MODIS干旱指数对华北干旱的敏感性分析

针对近年来干旱发生频繁的华北地区,通过利用2000-2009年MODIS数据和气象观测站降水资料,建立草地和农田距平植被指数(AVI)与不同时间尺度标准化降水指数(SPI)之间的相关统计模型,比较AVI和距平水分指数(AWI)对干旱响应的敏感性。结果表明：(1)植被生长季AVI与不同时间尺度SPI的相关关系不同。草地AVI与1个月尺度的SPI(即1-SPI)相关系数较低,而与3-SPI相关最显著;而农田区AVI与SPI的相关性较低,总体上农田AVI与3-SPI的相关性较高;(2) AWI与AVI类似,也对SPI存在时滞响应,均与3-SPI有着极显著的相关关系,并且在干旱发生较严重的6~8月份AWI与3-SPI的相关性好于AVI与3-SPI的相关性;(3)运用AWI反演的华北地区2009年夏季干旱分布图较好地反映了旱情的时空分布,与相关气象资料结果相符合。     

黄土高原气象干旱和农业干旱特征及其相互关系研究

选择标准化降水指数（SPI）和植被状态指数（VCI）分别作为评价黄土高原气象干旱和农业干旱的指标,使用干旱频率和Sen斜率分析了黄土高原地区干旱的分布特征与变化趋势,并探讨了气象干旱与农业干旱的相关性。结果表明：① 黄土高原西部干旱频率总体上高于东部。气象干旱和农业干旱变化趋势在空间上表现有所不同,黄土高原西部、北部气象干旱呈不显著减缓趋势,东部和南部呈不显著加重趋势,但绝大部分地区的农业干旱呈减缓趋势,尤其是400 mm等降水量一线两侧区域。② 季节上,黄土高原夏季和秋季气象干旱频率较高,春季和冬季气象干旱频率相对较低。黄土高原农业干旱频率春季最高,夏季其次,VCI对农业干旱实时监测的适用性更强。③ 不同季节,农业干旱滞后气象干旱的时间长短不同,冬季滞后约2个月,春季滞后约1个月,夏季和秋季滞后少于1个月。黄土高原一熟制种植区的SPI-12值与VCI值具有较好的正相关性。研究结果可以为黄土高原的干旱监测和预警、干旱区划以及干旱灾害风险评估提供科学依据。     

A SIMPLE SOIL MOISTURE INDEX TO FORECAST CROP YIELDS

Neutron probe soil moisture measurements obtained biweekly during the growing season between 1982 and 1991 from multiple depths under grass-covered plots at 17 Illinois Climate Network sites are used to forecast crop yields. A Soil Moisture Index (SMIX) that combines the effect of intensity, duration, and timing of drought or excessively wet conditions was computed by integrating the quantity of available soil moisture throughout the rooting zone over the growing season. Relationships between the SMIX values and crop yields are evaluated at county, regional, and statewide scales. Coefficients of determination (r ²) for relationships between the SMIX values and maize, soybeans, and hay yields at the statewide level are 0.88, 0.74, and 0.81, respectively, when the period of integration is terminated at the end of the growing season. This new soil index can be employed to forecast yields as early as 12 weeks before harvest for the state of Illinois. However, predictions with RMSE ≤ 10% of the mean yield can be achieved only for SMIX integration periods ending 5, 9, and 6 weeks before harvest for maize, soybeans, and hay, respectively. Nomograms are presented for using the relationships between the SMIX values and crop yields to forecast Illinois's major crops well before harvest.     

