Normalized Difference Vegetation Index Ratio Research Articles

Can Indoor Residents Perceive Green and Blue Spaces in Communities as Posted Sentiments? A Verification in Nanchang

Ecological infrastructures (EIs), such as public and urban green and blue spaces (GBSs), have been well demonstrated to benefit visitors’ mental well-being. Experiences in community GBSs may also evoke positive emotions for their residents. In this study, 54 communities in Nanchang were chosen as objective sites, where landscape metrics of GBSs were remotely evaluated. A total of 2105 local residents’ facial expressions (with happy, sad, and neutral emotions) were obtained from Sina Weibo. Inhabitants showed more net positive emotions (happy minus sad) in cold seasons, and females smiled more frequently than males. Newly constructed communities with houses for sale had larger areas of normalized difference vegetation index (NDVI) and built-up index compared to communities with no houses for sale. Neither the availability of houses for sale nor housing price had any effect on facial expression scores. Poisson regression revealed significant coefficients (β) of positive emotions with largeness of green space (GS) and blue space (BS). Overall, BS had a stronger contribution (β, 0.6–1.1) to residents showing positive emotions relative to GS (β, −2.45–0.89), whose area ratio of NDVI increased the frequency of showing happiness. We recommend constructing GBSs with over 0.68 km2 of GS and over 2000 m2 of BS per community, where the area ratio of GS should be more than 70% of the total if the goal is to evoke more happiness in residents.

Nonlinear effects of thermokarst lakes on peripheral vegetation greenness across the Qinghai-Tibet Plateau using stable isotopes and satellite detection

Thermokarst lakes (TLs) widespread in thawing permafrost can degrade vegetation through thermomechanical erosion and waterlogging. However, whether TLs change water sources and alleviate water stress for plants is unknown, and previous knowledge about regional TL effects on surrounding vegetation greenness is rare. Here, we synthesized field investigations, stable isotopes, and remote sensing images from an unmanned aerial vehicle and Sentinel-2 to determine the effects of over 160,000 TLs on their surrounding growing-season normalized difference vegetation index (NDVI) in the Qinghai-Tibet Plateau. The results are as follows: 1) With the largest water source shifting from 0 to 10 cm soil water to lake water, TL-affected plants can grow better than TL-unaffected plants, which is associated with soil texture and the development stage of the lake. 2) Overall, the median affecting distances of TLs on surrounding surface moisture (tasseled cap wetness, TCW) and NDVI were 50 m with their 25th–75th percentiles of 40–70 m and 40–60 m, respectively; compared with the unaffected areas, TLs increased peripheral TCW but reduced NDVI with their median change rates of 19.84% and −10.42%, respectively. 3) However, the nonlinear response of NDVI to the TCW gradient was dominant, which was featured by a local peak NDVI due to the coexistence of the physical destruction and improved water availability, and both TCW and NDVI at the peak area were explicitly larger than those at the unaffected area. 4) Along southeast-northwest environmental gradients (topographic, climatic, and edaphic factors), the affected range and degradation ratio of NDVI were greater under drier climate, larger lake area, sand-richer soil, fewer soil nutrients, and worse vegetation type (e.g., alpine desert). Briefly, the net adverse consequence on NDVI suggests that TLs primarily represent permafrost-supported ecosystems deteriorating, but the clear nonlinear effects advance the knowledge of this landscape; additionally, these local vegetation changes can help interpret the regional greening/browning and promote the research on the biogeochemical interaction among TL, soil, and plants under climate warming and permafrost thawing.

Study on the Classification and Change Detection Methods of Drylands in Arid and Semi-Arid Regions

The aim of this study was to clarify the distribution of irrigated drylands in arid and semi-arid areas, where complex terrain, diverse crops and staggered cultivated lands exist. This paper studied the classification methods of irrigated drylands based on temperature, precipitation, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) from Landsat data in the one-harvest area of the northern Loess Plateau of China by using the Google Earth Engine (GEE) platform. An extraction method was proposed for irrigated drylands in arid and semi-arid regions of northwest China. In addition, the change types of irrigated and rainfed drylands in the two periods were classified, and a method was also put forward to directly classify the change types by using the image differences between the two periods combined with the classification results of each period. It was found that combining the ratio of NDVI and NDWI with the accumulated values of temperature and precipitation of the 30 days before imaging could effectively improve the classification accuracy. Moreover, directly classifying the gaps of remote sensing factors in the time dimension before combining spatial clustering information could yield a more accurate type of change, because the accumulation of errors in the change maps obtained from the overlay analysis of distribution maps of the two periods could be avoided. The accuracy of classification could be improved by introducing the dynamic information of time dimension into the classification of historical periods. This study complements the extraction method for this type of irrigated dryland, and the classification results can improve the accuracy of existing products in terms of spatial resolution, which can fill the shortage of detailed distribution data for irrigated and rainfed drylands in this region.

