Detecting Global Vegetation Changes Using Mann-Kendal(MK) Trend Test for 1982–2015 Time Period

Vegetation is the main component of the terrestrial ecosystem and plays a key role in global climate change. Remotely sensed vegetation indices are widely used to detect vegetation trends at large scales. To understand the trends of vegetation cover, this research examined the spatial-temporal trends of global vegetation by employing the normalized difference vegetation index(NDVI) from the Advanced Very High Resolution Radiometer(AVHRR) Global Inventory Modeling and Mapping Studies(GIMMS) time series(1982–2015). Ten samples were selected to test the temporal trend of NDVI, and the results show that in arid and semi-arid regions, NDVI showed a deceasing trend, while it showed a growing trend in other regions. Mann-Kendal(MK) trend test results indicate that 83.37% of NDVI pixels exhibited positive trends and that only 16.63% showed negative trends(P 0.05) during the period from 1982 to 2015. The increasing NDVI trends primarily occurred in tree-covered regions because of forest growth and re-growth and also because of vegetation succession after a forest disturbance. The increasing trend of the NDVI in cropland regions was primarily because of the increasing cropland area and the improvement in planting techniques. This research describes the spatial vegetation trends at a global scale over the past 30+ years, especially for different land cover types.     

水土流失区马尾松林植被提取的土壤调节指数分析

为实现水土流失区植被遥感信息的准确提取,本文采用2007年ALOS 10 m多光谱影像,利用土壤调节植被指数SAVI和MSAVI,对福建长汀水土流失区马尾松林不同植被覆盖密度的3个实验区进行植被提取,并选用不同的土壤调节因子（L=0.25,0.5,0.75,1）做实验,将结果和以NDVI植被指数提取的结果进行对比,分析了提取效果及受土壤噪音的影响程度。实验表明,SAVI指数能提高水土流失区的植被提取精度。在中、低植被覆盖区,其提取的总精度比NDVI高出2%~7%,Kappa系数高出7%~18%;而土壤调节因子L的取值对植被信息的提取也呈现出一定的规律性,即：随着L从0向1递增,SAVI提取稀疏植被的能力上升而探测阴坡植被的能力下降。总体来看,对于低植被覆盖和中等植被覆盖地区,可分别用SAVI（L取0.75）和SAVI（L取0.5）来提取植被信息,对于高植被覆盖区,仍可直接用NDVI进行植被信息提取;研究发现MSAVI在植被信息提取中并不具有特别的优势。     

Effect of Mathematical Expression of Vegetation Indices on the Estimation of Phenology Trends from Satellite Data

Vegetation indices(VIs) from satellite remote sensing have been extensively applied to analyze the trends of vegetation phenology. In this paper, the NDVI(normalized difference vegetation index) and SR(simple ration), which are calculated from the same spectral bands of MODIS data with different mathematical expressions, were used to extract the start date(SOS) and end date(EOS) of the growing season in northern China and Mongolia from 2000 to 2015. The results show that different vegetation indices would lead to differences in vegetation phenology especially in their trends. The mean SOS from NDVI is 15.5 d earlier than that from SR, and the mean EOS from NDVI is 13.4 d later than that from SR. It should be noted that 16.3% of SOS and 17.2% of EOS derived from NDVI and SR exhibit opposite trends. The phenology dates and trends from NDVI are also inconsistent with those of SR among various vegetation types. These differences based on different mathematical expressions in NDVI and SR result from different resistances to noise and sensitivities to spectral signal at different stage of growing season. NDVI is prone to be effected more by low noise and is less sensitive to dense vegetation. While SR is affected more by high noise and is less sensitive to sparse vegetation. Therefore, vegetation indices are one of the uncertainty sources of remote sensing-based phenology, and appropriate indices should be used to detect vegetation phenology for different growth stages and estimate phenology trends.     