Application of Multi-Temporal MODIS NDVI Data to Assess Practiced Maize Calendars in Rwanda

Crop calendar is an important tool providing relevant information on crops cycles in a specific area for effective agricultural management. Crop calendars vary in different areas given dissimilarities in agro-ecosystems’ characteristics. This research used multi-temporal MODIS NDVI stratification to assess differences in practiced maize crop calendars in various areas of Rwanda. Four (4) sample NDVI strata dominated by agriculture were purposively chosen, and 433 local farmers were randomly selected from the strata for interviews. The collected information helped to know about their maize planting as well as harvesting dates in order to generate maize calendars per NDVI strata. The generated crop calendars were later classified using k-means unsupervised classification, and produced 4 groupings of practiced maize calendars irrespective of NDVI strata. ANOVA results revealed significant differences between both the generated maize crop calendars by NDVI strata and the practiced crop calendars irrespective of NDVI strata, at p = 0.05. Moreover, chi-square tests and t-tests revealed not only a significant relationship between maize calendars and number of crop growing seasons, but also a significant relationship between maize calendars and NDVI strata, at p = 0.05. Finally, findings of this research contrasted the present conviction that there exist a single general maize calendar all over the country. Instead, the results were in accordance with the fact that Rwanda agro-ecosystems differ from East to West in terms of, mainly, altitude and rainfall patterns variations.     

广东省干旱趋势变化和空间分布特征

利用广东省86个地面站的降水和气温资料,定义广东省月干湿气候指数。定义的干湿气候指数可以明显地区分广东省干湿季,而且对春季粤南偏旱、秋季粤北偏旱也有反映,体现指数定义的合理性。趋势分析表明:全省2~3月、7~8月和12月明显变湿,而10~11月显著变干,其余月份趋势不明显。趋势分析结果指出,广东省未来的秋季旱情可能有加重的趋势,而冬春季旱情会有所缓解。各月趋势的空间分布有很大差异,分析结果指出,其年际变率的主要影响因子可能为海-气相互作用过程和陆-气相互作用过程。     

Linear regression relationships between NDVI, vegetation and rainfall in Etosha National Park, Namibia

Estimations of 10-day interval green vegetation cover and biomass, 10-day interval cumulative rainfall, as well as annual rainfall are compared with 10-day interval and rainy season NDVI and MVC using linear regression analysis. Raw data were smoothed by averaging and removing dry season outliers. Results indicate that the ability of NDVI and MVC to predict green vegetation cover, cumulative rainfall and annual rainfall is poorer for raw data than for averaged, outlier-removed data. It is recommended that the standard error of the raw data predictions are used to indicate the fundamental error in these relationships, and that the equations of the averaged, outlier-removed data are used to indicate the fundamental strength of NDVI or MVC in predicting vegetation or rainfall. The practical use of integrated rainy season MVC images are discussed.     

基于MODIS和TRMM数据的黄土高原农业干旱监测

农业干旱对农业生产影响最为严重,基于站点观测数据的干旱指数不能准确监测区域尺度的农业干旱特征。因此,利用2003—2015年MODIS地表温度(LST)、植被指数(NDVI)和TRMM降水(3B43)数据以及1960—2015年黄土高原地区及周边92个气象站点的月均温和月降水量数据,构建了综合遥感干旱监测模型规模干旱条件指数(Scale Drought Condition Index,SDCI),对黄土高原地区农用地生长季(4～10月)旱情的时空分布特征进行研究,结果表明:黄土高原地区农用地生长季多年平均干旱状态为中度干旱,干旱程度在空间上表现为西北部较严重,东南部较轻。2003—2015年黄土高原地区旱情年际变化总体呈波动减轻趋势,2003—2007年旱情越来越严重,2007—2014年旱情波动减轻,2014—2015年旱情有所加重。黄土高原地区旱情年内变化表现4～8月持续减轻,8～10月持续加重,干旱程度具体表现为4月、5月、6月和10月呈中度干旱,7月、8月和9月呈轻度干旱。研究表明利用多源遥感数据构建的具有适当权重的SDCI可以有效监测黄土高原地区作物生长季的干旱状况。     

Mesoscale Satellite Bioclimatology

This paper examines the strength of relationships between the Normalized Difference Vegetation Index (NDVI) and climatic data, when examined at the mesoscale. Mean monthly AVHRR NDVI data for 1988-1996 for the months of April through October for State of Kansas, its nine climatic divisions (CDs), and dominant land cover types within each CD were used. Corresponding climatic and water budget data were obtained or derived from National Climatic Data Center data. Temperature, precipitation, and NDVI deviations from normal were determined. Statistical analysis revealed significant relationships between NDVI and climatic variables, although strengths of the associations were modest. The highest correlation coefficient (r) for the state as a whole was 0.53, between NDVI and estimated actual evapotranspiration. When examined by climatic division or major land cover type, relationships between NDVI and a drought index were statistically significant in most cases and ranged from 0.30 to 0.56.     