基于夜间灯光数据的甘青宁城市扩展及其建成区植被变化特征

PDF HTML阅读 XML下载 导出引用 引用提醒 基于夜间灯光数据的甘青宁城市扩展及其建成区植被变化特征 DOI: 10.5846/stxb202005141227 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 甘肃农业大学大学生创新创业计划项目（202102045）；国家自然科学基金青年项目（41907406）；甘肃农业大学科技创新基金（GAU-KYQD-2018-23） Characteristics of urban expansion and vegetation change in built-up areas of Gan-Qing-Ning based on nighttime light data Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:开展针对黄河上游甘青宁地区城市建成区空间发展模式及其植被变化特征的研究，可为构建科学合理的城市发展体系、维护区域生态安全屏障提供重要的参考依据。以DMSP/OLS和统计数据为基础，运用统计数据比较法提取了甘青宁地区21座地级市（州）的城市建成区边界，并从城市空间扩展特征、扩展速度、动态度、紧凑度和重心迁移5个方面对城市扩展特征进行分析；在此基础上，引入SPOT/VEGETATION NDVI数据，以年均NDVI作为表征城市建成区植被状况的指标，从NDVI总和、均值、比值及其变化量、年际变化率及其变化百分率和稳定性5个方面对研究区2002-2013年城市建成区的植被变化进行研究。结果表明：1）采用统计数据比较法提取获得的研究区城市建成区精度较高，误差率在6.7%以内；2）城市用地围绕河西走廊及黄河上游地区形成不连续的"几"字型空间形态，并具有点状、线状和面状3种不同的分布模式；3）城市扩展年均速及动态度大体呈上升趋势，且2010-2013年的城市扩展速度（4.53 km2/a）是2006-2010年的2倍；4）除酒泉、海西、白银、天水、石嘴山和兰州外，其他城市建成区紧凑度指数均较高；5）城市重心在第一（2002-2006）和第二阶段（2006-2010）均向北发生迁移，在第三阶段（2010-2013）则向南发生迁移；6）城市建成区NDVI总和随建成区面积的增加呈上升趋势；7）城市建成区植被整体呈向好趋势，从NDVI均值看，2002-2006年植被状况变差，而2006-2013年又有所改善，且NDVI均值分布具有明显的空间差异，中西部地区普遍小于东部；从NDVI年际变化率和变化百分率来看，各城市建成区均大于外围背景区；8）城市建成区植被状况普遍较背景区差，且2002-2013年近4/7的城市建成区NDVI比值及其变化量均呈下降趋势；9）城市建成区植被稳定性普遍较差，半数以上城市的变异系数在12年间均有不同程度的增加。 Abstract:Carrying out research on the spatial development pattern and vegetation change characteristics of urban built-up areas in the Gan-Qing-Ning region on the upper reaches of the Yellow River can provide an important reference for building a scientific and reasonable urban development system and maintaining regional ecological security barriers. Based on DMSP/OLS and statistical data, this paper extracted the urban built-up area boundaries of 21 prefecture-level cities (prefectures) in Gan-Qing-Ning region by using statistical data comparison method, and analyzed the urban expansion characteristics from five aspects:urban spatial expansion characteristics, expansion speed, dynamic degree, compactness and center of gravity transfer. On this basis, the SPOT/VEGETATION NDVI (Normalized Difference Vegetation Index) data was introduced, and the annual average NDVI was used as an indicator to represent the vegetation status in urban built-up areas. The vegetation change of urban built-up areas in the study area from 2002 to 2013 was studied from five aspects:sum, mean, ratio and its change amount, interannual change rate, percentage and stability of NDVI. The results showed that:1) As one of the effective methods to extract urban built-up area, the statistical data comparison method had high accuracy in our study area, and the error rate was within 6.7%. 2) The urban land formed a discontinuous spatial pattern of "几" around the Hexi Corridor and the upper reaches of the Yellow River, and had three different distribution patterns:point, line and plane. 3) The annual average rate and dynamic degree of urban expansion showed an upward trend, and the rate of urban expansion during 2010-2013 (4.53 km2/a) was twice as high as that during 2006-2010. 4) Except for Jiuquan, Haixi, Baiyin, Tianshui, Shizuishan and Lanzhou, the compactness index of other urban build-up areas was relatively high. 5) In the first stage (2002-2006) and the second stage (2006-2010), the center of gravity shifted northward, and in the third stage (2010-2013), the center of gravity shifted southward. 6) The total NDVI of urban built-up area increased with the increase of built-up area. 7) The vegetation in urban built-up areas showed a positive trend on the whole. From the perspective of the mean NDVI, the vegetation condition got worse from 2002 to 2006, and improved from 2006 to 2013. Moreover, the mean NDVI distribution showed obvious spatial differences, and the central and western regions were generally smaller than the eastern ones. From the perspective of the interannual variation rate and percentage of NDVI, the built-up area of each city was larger than the peripheral background area. 8) The vegetation status in urban built-up areas was generally worse than that in background areas, and the NDVI ratio and its variation in nearly 4/7 urban built-up areas showed a downward trend from 2002 to 2013. 9) Vegetation stability in urban built-up areas was poor, and the variation coefficients of more than half of the cities increased to varying degrees in the past 12 years. 参考文献 相似文献 引证文献

