Assessment of vegetation cover changes and the contributing factors in the Al-Ahsa Oasis using Normalized Difference Vegetation Index(NDVI)

The abandonment of date palm grove of the former Al-Ahsa Oasis in the eastern region of Saudi Arabia has resulted in the conversion of delicate agricultural area into urban area.The current state of the oasis is influenced by both expansion and degradation factors.Therefore,it is important to study the spatiotemporal variation of vegetation cover for the sustainable management of oasis resources.This study used Landsat satellite images in 1987,2002,and 2021 to monitor the spatiotemporal variation of vegetation cover in the Al-Ahsa Oasis,applied multi-temporal Normalized Difference Vegetation Index(NDVI)data spanning from 1987 to 2021 to assess environmental and spatiotemporal variations that have occurred in the Al-Ahsa Oasis,and investigated the factors influencing these variation.This study reveals that there is a significant improvement in the ecological environment of the oasis during 1987–2021,with increase of NDVI values being higher than 0.10.In 2021,the highest NDVI value is generally above 0.70,while the lowest value remains largely unchanged.However,there is a remarkable increase in NDVI values between 0.20 and 0.30.The area of low NDVI values(0.00–0.20)has remained almost stable,but the region with high NDVI values(above 0.70)expands during 1987–2021.Furthermore,this study finds that in 1987–2002,the increase of vegetation cover is most notable in the northern region of the study area,whereas from 2002 to 2021,the increase of vegetation cover is mainly concentrated in the northern and southern regions of the study area.From 1987 to 2021,NDVI values exhibit the most pronounced variation,with a significant increase in the“green”zone(characterized by NDVI values exceeding 0.40),indicating a substantial enhancement in the ecological environment of the oasis.The NDVI classification is validated through 50 ground validation points in the study area,demonstrating a mean accuracy of 92.00%in the detection of vegetation cover.In general,both the user’s and producer’s accuracies of NDVI classification are extremely high in 1987,2002,and 2021.Finally,this study suggests that environmental authorities should strengthen their overall forestry project arrangements to combat sand encroachment and enhance the ecological environment of the Al-Ahsa Oasis.

Interannual Variability of the Normalized Difference Vegetation Index on the Tibetan Plateau and Its Relationship with Climate Change

The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly affects the local land ecosystem and could consequently lead to notable vegetation changes. In this paper, the interannual variations of the plateau vegetation are investigated using a 21-year normalized difference vegetation index （NDVI） dataset to quantify the consequences of climate warming for the regional ecosystem and its interactions. The results show that vegetation coverage is best in the eastern and southern plateau regions and deteriorates toward the west and north. On the whole, vegetation activity demonstrates a gradual enhancement in an oscillatory manner during 1982-2002. The temporal variation also exhibits striking regional differences： an increasing trend is most apparent in the west, south, north and southeast, whereas a decreasing trend is present along the southern plateau boundary and in the central-east region. Covariance analysis between the NDVI and surface temperature/precipitation suggests that vegetation change is closely related to climate change. However, the controlling physical processes vary geographically. In the west and east, vegetation variability is found to be driven predominantly by temperature, with the impact of precipitation being of secondary importance. In the central plateau, however, temperature and precipitation factors are equally important in modulating the interannual vegetation variability.

Simple method for extracting the seasonal signals of photochemical reflectance index and normalized difference vegetation index measured using a spectral reflectance sensor

