、农耕地开垦率及保安林地受人为潜在开发率等冲击指标，评估垦丁公园境内各编号保安林所受到的人为冲击。研究结果显示，共有8处保安林所受之冲击最为严重，值得管理者加以重视。     

Assessing the Priorities for Sustainable Forest Management in the Sikkim Himalaya,India: A Remote Sensing Based Approach

Sikkim is a small, mountainous, Indian state (7,096 km²) located in the eastern Himalayan region. Though a global biodiversity hotspot, it has been relatively less studied. A detailed forest type, density and change dynamics study was undertaken, using SATELLITE remote sensing data and intensive field verification. The landscape was found to be dominated by alpine and nival ecosystems, with a large portion above the tree line, considerable snow cover, and a sizeable area under forest cover (72%, 5,094 km²). A total of 18 landscape components including 14 vegetation classes were delineated, with the major ones being oak forest, alpine meadow, alpine scrub, conifer forest and alder-cardamom agro-forestry. Of the 3,154 km² of forests below the tree line, 40% were found to be dense (>40% tree canopy cover). A sizeable portion of the non dense forests below the tree line was contributed by the degradation of oak forests, which was confirmed by change detection analysis. However on a positive front over the past decade, ban on grazing and felling of trees in forests has been implemented. In order to expand the extent of dense forests, further efforts are needed for the restoration of oak forests such as fire protection, providing alternatives to firewood use, promotion of alder-cardamom agro-forestry in the private lands and protection of the small-sized, fragmented forest patches in the subtropical belt.     

基于Skyline的三维林火模拟分析系统

森林是国家的重要资源,是人类赖以生存的自然环境条件,森林火灾的防护是林业工作的重要组成部分,保护森林资源是全国乃至全人类的重要任务。本文利用Skyline软件,根据林火扩散模型的特征、崂山市地形等因素,选取王正非模型模拟林火扩散,系统实现了基础信息的管理、图层管理、火场管理、火险等级划分等功能,在一定程度上为指导森林防火工作提供了科学依据。     

Landslide inventory validation and susceptibility mapping in the Gerecse Hills,Hungary

Landslides pose a threat to property both in the populated and cultivated areas of the Gerecse Hills (Hungary). The currently available landslide inventory database holds the records from many sites in the area, but the database is out-of-date. Here we address the problem of revising the National Landslides Cadastre landslide inventory database by creating a landslide suscept- ibility map with a multivariate model based on likelihood ratio functions. The model is applied to the TanDEM-X DEM (0.4″ res.), the current landslide inventory of the area, and data acquired from geological maps. By comparing the distributions of four variables in the landslide and non-landslide area with grid computation methods, the model yields landslide susceptibility estimates for the study area. The estimations show to what extent a certain area is similar to the sample areas, therefore, its likelihood to be affected by landslides in the future. The accuracy of the model predictions was checked in the field and compared to the results of our previous study using the SRTM-1 DEM for a similar analysis. The model gave accurate estimates when certain correction measures were applied to the input datasets. The limitations of the model, the input datasets, and the suggested correction measures are also discussed.