Mapping paddy rice with multi-date moderate-resolution imaging spectroradiometer (MODIS) data in China

The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer(MODIS) data in China.Paddy rice fields were extracted by identifying the unique char-acteristic of high soil moisture in the flooding and transplanting period with improved algorithms based on rice growth calendar regionalization.The characteristic could be reflected by the enhanced vegetation index(EVI) and the land surface water index(LSWI) derived from MODIS sensor data.Algorithms for single,early,and late rice identification were obtained from selected typical test sites.The algorithms could not only separate early rice and late rice planted in the same fields,but also reduce the uncertainties.The areal accuracy of the MODIS-derived results was validated by comparison with agricultural statistics,and the spatial matching was examined by ETM+(enhanced thematic mapper plus) images in a test region.Major factors that might cause errors,such as the coarse spatial resolution and noises in the MODIS data,were discussed.Although not suitable for monitoring the inter-annual variations due to some inevitable factors,the MODIS-derived results were useful for obtaining spatial distribution maps of paddy rice on a large scale,and they might provide reference for further studies.

基于MODIS影像渤海2012年海冰变化分析

海冰是影响渤海冬季海运的严重灾害,研究年度周期内海冰时空变化具有重要意义。依据研究内容选择11期具有代表性的中分辨率成像光谱仪(MODerate-resolution Imaging Spectroradiometer,MODIS)影像数据,采用ENVI(The Environment for Visualizing Images)软件进行预处理,利用目视解译方法提取海冰面积与空间位置信息,采用ArcGIS软件制作了海冰时空变化图、海冰结冻与融化过程变化图。最后,对海冰面积变化、海冰结冻与融化过程进行了详细分析。研究结果表明,利用MODIS影像进行年度周期内海冰变化分析技术方法是可行的。

基于MODIS与HJ-1多源卫星的上海海域溢油事故诊断

随着上海港海上运输业和石油产业链的日趋发达,海上溢油事故风险也随之加剧。本文就2012年发生在上海海域吴淞口和九段沙附近的2起重大溢油事故,基于美国NASA(National Aeronautics and Space Administration)中等分辨率MODIS(Moderate-resolution Imaging Spectroradiometer)与国产"环境一号"卫星HJ-1的多源卫星数据,对溢油信息进行对比,通过对油水敏感通道进行波段比值运算,突出油膜与背景海水的光谱反射率差异,再结合重柴油光谱特征,利用图像分割的阈值确定法,从疑似溢油区域中有效提取溢油信息,实现溢油区域定位、溢油面积和溢油量的诊断,为事发后海域应急响应工作提供基础性分析依据。

Review of large scale crop remote sensing monitoring based on MODIS data

China has a vast territory with abundant crops,and how to collect crop information in China timely,objectively and accurately,is of great significance to the scientific guidance of agricultural development.In this paper,by selecting moderateresolution imaging spectroradiometer(MODIS)data as the main information source,on the basis of spectral and biological characteristics mechanism of the crop,and using the freely available advantage of hyperspectral temporal MODIS data,conduct large scale agricultural remote sensing monitoring research,develop applicable model and algorithm,which can achieve large scale remote sensing extraction and yield estimation of major crop type information,and improve the accuracy of crop quantitative remote sensing.Moreover,the present situation of global crop remote sensing monitoring based on MODIS data is analyzed.Meanwhile,the climate and environment grid agriculture information system using large-scale agricultural condition remote sensing monitoring has been attempted preliminary.

MODIS产品反演与WRF模式默认植被覆盖度对比研究

WRF模式气候态植被覆盖度GVF数据集的制作源于卫星遥感资料,由于制作时间较早代表性逐渐变差,最新的MODIS遥感产品可用于WRF模式下垫面数据集的更新。本文利用2013年MODIS卫星遥感产品反演的植被覆盖度更新WRF模式默认的气候态数据集,进一步利用WRF模式计算与GVF相关的地表参数,并与WRF模式默认数据进行对比。结果表明:利用MODIS更新后的GVF在2013年不同季节均较WRF模式默认的气候态GVF偏高,尤其是中国南方和东北地区表现的"更绿";MODIS制作GVF的原数据空间分辨率为1 km,较WRF模式默认数据集的分辨率更高,适合高分辨率中尺度模式下垫面数据集的更新,更新后的GVF数据更细致,尤其是夏季城市下垫面GVF较周围偏低非常明显;通过分析GVF变化引起的叶面积指数、地表反照率和地表发射率的变化可知,农作物植被类型叶面积指数的变化最显著。东北地区森林覆盖虽较广,但由于森林的叶面积指数年季变化相对较小,叶面积指数增量并没有农作物的明显。地表反照率和地表发射率也与WRF模式默认值有一定的差异。通过对比可见,更新后的GVF对WRF模式下垫面描述有一定的影响,需进一步开展季节尺度的模拟试验,对比植被覆盖度的变化对WRF模式模拟的影响。