A spectral reflectance sensor(SRS)fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI)and photochemical reflectance index(PRI).NDVI is useful for indicating crop growth/phenology,whereas PRI was developed for observing physiological conditions.Thus,the seasonal change patterns of NDVI and PRI are two valuable pieces of information in a crop-monitoring system.However,capturing the seasonal patterns is considered challenging because the vegetation index values estimated by the reflection from vegetation are often governed by meteorological conditions,such as solar irradiance and precipitation.Further,unlike growth/phenology,the physiological condition has diurnal changes as well as seasonal characteristics.This study proposed a novel filtering method for extracting the seasonal signals of SRS-based NDVI and PRI in paddy rice,barley,and garlic.First,the measurement accuracy of SRSs was compared with handheld spectrometers,and the R^(2)values between the two devices were 0.96 and 0.81 for NDVI and PRI,respectively.Second,the experimental study of threshold criteria with respect to meteorological variables(i.e.,insolation,cloudiness,sunshine duration,and precipitation)was conducted,and sunshine duration was the most useful one for excluding distorted values of the vegetation indices.After data processing based on sunshine duration,the R^(2)values between the measured vegetation indices and the extracted seasonal signals of vegetation indices increased by approximately 0.002–0.004(NDVI)and 0.065–0.298(PRI)on the three crops,and the seasonal signals of vegetation indices became noticeably improved.This method will contribute to an agricultural monitoring system by identifying the seasonal changes in crop growth and physiological conditions.

Drought trend analysis in a semi-arid area of Iraq based on Normalized Difference Vegetation Index, Normalized Difference Water Index and Standardized Precipitation Index

Drought was a severe recurring phenomenon in Iraq over the past two decades due to climate change despite the fact that Iraq has been one of the most water-rich countries in the Middle East in the past.The Iraqi Kurdistan Region(IKR)is located in the north of Iraq,which has also suffered from extreme drought.In this study,the drought severity status in Sulaimaniyah Province,one of four provinces of the IKR,was investigated for the years from 1998 to 2017.Thus,Landsat time series dataset,including 40 images,were downloaded and used in this study.The Normalized Difference Vegetation Index(NDVI)and the Normalized Difference Water Index(NDWI)were utilized as spectral-based drought indices and the Standardized Precipitation Index(SPI)was employed as a meteorological-based drought index,to assess the drought severity and analyse the changes of vegetative cover and water bodies.The study area experienced precipitation deficiency and severe drought in 1999,2000,2008,2009,and 2012.Study findings also revealed a drop in the vegetative cover by 33.3%in the year 2000.Furthermore,the most significant shrinkage in water bodies was observed in the Lake Darbandikhan(LDK),which lost 40.5%of its total surface area in 2009.The statistical analyses revealed that precipitation was significantly positively correlated with the SPI and the surface area of the LDK(correlation coefficients of 0.92 and 0.72,respectively).The relationship between SPI and NDVI-based vegetation cover was positive but not significant.Low precipitation did not always correspond to vegetative drought;the delay of the effect of precipitation on NDVI was one year.

Retrospective analysis of two northern California wild-land fires via Landsat five satellite imagery and Normalized Difference Vegetation Index (NDVI)

Wild-land fires are a dynamic and destructive force in natural ecosystems. In recent decades, fire disturbances have increased concerns and awareness over significant economic loss and landscape change. The focus of this research was to study two northern California wild-land fires: Butte Humboldt Complex and Butte Lightning Complex of 2008 and assessment of vegetation recovery after the fires via ground based measurements and utilization of Landsat 5 imagery and analysis software to assess landscape change. Multi-temporal and burn severity dynamics and assessment through satellite imagery were used to visually ascertain levels of landscape change, under two temporal scales. Visual interpretation indicated noticeable levels of landscape change and relevant insight into the magnitude and impact of both wild-land fires. Normalized Burn Ratio (NBR) and delta NBR (DNBR) data allowed for quantitative analysis of burn severity levels. DNBR results indicate low severity and low re-growth for Butte Humboldt Complex “burned center” subplots. In contrast, DNBR values for Butte Lightning Complex “burned center” subplots indicated low-moderate burn severity levels.

Monitoring vegetation drought in the nine major river basins of China based on a new developed Vegetation Drought Condition Index

