Vegetation greenness modeling in response to climate change for Northeast Thailand

In Northeast Thailand, the climate change has resulted in erratic rainfall and tem- perature patterns. The region has experienced both periods of drought and seasonal floods with the increasing severity. This study investigated the seasonal variation of vegetation greenness based on the Normalized Difference Vegetation Index （NDVI） in major land cover types in the region. An assessment of the relationship between climate patterns and vegeta- tion conditions observed from NDVI was made. NDVI data were collected from year 2001 to 2009 using multi-temporal Terra MODIS Vegetation Indices Product （MOD13Q1）. NDVI pro- files were developed to measure vegetation dynamics and variation according to land cover types. Meteorological information, i.e. rainfall and temperature, for a 30 year time span from 1980 to 2009 was analyzed for their patterns. Furthermore, the data taken from the period of 2001-2009, were digitally encoded into GIS database and the spatial patterns of monthly rainfall and temperature maps were generated based on kriging technique. The results showed a decreasing trend in NDVI values for both deciduous and evergreen forests. The highest productivity and biomass were observed in dry evergreen forests and the lowest in paddy fields. Temperature was found to be increasing slightly from 1980 to 2009 while no significant trends in rainfall amounts were observed. In dry evergreen forest, NDVI was not correlated with rainfall but was significant negatively correlated with temperature. These re- sults indicated that the overall productivity in dry evergreen forest was affected by increasing temperatures. A vegetation greenness model was developed from correlations between NDVI and meteorological data using linear regression. The model could be used to observe the change in vegetation greenness and dynamics affected by temperature and rainfall.     

基于偏最小二乘法的玉米FPAR高光谱反演模型研究

以ASD FR便携式光谱仪与LI-191SA光量子仪对吉林中西部的玉米田进行多次观测,采集到123组有效数据,基于偏最小二乘法(PLS)对玉米FPAR进行高光谱反演。对可见光与近红外光谱(400～1 500nm)进行分析并建立反演模型,对FPAR预测效果进行验证,验证模型的R2为0.785,RMSE为0.117;同时进行了玉米FPAR与光谱反射率、反射率一阶导数之间的关系分析及植被指数与玉米FPAR之间的回归分析。研究结果表明,PLS方法建立的模型可有效地从玉米高光谱反射率数据反演出FPAR含量,反演结果精度较植被指数高。     

蒙古东部野火时空格局及其影响因素

基于MCD64A1过火迹地产品、土地覆盖、植被指数和气候等数据,采用空间统计分析和相关分析方法研究了2001—2017年蒙古东部野火时空动态及其影响因素。结果表明：（1）4—6月是野火发生最主要的时段,10月野火灾害也较严重,特别集中于年内第107—127、145—189、279—301日3个时段;2001—2017年,蒙古东部野火过火面积年际间波动较大,2003、2007、2011、2012、2015年是野火发生的高峰年。（2）从野火发生的空间格局看,野火灾害主要发生在东方、肯特、苏赫巴托尔、色楞格、中央省;草原火是蒙古东部主要的过火类型。（3）过火面积主要受降水、温度和植被状况影响;3月过火面积主要与3个月累积的干旱状况有关,而6、7月过火面积主要与当月温度相关,9月过火面积主要受当月降水量影响;在季节尺度上,春季过火面积还与前一年秋季植被状况显著相关,冬季过火面积与当季地表温度呈显著正相关。（4）大气环流与蒙古东部的野火发生、蔓延密切相关,4月过火面积主要受3个月累积北极涛动影响,7月过火面积主要受3个月累积太平洋十年涛动影响,9月过火面积主要受火前北大西洋涛动影响,而11月过火面积主要受3个月累积南方涛动和太平洋十年涛动影响。年尺度上的过火面积主要受北大西洋涛动显著影响。     

