MODIS植被指数的美国玉米单产遥感估测     

任建强  陈仲新  周清波  刘佳  唐华俊 《遥感学报》2015,19(4):568-577

针对中国开展的国外农作物产量遥感估测大多依靠中低分辨率耕地信息、省级(州级)或国家级作物产量统计数据的现状,本文以美国玉米为例,探讨利用多年中高分辨率作物分布信息、时序遥感植被指数和县级作物产量统计数据开展国外重点地区作物单产遥感估测技术研究,以期进一步提高中国对国外农作物产量监测精度和精细化水平。首先,利用美国农业部国家农业统计局(NASS/USDA)生产的作物分布数据(CDL)获得多个年份玉米空间分布图,并对相应年份250 m分辨率16天合成的MODIS-NDVI时序数据进行掩膜处理,统计获得每年各县域内玉米主要生育期NDVI均值;其次,以各州为估产区,以多年县级玉米统计单产和县域内玉米主要生育期NDVI均值为基础,建立各州玉米主要生育期NDVI与玉米单产间关系模型;然后,通过主要生育期玉米单产和玉米植被指数间拟合程度,筛选确定各州玉米最佳估产期和最佳估产模型。最终,利用最佳估产模型实现美国各州玉米单产估测和全国玉米单产推算。其中,建模数据覆盖时间为2007年—2010年,验证数据为2011年。结果表明,应用最佳估产模型的2011年美国各州玉米单产估测相对误差在-4.16%—4.92%,均方根误差在148.75—820.93 kg/ha,各州估测结果计算获得全国玉米单产的相对误差仅为2.12%,均方根误差为285.57 kg/ha。可见,本研究的作物单产遥感估测技术方法具有一定可行性,可准确估测全球重点地区作物单产信息。  相似文献   

Semi-automatic delineation of badlands using contrast in vegetation activity: a case study in the lower Chambal valley,India     

V. Ranga  A. Van Rompaey  J. Poesen  S.N. Mohapatra  P. Pani 《国际地球制图》2015,30(8):919-936

Population growth worldwide leads to an increasing pressure on the land. Recent studies reported that many areas covered by badlands are decreasing because parts of badlands are being levelled and converted into arable land. It is important to monitor these changes for environmental planning. This paper proposes a remote-sensing-based detection method which allows mapping of badland dynamics based on seasonal vegetation changes in the lower Chambal valley, India. Supervised classification was applied on three Landsat (Thematic Mapper) images, from 3 different seasons; January (winter), April (summer) and October (post-monsoon). Different band selection methods were applied to get the best classification. Validation was done by ground referencing and a GeoEye-1 satellite image. The image from January performed best with overall accuracy of 87% and 0.69 of kappa. This method opens the possibilities of using semi-automatic classification for the Chambal badlands which is so far mapped with manual interpretations only.  相似文献   

From the Seam to the Stove: greenhouse gas assessment and the coal seam gas industry in Australia     

Mischa Vickas  Christopher Dey 《The Australian geographer》2015,46(1):73-90

In Australia, Coal Seam Gas (CSG) is a relatively new source of natural gas commonly advocated as a lower greenhouse gas (GHG) emissions alternative to coal. This study investigates how GHG emissions have been, and potentially could be, assessed within the Australian CSG industry. The research involved a document analysis of several Environmental Impact Statements (EISs) and consultant reports prepared as part of the Environmental Impact Assessment (EIA) process for major CSG projects in New South Wales (NSW) and Queensland (Qld). There were found to be inconsistencies in the conduct of greenhouse assessment by the CSG industry, including how complete and transparent assessments were, as well as how effectively they addressed project emission intensity and cumulative impacts. There were also found to be large inconsistencies between assessments carried out for Qld projects and those for NSW projects, likely because of differences in how assessment requirements are applied by planning bodies. This study also highlights how alternative assessment approaches, such as Cumulative Impact Assessment (CIA) and Strategic Environmental Assessment (SEA), have potential to enable a broader and more consistent understanding of emission sources that cross a range of geographical and project boundaries.  相似文献   

