Biotic factors and occurrence of Lutzomyia longipalpis in endemic area of visceral leishmaniasis, Mato Grosso do Sul, Brazil

The relationships between environmental exposure to risk agents and health conditions have been studied with the aid of remote sensing imagery, a tool particularly useful in the study of vegetation cover. This study aims to evaluate the influence of environmental variables on the spatial distribution of the abundance of Lutzomyia longipalpis and the reported canine and human visceral leishmaniasis (VL) cases at an urban area of Campo Grande, state of Mato Grosso do Sul. The sandfly captures were performed in 13 residences that were selected by raffle considering four residences or collection station for buffer. These buffers were generated from the central house with about 50, 100 and 200 m from it in an endemic area of VL. The abundance of sandflies and human and canine cases were georreferenced using the GIS software PCI Geomatica. The normalized difference vegetation index (NDVI) and percentage of land covered by vegetation were the environmental variables extracted from a remote sensing IKONOS-2 image. The average NDVI was considered as the complexity of habitat and the standard deviation as the heterogeneity of habitat. One thousand three hundred sixty-seven specimens were collected during the catch. We found a significant positive linear correlation between the abundance of sandflies and the percentage of vegetation cover and average NDVI. However, there was no significant association between habitat heterogeneity and the abundance of these flies.     

Advances in satellite remote sensing of pheno-climatic features for epidemiological applications

Geographical Information Systems (GIS) and Remote Sensing (RS) technologies are being used increasingly to study the spatial and temporal patterns of diseases. They can be used to complement conventional ecological monitoring and modelling techniques, and provide a means to portray complex relationships in the ecology of diseases with strong environmental determinants. In particular, satellite technology has been extraordinarily improved during recent years, providing new parameters useful to understand the epidemiology of parasites, such as vegetation indices, land surface temperatures, soil moisture and rainfall indices. In the present review, Normalized Difference Vegetation Index (NDVI) is primarily considered, since it is the index characterizing vegetation that is most used in epidemiological studies. Multi-temporal study of RS data allows collection of bio-climatic information about risk area distribution, along with predictive studies and anticipatory models of diseases, at different geographic scales ranging from global to local. The main physical and technological basis of a mathematical model, effective at different scales, for identification of landscape pheno-climatic features is described in the current paper.     

基于RS和GIS的毛乌素沙地植被盖度定量估测

选取毛乌素沙地东北部的伊金霍洛旗为研究区域,以少量野外定位调查数据与其对应的遥感信息和GIS信息为基础,利用岭估计分析方法,对植被盖度估测模型及其影响因子进行系统研究.结果表明,植被盖度除受NDVI影响外,还与其他遥感信息紧密相关,岭估计方法明显地改善了最小二乘估计的缺陷,克服了变量间由于存在复共线性关系对求解待定参数所造成的不利影响,提高了估测精度.建立了以像元为单位的植被盖度估测模型,其模型检验精度达98.7%.此外,还建立了区域性植被盖度地理信息系统,实现了研究区域内任意一点(像元)或任意土地单元植被盖度的查询、更新及自动制图.     

退耕还林(草)过程中陕北地区NDVI时空变异及其驱动因子的地理探测

地表植被作为生态环境变化的敏感因子,对维持区域生态稳定性具有重要作用.基于退耕还林(草)生态工程实施过程中2000-2019年陕北地区的MODIS NDVI数据,结合地形、地貌、气候、土壤和植被等环境因子,探究NDVI时空变异特征,并运用地理探测器模型对植被NDVI影响因子及其影响程度进行探测,最终确定主要环境因子对N...     