青藏高原MODIS地表反照率和GLASS地表反照率的对比分析

对比分析了青藏高原MODIS地表反照率产品和GLASS地表反照率产品的空间分布连续性、高质量反演结果的比例,应用青藏高原CAMP/Tibet试验期间的高精度观测数据评估了两种产品的精度,通过人工目视解译MODIS地表反射率图像并结合MODIS积雪产品分析了影响两种产品精度的原因,结果表明:1)GLASS地表反照率产品具有比MODIS地表反照率产品更好的空间分布连续性和更高的反演质量;2)绝大多数时段内两种产品都能与地面观测结果保持较好的一致性,能准确地反映地表反照率的异常变化过程;3)局地积雪是影响两种产品精度的重要因素之一;4)积雪条件下,GLASS地表反照率反演算法比MODIS地表反照率反演算法更具优势。研究结果有助于促进人们对地表反照率卫星遥感反演产品的认识,改进青藏高原地表反照率卫星遥感反演算法,提高青藏高原地表反照率卫星遥感反演结果的精度、反演质量和空间分布连续性。

Assessment of rice fields by GIS／GPS-supported classification of MODIS data

The new Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite image offers a large choice of opportunities for operational applications. The 1-km Advanced Very High Resolution Radiometer (AVHRR) image is not suitable for retrieval of field level parameter and Landsat data are not frequent enough for monitoring changes in crop parameters during the critical crop growth periods.A methodology to map areas of paddy fields using MODIS,geographic information system (GIS) and global position system (GPS) is introduced in this paper. Training samples are selected and located with the help of GPS to provide maximal accuracy.A concept of assessing areas of potential cultivation of rice is suggested by means of GIS integration. By integration of MODIS with GIS and GPS technologies the actual areas of rice fields in 2002 have been mapped. The classification accuracy was 95.7% percent compared with the statistical data of the Agricultural Bureau of Zhejiang Province.

Global Water Vapor Content Decreases from 2003 to 2012： An Analysis Based on MODIS Data

Water vapor in the earth′s upper atmosphere plays a crucial role in the radiative balance, hydrological process, and climate change. Based on the latest moderate-resolution imaging spectroradiometer(MODIS) data, this study probes the spatio-temporal variations of global water vapor content in the past decade. It is found that overall the global water vapor content declined from 2003 to 2012(slope b = –0.0149, R = 0.893, P = 0.0005). The decreasing trend over the ocean surface(b = –0.0170, R = 0.908, P = 0.0003) is more explicit than that over terrestrial surface(b = –0.0100, R = 0.782, P = 0.0070), more significant over the Northern Hemisphere(b = –0.0175, R = 0.923, P = 0.0001) than that over the Southern Hemisphere(b = –0.0123, R = 0.826, P = 0.0030). In addition, the analytical results indicate that water vapor content are decreasing obviously between latitude of 36°N and 36°S(b = 0.0224, R = 0.892, P = 0.0005), especially between latitude of 0°N and 36°N(b = 0.0263, R = 0.931, P = 0.0001), while the water vapor concentrations are increasing slightly in the Arctic regions(b = 0.0028, R = 0.612, P = 0.0590). The decreasing and spatial variation of water vapor content regulates the effects of carbon dioxide which is the main reason of the trend in global surface temperatures becoming nearly flat since the late 1990 s. The spatio-temporal variations of water vapor content also affect the growth and spatial distribution of global vegetation which also regulates the global surface temperature change, and the climate change is mainly caused by the earth's orbit position in the solar and galaxy system. A big data model based on gravitational-magmatic change with the solar or the galactic system is proposed to be built for analyzing how the earth's orbit position in the solar and galaxy system affects spatio-temporal variations of global water vapor content, vegetation and temperature at large spatio-temporal scale. This comprehensive examination of water vapor changes promises a holistic understanding of the global climate change and potential underlying mechanisms.