基于MODIS时序数据的中国西南地区主要植被生态系统干扰动态监测及分析

在自然或人为活动的干扰下,生态系统的正常功能或多或少受到影响。生态系统干扰信息可为跟踪气候变化响应、探寻全球碳循环路径和维系生态系统功能提供重要参考。飞速发展的遥感技术为生态系统干扰信息的获取提供了新的思路,高时空分辨率的遥感影像能及时有效地监测干扰事件发生的时间和位置。本文以中国西南地区为例,选用2005—2016年MODIS影像的地表温度LST（Land Surface Temperature）和增强型植被指数EVI（Enhanced Vegetation Index）产品,首先应用遥感干扰指数模型提取2007—2016年的逐年生态系统干扰数据,然后研究了西南地区森林与草地灌丛生态系统干扰的时空分布,并通过地面着火点观测记录、遥感火烧迹地数据、Google Earth和政府报告等验证干扰指数模型的有效性,最后明晰中国西南地区森林与草地灌丛干扰强度的分布特征。结果表明：① 本文使用的遥感干扰指数模型对干扰事件十分敏感,明显优于单独使用EVI或LST。② 本文提取的森林生态系统干扰和草地灌丛生态系统干扰与Google Earth、气象数据等保持高度一致。③ 森林与草地灌丛干扰是研究区内最主要的生态系统干扰,约占每年总干扰面积的90%。④ 森林干扰最强烈区在川西高原地区,可能的干扰类型为森林火灾,草地灌丛干扰最强烈区为青藏高原农牧区,可能的干扰类型为气象干旱干扰。     

Spatial and temporal patterns of fires in tropical savannas of Indonesia

This paper examines spatial and temporal patterns of large to medium‐sized fires across the Indonesian Archipelago using remote sensing, particularly the MODIS fire products, over a 14 years period (2000–13 inclusive) in conjunction with climatic and land data in a GIS. Results showed fires (burned area and number of fires) were detected the most in year 2002 and least in 2010. The extent of burning was correlated with the annual Southern Oscillation Index with most burning occurring during times of sustained negative SOI values, which generally means drier conditions across the region. Most of the detected fires occurred in the middle of the dry season and in drier eastern Indonesia. Across Indonesia, approximately 1.5 per cent of available open vegetation area burned, whereas only 0.5 per cent of forest area burned. Most open vegetation burning was detected in the savanna with an area equivalent to 11.1 per cent of its extent being burned over the 14 years. On Sumba Island, where the pronounced dry season extends for at least four months, open vegetation is the most common land cover type, of which 99 per cent burned by area over the study period making it the island with the most burned areas in the Indonesian Archipelago.     

基于Landsat时间序列遥感数据的华北平原农田火烧迹地检测与制图

以河南省漯河市、周口市和驻马店市交界处为研究区,基于2000年10月~2011年12月间的101幅图像,采用谐波模型和断点识别算法拟合Landsat时间序列实现对过火像元的检测,并将结果与目视解译结果、MODIS火烧迹地产品MCD64A1检测结果对比进行精度分析。结果表明：① 随着燃烧面积指数BAI (Burned Area Index)异常值阈值增大,焚烧火点误判误差减小,漏判误差增大,火烧迹地制图的总体精度先增大后减小;② 当BAI异常值阈值2.9×RMSE（Root Mean Square Error）时,该方法总体精度达到最高93.25%,MCD64A1产品总体精度为70.25%;③ 本文算法的漏判误差和误判误差相对平衡,而MCD64A1产品的漏判误差远大于误判误差。研究表明,相比MODIS火烧迹地产品数据,Landsat时间序列火烧迹地法可更有效地检测农田火烧迹地。     

Mapping fire regimes in China using MODIS active fire and burned area data

Relatively little is known about vegetation fire regimes in China. In this study, we investigated fire regime characteristics and their potential drivers, utilizing information extracted from the MODerate resolution Imaging Spectrometer (MODIS) satellite. Twelve fire regime variables were selected and computed on a regular grid over all of China, using MODIS burned area and active fire data during the period 2001 to 2016, to identify fire incidence and its inter-annual variability, seasonality, intensity, fire size distribution and vegetation types affected by fire. The variables were normalized and clustered to define six fire regimes with distinctive fire attributes. Results show that 78.6% of the land in China was affected by fire during the study period. The barren or sparsely vegetated lands of western China are nearly fire-free. Active fires were observed in Central China, but area burned was not detectable from MODIS. Forest fires in northeastern China are relatively large, infrequent, with a short fire season that peaks in non-winter seasons and higher inter-annual variability, implying a high likelihood of accidental causes. In contrast, forest fires in southern China are relatively small, frequent, with a long fire season that peaks in non-summer seasons, and lower inter-annual variability, suggesting regular use as a land management tool. Low inter-annual variability and low fire intensity were associated with cropland fires, whereas grassland fires generally exhibit the opposite traits. We have also discussed the potential drivers of each fire regime characteristics.     