卫星影像数据构建山地植被指数与应用分析

 本研究以Landsat影像为数据源,在分析复杂地形山地植被在阳坡和阴坡反射率差异特征的基础上,提出一种归一化差值山地植被指数NDMVI (Normalized Difference Mountain Vegetation Index)。该指数模型无需辅助数据(如DEM)的支持,通过同时降低近红外波段(TM4)和红光波段(TM3)反射率的方法来消除或抑制地形的影响,具有较强的可操作性。研究表明:NDMVI与太阳入射角余弦值(cos i)的相关性相当小,对地形起伏变化表现不敏感,可有效消除或抑制地形的影响;比NDVI值动态变化范围更宽,对地物有更强的遥感识别能力;该模型抑制地形影响的效果比用C校正模型的效果更佳,不会出现过度校正的问题。     

玉米叶面积指数的CHRIS/PROBA数据反演分析

叶面积指数(LAI)是衡量植被生态状况和估算作物产量的一个重要指标。LAI的反演是定量遥感研究的重要内容。传统的经验统计反演方法基于单一观测角度的遥感数据进行,忽略了地物反射率的方向性。若在反演中加入多观测角度的信息,则有可能提升LAI反演的精度。以2008年甘肃省张掖市玉米实验区为研究区,利用欧空局的CHRIS/PROBA多角度高光谱数据对比分析了传统植被指数NDVI、RVI、EVI的变化规律及其反演玉米叶面积指数LAI的精度,并根据NDVI随观测角度的变化规律,构造出新型多角度归一化植被指数MNDVI,分别对实测叶面积指数进行线性回归并利用实测数据对估算LAI进行精度验证,结果表明：新型MNDVI指数相比于传统NDVI、RVI、EVI对LAI的反演精度有了显著提升,估算模型决定系数R²达到0.716,精度验证均方根误差为0.127,平均减小了33.3%。     

地形复杂山区常用植被指数的地形校正对比

植被指数能反映地表植被生长、覆盖等情况,常作为反演植物生物物理参量的有效参数。然而,在地形复杂的山区,由于地形效应的影响,导致一些植被指数适用性受限。基于以上现状,本文以贵州省江口县为研究区,采用4种地形校正模型（Teillet-回归模型、Minnaert模型、C模型、SCS+C模型）对常用植被指数（SR、MSR、NDVI、SAVI、MSAVI、EVI）进行地形校正,以评价不同坡度条件下植被指数地形校正效果。结果表明：地形校正对缓解波段比形式的植被指数（SR、MSR、NDVI）地形效应的作用有限,而对非波段比形式的植被指数（SAVI、MSAVI、EVI）效果较好。另外,随着坡度增加,地形效应显著,地形校正效果也更明显：坡度较小时,波段比形式的植被指数无需进行地形校正,而建议非波段比形式的植被指数进行地形校正;坡度较大时,建议2类植被指数都进行地形校正,但非波段比形式的植被指数可能会发生过度校正现象。此外,地形校正后非波段比形式的植被指数与森林地上生物量线性回归模型的精度明显提高。因此,建议在地形复杂山区利用非波段比形式的植被指数进行定量反演时,先进行地形校正。     

Morphology and controlling factors of the longitudinal profile of gullies in the Yuanmou dry-hot valley

The morphology of the gully longitudinal profile (GLP) is an important topographic index of the gully bottom associated with the evolution of the gullies. This index can be used to predict the development trend and evaluate the eroded volumes and soil losses by gullying. To depict the morphology of GLP and understand its controlling factors, the Global Positioning System Real-time Kinematic (GPS RTK) and the total station were used to measure the detail points along the gully bottom of 122 gullies at six sites of the Yuanmou dry-hot Valley. Then, nine parameters including length (Lt), horizontal distance (Dh), height (H), vertical erosional area (A), vertical curvature (Cv), concavity (Ca), average gradient (Ga), gully length-gradient index (GL), normalized gully length-gradient index (Ngl), were calculated and mapped using CASS, Excel and SPSS. The results showed that this study area is dominated by slightly concave and medium gradient GLPs, and the lithology of most gullies is sandstone and siltstone. Although different types of GLPs appear at different sites, all parameters present a positively skewed distribution. There are relatively strong correlations between several parameters: namely Lt and H, Dh and H, Lt and A, Dh and A, H and GL. Most GLPs, except three, have a best fit of exponential functions with quasistraight shapes. Soil properties, vegetation coverage, piping erosion and topography are important factors to affect the GLP morphology. This study provides useful insight into the knowledge of GLP morphology and its influential factors that are of critical importance to prevent and control gully erosion.     