中国干旱灾害评估与空间特征分析(英文)

Based on the monthly precipitation data for the period 1960-2008 from 616 rainfall stations and the phenology data of main grain crops,the spatial characteristics of drought hazard in China were investigated at a 10 km×10 km grid-cell scale using a GIS-based drought hazard assessment model,which was constructed by using 3-month Standard Pre-cipitation Index (SPI).Drought-prone areas and heavy drought centers were also identified in this study.The spatial distribution of drought hazard in China shows apparent east-west dif-ference,with the eastern part of China being far more hazardous than the western part.High hazard areas are common in the eastern and central parts of Inner Mongolian Plateau,the central part of Northeast China Plain,the northern part of Heilongjiang,the southeastern part of Qinghai-Tibet Plateau,the central and southern parts of Loess Plateau,the southern part of North China Plain,the northern and southern parts of Yangtze River Plain,and Yun-nan-Guizhou Plateau.Furthermore,obvious differences in drought hazard were found both within and between different agricultural zonings.     

Visualizing and quantifying the movement of vegetative drought using remote-sensing data and GIS

Remote-sensing-based drought monitoring methods provide fast and useful information for a sustainable management strategy of drought impact over a region. Common pixel-based monitoring methods are limited in the analysis of the dynamics of this impact at regional scale. For instance, these hardly allow us to quantify the movement of drought in space and time and to compare drought with rainfall deficits without losing the variability of these events within a region. This study proposed an object-based approach that allowed us to visualize and quantify the spatio-temporal movement of drought impact on vegetation, called vegetative drought, in a region. The GIS software Dynomap was used to extract and track objects. Measures of distance and angle were used for determining the speed and direction of vegetative drought and rainfall deficit objects, calculated from the National Oceanic and Atmospheric Administration's (NOAA's) normalized difference vegetation index and rainfall estimates data. The methods were applied to the two rainy seasons during the drought year 1999 in East Africa. Results showed that vegetative drought objects moved into the southwestern direction at an average angle of??138.5° during the first season and??144.5° during the second season. The speed of objects varied between 38 km dekad^?1 and 185 km dekad^?1 during the first season and between 33 km dekad^?1 and 144 km dekad^?1 during the second season, reflecting the rate of spread between dekads. Vegetative drought objects close to rainfall deficit objects showed similar trajectories and sometimes regions overlapped. This indicated that the two events are related. We conclude that a spatiotemporal relationship existed between the two types of events and that this could be quantified.     

30年来呼伦贝尔地区草地植被对气候变化的响应(英文)

Global warming has led to significant vegetation changes especially in the past 20 years. Hulun Buir Grassland in Inner Mongolia, one of the world’s three prairies, is undergoing a process of prominent warming and drying. It is essential to investigate the effects of climatic change (temperature and precipitation) on vegetation dynamics for a better understanding of climatic change. NDVI (Normalized Difference Vegetation Index), reflecting characteristics of plant growth, vegetation coverage and biomass, is used as an indicator to monitor vegetation changes. GIMMS NDVI from 1981 to 2006 and MODIS NDVI from 2000 to 2009 were adopted and integrated in this study to extract the time series characteristics of vegetation changes in Hulun Buir Grassland. The responses of vegetation coverage to climatic change on the yearly, seasonal and monthly scales were analyzed combined with temperature and precipitation data of seven meteorological sites. In the past 30 years, vegetation coverage was more correlated with climatic factors, and the correlations were dependent on the time scales. On an inter-annual scale, vegetation change was better correlated with precipitation, suggesting that rainfall was the main factor for driving vegetation changes. On a seasonal-interannual scale, correlations between vegetation coverage change and climatic factors showed that the sensitivity of vegetation growth to the aqueous and thermal condition changes was different in different seasons. The sensitivity of vegetation growth to temperature in summers was higher than in the other seasons, while its sensitivity to rainfall in both summers and autumns was higher, especially in summers. On a monthly-interannual scale, correlations between vegetation coverage change and climatic factors during growth seasons showed that the response of vegetation changes to temperature in both April and May was stronger. This indicates that the temperature effect occurs in the early stage of vegetation growth. Correlations between vegetation growth and precipitation of the month before the current month, were better from May to August, showing a hysteresis response of vegetation growth to rainfall. Grasses get green and begin to grow in April, and the impacts of temperature on grass growth are obvious. The increase of NDVI in April may be due to climatic warming that leads to an advanced growth season. In summary, relationships between monthly-interannual variations of vegetation coverage and climatic factors represent the temporal rhythm controls of temperature and precipitation on grass growth largely.     

