塔里木河下游植被指数的遥感监测

为了了解塔里木河下游9次应急输水的生态环境效益，利用MODIS—NDVI最大合成法、差值法，分析了塔里木河下游植被指数的年际变化情况，结果表明：（1）塔里木河下游地区植被覆盖度变化中增加区面积呈增加趋势。（2）2002年与输水初期相比，植被覆盖度增加区主要分布于上段和中段的老塔里木河及其文阔尔河河道两侧，下段河道覆盖度增加区仅零星分布于距河道0．3km左右的地势低洼区域。2003年以后，下段植被覆盖度增加区面积已达84．30km^2，是2002年的3．16倍，主要分布在距离河道0．5km左右的河道两侧。至2007年塔里木河下游河道两侧植被覆盖度增加区的变化是比较显著的，特别是下段植被覆盖增加区呈带状分布于距河道1．5km左右的范围内。植被指数遥感监测说明塔里木河下游地区的生态环境得到明显改善。     

1982—2022年黄土高原归一化植被指数变化的时空特征

长时间地表植被指数变化序列构建与分析是生态环境监测领域的重要内容。以我国生态工程建设重点地区——黄土高原为研究区，采用时间序列的方差匹配方法，融合了2套卫星遥感的归一化植被指数(NDVI)数据产品(GIMMS 3g和MODIS),建立了覆盖1982—2022年的黄土高原暖季(5—9月)NDVI数据集，揭示了其间黄土高原植被覆盖变化的时空特征。研究发现：黄土高原暖季NDVI呈现“先慢后快”的增加趋势，转折点大致出现在2002年，1982—2002年暖季NDVI增速仅为0.01/(10 a),2003—2022年增速高达0.06/(10 a),其中十八大以来增速尤为显著；暖季NDVI快速增加区域主要位于黄土高原中部，并向东北、西南方向延展，与“退耕还林(草)”重点区域范围基本一致；在黄土高原南部、东部和青海省东部一带，暖季NDVI呈缓慢下降趋势。过去40年间黄土高原NDVI增加与生态工程建设关系密切。     

2001-2005年新疆植被覆盖动态变化及原因分析

利用2001-2005年新疆归一化植被指数NDVI,得出该时间段新疆植被覆盖整体呈增加趋势,但局部有退化现象.对2001 - 2005年植被覆盖变化原因进行了分析,阐明降水是新疆植被覆盖变化的主要驱动因子之一.     

20年间艾比湖流域植被覆盖度景观格局变化

选取艾比湖流域1990年、2001年、2011年同期（9月）3期I．and．satTM遥感影像，基于归一化植被指数NDVI，提取植被覆盖等级图，利用ArcGIS9．3和Fragstas3．3对该流域植被景观的变化进行了分析研究。结果表明：1990—2011年，该流域植被覆盖度变化明显，低植被覆盖区和较低植被覆盖区都有所减少，分别由1990年的34．05％和32．94％减少到2011年的32．8％和24．06％；较高植被覆盖区和高植被覆盖区有所增加，分别由8．49％和5．20％增长到15．13％和9．83％，但水域面积退化明显，由1990年的525．9765km2缩小至494．9876km2，减少了30．9889km2，退缩幅度达O．4％；最大斑块指数（LPI）由17．04上升到21．10，香农多样性指数（SHDI）和香农均势度指数（SHEI）分别由1．5387和0．8588增长到1．6395和0．9150。表明艾比湖流域景观格局混杂程度愈来愈高，空间异质性在逐年加强，总体空间格局向破碎化趋势发展。     

基于神东中心区植被覆盖变化的多时相遥感监测

准确、快速地获取植被覆盖信息是矿区生态恢复和建设的关键与重点。以神东中心区为研究对象,利用2002、2005、2007、2010、2012年Landsat TM/ETM+和HJ1A-CCD1五景同期遥感数据,采用像元二分模型法,归一化植被指数(NDVI)值反演植被覆盖度,对研究区生态环境变化规律进行分析。结果表明,神东中心区平均植被覆盖度整体呈上升趋势,区内绝大部分地表覆盖程度得到改善,改善区面积达64.01%,退化区面积只有15.34%。该方法快速、定量地反映矿区植被覆盖及变化情况,为矿区生态环境动态监测和治理提供技术支持。     