Impacts of Drought and Human Activity on Vegetation Growth in the Grain for Green Program Region,China

The Chinese government adopted six ecological restoration programs to improve its natural environments. Although these programs have proven successful in improving local environments, some studies have questioned their performance when regions suffer from drought. Whether we should consider the effects of drought on vegetation change in assessments of the benefits of ecological restoration programs is unclear. Therefore, taking the Grain for Green Program(GGP) region as a study area, we estimated vegetation growth in the region from 2000–2010 to clarify the trends in vegetation and their driving forces. Results showed that: 1) vegetation growth increased in the GGP region during 2000–2010, with 59.4% of the area showing an increase in the Normalized Difference Vegetation Index(NDVI). This confirmed the benefits of the ecological restoration program. 2) Drought can affect the vegetation change trend, but human activity plays a significant role in altering vegetation growth, and the slight downward trend in the NDVI was not consistent with the severity of the drought. Positive human activity led to increased NDVI in 89.13% of areas. Of these, 22.52% suffered drought, but positive human activity offset the damage in part. 3) Results of this research suggest that appropriate human activity can maximize the benefits of ecological restoration programs and minimize the effects of extreme weather. We therefore recommend incorporating eco-risk assessment and scientific management mechanisms in the design and management of ecosystem restoration programs.     

2010年中国西南旱情的时空特征分析——基于MODIS数据归一化干旱指数

 近年来,干旱灾害频繁发生,对区域内农业生产和生态环境造成了极大的破坏。为了快速准确地获取大面积地表土壤水分信息用以评估地表受旱程度,本文以2010年年初中国西南大旱为例,运用MODIS可见光-红外波段数据以及像元可信度综合生成了归一化干旱指数(NDDI)。同时,结合研究区内地面气象站点实测的土壤湿度数据验证了NDDI对地表土壤湿度的敏感度。结果表明:相比于植被状态指数(VCI)干旱监测模型,NDDI能更加灵敏地对浅层地表干湿变化做出迅速响应。最后,本文利用NDDI分析了2010年年初中国西南大旱旱情发展的时空演变过程,宏观上重现了此次旱情的发展历程,并使用该指数统计了不同时间节点、不同干旱等级下的贵州省土地受旱面积。结果显示:2010年1月-2010年4月为贵州省旱情最为严重的4个月,平均受旱面积达103 352km²,最大受旱面积达132 257km²,占贵州省总面积的75%以上。同时,旱情等级为重旱的土地面积最大达到88 246 km²,占贵州全境土地面积的50%以上。     

Spatial distribution of land cover and vegetation activity along topographic gradient in an arid river valley, SW China

Anthropogenic activities have become more and more important in characterizing the landscape, but their impacts are still restricted by natural environments. This paper discusses the interactions of anthropogenic activity, vegetation activity and topography through describing the spatial distribution of land cover and vegetation activity （represented by Normalized Difference Vegetation Index, NDVI） along topographic gradient in a mountainous area of southwestern China. Our results indicate that the existing landscape pattern is controlled by anthropogenic activities as well as topographic factors. Intensive anthropogenic activities mainly occur in areas with relatively low elevation, gentle and concave slopes, as these areas are easy and convenient to attain for human. Because of the destruction by human, some land cover types （mainly grassland and shrub） are only found in relatively harsher environments. This study also finds that topographic wetness index （W） used in other places only reflects runoff generation capacity, but not indicate the real spatial pattern of soil water content in this area. The relationships between NDVI and W, and NDVI and length slope factor （LSF） show that runoff and erosion have complex effects on vegetation activity. Greater values of W and LSF will lead to stronger capacity to produce runoff and transport sediment, and thereby increase soil water content and soil deposition, whereas beyond a certain threshold runoff and erosion are so strong that they would destruct vegetation growth. This study provides information needed to successfully restore native vegetation, improve land management, and promote sustainable development in mountainous areas, especially for developing regions.     

Spatial variability of soil development indices and their compatibility with soil taxonomic classes in a hilly landscape: a case study at Bandar village,Northern Iran