Relationships between Normalized Difference Vegetation Index (NDVI) and carbon fluxes of biologic soil crusts assessed by ground measurements

The aim of this research was to study the relationships between the biological soil crusts (BSC), spectral reflectance and photosynthetic activity. Twenty field campaigns, each lasting several days, were conducted during the 2002–2003 rainy season at sand dune and loess environments in the north-western Negev desert of Israel. Simultaneous measurements of CO₂ net exchange and spectral reflectance were carried out for several types of BSC. The Normalized Difference Vegetation Index (NDVI) was derived from the BSC reflectance and correlated with their CO₂ exchange data. The relationship between NDVI and CO₂ exchange is discussed in detail with respect to environmental factors, such as soil water content, air temperature, and light intensity. Fairly good correlations were found in the rainy season. The NDVI was useful in indicating the potential magnitude and capacity of the BSC assimilation activity. Furthermore, the index corresponded well with different rates of photosynthetic activity of the different types of microphytes. The results demonstrate that spectral reflectances of the BSC can be related to photosynthetic activities and posseses the potential to assess the amount of carbon sequestration by these microphytes on an areal scale using satellite images.     

30年来呼伦贝尔地区草地植被对气候变化的响应(英文)

Global warming has led to significant vegetation changes especially in the past 20 years. Hulun Buir Grassland in Inner Mongolia, one of the world’s three prairies, is undergoing a process of prominent warming and drying. It is essential to investigate the effects of climatic change (temperature and precipitation) on vegetation dynamics for a better understanding of climatic change. NDVI (Normalized Difference Vegetation Index), reflecting characteristics of plant growth, vegetation coverage and biomass, is...     

近30 年来呼伦贝尔地区草地植被变化对气候变化的响应

基于1981-2006 年的GIMMS NDVI数据和2000-2009 年的MODIS NDVI数据反演呼伦贝尔地区草地变化,结合1981-2009 年该地区7 个气象站点的气温和降水数据,分别从年际变化、季节变化和月变化角度分析该地区草地变化对气候变化的响应。结果表明,从年际变化来看,降水是驱动草地植被年际变化的主要因素;从季节变化来看,草地植被生长在不同季节对水热条件变化的敏感性不同,春季草地植被生长对气温变化的敏感性较降水变化高,夏季和秋季草地植被的生长对降水变化的敏感性则高于对气温变化的敏感性,其中以夏季最为显著;从月变化来看,4 月和5 月草地植被变化受气温变化影响较明显;5-8 月与前一月降水变化关系密切,说明植被生长对降水变化具有一定的滞后性;4 月正值草本植物萌芽期,而4 月份草地生长与年气温变化关系最为密切,一定程度上说明4 月份表征植被生长的NDVI值增加可能是由于气候变暖引起的草地植被生长季提前产生的。综上所述,通过植被与气候要素月变化的关系可以具体地揭示气温和降水对草地植被生长的季节韵律控制。     