基于TM影像的桂林市植被覆盖时空动态监测与分析

以西部地区中等规模城市——桂林市为例,利用1991、2006年两期TM卫星影像数据,在对原始数据预处理的基础上,提取归一化植被指数(NDVI)。依据混合像元二分模型,生成桂林市所辖5城区的两期植被覆盖度监测分类图像,对区域植被覆盖状况进行时空动态变化分析。结果表明,1991年~2006年间,城市植被覆盖区面积总体呈现下降趋势;在划分的3类植被覆盖类型中,低植被覆盖区面积减少幅度最为明显,中、高植被覆盖区面积有不同程度增长;低植被覆盖区主要分布在城市建成区与一些村镇外围区域,中、高植被覆盖区集中分布在城市远郊地带。此外,随着城市化的迅速发展,城乡各类建设用地面积不断增加,城市边缘地带的绿色植被正逐步被人工景观所取代。     

基于遥感和像元二分模型的新疆植被覆盖度格局动态监测

利用MODIS归一化植被指数(NDVI)资料反演了2006—2015年新疆植被覆盖状况,获取不同时期的植被覆盖度图,并进一步分析了植被覆盖度变化的原因。结果表明:新疆植被覆盖度呈现北部高于南部、西部高于东部的分布特征,其中西部和西北部的山地森林、草地以及天山北坡绿洲农作物、草地区域植被覆盖情况最好。过去10年间,新疆植被覆盖度总体呈上升趋势,2015年植被覆盖度达到最高,为16.68%。生态恢复工程、降水和气温等是影响植被覆盖度变化的主要因素。     

基于Sentinel-2数据的苏州消夏湾生态安全缓冲区植被生长状况遥感监测评估

利用2021—2022年Sentinel-2卫星搭载的多光谱成像仪（MSI）遥感数据，通过SNAP遥感软件提供的植被生物物理参数处理模块（Biophysical Processor），反演了苏州消夏湾生态安全缓冲区的5种植被生物物理参数，包括植被吸收光合有效辐射比例（FAPAR）、植被覆盖度（FVC）、叶面积指数（LAI）、冠层叶绿素含量（CCC）和冠层含水量（CWC），开展植被生态环境监测评估研究。结果表明，该生态安全缓冲区2021年建成并投入运行后，植被覆盖度和生物量有所增加，区域植被冠层结构有所改善，植被生物物理参数从一定的角度反映了消夏湾生态安全缓冲区发挥了生态涵养成效。该研究方法能在大尺度上快捷、高效地反演植被生物物理参数，可为通过植被遥感动态监测评估生态安全缓冲区的生态功能提供有益的借鉴。     

基于Sentinel-2与随机森林算法的太湖水生植被分布监测

基于2018—2021年太湖地区哨兵2号（Sentinel-2）卫星遥感影像和随机森林算法，结合植被敏感指数，开展太湖水生植被分布监测，综合分析了水生植被的时空变化特征，初步揭示了太湖水生植被的动态变化。结果表明，太湖水生植被分布面积有逐年上升的趋势，且年间变化具有明显的单峰型特征，表现为春季沉寂，夏季快速增长，秋季达到暴发期，冬季面积开始减退；太湖水生植被主要分布于东太湖、东部沿岸和贡湖，类型以沉水植被为主，其中浮叶植被主要分布于东太湖，挺水植被主要分布于东太湖沿岸的浅水区域；沉水植被主要分布于东部沿岸和贡湖；水生植被主要分布的东太湖水域，其水质总体优于太湖其他水域。     

塔里木河重要生态功能区生态环境质量评价

采用长时间多源遥感数据对塔里木河重要生态功能区进行了土地利用变化、植被指数分析,同时结合多年地面调查监测数据,系统分析了区域生态环境变化情况,并对近五年区域生态环境质量开展了评价,环境质量变化值ΔI为2.58,生态环境质量略有下降,其中环境状况指标和植被覆盖率指数起主导作用。     

River pollution remediation monitored by optical and infrared high-resolution satellite images