Soil complexity and its multivariable nature restrict the precision of soil maps that are essential tools for soil sustainable management. Most methods developed for reducing impurities of soil map units focus on soil external properties. Taking into account the soil internal properties like geochemical weathering indices could increase the map unit’s purity. However, the compatibility of these indices with Soil Taxonomic Classes has not been studied yet. This study has been performed in a hilly region with different soil types, vegetation and diverse topographic attributes to illustrate the spatial variability of soil weathering indices and their compatibility with Soil Taxonomic Classes. The grid sampling is at 100 m interval. Physico-chemical and total elemental analyses were performed on 184 and 56 soil samples respectively. Eight topographic attributes and 14 common soil development indices were determined. Principal components analysis (PCA) was done to identify the most important components. The results indicated that Morphological Index (MI) was the best index to show the degree of soil development in the studied region. Spatial distribution of Soil Taxonomic Classes showed relatively good compatibility with the first principal component (PC1), Vogt (V) and morphological indices. This study showed that using soil development indices with the conventional methods could be helpful tools in soil survey investigations     

京津冀地区植被时空动态及定量归因

作为气候变化的敏感指示器,植被的物候、生长、空间分布格局等特征及其动态变化主要取决于气候环境中的水热条件,因此在气候变化背景下,气候-植被关系成为了全球变化研究的前沿和热点问题。本文综合平均温度、降水、水汽压、湿度、日照时数、SPEI等气候因子,坡度、坡向海拔等地形因子及人为活动因子,应用地理探测器方法针对2006-2015年京津冀地区不同季节NDVI、不同地貌类型区、不同植被类型区生长季NDVI的定量归因研究,揭示了过去10年间植被时空分布格局,及植被对气候、非气候因素响应的季节差异与区域差异,以期为生态工程的建设与修复提供参考意义。趋势分析表明：①2006-2015年京津冀地区NDVI呈现增加趋势,但存在显著的空间差异,如山地生长季NDVI的增长速率大于平原、台地、丘陵等地;②基于地理探测器的定量归因结果表明,降水是年尺度上NDVI空间分布的主导因子（解释力39.4%）,土地利用与降水的交互作用对NDVI的影响最为明显（q=58.2%）;③NDVI对气候因子的响应存在季节性及区域性差异,水汽压是春季NDVI空间分布的主导因子,湿度是夏、秋两季的主导因子,土地利用是冬季的主导因子;④影响因子对生长季NDVI的解释力因不同地貌类型区、不同植被类型区而差异显著。     

Effects of normalized difference vegetation index and related wavebands’ characteristics on detecting spatial heterogeneity using variogram-based analysis

Spatial heterogeneity is widely used in diverse applications, such as recognizing ecological process, guiding ecological restoration, managing land use, etc. Many researches have focused on the inherent scale multiplicity of spatial heterogeneity by using various environmental variables. How these variables affect their corresponding spatial heterogeneities, however, have received little attention. In this paper, we examined the effects of characteristics of normalized difference vegetation index (NDVI) and its related bands variable images, namely red and near infrared (NIR), on their corresponding spatial heterogeneity detection based on variogram models. In a coastal wetland region, two groups of study sites with distinct fractal vegetation cover were tested and analyzed. The results show that: 1) in high fractal vegetation cover (H-FVC) area, NDVI and NIR variables display a similar ability in detecting the spatial heterogeneity caused by vegetation growing status structure; 2) in low fractal vegetation cover (L-FVC) area, the NIR and red variables outperform NDVI in the survey of soil spatial heterogeneity; and 3) generally, NIR variable is ubiquitously applicable for vegetation spatial heterogeneity investigation in different fractal vegetation covers. Moreover, as variable selection for remote sensing applications should fully take the characteristics of variables and the study object into account, the proposed variogram analysis method can make the variable selection objectively and scientifically, especially in studies related to spatial heterogeneity using remotely sensed data.     

Effect of Temporal Resolution of NDVI on Potential Evapotranspiration Estimation and Hydrological Model Performance

Normalized difference vegetation index (NDVI) data, obtained from remote sensing information, are essential in the Shuttleworth-Wallace (S-W) model for estimation of evapotranspiration. In order to study the effect of temporal resolution of NDVI on potential evapotranspiration (PET) estimation and hydrological model performance, monthly and 10-day NDVI data set were used to estimate potential evapotranspiration from January 1985 to December 1987 in Huangnizhuang catchment, Anhui Province, China. The differences of the two calculation results were analyzed and used to drive the block-wise use of the TOPMODEL with the Muskingum-Cunge routing (BTOPMC) model to test the effect on model performance. The results show that both annual and monthly PETs estimated by 10-day NDVI are lower than those estimated by monthly NDVI. Annual PET from the vegetation root zone (PETr) lowers 9.77%-13.64% and monthly PETr lowers 3.28%-17.44% in the whole basin. PET from the vegetation interception (PETi) shows the same trend as PETr. In addition, temporal resolution of NDVI has more effect on PETr in summer and on PETi in winter. The correlation between PETr as estimated by 10-day NDVI and pan measurement (R2= 0.835) is better than that between monthly NDVI and pan measurement (R2 = 0.775). The two potential evapotranspiration estimates were used to drive the BTOPMC model and calibrate parameters, and model performance was found to be similar. In summary, the effect of temporal resolution of NDVI on potential evapotranspiration estimation is significant, but trivial on hydrological model performance.     