Rapid vegetation recovery at landslide scars detected by multitemporal high-resolution satellite imagery at Aso volcano, Japan

Vegetation cover is an important factor in hillslope stability and landslide susceptibility. The objective of this study is to explore vegetation recovery in rainfall-induced and coseismic landslide scars at the Aso volcano in Japan. We focus on the temporal changes and effect of topography on vegetation recovery using multitemporal satellite images of RapidEye from 2010 to 2019 and PlanetScope from 2016 to 2020 and finer spatial resolution images of unmanned aerial vehicles (UAVs). The study area is characterized by semi-natural grassland and frequent landslide events triggered by heavy rainfall in 2012 and the 2016 Kumamoto earthquake. This study validates grass vegetation recovery using the normalized difference vegetation index (NDVI) and NDVI ratio, which represents the relative difference in NDVI between the landslide scars and grass areas. The results show a distinct decrease in the NDVI ratio at landslide scars after the heavy rainfall and Kumamoto earthquake. The NDVI ratio rapidly increases in landslide scars after the events. The results indicate that NDVI at both landslide scars will reach the same level as the pre-landslide grass vegetation within 12 years. The slope aspect direction determines the topographic effects of grass vegetation recovery. The north- to west-facing landslide scars seemed to experience rapid grass vegetation recovery.

Leveraging time series analysis of radar coherence and normalized difference vegetation index ratios to characterize pre-failure activity of the Mud Creek landslide, California

Abstract. Assessing landslide activity at large scales has historically been a challenging problem. Here, we present a different approach on radar coherence and normalized difference vegetation index (NDVI) analyses – metrics that are typically used to map landslides post-failure – and leverage a time series analysis to characterize the pre-failure activity of the Mud Creek landslide in California. Our method computes the ratio of mean interferometric coherence or NDVI on the unstable slope relative to that of the surrounding hillslope. This approach has the advantage that it eliminates the negative impacts of long temporal baselines that can interfere with the analysis of interferometric synthetic aperture (InSAR) data, as well as interferences from atmospheric and environmental factors. We show that the coherence ratio of the Mud Creek landslide dropped by 50 % when the slide began to accelerate 5 months prior to its catastrophic failure in 2017. Coincidentally, the NDVI ratio began a near-linear decline. A similar behavior is visible during an earlier acceleration of the landslide in 2016. This suggests that radar coherence and NDVI ratios may be useful for assessing landslide activity. Our study demonstrates that data from the ascending track provide the more reliable coherence ratios, despite being poorly suited to measure the slope's precursory deformation. Combined, these insights suggest that this type of analysis may complement traditional InSAR analysis in useful ways and provide an opportunity to assess landslide activity at regional scales.