The Bormida River Basin, located in the northwestern region of Italy, has been strongly contaminated by the ACNA chemical factory. This factory was in operation from 1892 to 1998, and contamination from the factory has had deleterious consequences on the water quality, agriculture, natural ecosystems and human health. Attempts have been made to remediate the site. The aims of this study were to use high-resolution satellite images combined with a classical remote sensing methodology to monitor vegetation conditions along the Bormida River, both upstream and downstream of the ACNA chemical factory site, and to compare the results obtained at different times before and after the remediation process. The trends of the Normalised Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) along the riverbanks are used to assess the effect of water pollution on vegetation. NDVI and EVI values show that the contamination produced by the ACNA factory had less severe effects in the year 2007, when most of the remediation activities were concluded, than in 2006 and 2003. In 2007, the contamination effects were noticeable up to 6 km downstream of the factory, whereas in 2003 and 2006 the influence range was up to about 12 km downstream of the factory. The results of this study show the effectiveness of remediation activities that have been taking place in this area. In addition, the comparison between NDVI and EVI shows that the EVI is more suitable to characterise the vegetation health and can be considered an additional tool to assess vegetation health and to monitor restoration activities.     

Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p?<?0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p?<?0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management.     

Impacts of ecological water conveyance on groundwater dynamics and vegetation recovery in the lower reaches of the Tarim River in northwest China

The ecological water conveyance project (EWCP) in the lower reaches of the Tarim River provided a valuable opportunity to study hydro-ecological processes of desert riparian vegetation. Ecological effects of the EWCP were assessed at large spatial and temporal scales based on 13 years of monitoring data. This study analyzed the trends in hydrological processes and the ecological effects of the EWCP. The EWCP resulted in increased groundwater storage—expressed as a general rise in the groundwater table—and improved soil moisture conditions. The change of water conditions also directly affected vegetative cover and the phenology of herbs, trees, and shrubs. Vegetative cover of herbs was most closely correlated to groundwater depth at the last year-end (R?=?0.81), and trees and shrubs were most closely correlated to annual average groundwater depth (R?=?0.79 and 0.66, respectively). The Normalized Difference Vegetation Index (NDVI) responded to groundwater depth on a 1-year time lag. Although the EWCP improved the NDVI, the study area is still sparsely vegetated. The main limitation of the EWCP is that it can only preserve the survival of existing vegetation, but it does not effectively promote the reproduction and regeneration of natural vegetation.     

Applying Satellite Imagery to Triage Assessment of Ecosystem Health

Considerable evidence documents that certain changes in vegetation and soils result in irreversibly degraded rangeland ecosystems. We used Advanced Very High Resolution Radiometer (AVHRR) imagery to develop calibration patterns of change in the Normalized Difference Vegetation Index (NDVI) over the growing season for selected sites for which we had ground data and historical data characterizing these sites as irreversibly degraded. We used the NDVI curves for these training sites to classify and map the irreversibly degraded rangelands in southern New Mexico. We composited images into four year blocks: 1988–1991, 1989–1992, and 1990–1993. The overlap in pixels classified as irreversibly degraded ranged from 42.6% to 84.3% in year block comparisons. Quantitative data on vegetation composition and cover were collected at 13 sites within a small portion of the study area. Wide coverage reconnaissance of boundaries between vegetation types was also conducted for comparisons with year block maps. The year block 1988–1991 provided the most accurate delineation of degraded areas. The rangelands of southern New Mexico experienced above average precipitation from 1990–1993. The above average precipitation resulted in spatially variable productivity of ephemeral weedy plants on the training sites and degraded rangelands which resulted in much smaller areas classified as irreversibly degraded. We selected imagery for a single year, 1989, which was characterized by the absence of spring annual plant production in order to eliminate the confounding effect of reflectance from annual weeds. That image analysis classified more than 20% of the rangelands as irreversibly degraded because areas with shrub-grass mosaic were included in the degraded classification. The single year image included more than double the area classified as irreversibly degraded by the year blocks. AVHRR imagery can be used to make triage assessments of irreversibly degraded rangeland but such assessment requires understanding productivity patterns and variability across the landscapes of the region and careful selection of the years from which imagery is chosen.     

