Monitoring ecosystem dynamics in northwestern Ethiopia using NDVI and climate variables to assess long term trends in dryland vegetation variability

Dryland ecosystems are highly vulnerable to environmental changes. Monitoring is vital in order to evaluate their response to fluctuating rainfall and temperature patterns for long-term ecosystem safeguarding. Monitoring of long term changes of normalized difference vegetation index (NDVI) and climate variables are fundamental for better understanding of change trajectories in dryland ecosystem, and to ascertain their potential interaction with anthropogenic drivers. In this study, we identify determinant factors of dryland changes by using MODIS NDVI, precipitation and temperature data for Breaks for Additive Seasonal and Trend (BFAST) and Mann Kendall test statistic. BFAST predicts iteratively time and number of changes within a time series data to depict the size and direction of changes. Analysis of NDVI, precipitation and temperature time series data showed substantial changes during the study period of 2000–2014. There is a reduction trend in vegetation showed by the decline in NDVI, with significant breakpoints till 2009 and recovery afterwards, without a significant change in annual trends of precipitation (α < 0.05) for the same study period. Furthermore 2 positive climate trends were founded: a) a significant positive trend on long term annual rainfall during the main rainy seasons and; 2) a significant (α < 0.05) annual increment of the long term mean minimum and mean maximum temperature of 0.03 °C/year and 0.04 °C/year, respectively. This assessment showed that climate variables cannot be considered as the main factors in explaining the observed patterns of vegetation dynamics. Seasonal and interannual precipitation changes have a lower weight as driving factors for the reduction in vegetation trends. Hence, the decline in vegetation productivity of the region can be attributed to the increasing pressure of human activities.     

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.     

青海高寒草甸退化演替中的植被指数

随着气候变化和人为活动干扰,高寒草甸退化已成为青藏高原严重的生态环境问题,精准识别其退化程度并制定相应恢复策略,对实现高寒草甸可持续发展具有重要意义。目前,低空间分辨率MODIS数据为草地遥感监测的主要数据源,但难以满足景观破碎度或异质性较强地区的应用。本研究基于野外调查资料,利用多源遥感数据（MODIS、Landsat、Sentinel-2）研究不同空间分辨率归一化植被指数（NDVI）对高寒草甸退化演替的响应,为准确评估青藏高原高寒草甸退化程度提供依据。结果表明：（1）随着高寒草甸退化,植被群落优势种演化趋势为禾草—矮嵩草—小嵩草—杂草群落;植被高度和生物量先快速下降,然后缓慢下降或趋于稳定,植被覆盖度和NDVI的变化呈相反特征。（2）随着湿地草甸旱化,植被群落优势种从藏嵩草演变为矮嵩草或小嵩草,湿地旱化初期植被高度、生物量和覆盖度平均值略低于原生湿地,NDVI略大于原生湿地,差异不显著。（3）植被高度、覆盖度和生物量与Sentinel-2或Landsat的NDVI相关性均优于MODIS,说明Sentinel-2和Landsat的NDVI对高寒草甸退化演替过程更加敏感,采用该数据能更准确评估高寒草甸退化程度。     

Monitoring degradation in arid and semi-arid forests and woodlands: The case of the argan woodlands (Morocco)

Arid and semi-arid forests and woodlands (hereafter called «dryland forests»), in spite of their ecological and social importance, have received little attention in land change studies. Growing evidence shows that these forests have been receding at very high rates in many places, suggesting a need for a better understanding of the processes and causes of dryland forest degradation. Changes in the extent of dryland forests are debated in part because estimates of forest and woodland areas in drylands are uncertain. Causal explanations of the degradation tend to draw on the literature on desertification and tropical deforestation, and to emphasize either local or remote, and either social or biophysical drivers. This study contributes to a better understanding of dryland forest degradation as a basis for conservation policies. Firstly, we argue that monitoring arid and semi-arid forests and woodlands using area estimates may lead to an underestimation of the severity of change because tree density change often exceeds area change. Secondly, we argue that the analysis of degradation processes in these multifunctional landscapes should integrate both local and remote, and both social and biophysical factors. We use a case study of degradation in the argania woodlands in semi-arid to arid Southwest Morocco to test these two claims. We used gridded tree counts on aerial photographs and satellite images to estimate forest change between 1970 and 2007, and we tested several possible causes of change on the basis of original socio-economic field surveys and climatic and topographic data. We found that forest density declined by 44.5% during this period, a figure that is significantly underestimated if forest area change is used as a measure of degradation. Increasing aridity and, to a lesser extent, fuelwood extraction were related to forest decline. No effect of grazing by local livestock was found.     