Comparison of some vegetation indices in seasonal information

With the development of vegetation indices, the reflection capability of vegetation indices to the state of vegetation has been improved in various degrees. Especially, the vegetation index of Terra/MODIS-EVI is believed to have the highest sensitivity to the seasonality of vegetation. This study compares the reflection susceptibility of three vegetation indices （NOAA/AVHRR-NDVI, Terra/MODIS-NDVI and Terra/MODIS-EVI） to the seasonal variations of vegetation in the mid-south of Yunnan Province of China. It has been found that Terra/MODIS-EVI does best in the elimination of external disturbance. Firstly, it obviously improves the linear relationship with vegetation cover degree, especially in the high vegetation coverage area. Secondly, it avoids the emergence of vegetation index saturation. Thirdly, it reduces the environmental influence including both effects of atmosphere and soil. So it is believed that the Terra/MODIS-EVI can offer excellent tool for quantitative research of remote sensing, and has realized to be oriented by data with high quality.     

Evaluation of Forest Damaged Area and Severity Caused by Ice-snow Frozen Disasters over Southern China with Remote Sensing

The accurate assessment of forest damage is important basis for the forest post-disaster recovery process and ecosystem management. This study evaluates the spatial distribution of damaged forest and its damaged severity caused by ice-snow disaster that occurred in southern China during January 10 to February 2 in 2008. The moderate-resolution imaging spectroradiometer(MODIS)13 Q1 products are used, which include two vegetation indices data of NDVI(Normalized Difference Vegetation Index) and EVI(Enhanced Vegetation Index). Furtherly, after Quality Screening(QS) and Savizky-Golay(S-G) filtering of MODIS 13 Q1 data, four evaluation indices are obtained, which are NDVI with QS(QSNDVI), EVI with QS(QSEVI), NDVI with S-G filtering(SGNDVI) and EVI with S-G filtering(SGEVI). The study provides a new way of firstly determining the threshold for each image pixel for damaged forest evaluation, by computing the pre-disaster reference value and change threshold with vegetation index from remote sensing data. Results show obvious improvement with the new way for forest damage evaluation, evaluation result of forest damage is much close to the field survey data with standard error of only 0.95 and 1/3 less than the result that evaluated from other threshold method. Comparatively, the QSNDVI shows better performance than other three indices on evaluating forest damages. The evaluated result with QSNDVI shows that the severe, moderate, mild damaged rates of Southern China forests are 47.33%, 34.15%, 18.52%, respectively. By analyzing the influence of topographic and meteorological factors on forest-vegetation damage, we found that the precipitation on freezing days has greater impact on forest-vegetation damage, which is regarded as the most important factor. This study could be a scientific and reliable reference for evaluating the forest damages from ice-snow frozen disasters.     

基于光谱时间序列拟合的中国南方水稻遥感识别方法研究

多云多雾现象是农作物遥感分类经常遇到的问题,影响分类精度。为解决此类问题,本文提出一种基于时间序列GF-1号遥感影像识别水稻方法。利用多时相时间序列的GF-1号遥感影像提取中稻、晚稻的近红外波段（NIR）反射率、红光（R）波段反射率、归一化植被指数（NDVI）特征;拟合光谱和植被指数时间序列特征曲线;分析多时相影像离散近红外波段 、红光波段、NDVI值落在拟合中稻、晚稻近红外波段、红光波段、NDVI时间序列曲线两侧的敏感性区域的比例,该区域也可以视为水稻作物识别特征的目标特征区域,只有达到一定的比例才能视为某类水稻作物。在此情形下,需要综合3种情况进行集中投票决定其最终分类结果。研究表明：该方法可以在多云雾地区对中稻和晚稻精确识别,中稻和晚稻用户精度可达95.97%和95.95%,总体精度为95.76%,kappa系数为0.9335。实验结果表明了NIR、R、NDVI时间序列曲线拟合的有效性,以及拟合曲线目标特征区域设置的合理性。     