基于VSWI和SPI的2000—2016年河南省干旱特征研究

干旱是一种常见且严重的自然灾害,极大地影响着我国的农业生产。以河南省为例,利用MODIS产品植被指数和地表温度数据,构建表征区域干旱特征的植被供水指数（VSWI_N、VSWI_E）,并与河南省16个国家级气象站点数据计算的2000-2016年不同时间尺度的标准化降水指数（SPI）进行对比分析。结果表明：VSWI_E比VSWI_N更适用于河南省干旱的研究;3个月和12个月尺度的SPI值与VSWI的相关性较高;从时间上看,河南省发生干旱频率较高,春旱和夏旱发生频率分别为0.33和0.30,总体干旱趋势更加明显,其中春旱最严重的是2000年,夏旱最严重的是2014年;从空间上来看,豫北和豫西地区比豫南干旱程度严重。     

Mesoscale Satellite Bioclimatology

This paper examines the strength of relationships between the Normalized Difference Vegetation Index (NDVI) and climatic data, when examined at the mesoscale. Mean monthly AVHRR NDVI data for 1988‐1996 for the months of April through October for State of Kansas, its nine climatic divisions (CDs), and dominant land cover types within each CD were used. Corresponding climatic and water budget data were obtained or derived from National Climatic Data Center data. Temperature, precipitation, and NDVI deviations from normal were determined. Statistical analysis revealed significant relationships between NDVI and climatic variables, although strengths of the associations were modest. The highest correlation coefficient (r) for the state as a whole was 0.53, between NDVI and estimated actual evapotranspiration. When examined by climatic division or major land cover type, relationships between NDVI and a drought index were statistically significant in most cases and ranged from 0.30 to 0.56.     

Trends and Spatial Patterns of Drought Incidence in the Omo‐Ghibe River Basin,Ethiopia

The objective of this paper is to evaluate trends and spatial patterns of drought incidence across the Omo‐Ghibe River Basin using monthly rainfall data from eight stations for the period 1972–2007. It also aims to estimate the probability of drought episodes for a 100‐year period. Drought indices were generated using the Standard Precipitation Index (SPI) computed at 3‐, 6‐, 12‐ and 24‐month time‐steps for three intensity classes: moderate, severe and extreme drought events. The Mann–Kendall's trend test and Sen's slope estimator were employed to detect temporal changes. The results show complex spatial patterns on the frequency and magnitude of drought events across the study area for all timescales and intensity classes. However, the total number of drought events for the three intensity classes for all timescales were larger in the southern lowlands, where there exists a serious water scarcity for the rain‐fed pastoral system, than in the northeastern part (around Wolaita Sodo area). In contrast to this, the longest and most extreme (SPI < ?4.0) drought events for all timescales were observed at Wolaita Sodo station. In a 100‐year period one could expect 57–69 drought events with 3 months' duration, 19–34 events with 6 months' duration, 9–16 events with 12 months' duration and 5–9 events with 24 months' duration. The SPI values show negative rainfall anomalies in the 1980s while positive anomalies have occurred in the 1990s and 2000s, which implies tendency towards decreasing drought events. The Mann–Kendall's trend test for the 12‐ and 24‐month timescales and for seasonal events also confirms this general trend.     