Climate Change May Increase the Drought Stress of Mesophytic Trees Downslope With Ongoing Forest Mesophication Under a History of Fire Suppression

In mountainous headwater catchments, downslope flow of subsurface water could buffer downslope forest communities from soil moisture stress during drought. Here we investigated changes in landscape-scale vegetation patterns at five forested headwater catchments in the Coweeta Hydrologic Laboratory in the southern Appalachians. We used a ca. 30-year Landsat Thematic Mapper (TM) image record of normalized difference vegetation index (NDVI), spanning a period of recorded warming since the mid-1970. We then, related spatial and temporal canopy patterns to seasonal water balance, streamflow recession behavior, and low flow dynamics from the long-term hydrologic records. All hydrologic metrics indicated increasing evapotranspiration, decreasing streamflow given precipitation, and potentially decreasing downslope subsidy at the watershed scale over time, especially during low-flow periods. Contrary to expectations, leaf area index (LAI) and basal area increased more upslope compared to downslope over time, coincident with warming. Trends in the ratio of NDVI in upslope and downslope topographic positions were also supported by long-term tree basal area increment, litterfall, and sap flux data in one of the reference watersheds. Mesophytic trees downslope appeared to respond more to frequent droughts and experience lower growth than xerophytic trees upslope, closely mediated by the isohydric/anisohydric continuum along hydrologic flow paths. Considering ongoing forest “mesophication” under a history of fire suppression across the eastern US deciduous forests, this study suggests that mesophytic trees downslope may be more vulnerable than xerophytic trees upslope under ongoing climate change due to an apparent dependence on upslope water subsidy.

Evaluating street view exposure measures of visible green space for health research.

Urban green space, or natural environments, are associated with multiple physical and mental health outcomes. Several proposed pathways of action for these benefits (e.g., stress reduction and attention restoration) require visual perception of green space; however, existing green space exposure measures commonly used in epidemiological studies do not capture street-scale exposures. We downloaded 254 Google Street View (GSV) panorama images from Portland, Oregon and calculated percent of green in each image, called Green View Index (GVI). For these locations we also calculated satellite-based normalized difference vegetation index (NDVI), % tree cover, % green space, % street tree buffering, distance to parks, and several neighborhood socio-economic variables. Correlations between the GVI and other green space measures were low (-0.02 to 0.50), suggesting GSV-based measures captured unique information about green space exposures. We further developed a GVI:NDVI ratio, which was associated with the amount of vertical green space in an image. The GVI and GVI:NDVI ratio were weakly related to neighborhood socioeconomic status and are therefore less susceptible to confounding in health studies compared to other green space measures. GSV measures captured unique characteristics of the green space environment and offer a new approach to examine green space and health associations in epidemiological research.

Study of NDVI Application on Turbidity in Reservoirs

Turbidity (TB), an important factor that determines water quality, can influence the water supply of reservoirs. Using a submerged optical sensor, the TB of a body of water can be observed. This study aims to use remote sensing (RS) technology in order to examine TB variations of the water in reservoirs. In general, previous studies have focused on evaluating the relationships among a number of single-spectrum bands and in situ data. In this study, we included the Normalized Difference Vegetation Index (NDVI) among the TB monitoring methods for reservoirs and investigated its practical utility. The ratio of NDVI is between −1 and 1. A negative value indicates water or snow; a value of 0 indicates rock or bare soil; and a positive value indicates a vegetative cover. We consider the value of NDVI to be close to −1 in clean water and close to 0 in turbid water. TB, which is the scattering degree of incident light into water, is observed using a submerged optical sensor. Water appears turbid if floating material or suspended solids are found. Therefore, we use NDVI in this study in an attempt to estimate TB concentration. Images from the Landsat-7 ETM+ satellite were used to observe several important reservoirs in northern Taiwan, and multiple linear regression (MLR) was used for analysis. This study examines the data of 47 samples and found the gaps between the 3 days of the in situ date and the date the images were taken. We found that the NDVI has a negative correlation with TB. After including the NDVI in our model, its explaining ability and improvement rate increased by 11.2 and 8.72 %, respectively. Therefore, using the NDVI can provide additional reflective information, as well as improve the model’s accuracy.