The study of estimation method of broadband emissivity from EOS/MODIS data

The broadband emissivity is an important parameter for estimating the energy balance of the Earth. This study focuses on estimating the window （8 -12 μm） emissivity from the MODIS （mod- erate-resolution imaging spectroradiometer） data, and two methods are built. The regression method obtains the broadband emissivity from MODllB1 - 5KM product, whose coefficient is developed by using 128 spectra, and the standard deviation of error is about 0.0118 and the mean error is about O. 0084. Although the estimation accuracy is very high while the broadband emissivity is estimated from the emissivity of bands 29, 31 and 32 obtained from MOD11B1 _ 5KM product, the standard deviations of errors of single emissivity in bands 29, 31, 32 are about 0.009 for MOD11B1 5KM product, so the total error is about O. 02 and resolution is about 5km × 5km. A combined radiative transfer model with dynamic learning neural network method is used to estimate the broadband emis- sivity from MODIS 1B data. The standard deviation of error is about 0.016, the mean error is about 0.01, and the resolution is about 1 km x 1 km. The validation and application analysis indicates that the regression is simpler and more practical, and estimation accuracy of the dynamic learning neural network method is higher. Considering the needs for accuracy and practicalities in application, one of them can be chosen to estimate the broadband emissivity from MODIS data.

Characteristics and generations of internal wave in the Sulu Sea inferred from optical satellite images

Characteristics and generation of internal waves(IWs)in the Sulu Sea are studied using Moderate-Resolution Imaging Spectroradiometer(MODIS)and Visible Infrared Imaging Radiometer Suite(VIIRS)images taken from October 2016 to September 2019.Satellite observations show that IWs in the Sulu Sea mainly located in the shallower western areas with occasional observations in the deeper eastern regions.The dominant length of wave crest(LWC)of IWs is between 50 and 150 km with the largest LWC reaching over 300 km.The analysis of temporal distributions of IWs shows that March has the most IWs and July has the least.Further analysis shows that the seasonal variation is mainly due to the cloud contamination of optical satellite images.New generation sites of IWs are analyzed using satellite images.Six possible generation sites for IWs in the western Sulu Sea and one generation site for IWs in the eastern Sulu Sea are found using the ray-tracing method.Multi IW sources in the same strait are found,which may be due to the seawater fl ow over the strait in diff erent directions.The analysis shows that IWs with long wave crest in the Sulu Sea is a combined eff ort of all straits between small islands in the Sulu Archipelago.Remote generated IWs with long wave crest in the eastern Sulu Sea are studied,which are generated at the straits around(121.5°E,6°N)by the nonlinear evolution of internal tide originated from the Sulu Archipelago.

Spatial and seasonal characterization of net primary productivity and climate variables in southeastern China using MODIS data

We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts delayed and continuous effects. This study expands on this by mapping the seasonal characterization of NPP and climate variables from space using geographic information system (GIS) technology at the pixel level. Our approach was developed in southeastern China using moderate-resolution imaging spectroradiometer (MODIS) data. The results showed that air temperature,precipitation and sunshine percentage contributed significantly to seasonal variation of NPP. In the northern portion of the study area,a significant positive 32-d lagged correlation was observed between seasonal variation of NPP and climate (P<0.01),and the influences of changing climate on NPP lasted for 48 d or 64 d. In central southeastern China,NPP showed 16-d,48-d,and 96-d lagged correlation with air temperature,precipitation,and sunshine percentage,respectively (P<0.01); the influences of air temperature and precipitation on NPP lasted for 48 d or 64 d,while sunshine influence on NPP only persisted for 16 d. Due to complex topography and vegetation distribution in the southern part of the study region,the spatial patterns of vegetation-climate relationship became complicated and diversiform,especially for precipitation influences on NPP. In the northern part of the study area,all vegetation NPP had an almost similar response to seasonal variation of air temperature except for broad crops. The impacts of seasonal variation of precipitation and sunshine on broad and cereal crop NPP were slightly different from other vegetation NPP.