基于生境可获得性的完达山地区马鹿(Cervus elaphus xanthopygus)冬季生境选择

于2004～2005年冬季研究了完达山地区马鹿的生境利用和选择。在野外调查的基础上,获取了研究地区马鹿种群水平上的生境利用数据;利用地理信息系统和遥感技术,从区域尺度上测度了各类生境因子的可获得性。通过比较被利用生境与可获得生境,测度了马鹿冬季对各类生境或生态因子的选择。结果表明,马鹿对植被类型、海拔、坡向、NDVI等级、到公路距离表现出非比例利用,对坡度的利用与其可获得性则没有显著性差异。马鹿选择采伐迹地,低郁闭度生境（第2、3NDVI等级）,200～300m海拔区间,南坡,距离公路600～700m的区间。马鹿采食生境和卧息生境对各类因子具有不同的选择性,表现出不同功能生境分离的特征。对于采食生境,马鹿选择采伐迹地、阔叶疏林,低郁闭度（第2、3NDVI等级）,南坡;对于卧息生境,马鹿仅选择采伐迹地,低郁闭度（第2、3、4NDVI等级）。根据马鹿活动样点的出现与否,建立了马鹿冬季生境选择的逻辑斯谛回归模型。模型回判结果表明,该模型对马鹿活动样方与对照样方的总体正确预测率为74．4％,对马鹿活动样方的正确预测率为84．2％,对对照样方的正确预测率为62．4％,能够较好的预测生境利用概率。     

Use of remote sensing and geographical information systems to estimate green space surface-temperature change as a result of urban expansion

A combined approach of remote sensing (RS) and geographical information systems (GIS) was used in this study to identify the impact on urban surface radiant temperature (SRT) of urban green-space change. Urban SRT increases as green-space area is converted into non-green-space area. Also, well preserved green space and newly connected green space contribute to a decrease of the SRT. Seoul Metropolitan area is rapidly expanding. Existing urban SRT studies have, however, mainly been conducted for Seoul City. The most rapidly expanding area in Korea is now the Seoul suburban area, for example the Mt Gwanggyo area. Although changes of SRT and normalized difference vegetation index (NDVI) as a result of land-use change have been measured in many other studies, the results in these studies were derived from data from different seasons. Also, these studies did not examine a newly expanding area. Considering these problems, the same seasonal multitemporal data were used in this study to derive the SRT change for the same season in different years. This study confirmed the importance of effective management and location of urban green space for urban SRT mitigation. Ultimately, the impact on urban SRT of urban green-space change should be regarded as an important factor in urban planning.     

近10年湖北省植被指数时空变化特征及其驱动力

为了明确湖北省植被长势变化特征及其影响因子,研究利用Landsat影像提取2005年、2010年以及2015年湖北省景观类型信息,分析近10年来景观时空变化特征;基于2005-2015年夏季MODIS/NDVI数据,采用一元线性回归、Theil-Sen median趋势、Mann-Kendall检验等分析方法对NDVI时空变化特征及其显著性进行探讨;采用最小二乘法对NDVI与气候之间的相关关系进行分析。使用DMSP/OLS和NPP/VIIRS夜间灯光数据探讨NDVI与人类经济活动之间的关系。结果表明：研究区景观类型变化以建设用地和耕地为主。耕地面积呈现逐年减少的趋势,主要转变为建设用地。建设用地面积不断增多,主要由耕地和林地转变而来,集中在武汉、荆州、襄阳城市圈;研究区NDVI值整体上表现为西高东低,以林地为主的十堰、恩施等地区NDVI值较高,以建设用地为主的武汉、襄阳、荆州等地区NDVI值较低;整体上NDVI变化呈轻微改善趋势,局部地区下降明显,鄂西北、鄂西南等地区NDVI稍有上升,武汉城市圈植被呈退化趋势;NDVI与降水量、气温的相关性均较弱,气候因子不是该区NDVI变化的主导因子;NDVI与夜间灯光亮度值呈显著负相关,相关系数达-0.8030,整体上人类经济活动与NDVI呈负相关关系,且有着分区性的特点,在武汉、襄阳等以建设用地为主的地区人类经济活动对NDVI起抑制作用,而在恩施、十堰等林地为主的地区人类活动对NDVI起促进作用。人类社会经济活动是影响研究区景观格局和植被变化的重要驱动力,城镇化扩张是湖北省植被变化的主要原因。     