Changing climate affects vegetation growth in the arid region of the northwestern China

The northwestern China is a typical dry-land region of Inner Asia, where significant climate change has been observed over the past several decades. How the regional vegetation, particularly the grassland-oasis-desert complex, responds to such climatic change is poorly understood. To address this question, we investigated spatio-temporal changes in vegetation growth and their responses to a changing climate by biome and bioregion, using satellite-sensed Normalized Difference Vegetation Index (NDVI) data from 1982 to 2003, along with corresponding climate data. Over the past 22 years, about 30% of the total vegetated area showed an annual increase of 0.7% in growing season NDVI. This trend occurred in all biomes and all bioregions except Sawuer, a subregion of the study area with no significant climate change. Further analyses indicated that NDVI change was highly correlated with the current precipitation and evapotranspiration in growing season but was not associated with temperature. We also found that NDVI was positively correlated with the preceding winter precipitation. These findings suggest that precipitation may be the key cause of vegetation growth in this area, even for mountain forests and grasslands, whose growth are often regarded to be limited by low temperate in winter and early spring.     

新疆荒漠稀疏植被覆盖度信息遥感提取方法比较

植被覆盖度信息是荒漠生态环境表征的重要指标之一。荒漠区地表植被稀疏,在遥感光谱信息中表现较弱,通用的植被覆盖度遥感提取方法应用于干旱荒漠区存在一定的局限性,为了探寻一种满足大尺度荒漠地区的植被覆盖度信息的提取方法,必须对比和分析现有的遥感方法在干旱荒漠区的应用效果。以新疆荒漠区为例,利用MODIS遥感影像和野外植被覆盖度实测数据,对常用的6种遥感植被覆盖度提取方法（改进的三波段梯度差法、像元二分法、线型混合像元分解法、归一化植被指数法、增强型植被指数法和修正型土壤调整植被指数法）的结果进行精度验证和对比分析。结果表明：MODIS影像上较难提取纯荒漠植被像元,用农作物的像元值代替会降低像元二分法和线性混合像元分解模型的模拟精度;植被指数法对地面实测数据依赖性较大,模拟的精度差异很大,仅考虑红光和近红外的归一化植被指数法模拟精度最低,而综合考虑土壤和大气因素的增强型植被指数法的模拟结果精度最高;改进的三波段最大梯度差法虽然模拟精度稍次之（R²=0.74;RMSE=13.46）,但依据光谱的物理特性,能显著地反映南、北疆荒漠植被覆盖度的差异,是目前大尺度的荒漠区覆盖植被信息提取较为适宜的方法之一。     

大面积棉花长势的MODIS监测分析方法与实践

大面积棉花的生长状况监测比较复杂,目前还没有比较成熟的方法。以往遥感监测应用较多的是NOAA—AVHRR数据,监测精度和监测效果不高。本文利用新一代传感器MODIS数据,结合实测的地面农作物生长发育农学参数,系统地分析了石河子地区棉花播种到收获整个田间遥感归一化指数(NDVI)及其对应的叶而积指数(LAI)的变化规律,证明MODIS叶面积指数和实测LAI有很高的一致性,MODISIAI的变化状况与棉花长势变化基本一致,实现了较为精确的石河子地区大面积棉花长势的遥感动态监测。     

南澳岛退化草坡的植被恢复研究

在南澳岛建立次生草坡对照及草坡种植试验样地,观测群落植物多样性、土壤肥力及生物量变化,以探讨海岛退化草坡的植被恢复过程。结果显示,海岛迎风面上修建公路、风能发电场或开垦后的弃耕祼地在自然状况下很难恢复其植被,植物种类和数量甚至有所减少,植被覆盖度下降,需要进行人工植被恢复;在迎风面恶劣的环境下,次生草坡可能是一种偏途顶极,短时间内植物多样性变化不大。退化草坡的土壤肥力较低,开垦后若不及时恢复适当植被,情况会恶化。该岛草坡的生物量均较低,远低于该岛一般人工林或次生林的水平。海岛本身存在水分、土壤、生物条件等方面的脆弱性,在工程建设过程中应尽量避免对地形地貌和植被造成破坏,一旦破坏要尽快进行适生的人工植被恢复。     