基于可见光红外成像辐射仪数据的地表温度反演

地表温度是农业旱灾和作物估产模型的重要参数。该文针对可见光红外成像辐射仪(visible infrared imager radiometer suite,VIIRS)传感器缺乏水汽通道的特点,联合Aqua卫星搭载的中分辨率成像光谱仪(moderate-resolution imaging spectroradiometer,MODIS)数据提出了基于分裂窗算法的VIIRS地表温度反演方法。对地表发射率和大气透过率这2个关键参数的获取进行了详细分析,选取了处于作物生长期的2013年6月4日VIIRS数据进行实例验证分析。结果表明,与全国气象数据比较该文算法在大尺度上能够较好地获取中国地表温度;与MODIS数据温度产品在高温产粮区比较,该文算法与MODIS温度产品精度较一致,两者差值小于1 K。使用MODTRAN(moderate resolution transmission)软件对算法的精度进行了模拟评价验证,分析表明:在一定的水汽和地表发射率条件下,算法反演精度一般保持在1 K内,平均误差为0.431 K,误差标准偏差为0.247 K。能够为农业干旱、作物长势等农情信息监测提供所需的地表温度数据。

京津冀地区气溶胶时空分布及与城市化关系的研究

利用AERONET(AErosol RObotic NETwork)数据对2008~2012年Terra MODIS(MOderate-resolution Imaging Spectroradiometer)C006 3 km卫星遥感气溶胶产品在京津冀地区的适用性进行了验证,分析京津冀地区3km分辨率气溶胶光学厚度(AOD)的时空分布和变化特征。利用DMSP(Defense Meteorological Satellite System)/OLS(Operational Linescan System)夜间灯光数据作为城市化评价手段,对京津冀地区城市化与AOD时空分布之间的关系进行了研究。结果表明:(1)MODIS 3 km气溶胶产品遥感反演数据和同期AERONET监测数据在研究区具有很好的一致性,相关系数达0.91,满足期望要求;(2)时间上,2008~2012年研究区年平均AOD值在0.361~0.453之间变化,年际间变化浮动大,总体呈下降趋势;AOD春季呈明显下降趋势,夏季总体呈微弱上升趋势,秋季和冬季呈明显上升趋势;(3)空间上,2008~2012年北京、天津和河北中南部的AOD值较高,河北北边AOD值较低;四季AOD空间分布呈现较强烈季节变化,夏季最高,冬季最低;(4)夜间灯光数据和AOD时空分布不仅在空间分布上呈现较好的一致性,且2008~2012年二者的地理权重回归(GWR)模型拟合度R2达0.8左右。研究区内AOD与夜间灯光数据二者相关性显著,城市化发展水平和人类活动对气溶胶的分布有着明显的影响。

我国北方地区植被总初级生产力的空间分布与季节变化

本研究通过集成TerraMODIS卫星影像数据与地面通量台站的观测数据,改进了基于遥感的VPM光能利用率模型,模拟了我国北方地区2008年陆地生态系统总初级生产力(GPP)的空间分布与季节变化。研究表明:(1)我国北方地区植被GPP在空间分布上表现为东高西低的特征,年均值为518.36g/m2(C重量,下同)。(2)我国北方地区主要植被类型的GPP有较强的季节动态,大体上都表现出单峰变化趋势。GPP值按照由大到小顺序依次为:夏绿阔叶林(DBF)>针阔混交林(MF)>农田(Crop)>落叶针叶林(DNF)>常绿针叶林(ENF)>草地(Grass)>稀疏灌丛(Oshrub)>裸地或稀疏植被(BSV)。(3)整个区域的GPP季相变化表现为:夏季最高,达到32.80g.m-2.(8d)-1,为全年最大值;春季GPP为5.67g.m-2.(8d)-1,与秋季的5.08g.m-2.(8d)-1较为接近,冬季GPP最弱,仅为0.07g.m-2.(8d)-1。与通量台站实测值及前人研究结果的比较表明,本文所模拟的GPP与观测值之间的相对误差绝对值多小于15%,表明模拟结果具有较好的可靠性。这说明通过集成遥感观测数据与台站观测数据的方法来模拟GPP,可以较准确地模拟区域尺度的GPP空间分布与时间变化,这为深入研究陆气相互作用提供了重要研究手段。

福建围填海及其对海洋环境影响的遥感初探

把遥感技术应用于海岸带现状的动态研究和遥感海洋环境反演是当前遥感应用的热点之一。文章主要利用美国资源卫星专题扫描仪(thematic mapper,TM)遥感影像研究福建围填海状况及大陆海岸线的变化,通过ENVI、ArcGIS软件对研究区遥感影像进行处理,实现海岸线的自动提取、土地分类,以监测福建围填海的动态变化。通过相同季节的中分辨率成像光谱仪(moderate-resolution imaging spectroradiometer,MODIS)遥感影像反演福建海域海水表层温度及叶绿素浓度等海洋参数来了解围填海对海洋环境的可能影响。