Correlations Between Hybrid Bermudagrass Morphology and Wear Tolerance

Hybrid bermudagrasses (Cynodon dactylon × C. transvaalensis) typically have excellent wear tolerance when compared with other turfgrass species. This trait should be evaluated during variety development to reduce the risk of failure when new grasses are planted in areas with traffic stress. The objective of this research was to evaluate the wear tolerance of four hybrid bermudagrasses with differing morphological characteristics. Traffic was applied to the hybrid bermudagrass varieties ‘Tifway’, ‘TifSport’, and ‘TifTuf’, as well as an experimental hybrids (04-76) using a traffic simulator for 6 weeks. Leaf morphology (leaf width, length, and angle) and quantitative measure of density and color [normalized difference vegetation index ratio (NDVI), dark green color index (DGCI), and percent green turf color] were characterized before traffic, and then percent green turf color after 6 weeks of traffic was measured to estimate wear tolerance. ‘TifTuf’ hybrid bermudagrass provided the greatest wear tolerance, as well as the narrowest and shortest leaf lengths, greatest NDVI values and percent green color, and lowest DGCI before traffic. Conversely, 04-76 produced the poorest wear tolerance, as well as the widest and longest leaves, lowest NDVI values and percent green color, and highest DGCI values before traffic. Regression analysis determined that DGCI, leaf length, and leaf width were inversely, or negatively, correlated to wear tolerance, whereas percent green turf color before traffic was directly correlated to wear tolerance. For these hybrids, DGCI had the strongest correlation to increased wear tolerance.

Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data

In this study, we have used four methods to investigate the start of the growing season (SGS) on the Tibetan Plateau (TP) from 1982 to 2012, using Normalized Difference Vegetation Index (NDVI) data obtained from Global Inventory Modeling and Mapping Studies (GIMSS, 1982–2006) and SPOT VEGETATION (SPOT-VGT, 1999–2012). SGS values estimated using the four methods show similar spatial patterns along latitudinal or altitudinal gradients, but with significant variations in the SGS dates. The largest discrepancies are mainly found in the regions with the highest or the lowest vegetation coverage. Between 1982 and 1998, the SGS values derived from the four methods all display an advancing trend, however, according to the more recent SPOT VGT data (1999–2012), there is no continuously advancing trend of SGS on the TP. Analysis of the correlation between the SGS values derived from GIMMS and SPOT between 1999 and 2006 demonstrates consistency in the tendency with regard both to the data sources and to the four analysis methods used. Compared with other methods, the greatest consistency between the in situ data and the SGS values retrieved is obtained with Method 3 (Threshold of NDVI ratio). To avoid error, in a vast region with diverse vegetation types and physical environments, it is critical to know the seasonal change characteristics of the different vegetation types, particularly in areas with sparse grassland or evergreen forest.

Evaluating salinity damage to crops through satellite data analysis: application to typhoon affected areas of southern Japan

In recent times, tsunamis and typhoons have threatened Japan’s coastal lands with increased flooding and salinity. Using satellite data, we monitored the effect of increased salinity on vegetation health in the coastal area of southern Japan, which was affected by flooding following Typhoon 9918 in 1999. An index of plant activity called the Normalized Difference Vegetation Index (NDVI) was evaluated before and after the typhoon, and the change in NDVI was computed as a comparison measure. The results were then correlated with electric conductivity, which is a measure of soil salinity. A strong negative correlation was found between NDVI ratio and salt concentration (r = − 0.7731, n = 50, p < 0.0001), indicating that the reduced NDVI values were attributable to increased salinity from the flooding. These results not only provide useful insight into a rapid method of assessing large-scale flood impacts using satellite data, but also validate the monitoring of NDVI as an indicator of salinity damage to vegetation. To summarise, by understanding the changes in vegetation health following natural disasters such as flooding (as revealed by NDVI), we can potentially develop improved management strategies.