黄土高原归一化植被指数与自然环境因子的空间关联性——基于地理探测器

植被对改善黄土高原脆弱的生态环境有着关键作用,系统研究黄土高原归一化植被指数(NDVI)空间分布和环境因子的空间关联性,可为新时代黄土高原植被高质量建设提供科学依据。以黄土高原2000-2017年年均植被NDVI为研究对象,选取气候要素、地形因素、土壤类型和植被类型等自然环境因子,运用GIS和地理探测器技术手段,在剔除土地利用类型发生变化栅格的基础上,研究黄土高原年均NDVI与环境因子的空间关联性,结果表明:2000-2017年黄土高原年均NDVI值在0.016-0.72之间,呈地带性分布,由西北部向东南部逐渐升高,大于0.3的区域占50.23%;2000-2017年黄土高原年均植被NDVI分布具有空间异质性,且在不同植被区、地貌区、土壤区和气候区中,NDVI空间分布的主要环境驱动因子具有差异性。年均降雨量对NDVI空间分布具有强解释力,是黄土高原85.20%的区域植被生长的主要制约因子;约12.01%的区域主要受土壤类型影响,为中等解释力,其余区域的植被生长主要受年均气温,日照时数或海拔影响。建议综合考虑不同环境条件下植被NDVI的空间分布与环境影响因子的空间关联性,明确不同区域中植被NDVI的环境制约因子,以制约因子定植,在防止土壤干燥化、贫瘠化的前提下,提高植被覆盖率和生物多样性,以期促进黄土高原植被建设高质量发展。     

岷江上游植被冠层降水截留的空间模拟

 通过对岷江上游实地踏查和定位观测研究,结合MODIS遥感数据,利用“3S”技术对岷江上游植被冠层降水截留进行了空间模拟。研究结果表明：岷江上游植被叶面积指数（LAI）与增强性植被指数（EVI）以二项式关系拟合效果较好。由于归一化植被指数（NDVI）存在的饱和问题,研究采用EVI反演LAI,统计结果表明：岷江上游LAI值在0～2之间的占28.57%,在2～4.5之间的占63.06%,大于4.5的占8.37%,其中LAI最大值为7.394;从冠层最大降水截留模拟结果来看: 植被较好的地区,如卧龙、米亚罗的植被冠层最大降水截留量较大,而干旱河谷、上游高山草甸等地的植被冠层最大降水截留量相对较低;附加冠层降水截留与降雨量呈线性相关,模型验证时以此为基础,模型模拟的结果较为理想。     

Patterns of herbivore species richness in Kenya and current ecoclimatic stability

The increased attention to biodiversity worldwide has stimulatedinterest in understanding biophysical factors associated with indicators ofbiodiversity such as species richness. Although levels of biodiversity may seemto be equivalent in different areas, high species richness may be caused byaccumulation of species over a long time in places where environmentalconditions remained stable and predictable. The advanced very high resolutionradiometer (AVHRR)–normalized difference vegetation index (NDVI) has beenestablished to be a good proxy for studying interannual climate variability aswell as regional drought condition. In this study, I examined the relationshipbetween large herbivore species richness and AVHRR–NDVI derivedclimatic-variability indices, interannual average NDVI and coefficient ofvariation of NDVI at a regional spatial scale in Kenya. Regions with a relativelylow coefficient of variation of NDVI and high interannual average NDVIcharacterize current ecoclimatic stability. By contrast, a high coefficient ofvariation of NDVI and relatively low interannual average NDVI characterizeecoclimatic instability (drought risk). Statistical analyses revealed that a highinterannual average NDVI increases species richness, whereas a high coefficient ofvariation of NDVI lowers species richness. This indicates that maximum numbers ofspecies are found in regions with current ecoclimatic stability. Understandingsuch relationships can help in explaining spatial distribution of speciesrichness and predicting global changes resulting from human impacts on theenvironment.     