The spatiotemporal dynamics of urbanisation and local climate: A case study of Islamabad,Pakistan

Rapid and unplanned urbanisation, together with climate change, are increasingly affecting the local climatic conditions of urban settlements. Spatiotemporal analysis using land use/land cover (LULC), land surface temperature (LST), and local climatic zone (LCZ) assessments have been helpful in understanding the urbanisation characteristics and morphology. Islamabad, the capital and the only planned city of Pakistan, has witnessed a consistent rise in local temperatures, increased built-up areas, and reduced vegetation cover during the past decades. This study explores the spatiotemporal dynamics of LULC, LST, and LCZ in Islamabad using satellite remote sensing data and spectral indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The results indicate a whopping increase in a built-up area in the city (113% during 2013 and 2019). A positive correlation between LST and NDBI, whereas a negative correlation between LST and NDVI clearly indicates how urbanisation (and reduction in vegetation cover) are impacting the local temperatures. Assessment and analysis of LCZs helped to understand the variations and deviations of current LULC from the master plan. It was observed that compact low-rise urban development is the most prevalent. The outcomes of this study are expected to inform the urban planners, climatologists, and policymakers with the knowledge helpful for devising climate-resilient development policies that could reduce thermal stresses in the capital cities.     

A change vector analysis technique for monitoring land cover changes in Copsa Mica,Romania, in the period 1985–2011

During the communist regime, Romania’s planned economy focused exclusively on production neglecting the environment protection. The lack of less polluting production technologies and of environmental protection measures led to excessive pollution in certain industrialized areas. This is the case of the town of Copsa Mica in Sibiu County, which in 1987 was considered one of the most polluted towns in Europe. The present study assesses the change vector analysis (CVA) technique using a Landsat Thematic Mapper (TM) image time series to monitor land cover changes caused by carbon black and heavy metal pollution. CVA was applied to the tasseled cap greenness (TCG) and tasseled cap brightness (TCB) indices, as well as to the Normalized Difference Vegetation Index (NDVI) and bare soil index (BI). Various maps were generated for the periods 1985–1994, 1994–2003, 2003–2011, and 1985–2011, and threshold values were determined for the detection of land cover change/no change. The change direction and magnitude values were cross-tabulated and classified. The technique was assessed based on the change versus no-change error matrix. The results show that in the area of Copsa Mica, land cover changes occurred because of a considerable decrease in the area affected by carbon black and heavy metal pollution. The CVA technique proved efficient in monitoring the land cover changes caused by pollution and especially by carbon black pollution. Soil pollution by heavy metals is reflected in the bare soil surfaces present in the imagery.     

Using NDVI to Assess Vegetative Land Cover Change in Central Puget Sound

We used the Normalized Difference Vegetation Index (NDVI) in the rapidly growing Puget Sound region over three 5-year time blocks between 1986–1999 at three spatial scales in 42 Watershed Administrative Units (WAUs) to assess changes in the amounts and patterns of green vegetation. On average, approximately 20% of the area in each WAU experienced significant NDVI change over each 5-year time block. Cumulative NDVI change over 15 years (summing change over each 5-year time block) was an average of approximately 60% of each WAU, but was as high as 100% in some. At the regional scale, seasonal weather patterns and green-up from logging were the primary drivers of observed increases in NDVI values. At the WAU scale, anthropogenic factors were important drivers of both positive and negative NDVI change. For example, population density was highly correlated with negative NDVI change over 15 years (r = 0.66, P < 0.01), as was road density (r = 0.71, P < 0.01). At the smallest scale (within 3 case study WAUs) land use differences such as preserving versus harvesting forest lands drove vegetation change. We conclude that large areas within most watersheds are continually and heavily impacted by the high levels of human use and development over short time periods. Our results indicate that varying patterns and processes can be detected at multiple scales using changes in NDVIa values.     

Monitoring global change: Comparison of forest cover estimates using remote sensing and inventory approaches

Satellite-based remote sensing offers great potential for frequent assessment of forest cover over broad spatial scales, however, calibration and validation using ground-based surveys are needed. In this study, forest cover estimates for the United States from a recently developed land surface cover map generated from satellite remote sensing data were compared to state-level inventory data from the U.S. National Resources Planning Act Timber Database. The land cover map was produced at the U.S. Geological Survey EROS Data Center and is based on imagery from the AVHRR sensor (spatial resolution 1.1 km). Vegetation type was classified using the temporal signal in the Normalized Difference Vegetation Index derived from AVHRR data. Comparisons revealed close agreement in the estimate of forest cover for extensively forested states with large polygons of relatively similar vegetation such as Oregon. Larger forest cover differences were observed in other states with some regional patterns in the level of agreement apparent.Comparisons in inventory- and remote sensing-based estimates of current forested area with potential vegetation maps indicated the magnitude of past land use change and the potential for future changes. The remote sensing approach appears to hold promise for conducting surveys of forest cover where inventory data are limited or where rates of vegetation change, due to human or climatic factors, are rapid.