基于MODIS数据估算晴空陆地光合有效辐射

陆-气圈层物质与能量交换的核心过程是植物的光合作用,而光合有效辐射则是影响光合作用过程的关键因子,在不同的陆地生态系统模型中,都是重要的输入参数。作者以MODIS卫星数据为基础,反演晴空下影响光合有效辐射的大气因子参数大气可降水量、气溶胶,根据辐射传输方程从大气顶层光合有效辐射反演高分辨率陆地光合有效辐射。算法采用查找表替换辐射传输模型,使其能够对大批量、像元级的数据进行处理。将该算法应用于对华北平原的部分区域进行反演,并使用中国生态网络禹城试验站的自动测量数据对结果进行检验,最大误差在10%以内。     

Improving the assessment of the natural fire hazard in nature reserves

The need to improve the assessment of the wildfire hazard in nature reserves is considered. It is suggested that the natural vegetation fuel map compiled by using a specially developed determinant of the types of main conductors of burning having regard to the period of a fire-hazardous season should be used for such purposes. The types of prime conductors of burning constitute the major group of vegetation fuels which determines the possibility of the spread of burning across the territory covered by vegetation. A classification of this group was carried out on the basis of long-term pyrological investigations in different regions of the RF. The vegetation fuel maps are presented for the Stolby nature reserve, separately for the spring (autumn) and summer seasons, because the southern-taiga forests are characterized by a predominance of the grass forest types with the involvement of gramineous species. The map of the current wildfire hazard is compiled and presented as an example, on the basis of the vegetation fuel map for the spring (autumn) periods of the season for drought class II according to the weather conditions. This map is representative of the possibility or impossibility of the spread of burning for each area in the nature reserve in the event that the source of fire (of anthropogenic or natural origins) appears. It is shown that vegetation fuel map can be compiled for any nature reserve by using the determinant of the types of prime conductors of burning.     

藏东南三江并流核心区植被时空动态变化及其气候驱动力分析

植被生长状况及其分布对气候等影响因子的响应是当前生态学研究的热点之一。基于2000—2016年MODIS NDVI数据和气象数据,用Sen+Mann-Kendall等方法分析了藏东南三江并流核心区植被的时空变化及其与气候因子的关系。研究结果表明：① 该区植被覆盖整体趋于稳定,呈缓慢增加趋势,不同植被类型覆盖空间异质性明显。② 植被变化趋势结果显示植被覆盖变化以稳定不变和改善趋势为主,区域总体呈稳中向好态势。③ 相关分析表明植被NDVI增加主要与气候暖化有关,与降水量相关性较小。此外,人类活动对植被影响的双重性表现为：大多地区植被改善受生态工程和围栏禁牧政策影响,局部地区植被退化则与城镇化进程加快有关。研究结果揭示气温是影响植被格局的主要气候因子,了解影响植被变化及其驱动因素的空间变异性可为山地植被生态环境保护建设提供一定的科学依据。     

青海湖流域草地产草量与MODIS植被指数的相关性分析

借鉴国内外基于遥感手段监测植被的方法,利用MODIS-NDVI遥感影像数据,探讨如何对草地变化进行监测。提取青海湖流域典型草原遥感影像植被指数,并与野外调查获得的79个样方生物量数据进行对比分析,建立了多个回归模型用于研究植被指数与草地产草量的相关关系。结果表明,植被指数与草地产草量之间存在较好的相关性,但是不同的回归模型与草地产草量相关性程度存在一定的差别,非线性回归模型优于一元线性回归模型,该方法的提出有助于监测青海湖流域草地变化情况。     

A STATISTICAL RELATIONSHIP BETWEEN EL NIÑO-SOUTHERN OSCILLATION AND FLORIDA WILDFIRE OCCURRENCE

Wildfires have long been an important environmental concern in Florida. Recent wildfires along the urban-rural interface of large cities in Florida have pointed to the need for an increased understanding of the physical and biological mechanisms that govern wildfire occurrence. Increased awareness of the relationships between global climate changes occurring in the tropics and their teleconnections outside the tropics dictate a reevaluation of the role of phenomena such as El Niño-Southern Oscillation on the risk of wildfire. One simple way of illustrating the relationship between ENSO and wildfire occurrence is the use of an Analysis of Variance (ANOVA) on wildfire data that has been categorized according to ENSO status (El Niño, La Niña, and neutral years). This research shows that a statistically significant relationship exists between ENSO conditions and annual wildfire occurrence in Florida when ENSO conditions are treated as a potential precursor to wildfire conditions. In particular, a statistically significant relationship exists between both acreage burned and average fire size, when the data are separated into El Niño and La Niña categories according to the previous year's ENSO status. This supports the idea that the climate from previous years has a measurable effect upon fire statistics in the years following the climate measurements, and that it may be possible to create a regional fire prediction model that incorporates ENSO information. [Key words: wildfire, natural hazards, ANOVA, Florida, ENSO.]     