基于RS、GIS的天目山自然保护区植被空间分布规律研究

以RS、GIS技术为工具。将天目山自然保护区的TM遥感影像进行处理与分类得到该区的植被分布图。利用GIS空间分析功能。研究了天目山自然保护区内各植被类型空间分布规律。重点研究了其中的一种植被类型。研究结果定量描述了自然保护区内各植被类型的高程、坡向、坡度分布,给出科学的统计结果。总结了研究区内植被类型的空间分布规律,把对植被类型的空间分布规律的定性理解转为定量描述,结合实际给出了理论解释。为自然保护区的规划、管理和保护提供了科学依据。     

Ecotope mapping for landscape ecological assessment of habitat and ecosystem

An ecotope (spatial eco-space) map that considers topography and bio-organism-relevant variables emerges as an important basic framework when landscape-scale characteristics for ecosystem management and wildlife conservation are needed. A spatio-geoecological framework based on geographic information systems (GIS) and a vegetation survey were developed for wildlife habitat evaluation of national parks and applied to a representative rugged valley area of Mt. Sorak National Park in Korea. An ecotope map was classified into hundreds of types and dozens of groups by combining biological and geophysical variables. Variables included: forest vegetation type, topographic solar radiation, normalized difference vegetation index (NDVI), elevation, and anthropogenic factors, such as, streams and roads. Layers of GIS variables were produced by field surveys, modeling, satellite images, or digitalization. Vegetation surveys were carried out to identify finer-scale distribution of vegetation types in the rugged valley area. Digital forest vegetation maps from the Forestry Administrator were then modified using the field-surveyed vegetation maps. Topographic solar radiation was predicted with a daily topographic radiation model. The NDVI was calculated from the satellite imagery of a Landsat Thematic Mapper. A digital elevation model (DEM) was used and the other layers were digitized using topographical maps with a scale of 1:25000. The aim of this study is to determine the geoecological factors relating to the spatial pattern of plant community. It was cleared by the spatial pattern of environmental variables and vegetation characteristics by detrended correspondence analysis using plant species and the environmental variables of each plot. The ordination component value of the first axis shows significant regression to some environmental variables. A case study of habitat evaluation was carried out using the resultant ecotope map. The spatial distribution of potential goral habitat and vegetation characteristics were predicted and the impact of human trails on the neighboring vegetation was also examined for restoration planning. The GIS-based framework developed for wildlife habitat evaluation is useful for natural resource management and human activity control in national parks in Korea.     

1982～2003年东北地区植被覆盖变化特征分析

利用1982~2003年GIMMS-NDVI数据集和GIS技术,结合多种统计分析方法,定量分析了东北地区植被覆盖时空变化规律。结果显示:(1)1982~2003年东北地区森林、草地和农田植被年内变化曲线均为单峰型,峰值都出现在夏季,森林植被年内NDVI变化曲线峰值最高,农田次之,草地最低。(2)22年期间,森林植被覆盖呈下降趋势;草地和农田植被覆盖总体亦呈下降趋势,但西辽河平原草地和松嫩平原农田植被覆盖呈上升趋势;相同植被类型比较,长白山东北部林地、西辽河平原草地、松嫩平原农田植被覆盖均比较稳定。(3)1982~2003年,东北地区植被覆盖总体呈缓慢下降趋势,其中1982~1992年,东北地区植被覆盖呈增加趋势,植被覆盖增加的面积为545 435 km2,占东北地区总面积的43.91%;植被覆盖减少面积为96 491 km2,占总面积的7.77%;1993~2003年,东北地区植被覆盖呈减少趋势,植被覆盖减少的面积为626 839 km2,占东北地区总面积的50.45%,植被覆盖增加的面积较少,仅为27 025 km2,占总面积的2.18%,且呈零星分布。研究表明,人类活动和自然因素的变化是东北地区植被覆盖下降的主要原因。     