The effect of global climate change on vegetation growth is variable.Timely and effective monitoring of vegetation drought is crucial for understanding its dynamics and mitigation,and even regional protection of ecological environments.In this study,we constructed a new drought index(i.e.,Vegetation Drought Condition Index(VDCI))based on precipitation,potential evapotranspiration,soil moisture and Normalized Difference Vegetation Index(NDVI)data,to monitor vegetation drought in the nine major river basins(including the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin,Yangtze River Basin,Southeast River Basin,Pearl River Basin,Southwest River Basin and Continental River Basin)in China at 1-month–12-month(T1–T12)time scales.We used the Pearson's correlation coefficients to assess the relationships between the drought indices(the developed VDCI and traditional drought indices including the Standardized Precipitation Evapotranspiration Index(SPEI),Standardized Soil Moisture Index(SSMI)and Self-calibrating Palmer Drought Severity Index(scPDSI))and the NDVI at T1–T12 time scales,and to estimate and compare the lag times of vegetation response to drought among different drought indices.The results showed that precipitation and potential evapotranspiration have positive and major influences on vegetation in the nine major river basins at T1–T6 time scales.Soil moisture shows a lower degree of negative influence on vegetation in different river basins at multiple time scales.Potential evapotranspiration shows a higher degree of positive influence on vegetation,and it acts as the primary influencing factor with higher area proportion at multiple time scales in different river basins.The VDCI has a stronger relationship with the NDVI in the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin and Yangtze River Basin at T1–T4 time scales.In general,the VDCI is more sensitive(with shorter lag time of vegetation response to drought)than the traditional drought indices(SPEI,scPDSI and SSMI)in monitoring vegetation drought,and thus it could be applied to monitor short-term vegetation drought.The VDCI developed in the study can reveal the law of unclear mechanisms between vegetation and climate,and can be applied in other fields of vegetation drought monitoring with complex mechanisms.

Mean Difference of Truncated Normal Distribution

The purpose of this paper is to broaden the knowledge of mean difference and, in particular, of an important distribution model known as truncated normal distribution, which is widely used in applied sciences and economics. In this work, we obtained the general formula of mean difference, which is not yet reported in literature, for the aforementioned distribution model and also for particular truncated cases.

Evaluating the Impact of Different Vegetation Types on NEE: A Case Study of Banni Grasslands, India

Estimation of NEE of Grasslands ecosystems becomes mandatory as these grasslands with their wide spread (almost 40% of land of the earth) and high plant diversity play a major role in global carbon balances and NEE at both local and global scale. The present study has been focused on understanding the role of different plant species responsible for variation in NEE of the Banni Grasslands of India. These grasslands form a belt of arid grassland having low growing forbs, graminoids and scattered tree cover. Due to its wide spread and inaccessibility of Banni, this study utilized spatial approach for evaluating carbon emissions and NEE. Landsat data was utilized for vegetation type classification and SMAP data for extraction of NEE values proved their potential for categorising vegetation type and generating NEE values precisely. Three major plant types were identified from the study area viz., Grasslands, Land with Acacia and Land with Prosopis. Grasses were dominant covering 77% and the rest of the area was occupied by the other two classes, i.e. Acacia and Prosopis. The NEE values were higher for the grasses when compared to the other two plant species proving to be the active sinks when compared to other plants. The differential contribution of NEE by species has been depicted in the present work.

Dynamicity of Land Use/Land Cover(LULC):An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation(DMC)in India

The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods,changing the landscape of regions outside the city and fostering the growth of physical infrastructure.Using multi-temporal satellite images,the dynamics of Land Use/Land Cover(LULC)changes,the impact of urban growth on LULC changes,and regional environmental implications were investigated in the peri-urban and rural neighbourhoods of Durgapur Municipal Corporation in India.The study used different case studies to highlight the study area’s heterogeneity,as the phenomenon of change is not consistent.Landsat TM and OLI-TIRS satellite images in 1991,2001,2011,and 2021 were used to analyse the changes in LULC types.We used the relative deviation(RD),annual change intensity(ACI),uniform intensity(UI)to show the dynamicity of LULC types(agriculture land;built-up land;fallow land;vegetated land;mining area;and water bodies)during 1991-2021.This study also applied the Decision-Making Trial and Evaluation Laboratory(DEMATEL)to measure environmental sensitivity zones and find out the causes of LULC changes.According to LULC statistics,agriculture land,built-up land,and mining area increased by 51.7,95.46,and 24.79 km^(2),respectively,from 1991 to 2021.The results also suggested that built-up land and mining area had the greatest land surface temperature(LST),whereas water bodies and vegetated land showed the lowest LST.Moreover,this study looked at the relationships among LST,spectral indices(Normalized Differenced Built-up Index(NDBI),Normalized Difference Vegetation Index(NDVI),and Normalized Difference Water Index(NDWI)),and environmental sensitivity.The results showed that all of the spectral indices have the strongest association with LST,indicating that built-up land had a far stronger influence on the LST.The spectral indices indicated that the decreasing trends of vegetated land and water bodies were 4.26 and 0.43 km^(2)/a,respectively,during 1991-2021.In summary,this study can help the policy-makers to predict the increasing rate of temperature and the causes for the temperature increase with the rapid expansion of built-up land,thus making effective peri-urban planning decisions.