利用MODIS/EVI数据分析干旱对西南地区植被的影响(英文)

2009年9月至2010年3月我国西南地区出现了有气象记录以来最严重的干旱,给当地的自然环境和生产、生活带来严重影响。本文利用多年MODIS/EVI数据求取距平植被指数来反映干旱对西南地区植被的影响。在此基础上,分析了西南地区植被受旱的时空格局及其可能影响因素。结果表明,我国西南地区植被受干旱影响的范围很大,超过地区总面积的50%,植被受旱程度时空差异显著。这种显著的差异除了受降水等气象因素影响外,还与不同植被类型对干旱的响应差异有很大关系。在西南地区三种主要的植被类型中,作物是最易受干旱影响的植被类型,草地次之,林地的抗旱能力最强。此外,植被干旱的空间分布与气象干旱也存在很大的差异,进一步证明了降水以外的其他因素对干旱程度的调节作用。研究证明与气象干旱指数相比,植被指数更能反映干旱的实际情况。但在使用植被指数衡量干旱影响时也要考虑到植被指数本身的局限性。     

Monitoring deforestation with MODIS Active Fires in Neotropical dry forests: An analysis of local-scale assessments in Mexico,Brazil and Bolivia

The detection of vegetation fires using remote sensing has proven useful for highlighting areas undergoing rapid conversion in humid forests, but not in tropical dry forest (TDF). To further understand this relationship, we explored the correlation between MODIS Active Fires and forest cover change at local scales using 3 × 3 km sampling grids in three TDF landscapes in Bolivia; Mexico, and Brazil. Our analysis showed no single overall correlation among sites between the frequency of fires reported by the MODIS Active Fire Mapping product and forest cover change. Also, aggregated patterns of fire occurrence in Brazil and Bolivia did not correspond to areas with high percentage of forest loss, which indicates that the fire/deforestation relationship in TDF is not apparent in a simple fire frequency map. However, statistically significant correlations were found in sampling boxes with 50–60%, 50–70%, 50–95% forest cover at “initial state” of the time series in the Mexican site, Bolivian site and Brazilian site, respectively. Our findings suggest that complex interactions between anthropogenic fire-use, satellite-detected fires, and deforestation in highly fragmented TDF landscapes are difficult to describe at regional scales and might only be possible to analyze using finer resolution sampling grids.     

Estimation of Daily Vapor Pressure Deficit Using MODIS Potential Evapotranspiration on the Tibetan Plateau

Vapor pressure deficit (VPD) is an important parameter in modelling hydrologic cycles and vegetation productivity. Meteorological stations are scarce in remote areas, which often results in imprecise estimations of VPD on the Tibetan Plateau. Moderate Resolution Imaging Spectroradiometer (MODIS) provides evapotranspiration data, which may offer the possibility of scaling up VPD estimations on the Tibetan Plateau. However, no studies thus far have estimated VPD using MODIS evapotranspiration data on the Tibetan Plateau. Therefore, this study used MODIS potential evapotranspiration (PET) to estimate VPD in alpine meadows, alpine steppes, croplands, forests and shrublands for the year, spring, summer, autumn and winter in 2000-2012. A series of root-mean- squared-error (RMSE) and mean-absolute-error (MAE) values were obtained for correlating measured VPD and estimated VPD using MODIS PET data for each listed time period and vegetation type: whole year (0.98-2.15 hPa and 0.68-1.44 hPa), spring (0.95-2.34 hPa and 0.72-1.54 hPa), summer (1.39-2.60 hPa and 0.89-1.96 hPa), autumn (0.78-1.93 hPa and 0.56-1.36 hPa), winter (0.48-1.40 hPa and 0.36-0.98 hPa), alpine steppes (0.48- 1.39 hPa and 0.36-1.00 hPa), alpine meadows (0.58-1.39 hPa and 0.44-0.90 hPa), croplands (1.10-2.55 hPa and 0.82-1.74 hPa), shrublands (0.98-1.90 hPa and 0.78-1.37 hPa), and forests (1.40-2.60 hPa and 0.98-1.96 hPa), respectively. Therefore, MODIS PET may be used to estimate VPD, and better results may be obtained if future studies incorporate vegetation types and seasons when the VPD data are estimated using MODIS PET on the Tibetan Plateau.