2000-2010年黄河流域植被覆盖的时空变化

黄河流域位于干旱、半干旱和半湿润地区,生态环境脆弱,近年来,在气候变化和人类活动影响下,植被覆盖状况发生了变化。因此需要对黄河流域植被覆盖的变化进行监测,进而掌握流域植被的动态变化特征。在此背景下,利用2000-2010年的250 m分辨率的MOD13Q1数据来研究黄河流域植被覆盖区域的NDVI时空变化特征。采用Theil-Sen Median趋势分析和Mann-Kendall检验来研究NDVI的变化趋势特征,通过对Theil-Sen Median趋势分析和Mann-Kendall检验的结果和Hurst指数的结果的叠加,来研究NDVI的可持续特征。研究表明：1）从空间分布上看,黄河流域NDVI呈现出西部和东南部高,北部低的特征;2）从时间变化特征上看,2000-2010年植被覆盖区域年均NDVI均值在0.3-0.4之间波动,其中2000-2004年NDVI波动较大,但自2005年以来NDVI呈现快速增长的趋势;3）从变化趋势上看,2000-2010年黄河流域植被改善的区域远远大于退化的区域,改善的区域占植被覆盖区域总面积的62.9%,退化的区域占27.7%,9.4%的区域NDVI稳定不变;4）从可持续性来看,86.0%的植被覆盖区域NDVI呈现正向可持续性,即NDVI的可持续性较强;由变化趋势与Hurst指数的耦合信息得出,持续改善的面积占植被覆盖区域总面积的53.7%,持续稳定不变的区域占7.8%,持续退化的区域占24.5%,另外14.0%的区域未来变化趋势无法确定,持续退化和未来变化趋势无法确定区域的植被变化状况需要研究人员继续关注。     

2000—2016年云南地区植被覆盖时空变化及其对水热因子的响应

基于2000-2016年MODIS-NDVI数据,利用趋势分析法以及线性相关分析等方法对云南地区植被月变化趋势、年际变化趋势进行详细分析;探讨植被覆盖变化与主要气候水热因子的关系。结果表明：研究区大部分地区植被覆盖良好,年NDVI的平均值为0.55,其中NDVI较高值（> 0.8）区域主要分布于南部,而西北部和中部城市地区NDVI值较低;自2000年开始,研究区NDVI总体呈显著（P < 0.05）增加趋势,年NDVI的变化斜率为0.0036,植被覆盖呈增加趋势的区域占研究区总面积79.80%;不同季节（春、夏、秋、冬）和生长季的植被状况均呈良性发展趋势;湿润指数和水热综合因子在滇西北与NDVI多呈负相关,在滇中地区以正相关为主;春、夏、秋3个季节NDVI受降水影响较大,而冬季NDVI则受气温影响较大;受降水影响较大的区域主要分布在中部和南部,受气温影响较大区域主要分布在滇西北、滇东北地区;NDVI在不同月份对气候因子的滞后时间存在差异,NDVI与当月气温的相关性强于与当月降水的相关性,植被生长对气温的响应无明显滞后效应,对降水存在3个月的滞后期。     

陕西省植被覆盖时空变化及其对极端气候的响应

基于2001—2018年MODIS NDVI数据,从生态分区视角分析陕西省归一化植被指数(NDVI)的时空变化特征,并结合该地区31个气象站点日值数据,探讨NDVI对极端气温和极端降水指数的响应特征。结果表明：(1)陕西省及其各生态区的NDVI变化均显著上升,整体呈南高北低的分布特点,其中秦巴山地落叶与阔叶林生态区(IV)NDVI值最高为0.86,陕北北部典型草原生态区(I)NDVI值最低为0.38。(2)年际尺度上,陕西省NDVI与极端气温暖极值(暖夜日数)和极端降水指数总体呈显著正相关(P<0.05),在陕西省北部NDVI变化主要受极端降水的影响,南部则对极端气温的敏感度更高。(3)多年月尺度上,各生态区NDVI对极端气温冷极值(最低气温、日最低气温的极低值和日最高气温的极低值)和极端气温暖极值(最高气温、日最低气温的极高值和日最高气温的极高值)存在明显的滞后性,滞后时间多为3个月;与极端降水指数(单日最大降水量和连续5日最大降水量)的滞后时间为2个月,说明陕西省内NDVI对极端气候的响应具有显著的滞后效应。     