Responses of Alpine Wetlands to Climate Changes on the Qinghai-Tibetan Plateau Based on Remote Sensing

The alpine wetlands in QTP(Qinghai-Tibetan Plateau)have been profoundly impacted along with global climate changes.We employ satellite datasets and climate data to explore the relationships between alpine wetlands and climate changes based on remote sensing data.Results show that:1)the wetland NDVI(Normalized Difference Vegetation Index)and GPP(Gross Primary Production)were more sensitive to air temperature than to precipitation rate.The wetland ET(evapotranspiration)across alpine wetlands was greatly correlated with precipitation rate.2)Alpine wetlands responses to climate changes varied spatially and temporally due to different geographic environments,variety of wetland formation and human disturbances.3)The vegetation responses of the Zoige wetland was the most noticeable and related to the temperature,while the GPP and NDVI of the Qiangtang Plateau and Gyaring-Ngoring Lake were significantly correlated with both temperature and precipitation.4)ET in the Zoige wetland showed a significantly positive trend,while ET in Maidika wetland and the Qiangtang plateau showed a negative trend,implying wetland degradation in those two wetland regions.The complexities of the impacts of climate changes on alpine wetlands indicate the necessity of further study to understand and conserve alpine wetland ecosystems.

基于MODIS的云南省2001-2020年林火发生时空特征分析

【目的】研究森林火灾发生的时空特征,掌握云南省林火发生的时空分异特征,定量分析林火发生规律,识别林火高发区和易发区,以进行森林火险分布科学区划。【方法】基于云南省2001—2020年中分辨率成像光谱仪(MODIS)火灾位置/热异常产品数据(MCD14DL),利用火位置信息中所具有的关联性与异质性等,采用统计分析、中心点分析、标准差椭圆法、Ripley’s K函数、核密度等方法,分析云南省林火发生的时空分布特征。【结果】①云南省2001—2020年间林火发生的年际波动较大,2010年出现火点高峰值;季节变化显著,林火主要集中在冬、春两季,春季火点最多且在3月出现高峰值。②林火发生具有显著的区域性特征,林火高发区主要分布在云南省西南部,其次是东南和西北部,东北部林火发生数最少。普洱市是林火发生的中位数中心,其西北部森林火点分布密度最高,核密度值约为0.43;其次是西双版纳州中西部区域,核密度值约为0.34;再者是大理州西北部和文山州东北部区域,这两处核密度值均约为0.26,这4个区域为云南省森林火点分布的热点区。③20年间,林火空间分布的方向性明显,云南省森林火点的总体重心位置正逐步由普洱一带向大理—楚雄—玉溪—红河州一带偏移。④云南省林火的整体空间分布类型为凝聚模式,但聚集程度不高且在逐渐分散。【结论】2001—2020年云南省林火发生不是完全随机分布的,而是呈现一定的时空分布规律。该特征规律有助于强化区域火情管理,增强重点防火区域的防火建设与宣传,科学安排防火工作,降低林火发生率,实现森林可持续发展。

Surface diurnal warming in the East China Sea derived from satellite remote sensing

Process of sea surface diurnal warming has drawn a lot of attention in recent years, but that occurs in shelf seas was rarely addressed. In the present work, surface diurnal warming strength in the East China Sea was calculated by the sea surface temperature(SST) data derived from the MODIS sensors carried by the satellites Aqua and Terra. Due to transit time difference, both the number of valid data and the surface diurnal warming strength computed by the MODIS-Aqua data are relatively larger than Terra. Therefore, the 10-year MODIS-Aqua data from 2005 to 2014 were used to analyze the monthly variability of the surface diurnal warming. Generally, the surface diurnal warming in the East China sea is stronger in summer and autumn but weaker in winter and spring, while it shows different peaks in different regions. Large events with ΔT≥5 K have also been discussed. They were found mainly in coastal area, especially near the Changjiang(Yangtze) River estuary. And there exists a high-incidence period from April to July. Furthermore, the relationship between surface diurnal warming and wind speed was discussed. Larger diurnal warming mainly lies in areas with low wind speed. And its possibility decreases with the increase of wind speed. Events with ΔT ≥2.5 K rarely occur when wind speed is over 12 m/s. Study on surface diurnal warming in the East China Sea may help to understand the daily scale air-sea interaction in the shelf seas. A potential application might be in the marine weather forecasts by numerical models. Its impact on the coastal eco-system and the activities of marine organisms can also be pursued.