高寒气候区生长季NDVI与昼夜不对称增温的Copula分析

利用1982—2016年的青海地区归一化植被指数和气象数据,基于马尔科夫链蒙特卡罗的Copula函数方法,深入探索昼夜增温不对称性与植被活动之间的复杂关系,揭示了昼夜增温和NDVI之间的联合概率分布及其季节性差异。研究结果表明,昼夜增温与NDVI之间的关系在不同季节呈现显著差异。尤其在秋季,昼夜增温对NDVI的影响最为显著,其次是夏季和春季。通过Copula函数模型,发现昼夜增温与NDVI在特定温度区间内呈现正相关,表明适宜的温度条件下昼夜增温对植被生长具有促进作用。然而,当昼夜增温超过某一阈值时,其对NDVI的促进作用转变为抑制作用,从而限制了植被的生长。同时,还揭示了重现期与昼夜增温及NDVI之间的关系。在较低的重现期下,昼夜增温与NDVI的联合概率较高,表明在这些条件下,植被生长良好的情况出现的频率较高。反之,较高的重现期对应于昼夜增温与NDVI较低的联合概率,表明植被生长受到抑制。本研究通过Copula函数提供了一个全新的视角来理解昼夜增温与植被动态之间的相互作用,强调了气温变化对植被生长影响的复杂性。

2000—2021年渭河流域NDVI变化及其影响因素

渭河流域是黄河中游重要的生态涵养地,同时也是黄土高原水土流失的典型区域,监测该地区植被生长变化趋势,并分析其与气候变化和人类活动的关系,对科学评估区域生态建设成效、黄土高原植被恢复和生态修复具有重要意义。基于2000—2021年归一化植被指数(NDVI)、气温、降水量、人口密度、土地利用数据,分析了渭河流域NDVI的时空变化特征,探究了气候变化和人类活动对NDVI变化趋势的影响。结果表明,2000—2021年,渭河流域植被生长季NDVI呈增加趋势,全区年平均增速为0.004。年际尺度上,NDVI与年平均降水量呈正相关关系,与年平均气温的相关性不显著;月尺度上,NDVI与4月和8月的气温、降水量均呈正相关关系,与7月气温呈弱的负相关关系。人口密度变化与NDVI变化趋势呈负相关,流域人口密度的减小有利于植被的恢复和改善。土地利用类型内部变化是植被NDVI变化的主要原因。NDVI显著减少区NDVI的减少趋势主要由关中平原耕地NDVI的减少引起,NDVI显著增加区NDVI的增加趋势主要由草地、林地以及黄土丘陵区、黄土残塬区耕地NDVI的增加引起。

基于Sentinel-2的青铜峡灌区水稻和玉米种植分布早期识别

及时准确地掌握灌区内作物种植分布对于灌溉水资源高效配置、农田精准管理具有重要指导意义。以宁夏青铜峡灌区为研究对象,利用多时相Sentinel-2卫星数据,通过水稻和玉米早期特征分析,提取关键的“水淹”信号和“植被”信号,构建时序归一化差异水体指数(MNDWI)和归一化植被指数(NDVI)特征值数据集,并通过样本分析关键特征阈值,构建水稻和玉米早期种植分布决策树模型,提取2022年宁夏青铜峡灌区水稻和玉米种植的空间分布。结果表明(:1)玉米和水稻苗期的后半段5月15—31日,水淹信号和植被信号是区分二者关键时期。(2)基于早期作物物候特征的方法,在5月16—31日获取的水稻和玉米图像制图精度高于90%,用户精度超过91%,总体精度超过90%,Kappa系数高于0.88,明显高于同时期随机森林方法的分类精度。(3)本研究提出的方法在早期水稻和玉米种植分布提取方面具有较强的适用性,并且能够在时空尺度上以较少的实地样本进行延展,同时在时间上也更有优势。因此,该方法为青铜峡灌区水稻和玉米种植分布早期调查提供了重要的方法支撑。