浙江省植被NDVI动态及其对气候的响应

利用GIMMS和MODIS两种归一化植被指数(NDVI)资料反演了1982—2010年浙江植被覆盖状况,结合同期研究区63个气象站点的气温、降水和湿润指数等气候指标,分析了该地区植被年际变化、月际变化及其对气候要素的响应特征。结果表明:(1)研究期间,浙江气候总体呈暖干化趋势,植被覆盖缓慢下降,主要是由于森林植被遭破坏,农业生产活动受抑制影响所致,其中NDVI显著减少的地区约占全省陆域面积的29.1%,主要发生在6—11月;(2)降水量及干湿程度对浙江植被NDVI年变化起着决定性作用。植被与气候要素年变化相关分析发现,NDVI与湿润指数关系较降水、气温更为密切,两者相关及偏相关系数均通过0.05水平的置信度检验,这表明在年际尺度上,湿度的增加增大了植被的生长势,有利于植被生长;(3)植被与气候要素月变化分析表明冬季的热量供给是影响浙江植被生长的重要因子,而植被变化对夏季降水和干湿程度的最大响应为滞后两个月;(4)农业生产水平的提高使得农作物种植区NDVI有所增加,人类活动对浙江植被覆盖的影响不可忽视。     

长江中上游地区退耕还林成效监测与评价

将长江中上游地区84个地市级区域作为一个整体,利用GIS综合解译分析归一化植被指数(NDVI)、土地利用类型和数字高程模型(DEM),揭示该区域退耕还林工程所取得的成效.结果表明: 2000-2015年,研究区域NDVI持续增长;与2000年相比,2015年长江中上游地区有2.1%的耕地不再耕种,坡度>35°坡耕地的25%实现了退耕,25°~35°坡耕地的2.7%实现了退耕,中坡度耕地绝大部分实现退耕;耕地主要转变为林地和草地.研究期间,林草覆盖度增加显著,增幅达21.9%;低植被覆盖度的土地面积大幅减少,植被覆盖度小于10%的面积减少95.3%,高植被覆盖度的土地面积显著增加;土壤侵蚀强度总体降低,轻度、强度、极强度等级土壤侵蚀的土地面积均减少10%以上,但剧烈土壤侵蚀状况未得到缓解.研究区森林覆盖率达到60%,但不同时段覆盖度的变化比例存在差异,空间分布不均匀,呈现东部高、西部低的特征,需要继续加强治理.     

Vegetation variation of mid-subtropical forest based on MODIS NDVI data — A case study of Jinggangshan City,Jiangxi Province

Vegetation variation is an important topic of global change research, which is of great significance to deeply understand the relationship between vegetation and global change or human activities, and to disclose regional environment evolution and transition. The dynamics of forest vegetation in the mid-subtropical zone have received little attention. Thus, this paper takes the typical distribution area of the subtropical forest ecosystem — Jinggangshan City in Jiangxi Province as a study area. The changes within the year, inter-annual changes trend and spatial variation of the mid-subtropical forest vegetation index during the recent 10 years are analyzed based on MODIS NDVI data from 2000–2011 with the spatial resolution of 250 m. The Savitzky–Golay filter is used to smooth the original MODIS NDVI data. The forest distribution data is taken as the mask to eliminate the impact of non-forest cover area. The results showed that: (1) The changes of forest vegetation index within the year present a single peak mode with the maximum value in July; in the past 10 years, the forest vegetation index fluctuated with a downward trend; NDVI values were high and stable in summer and autumn, but low and unstable in winter; (2) The distribution of NDVI values of forest vegetation had great spatial difference. The NDVI values were low in the area nearby non-forest area in the north, where the non-forest vegetation is widely distributed. The NDVI values were high in the northwestern and southeastern areas. The distribution of NDVI values are comparatively even in the middle area with the NDVI values of more than 0.7; (3) High NDVI values (>0.75) distributed most in the northwestern and southeastern areas with the altitude of 400–600 m. Low NDVI values (<0.65) distributed mostly in the northern areas with the altitude less than 400 m. As for different altitude zones, NDVI values are high in the area with altitude of 400–800 m and low in the area with altitude below 400 m or above 1200 m. There is an agreement between the spatial distribution of the NDVI value of forest vegetation and regional topography, because topography has great impacts on the distribution of forest types which are different in coverage; (4) The NDVI value of forest vegetation presents a downward trend in the northern area, but an increasing trend in the southern area. The vegetation coverage tends to decrease with high population density and intensive distribution of township and scenic spot.