Remote Detection of Varying Water Storage in Relation to Surfacial Temperature of Aral Sea

Lake monitoring by remote sensing is of significant importance to understanding the lake and ambient ecological and environmental processes. In particular, whether lake water storage variation could predict lake surfacial temperature or vice versa has long fascinated the research community, in that it would greatly benefit the monitoring missions and scientific interpretation of the lake change processes. This study attempted to remotely detect the dynamics of the Aral Sea and pursue the relationships between varying lake water storage attributes and surface water temperature by using MODIS LST(Moderate-resolution Imaging Spectroradiometer Land Surface Temperature) 8-day composite products, satellite altimeter data, and actual meteorological measurements. Their associations with lake Surface Water Temperatures(SWT) were then analyzed. Results showed the lake water surface areas and elevations of the North Aral Sea tended to increasing trend from 2001(2793.0 km^2, 13.6 m) to 2015(6997.8 km^2, 15.9 m), while those of the South Aral Sea showed a decreasing trend during 2001(20 434.6 km^2, 3.9 m) and 2015(3256.1 km^2, 0.9 m). In addition, the annual daytime and nighttime lake SWT both decreased in the North Aral Sea, while only the daytime SWT in the South Aral Sea exhibited an increase, indicating a rising deviation of diurnal temperatures in the South Aral Sea during the past 15 yr. Moreover, a lower correlation was found between variations in the daytime SWT and storage capacity in the South Aral Sea(R^2 = 0.33;P < 0.05), no fair correlations were tested between lake water storage and daytime SWT in the North Aral Sea nor between lake water storage and nighttime SWT in either part of the sea. These results implied that climate change, if any at least during the research period, has no significant effects on lake dynamics over the two sectors of the Aral Sea with anthropogenic disturbances. However, climate change and human activities may overlap to explain complex consequences in the lake storage variations. Our results may provide a reference for monitoring the spatiotemporal variations of lakes, increasing understanding of the lake water storage changes in relation to the lake SWT, which may benefit the ecological management of the Aral Sea region, in the effort to face the likely threats from climate change and human activities to the region.

Estimation of Terrestrial Net Primary Productivity in China from Fengyun-3D Satellite Data

Currently,the satellite data used to estimate terrestrial net primary productivity(NPP)in China are predominantly from foreign satellites,and very few studies have based their estimates on data from China’s Fengyun satellites.Moreover,despite their importance,the influence of land cover types and the normalized difference vegetation index(NDVI)on NPP estimation has not been clarified.This study employs the Carnegie–Ames–Stanford approach(CASA)model to compute the fraction of absorbed photosynthetically active radiation and the maximum light use efficiency suitable for the main vegetation types in China in accordance with the finer resolution observation and monitoring-global land cover(FROM-GLC)classification product.Then,the NPP is estimated from the Fengyun-3D(FY-3D)data and compared with the Moderate Resolution Imaging Spectroradiometer(MODIS)NPP product.The FY-3D NPP is also validated with existing research results and historical field-measured NPP data.In addition,the effects of land cover types and the NDVI on NPP estimation are analyzed.The results show that the CASA model and the FY-3D satellite data estimate an average NPP of 441.2 g C m^(−2) yr^(−1) in 2019 for China’s terrestrial vegetation,while the total NPP is 3.19 Pg C yr^(−1).Compared with the MODIS NPP,the FY-3D NPP is overestimated in areas of low vegetation productivity and is underestimated in high-productivity areas.These discrepancies are largely due to the differences between the FY-3D NDVI and MODIS NDVI.Compared with historical field-measured data,the FY-3D NPP estimation results outperformed the MODIS NPP results,although the deviation between the FY-3D NPP estimate and the in-situ measurement was large and may exceed 20%at the pixel scale.The land cover types and the NDVI significantly affected the spatial distribution of NPP and accounted for NPP deviations of 17.0%and 18.1%,respectively.Additionally,the total deviation resulting from the two factors reached 29.5%.These results show that accurate NDVI products and land cover types are important prerequisites for NPP estimation.