基于高分一号遥感影像的水体提取方法对比分析与改进

以高分一号遥感影像为数据源,以安徽省黄山市屯溪流域内的东方红水库为研究对象,采用单波段阈值法、两波段差值法、波段比值法、归一化差分水体指数(NDWI)法、归一化差分植被指数(NDVI)法共5种水陆像元度量方法,分别应用平均值法和最大类间方差迭代法两种阈值选取方法对东方红水库进行水体提取,探索最大类间方差迭代法在水体提取变量上的改进效果,在此基础上提出了一种改进的最大类间方差联合水体提取法,并对比了改进前后的水体提取效果。结果表明:改进后的水体提取方法可以很好地降低影像提取中产生的噪点,提高水体提取的精度,提取成果的平均相对误差为4.69%,决定系数为0.8579,相比于改进前平均相对误差降低了0.68%,决定系数提高了0.0539。

Response of remotely sensed Normalized Difference Water Deviation Index to the 2006 Drought of eastern Sichuan Basin

One of the most serious droughts in last century occurred in eastern Sichuan Basin in the summer of 2006 (hereinafter called the Drought). The response of Moderate Resolution Imaging Spectroradiometer (MODIS, boarding on NASA satellites of Terra and Aqua) to the Drought was analyzed in order to reach one practicable monitoring solution for regional soil moisture. Temporal process and spatial extension of the Drought were firstly estimated with ground meteorological and hydrological observations. Then, for the whole region of Sichuan and Chongqing, the remotely sensed Normalized Difference Water In- dex (NDWI) for the summers of 2001―2006 were calculated based on 8-day composite MODIS products, which were further used to construct a new water index (Normalized Difference Water Deviation Index, NDWDI) to examine the sensitivity of remote sensing in the Drought. The study showed that the NDWDI is more sensitive to regional drought than other absolute-soil-moisture-based indices. With the new index, the study extracted the spatial-temporal characteristics of the 2006 Drought, and explored its developing and withdrawing processes, which agreed with related statistics. Compared with ground method of drought observation, the NDWDI-based remote sensing solution of this paper is more pref- erable and practicable in that the local soil properties of water consumption and supply are implicitly taken into account, and the spatial representativity limit of ground observation is circumvented to a degree as satellite remotely senses the earth surface in a way of two-dimensional pixel matrix. So, the NDWDI-based method can be used to monitor regional soil water stress situation more practically and efficiently.

Mapping rice cropping systems using Landsat-derived Renormalized Index of Normalized Difference Vegetation Index （RNDVI） in the Poyang Lake Region, China

Mapping rice cropping systems with optical imagery in multiple cropping regions is challenging due to cloud contamination and data availability; development of a phenology-based algorithm with a reduced data demand is essential. In this study, the Landsat-derived Renorma- lized Index of Normalized Difference Vegetation Index （RNDVI） was proposed based on two temporal windows in which the NDVI values of single and early （or late） rice display inverse changes, and then applied to discriminate rice cropping systems. The Poyang Lake Region （PLR）, characterized by a typical cropping system of single cropping rice （SCR, or single rice） and double cropping rice （DCR, including early rice and late rice）, was selected as a testing area. The results showed that NDVI data derived from Landsat time-series at eight to sixteen days captures the temporal development of paddy rice. There are two key phenological stages during the overlapping growth period in which the NDVI values of SCR and DCR change inversely, namely the ripening phase of early rice and the growing phase of single rice as well as the ripening stage of single rice and the growing stage of late rice. NDVI derived from scenes in two temporal windows, specifically early August and early October, was used to construct the RNDVI for discriminating rice cropping systems in the polder area of the PLR, China. Comparison with ground truth data indicates high classification accuracy. The RNDVI approach highlights the inverse variations of NDVI values due to the difference of rice growth between two temporal windows. This makes the discrimination of rice cropping systems straightforward as it only needs to distinguish whether the candidate rice typeis in the period of growth （RNDVI 〈 0） or senescence （RNDVI 〉 0）.