The relationship between NDVI and precipitation on the Tibetan Plateau

The temporal and spatial changes of NDVI on the Tibetan Plateau, as well as the relationship between NDVI and precipitation, were discussed in this paper, by using 8-km resolution multi-temporal NOAA AVHRR-NDVI data from 1982 to 1999. Monthly maximum NDVI and monthly rainfall were used to analyze the seasonal changes, and annual maximum NDVI, annual effective precipitation and growing season precipitation (from April to August) were used to discuss the interannual changes. The dynamic change of NDVI and the corre-lation coefficients between NDVI and rainfall were computed for each pixel. The results are as follows: (1) The NDVI reached the peak in growing season (from July to September) on the Tibetan Plateau. In the northern and western parts of the plateau, the growing season was very short (about two or three months); but in the southern, vegetation grew almost all the year round. The correlation of monthly maximum NDVI and monthly rainfall varied in different areas. It was weak in the western, northern and southern parts, but strong in the central and eastern parts. (2) The spatial distribution of NDVI interannual dynamic change was different too. The increase areas were mainly distributed in southern Tibet montane shrub-steppe zone, western part of western Sichuan-eastern Tibet montane coniferous forest zone, western part of northern slopes of Kunlun montane desert zone and southeastern part of southern slopes of Himalaya montane evergreen broad-leaved forest zone; the decrease areas were mainly distributed in the Qaidam montane desert zone, the western and northern parts of eastern Qinghai-Qilian montane steppe zone, southern Qinghai high cold meadow steppe zone and Ngari montane desert-steppe and desert zone. The spatial distribution of correlation coeffi-cient between annual effective rainfall and annual maximum NDVI was similar to the growing season rainfall and annual maximum NDVI, and there was good relationship between NDVI and rainfall in the meadow and grassland with medium vegetation cover, and the effect of rainfall on vegetation was small in the forest and desert area.     

青藏高原植被覆盖变化与降水关系

The temporal and spatial changes of NDVI on the Tibetan Plateau, as well as the relationship between NDVI and precipitation, were discussed in this paper, by using 8-km resolution multi-temporal NOAA AVHRR-NDVI data from 1982 to 1999. Monthly maximum NDVI and monthly rainfall were used to analyze the seasonal changes, and annual maximum NDVI, annual effective precipitation and growing season precipitation (from April to August) were used to discuss the interannual changes. The dynamic change of NDVI and the corre- lation coefficients between NDVI and rainfall were computed for each pixel. The results are as follows: (1) The NDVI reached the peak in growing season (from July to September) on the Tibetan Plateau. In the northern and western parts of the plateau, the growing season was very short (about two or three months); but in the southern, vegetation grew almost all the year round. The correlation of monthly maximum NDVI and monthly rainfall varied in different areas. It was weak in the western, northern and southern parts, but strong in the central and eastern parts. (2) The spatial distribution of NDVI interannual dynamic change was different too. The increase areas were mainly distributed in southern Tibet montane shrub-steppe zone, western part of western Sichuan-eastern Tibet montane coniferous forest zone, western part of northern slopes of Kunlun montane desert zone and southeastern part of southern slopes of Himalaya montane evergreen broad-leaved forest zone; the decrease areas were mainly distributed in the Qaidam montane desert zone, the western and northern parts of eastern Qinghai-Qilian montane steppe zone, southern Qinghai high cold meadow steppe zone and Ngari montane desert-steppe and desert zone. The spatial distribution of correlation coeffi- cient between annual effective rainfall and annual maximum NDVI was similar to the growing season rainfall and annual maximum NDVI, and there was good relationship between NDVI and rainfall in the meadow and grassland with medium vegetation cover, and the effect of rainfall on vegetation was small in the forest and desert area.     

基于时间序列遥感数据的嵯岗国家沙化土地封禁保护成效评估

2013年中国启动实施了内蒙古自治区新巴尔虎左旗嵯岗国家沙化土地封禁保护区试点。本研究利用2001-2017年生长季NDVI数据分析了嵯岗封禁保护区及周边区域植被长势时空演变特征,分析了多年的生长季降水量和历年旱情,之后利用植被降水利用效率和NDVI残差趋势分析对保护成效进行了评估。结果表明:(1)封禁项目实施之前,封禁区内外植被长势变化趋势基本一致,而在项目实施后的2016、2017年,封禁区内NDVI距平明显高于封禁区外;(2)降水为影响该区域植被长势的主导气候因素,在封禁实施后的2015-2017年该区域连续3 a干旱,极大地限制了区域植被生长;(3)封禁区内植被降水利用效率和NDVI残差均呈现明显的增加趋势,而封禁区外变化不明显,说明封禁提升了植被的自我修复能力;(4)嵯岗封禁保护区由3个地块组成,其中嵯岗林场封禁效果比牧场八队和牧场十一队明显。国家沙化土地封禁保护措施有效促进了植被自我修复,提高了沙漠生态系统应对气候变化的能力。