Seasonal Response of Grasslands to Climate Change on the Tibetan Plateau

BackgroundMonitoring vegetation dynamics and their responses to climate change has been the subject of considerable research. This paper aims to detect change trends in grassland activity on the Tibetan Plateau between 1982 and 2006 and relate these to changes in climate.Methodology/Principal FindingsGrassland activity was analyzed by evaluating remotely sensed Normalized Difference Vegetation Index (NDVI) data collected at 15-day intervals between 1982 and 2006. The timings of vegetation stages (start of green-up, beginning of the growing season, plant maturity, start of senescence and end of the growing season) were assessed using the NDVI ratio method. Mean NDVI values were determined for major vegetation stages (green-up, fast growth, maturity and senescence). All vegetation variables were linked with datasets of monthly temperature and precipitation, and correlations between variables were established using Partial Least Squares regression. Most parts of the Tibetan Plateau showed significantly increasing temperatures, as well as clear advances in late season phenological stages by several weeks. Rainfall trends and significant long-term changes in early season phenology occurred on small parts of the plateau. Vegetation activity increased significantly for all vegetation stages. Most of these changes were related to increasing temperatures during the growing season and in some cases during the previous winter. Precipitation effects appeared less pronounced. Warming thus appears to have shortened the growing season, while increasing vegetation activity.Conclusions/SignificanceShortening of the growing season despite a longer thermally favorable period implies that vegetation on the Tibetan Plateau is unable to exploit additional thermal resources availed by climate change. Ecosystem composition may no longer be well attuned to the local temperature regime, which has changed rapidly over the past three decades. This apparent lag of the vegetation assemblage behind changes in climate should be taken into account when projecting the impacts of climate change on ecosystem processes.

Winter and spring warming result in delayed spring phenology on the Tibetan Plateau

Climate change has caused advances in spring phases of many plant species. Theoretically, however, strong warming in winter could slow the fulfillment of chilling requirements, which may delay spring phenology. This phenomenon should be particularly pronounced in regions that are experiencing rapid temperature increases and are characterized by highly temperature-responsive vegetation. To test this hypothesis, we used the Normalized Difference Vegetation Index ratio method to determine the beginning, end, and length of the growing season of meadow and steppe vegetation of the Tibetan Plateau in Western China between 1982 and 2006. We then correlated observed phenological dates with monthly temperatures for the entire period on record. For both vegetation types, spring phenology initially advanced, but started retreating in the mid-1990s in spite of continued warming. Together with an advancing end of the growing season for steppe vegetation, this led to a shortening of the growing period. Partial least-squares regression indicated that temperatures in both winter and spring had strong effects on spring phenology. Although warm springs led to an advance of the growing season, warm conditions in winter caused a delay of the spring phases. This delay appeared to be related to later fulfillment of chilling requirements. Because most plants from temperate and cold climates experience a period of dormancy in winter, it seems likely that similar effects occur in other environments. Continued warming may strengthen this effect and attenuate or even reverse the advancing trend in spring phenology that has dominated climate-change responses of plants thus far.

The influence of soil type on the relationships between NDVI, rainfall, and soil moisture in semiarid Botswana. I. NDVI response to rainfall

This study examines the variability of the normalized difference vegetation index (NDVI) over Bostwana during the period 1982–1987. Its relationship to rainfall is evaluated from 26 stations representing six vegetation formations and six soil types. The study demonstrates a linear relationship between rainfall and NDVI as long as rainfall does not exceed approximately 500 mm/yr or 50–100 mm / month. Above these limits, a “saturation” response occurs and NDVI increases with rainfall only very slowly. This occurs at much lower thresholds of rainfall over Botswana than over East Africa or the Sahel. The ratio of NDVI to rainfall in Botswana is several times higher than in savannas in these other two regions. Both this ratio, which represents the rain-use efficiency, and the total productivity of vegetation, as assessed from NDVI, vary with vegetation and soil type. The highest productivity and efficiency occur on the clay-rich vertisols, the lowest on the sandy arenosols and solonchaks. In general, the rain-use efficiency appears to be more a function of the underlying soil than of the vegetation formation.

NOAA-11 AVHRR visible and near-IR inflight calibration

An inflight calibration method for NOAA-11 AVHRR visible and near-infrared bands using desert reflectance is discussed. The results show a decrease in sensor systems response of 22 percent and 32 percent for the visible and near-infrared bands, respectively, relative to the published preflight calibration. The relative accuracy of the present calibration to the calibration of NOAA-9, published elsewhere, is + or - 3 percent. The absolute accuracy is around + or - 6 percent. An approximate correction to the Normalized Difference Vegetation Index ratio suggests that an increase of 0.06 is required.