A Geo‐spatial study for analysing temporal responses of NDVI to rainfall

Climate change has become a serious concern worldwide owing to its multifaceted impact upon the physical as well as socio‐economic environment (IPCC, 2013). Vulnerability to climate change is much higher in the developing countries like India, where the economy is mainly agro‐based and productivity from the agricultural sector is dependent upon summer monsoon rainfall. Hence, assessing the quantitative relationship between vegetation patterns and climatic influence has become an increasingly important study conducted on regional and global scales. As vegetation cover plays a key role in conserving the natural environment, studying the spatio‐temporal trend of vegetation is crucial in identifying changes in the natural environment. We analysed the spatial responses of SPOT‐VGT NDVI to TRMM based rainfall during a sixteen year period (1998–2013) in the Bundelkhand region of Central India. The Normalized Difference Vegetation Index (NDVI) has proven to be a strong indicator of global vegetation productivity. Among climatic factors, rainfall robustly influences both spatial and temporal outline of NDVI. In this study, we used linear regression for analysing the statistical relationship among NDVI and rainfall and their trends. The study reveals a varying pattern of vegetation dynamics in response to rainfall over the area.     

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.     

亚洲内陆干旱区NDVI与树木生长的气候响应及其影响因素

基于亚洲内陆干旱区的树木年轮宽度指数（RWI）、归一化差异植被指数（NDVI）和气候数据,采用空间统计方法和相关分析法分析了NDVI和RWI变化的一致性,探讨了NDVI和RWI对气候的响应,揭示了影响NDVI和RWI气候响应的相关因素。结果表明：1982—2000年亚洲内陆干旱区的树木生长和NDVI均呈增加趋势,生长季NDVI与RWI大多具有同步性变化特征,大多数地区5、6月NDVI受同期气温的影响,而4、5月NDVI主要受同期降水的影响;RWI主要受6—7月气温和4、6月和7月降水或帕默尔干旱指数（PDSI）的影响;大部分地区的NDVI和RWI对气温的响应具有一致性,但它们对降水或PDSI的响应存在很大差异;海拔和水热条件对不同地区的NDVI和RWI的气候响应有较大的影响。本研究对于认识亚洲内陆干旱区植被与树木生长的气候响应及其影响因素具有一定的科学意义。     

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.     

黄河流域植被覆盖度动态变化与降水的关系

利用8km分辨率Pathfinder NOAA-NDVI数据，对黄河流域1982－1999年地表植被覆盖的空间分布及时间序列变化进行了分析，并通过计算不同时段降水量与年最大NDVI之间的相关系数分析了降水对流域植被覆盖的影响。结果发现近20年来黄河流域平均植被覆盖度有增加趋势，但青藏高原上有所减小；汛期降水量的多少对地表植被覆盖度的年际变化起主要作用，其中草原地区影响最显著，而在森林植被区及部分灌溉农作区，降水的年际变化对地表覆盖的影响比较小。     

气候变化和生态建设对秦岭—淮河南北植被动态的影响

论文基于2000-2019年秦岭—淮河南北MODIS-NDVI植被覆盖数据,对中国南北过渡带植被时空变化进行分析,并探讨植被动态变化驱动因素.结果 表明:①在趋势变化上,2000-2019年秦岭—淮河南北植被显著恢复.其中,秦巴山区植被恢复面积占比最高,其次是巫山山区和关中平原;植被退化区面积占比仅为6.4％,主要分布...     

Mapping land degradation by comparison of vegetation production to spatially derived estimates of potential production

There is an urgent need for quantitative methods by which actual, as opposed to potential degradation can be mapped using spatially consistent criteria for large regions. This study tested the Local NPP Scaling (LNS) method, where the growth season sum NDVI (∑NDVI), a surrogate for productivity, of each pixel was expressed relative to the highest values (90th percentile) of ∑NDVI observed in all pixels falling within the same land capability unit (LCU). The objective of this study was to determine if the LNS approach can be used to map degraded areas: (i) by determining if areas with low LNS values co-occur with degraded areas mapped with Landsat TM and (ii) testing the persistence of these areas over multiple years. Most of the areas with low LNS values did coincide with degraded areas, with the exception of four LCUs, which either contained steep precipitation gradients or landscape variability, which probably obscured the human impacts. The performance of the LNS method is therefore largely determined by the level of detail of the stratification data (e.g. LCUs) used. The conclusion is that the LNS method is a valuable tool for mapping land degradation at a regional scale.     