基于植被状态指数的云南省农业干旱状况时空分析

本文首先计算了云南省2004-2013年农业干旱指数VCI,然后使用Pearson相关系数评价降水与VCI的相关性,基于VCI识别云南省2004-2013年农业干旱事件,最后,与SPEI气象干旱识别结果进行对比分析,在VCI农业干旱识别的基础上,使用干旱频率和干旱面积占比指标分析了云南省2004-2013年农业干旱时空特征。结果表明：降水只是影响VCI指数的关键因素之一;VCI和SPEI指数均能够较好对干旱进行监测并识别典型干旱,但两者的识别结果存在差异;云南省农业干旱频率在春冬两季较高,夏季较低,秋季介于夏季和春冬季之间;春夏冬三季农业干旱频率空间分布较为均匀,秋季农业干旱频率呈南低北高的分布态势,整体上北部干旱频率高于南部;2004-2013年云南省整体干旱面积占比呈现先减小后增加再波动的趋势,春冬两季整体干旱面积占比最高,分别为46.63%和47.18%,呈现下降趋势,夏季整体干旱面积占比最低,为43.81%,呈现上升趋势,秋季整体干旱面积占比介于冬春季和夏季之间,为45.74%,呈现下降趋势。总之,云南省农业干旱春冬易发性最高,影响范围最大,夏季易发性最低,影响范围最小。     

Spatial and seasonal pattern of macrozoobenthic assemblages and the congruence in water quality bioassessment using different taxa in artificial Mingzhu Lake in Shanghai

The spatial and seasonal pattern of macrozoobenthic structure and its relationship with environmental factors were studied from July 2006 to April 2008 in Mingzhu Lake, Chongming Island, Shanghai at the Changjiang River mouth. The congruences in water quality bioassessment based on diversity and biotic indices and using different taxonomic categories were also explored to find the best assessment method of water quality for the lake. All major structural characteristics of macrozoobenthic community, including species composition, abundance, biomass and four biomass-based diversity indices (Shannon’s diversity, Simpson’s diversity, Pielou’s evenness and Simpson’s evenness index) fluctuated significantly in season but in space. The above four abundance-based diversity indices plus abundance-based Margalef’s richness index did not display significant spatial variations; and significant seasonal differences were found in three indices only. Water temperature was the key environmental factor responsible for macrozoobenthic spatio-temporal distribution patterns. Water quality assessed by Shannon’s index (H _a′) and biological pollution index (BPI) rather than the other four biotic indices were consistent with those by trophic state index (TSI). Results from chironomids and oligochaetes did not always agree to those from the whole community when H _a′ or Hilsenhoff biotic index was applied to bioassessment. Therefore, combining multiple indices and avoiding a single taxonomic category to assess water quality are strongly recommended and in Mingzhu Lake using a mixture of H _a′ and BPI will ensure the most effective investigation of water quality. Our results also show that the main structural characteristics of macrozoobenthic communities in the small lake may display consistent spatial patterns.     

Spatial and temporal variation of drought index in a typical steep alpine terrain in Hengduan Mountains

This study describes the spatial and temporal variation of a drought index and makes inferences regarding the environmental factors that influence this variability in the Hengduan Mountains. A drought index is typically used to determine the moisture conditions and the magnitude of water deficiency in a given area. Based on data from 26 meteorological stations over the period 1960-2012, the spatial and temporal variations of the drought index were analyzed using a thin plate smoothing splines method that considered elevation as a covariate. The drought index was estimated based on the potential evapotranspiration (E₀) as defined by the Penman Monteith model modified by FAO (1998). The results of the reported analysis showed that the drought index in the Hengduan Mountains has been decreasing since 1960 at a rate of -0.008/a. This represented a progressive shift from the "sub-humid" class, which typified the wider area in the Hengduan Mountains, toward the "humid" class, which appeared in the Hengduan Mountains areas. The drought index was relatively high in the north and low in the south and the variation of the drought index varied with seasons. The drought index showed increasing trends in summer and autumn and it is greater in autumn than in summer, while it showed a decreasing trend in spring and winter. Drought index is inversely proportional to the soil relative humidity and Normalized Difference Vegetation Index (NDVI).