Detection of foreclosure-related landscape management changes using Landsat     

《Applied geography (Sevenoaks, England)》2015

The volume of properties affected by foreclosure over the past decade suggests the potential for dramatic change in vegetation cover due to changes in management. Yet, the specific pathology of each foreclosure, the temporal asynchrony among foreclosures, and differences in the area available for vegetation growth across properties presents challenges to observing and measuring change. This paper develops and tests a difference in deviations approach that compares the parcel NDVI to a neighborhood norm before and after foreclosure. The difference in deviations approach addresses the challenges of separating parcel-level change corresponding to foreclosure and identifies changes on both small and large parcels. The method relies on a time series of Landsat Normalized Difference Vegetation Index (NDVI) data, individual home foreclosure records and property tax assessment data for Maricopa County, Arizona from 2002 to 2012. To establish the level of difference associated with observable landscape change, we use a probit regression model, coding Google Earth images for properties across the range of observed deviations of difference. The basic assumption underlying the approach is that if foreclosure coincides with a change in management, it will lead to changes in vegetation structure and thus, NDVI values. We estimate that 13% of home foreclosures in Maricopa County over the period from 2002 to 2012 resulted in declines in vegetation whereas 6.5% resulted in vegetation increases. Future uses of this method for understanding landscape management in residential landscapes are discussed.  相似文献   

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure     

《Applied geography (Sevenoaks, England)》2015

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.  相似文献   

基于LSWI和NDVI时间序列的水田信息提取研究   总被引：5，自引：0，他引：5  

刘元亮  李艳  吴剑亮 《地理与地理信息科学》2015,31(3):32-37,2

利用多时相的Landsat TM/ETM+和DEM数据,分别采用直方图匹配(HM)和准不变特征点(PIFs)方法对影像序列进行相对辐射校正,减少了影像的光照和大气条件在时间上的不确定性,提高了归一化植被指数(NDVI)和地表水分指数(LSWI)的计算精度。根据水稻在不同生育期表现出的生理特征,基于LSWI和NDVI时间序列及高程特征,采用二叉树方法提取了浙江省金华市水田信息。经过验证,在空间上水田信息的提取精度达到92.3%,在县域尺度上提取面积与统计年鉴具有0.97的相关度。  相似文献   

Spectral anisotropy of subtropical deciduous forest using MISR and MODIS data acquired under large seasonal variation in solar zenith angle     

《International Journal of Applied Earth Observation and Geoinformation》2015

Recent studies in Amazonian tropical evergreen forests using the Multi-angle Imaging SpectroRadiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) have highlighted the importance of considering the view-illumination geometry in satellite data analysis. However, contrary to the observed for evergreen forests, bidirectional effects have not been evaluated in Brazilian subtropical deciduous forests. In this study, we used MISR data to characterize the reflectance and vegetation index anisotropies in subtropical deciduous forest from south Brazil under large seasonal solar zenith angle (SZA) variation and decreasing leaf area index (LAI) from the summer to winter. MODIS data were used to observe seasonal changes in the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Topographic effects on their determination were inspected by dividing data from the summer to winter and projecting results over a digital elevation model (DEM). By using the PROSAIL, we investigated the relative contribution of LAI and SZA to vegetation indices (VI) of deciduous forest. We also simulated and compared the MISR NDVI and EVI response of subtropical deciduous and tropical evergreen forests as a function of the large seasonal SZA amplitude of 33°. Results showed that the MODIS-MISR NDVI and EVI presented higher values in the summer and lower ones in the winter with decreasing LAI and increasing SZA or greater amounts of canopy shadows viewed by the sensors. In the winter, NDVI reduced local topographic effects due to the red-near infrared (NIR) band normalization. However, the contrary was observed for the three-band EVI that enhanced local variations in shaded and sunlit surfaces due to its strong dependence on the NIR band response. The reflectance anisotropy of the MISR bands increased from the summer to winter and was stronger in the backscattering direction at large view zenith angles (VZA). EVI was much more anisotropic than NDVI and the anisotropy increased from the summer to winter. It also increased from the forward scatter to the backscattering direction with the predominance of sunlit canopy components viewed by MISR, especially at large VZA. Modeling PROSAIL results confirmed the stronger anisotropy of EVI than NDVI for the subtropical deciduous and tropical evergreen forests. PROSAIL showed that LAI and SZA are coupled factors to decrease seasonally the VIs of deciduous forest with the first one having greater importance than the latter. However, PROSAIL seasonal variations in VIs were much smaller than those observed with MODIS data probably because the effects of shadows in heterogeneous canopy structures or/and cast by emergent trees and from local topography were not modeled.  相似文献   