1981-2010年气候变化和人类活动对内蒙古地区植被动态影响的定量研究

基于GIMMS NDVI以及MODIS NDVI数据,分析内蒙古地区1981-2010年的植被变化趋势,并结合气候、社会经济数据,以旗县为单位定量分析气候变化和人类活动对植被变化的影响,结果表明：①1981-2010年间,内蒙古地区植被变化具有典型的空间异质性,其中植被显著增加区域主要集中在西南部的阿拉善盟、鄂尔多斯市以及东部通辽市等地区,显著减少区域主要集中在北部的锡林郭勒盟以及东北部的呼伦贝尔市的部分地区;②对于植被显著增加区域,人类活动作用的影响面积最大,其次为气候因素,气候与人类活动的耦合作用也对植被增加有一定显著影响;内蒙古西部降雨量的增加、围封禁牧政策的实施以及农作物播种面积的增加为驱动植被增加的主要因素;③对于植被显著减少区域,人类活动的作用略大于气候因素;内蒙古中东部地区降雨减少以及近10年来部分旗县风速的增加是导致植被显著减少的重要气候因素;虽然人工造林、农作物播种面积会增加局部植被盖度,但在县域尺度不足以抵消干旱对植被生长的不利影响,反而会导致区域植被退化。     

应用遥感数据研究中国植被生态系统与气候的关系

应用1982-1994年NOAA/AVHRR的归一化植被指数（NDVI）资料和587个气象台站的数据对我国不同类型植被生态系统和气候的关系进行研究，首先将我国的植被类型划分为21类，在此基础上分别研究了不同时间尺度下我国不同区域，不同植被类型和气候的关系。结果表明：在多年平均状态下，植被生态系统NDVI水平主要受水分条件的影响；年内变化上，温度对植被生态系统季相变化化起着比降水略大的作用，年降水量造成了植被季相响应的差异，在年际变化上，分别研究了4个季节和整个生长期尺度上的关系，一般情形为温度和降水对植被的年际波动起着大致相反的作用，不同植被类型在不同的生长时期（季节）对气候的变化响应方式也不同，发现在植被的生长期，我国南方和北方的植被生态系统对温度和降水的响应方式相反；同时存在2个植被-气候敏感区，分别为我国北方的典型草原到森林的过渡区和云南中部部分区域。     

The aboveground biomass of desert steppe and its spatiotemporal variation in western Inner Mongolia

A precise understanding of the aboveground biomass of desert steppe and its spatio-temporal variation is important to understand how arid ecosystems respond to climate change and to ensure that scarce grassland resources are used rationally. On the basis of 756 ground survey quadrats sampled in western Inner Mongolia steppe in 2005–2011 and remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS)—the normalized difference vegetation index (NDVI) dataset for the period of 2001–2011—we developed a statistical model to estimate the aboveground biomass of the desert steppe and further explored the relationships between aboveground biomass and climate factors. The conclusions are as follows: (1) the aboveground biomass of the steppe in the research area was 5.27 Tg (1 Tg=10¹² g) on average over 11 years; between 2001 and 2011, the aboveground biomass of the western Inner Mongolia steppe exhibited fluctuations, with no significant trend over time; (2) the aboveground biomass of the steppe in the research area exhibits distinct spatial variation and generally decreases gradually from southeast to northwest; and (3) the important factor causing interannual variations in aboveground biomass is precipitation during the period from January to July, but we did not find a significant relationship between the aboveground biomass and the corresponding temperature changes. The precipitation in this period is also an important factor influencing the spatial distribution of aboveground biomass (R²=0.39, P<0.001), while the temperature might be a minor factor (R²=0.12, P<0.01). The uncertainties in our estimate are primarily due to uncertainty in converting the fresh grass yield estimates to dry weight, underestimates of the biomass of shrubs, and error in remote sensing dataset.     

Study on inter-seasonal and intra-seasonal relationships of meteorological and agricultural drought indices in the Rajasthan State of India

Use of rainfall anomaly based Standardized Precipitation Index (SPI) and satellite-derived Vegetation Condition Index (VCI) are becoming common to assess the impacts of drought on crops. This study analysed spatio-temporal intra-seasonal and inter-seasonal relationships for 24 years between rainfall and NDVI and between SPI and VCI to understand crop response to water availability in the Rajasthan State, India. To separate the effect of weather and technology on crop growth over time, a modification in VCI was proposed and called “Trend Adjusted VCI” (VCI_Tadj). The VCI_Tadj was computed for early, mid, late and whole crop seasons by deriving pixel wise crop phenology metrics from NDVI profile. Significant linear relationships were found between NDVI and rainfall but phase of crop season affected the strength of this relationship. The SPI and VCI_Tadj were linearly related in all the four seasons, the strength of relationship improved with the progress of crop season and these relationships were stronger than between rainfall and NDVI. These relationships broke down in irrigated croplands. As a result, the anomaly indices of SPI and VCI_Tadj and their intra-seasonal relationships can be used to study the response of crops to water availability for early detection and better prognosis of agricultural drought.     