基于MODIS-NDVI数据的延河流域植被覆盖时空变化及其对极端降水的响应

基于2010-2020年MODIS-NDVI数据,分析延河流域归一化植被指数(normalizeddifference vegetation index,NDVI)和极端降水指数,辅以利用Sen趋势分析、M-K趋势检验法、Pearson相关分析等方法,研究植被覆盖时空变化及其对极端降水的响应。结果表明:1)2010-2020年,延河流域NDVI呈显著增加趋势,植被覆盖状况逐年改善,其增加速率为0.073/(10 a)(P<0.001);2)空间上,延河流域NDVI呈现从东南到西北减小的布局;3)趋势上,NDVI呈上升和减小趋势的面积占比分别为98.02%和1.98%,整体呈上升趋势,植被覆盖显著改善;4)近11年极端降水指数总体趋势变化平缓,R20(number of very heavy precipitation days)、RX_(5day)(max5-day precipitation amount)、CDD(consecutive dry Days)和CWD(consecutive wet days)呈上升趋势,R_(95P)(very wet day precipitation)和SDII(simple daily intensity index)呈下降趋势;5)NDVI与极端降水指数的相关性整体上偏低,除SDII外,其余指数都与NDVI正相关,且NDVI与RX_(5day)相关性最强,与R20相关性最弱。

Correlation analysis of Normalized Different Vegetation Index(NDVI)difference series and climate variables in the Xilingole steppe,China from 1983 to 1999

There is a crucial need in the study of global change to understand how terrestrial ecosystems respond to the climate system.It has been demonstrated by many researches that Normalized Different Vegetation Index(NDVI)time series from remotely sensed data,which provide effective information of vegetation conditions on a large scale with highly temporal resolution,have a good relation with meteorological factors.However,few of these studies have taken the cumulative property of NDVI time series into account.In this study,NDVI difference series were proposed to replace the original NDVI time series with NDVI difference series to reappraise the relationship between NDVI and meteorological factors.As a proxy of the vegetation growing process,NDVI difference represents net primary productivity of vegetation at a certain time interval under an environment controlled by certain climatic conditions and other factors.This data replacement is helpful to eliminate the cumulative effect that exist in original NDVI time series,and thus is more appropriate to understand how climate system affects vegetation growth in a short time scale.By using the correlation analysis method,we studied the relationship between NOAA/AVHRR ten-day NDVI difference series and corresponding meteorological data from 1983 to 1999 from 11 meteorological stations located in the Xilingole steppe in Inner Mongolia.The results show that:(1)meteorological factors are found to be more significantly correlation with NDVI difference at the biomass-rising phase than that at the falling phase;(2)the relationship between NDVI difference and climate variables varies with vegetation types and vegetation communities.In a typical steppe dominated by Leymus chinensis,temperature has higher correlation with NDVI difference than precipitation does,and in a typical steppe dominated by Stipa krylovii,the correlation between temperature and NDVI difference is lower than that between precipitation and NDVI difference.In a typical steppe dominated by Stipa grandis,there is no significant difference between the two correlations.Precipitation is the key factor influencing vegetation growth in a desert steppe,and temperature has poor correlation with NDVI dif-ference;(3)the response of NDVI difference to precipitation is fast and almost simultaneous both in a typical steppe and desert steppe,however,mean temperature exhibits a time-lag effect especially in the desert steppe and some typical steppe dominated by Stipa krylovii;(4)the relationship between NDVI difference and temperature is becoming stronger with global warming.

冠层活性相关性状全基因组关联分析及其对产量性状遗传效应的解析

【目的】冠层活性是反映作物生长发育的重要指标,发掘小麦冠层活性相关基因并分析其与产量性状的关系,为解析产量遗传结构和辅助育种提供理论支撑。【方法】以166份国内外小麦品种为材料,将其种植于河南安阳和安徽濉溪,结合已构建的包含326570个来源于小麦90K和660K SNP芯片标记的高密度整合物理图谱,对苗期和花后10 d归一化植被指数(NDVI-S和NDVI-10)及花后10 d旗叶叶绿素含量(Chl-10)进行关联分析,并与前期利用相同材料得到的产量相关性状结果进行比较。【结果】NDVI-S、NDVI-10和Chl-10在基因型、环境及基因型×环境互作间变异方差均达极显著(P<0.01)差异,广义遗传力(hb2)分别为0.81、0.81和0.91。分别检测到13、12和15个与NDVI-S、NDVI-10和Chl-10显著相关的位点,其中,有12、11和12个为新位点,5个位点与2个以上性状有关。166份小麦品种含有NDVI-S、NDVI-10和Chl-10优异等位基因数变幅分别为4-11、3-11和4-12,且随着优异等位基因数目增加其对应表型值呈递增趋势。NDVI-S与千粒重、粒长和粒宽显著正相关(P<0.01);Chl-10与产量和旗叶宽显著正相关(P<0.01),与单位面积穗数、株高和穗下节长显著负相关(P<0.01)。检测到7个同时与产量和冠层活性相关的多效性位点。【结论】NDVI-S可用于品种产量性状的选择,检测到的稳定位点和多效性位点可在开发标记后用于育种材料的检测。

基于绿视率和NDVI的城市街道景观分析与优化研究

街道景观空间对市民健康和城市风貌具有重要影响。既往研究中常以归一化植被指数(NDVI)和绿视率(GVI)来分别代表二维和三维的绿色指标,但对二者的指标相关性研究甚少。采用基于深度学习的图像语义分割方法分析百度街景计算代表性街道的GVI,利用GF-1卫星数据计算NDVI,比较分析城市街道的GVI和NDVI指标特征及相关性。结果表明,1)中山市中心城区各代表街道GVI指标参差不齐,从8.06%到36.00%,其中石岐街道兴中道GVI最高;2)各街道观测点的NDVI均值随着缓冲区尺度的增加也随之呈现出不同变化,NDVI均值具有强烈的尺度敏感性;3)50 m GVI和DNVI均值的皮尔逊相关系数最高,达到0.832。在此基础上分析街道景观存在的不足并给出优化建议,为城市街景评估、空间优化、景观提升提供参考。

滴灌工程对农业生产能力的影响评估

滴灌工程作为干旱区绿洲灌溉农业增产增收的一项革命性技术工程,对农业生产和生态环境产生着深远影响。为了有效评估滴灌工程对农业生产能力的影响,将沙雅县作为研究区域,利用归一化差异植被指数(Normalized Difference Vegetation Index,NDVI)数据集、气象数据集和土地利用/覆被变化(Land Use/Cover Change,LUCC)数据集,对滴灌工程在建设与运行期间(2014-2022年)的县域NDVI及耕地面积时空变化进行分析。结果表明:①2014-2022年,全县耕地面积增加了83.83 km^(2),其中滴灌工程区占比71.22%。②滴灌工程区耕地NDVI平均增长率为0.44%/a,而非滴灌工程区耕地NDVI平均增长率仅为0.30%/a,滴灌工程区耕地NDVI变化较为明显。③滴灌工程实施后,年降水量降低了42.48%,然而县域NDVI却呈现出“增加—平缓—增加”的变化特征,平均增速为0.27%/a,平均增长11.53%。农业生产能力没有降低反而增加。滴灌工程的实施,不仅促进了土地流转与规模化经营,田块的破碎化程度降低,显著扩大了有效耕地面积,更重要的是县域农业产能(NDVI)与节水抗旱能力显著提升,沙雅县整体农业生产能力得到提高。因此,滴灌工程对于提高干旱区农业生产能力和生态环境具有重要意义。