气候和土地利用变化对塔里木河干流区植被覆盖变化的影响

基于遥感和地理信息系统技术,利用1998—2008年SPOT-VEGETATION归一化植被指数（NDVI）数据对塔里木河干流区1998—2007年植被覆盖的时空变化进行了监测,并从气候变化和土地利用变化双重角度分析了植被覆盖变化的原因。研究表明,塔里木河干流区植被覆盖变化经历了两个阶段:1998—2001年植被覆盖严重退化时期;2002—2007年植被覆盖度由急剧上升到缓慢下降再到持续升高时期,NDVI明显高于20世纪末期水平。塔里木河干流区植被覆盖变化存在显著的空间差异,绿洲农业灌溉区和退耕还林还草生态恢复区的植被覆盖度显著提高,天然草地植被区的植被退化严重。塔里木河干流区植被覆盖变化是气候和土地利用变化共同作用的结果。温度对植被覆盖变化的影响表现为对植被生长年内韵律的控制和秋季植被生长期的延长,年降水量的波动式上升是导致塔里木河干流区植被覆盖变化两个阶段呈现差异的主导因素。     

黄土高原植被降水利用效率对植被恢复/退化的响应

基于2000-2014年MODIS NDVI数据及气象数据,运用累计降水利用效率变化差异（CRD,cumulative rain use efficiency differences）估算模型和基于地形要素降水量插值法,探讨2000-2014年黄土高原RUE（降水利用效率rain use efficiency）对植被变化的响应,以期为黄土高原生态可持续发展提供数据支撑。结果表明：黄土高原大部分地区植被覆盖得以改善,其面积约占总面积的81%,区域边缘植被覆盖退化严重。黄土高原降水利用效率RUE与累计NDVI的相关性总体表现为“东南呈正相关,西北为负相关”的空间格局,全区相关系数以正相关为主。黄土高原CRD与植被变化趋势的相关性显著,其中,植被退化背景下,植被退化程度越严重,RUE越低;植被恢复背景下,RUE受“退耕还林还草”作用显著,2000-2005年,RUE呈上升趋势,2007年后,随着退耕还林还草政策的工作重心转移,RUE呈波动变化。     

Response Differences of MODIS-NDVI and MODIS-EVI to Climate Factors

To evaluate and provide an appropriate theoretical direction for research into climate-vegetation interactions using meteorological station data at different time scales, we examined differences between the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) and their responses to climate factors. We looked for correlations between data extracted from MOD13Q1 remote sensing images and meteorological station data for the two indexes. The results showed that even though NDVI and EVI are derived from the same remote sensing image, their response to climate factors was significantly different. In the same meteorological station, the correlation coefficients for NDVI, EVI and climate factors were different; correlation coefficients between NDVI, EVI and climate factors varied with meteorological station. In addition, there was a lag effect for responses of NDVI to average minimum temperature, average temperature, average vapor pressure, minimum relative humidity, extreme wind speed, maximum wind speed, average wind speed and average station air-pressure. EVI had a lag only for average minimum temperature, average vapor pressure, extreme wind speed, maximum wind speed and average station air-pressure. The lag period was variable, but most were in the -3 period. Different vegetation types had different sensitivities to climate. The correlation between meteorological stations and vegetation requires more attention in future research.     

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.     

Rainfall variability,rainfed agriculture and degree of human marginality in North Guanajuato,Mexico

Mexico has a heterogeneous climate due to its geographical location. Half of the Mexican territory is dryland, mostly in the centre and north of the country, within which agriculture is the main activity in the primary production sector. At present, climate variability has a strong impact on Mexican agriculture. This study analysed rainfall variability, its impact on the agricultural productivity in terms of harvested quantity and productivity of 1996‐2014, and in parallel, the role that socioeconomic development plays on the well‐being of the population who live in areas with rainfed agriculture and a semi‐dry climate. The data obtained were analysed with the Statistical Analysis System. A positive correlation was found between rainfall and productivity (r = 0.76 for maize; r = 0.711 for beans). Rainfall variations therefore have a great impact on agricultural productivity, on food security and on the economy. Besides production losses, a parallel consequence is marginalization of the population because producers' income is increasingly reduced due to smaller crop volumes.