三套NDVI长时间序列植被指数的对比——以玛曲为例     

沙莎  郭铌  李耀辉  韩涛 《干旱气象》2013,(4):657-665

NDVI／MODIS、NDVI／GIMMS和NDVI／NSMC是时间长度不同、空间分辨率相差甚远的3套ND—VI数据集,如何集成应用这些不同时间长度、不同分辨率的数据进行相关研究,数据集间的比较是最基础的工作。本文以甘肃省甘南州玛曲县为例,用直方图、相关分析、趋势分析等方法研究了这3套NDVI产品数据集的相互关系。结果表明：1）NDVI／NSMC与NDVI/MODIS的直方图具有类似的图像分布特征,但是NDVI／MODIS数据分布范围更大;2）3套NDVI在数值上表现为NDVI／MODIS〉NDVI／GIMMS〉NDVI／NSMC;3）3套数据集空间图像特征一致,两两间均具有十分显著的空间相关性,其中1月份相对最弱,5、10月份最强,三者相比NDVIfNSMC与NDVI／MODIS的空间相关性更强;4）1—3月、5—8月及年均的NDVI／GIMMS与NDVI／NSMC值存在显著的时间相关性,但两者逐年变化趋势存在较大差别,两者气候倾向率相差最大的高达5倍之多。NDVIfNSMC数据集在处理过程中可能未进行大气订正及交叉定标,这是造成共同源的NDVIfGIMMS与NDVI／NSMC差异较大的重要原因。  相似文献   

基于集合预报的中国极端强降水预报方法研究   总被引：3，自引：1，他引：2  

刘琳  陈静  程龙  林春泽  吴志鹏 《气象学报》2013,71(5):853-866

极端强降水天气属于小概率事件,其发生具有很多不确定的因素,预报难度很大。根据Anderson-Darling检验原理研究基于集合预报资料的极端强降水天气预报方法,利用2007—2010年中国T213集合预报资料和2001—2010年6—8月中国降水观测资料,分析观测与集合预报累积概率密度分布函数的特征,建立基于集合预报与模式历史预报累积概率密度分布函数连续差异的数学模型——极端降水天气预报指数(EPFI),并对2011年7月中国极端强降水天气进行预报试验。结果表明,极端降水天气预报指数可以充分利用集合降水累积概率密度分布的尾端信息,为极端强降水提供科学合理的预报,基于中国气象局(CMA) T213集合预报的极端降水天气预报指数可提前3—7 d发出极端强降水预警信号,随着预报时效的延长,预报技巧逐渐降低。研究还表明,模式气候累积概率分布的合理性将直接影响极端强降水天气识别能力。  相似文献   

Agricultural impacts on ecosystem functioning in temperate areas of North and South America     

Juan Pablo Guerschman  Jos María Paruelo 《Global and Planetary Change》2005,47(2-4):170

Land use has a large impact on ecosystem functioning, though evidences of these impacts at the regional scale are scarce. The objective of this paper was to analyze the impacts of agricultural land use on ecosystem functioning (radiation interception and carbon uptake) in temperate areas of North and South America. From land cover maps generated using high-resolution satellite images we selected sites dominated by row crops (RC), small grain crops (SG), pastures (PA), and rangelands (RA) in the Central Plains of USA and the Pampas of Argentina. These two regions share climatic characteristics and the agricultural conditions (crop types) are also very similar. Both areas were originally dominated by temperate grasslands. In these sites we extracted the temporal series of the normalized difference vegetation index (NDVI) from the NOAA satellites for the period 1989–1998 and calculated the mean seasonal NDVI curve for each site. Additionally, we calculated the mean annual NDVI, the maximum NDVI, the date of the year when the max NDVI was recorded and the interannual variability of these three attributes. We compared the mean values of each NDVI-derived attribute between land cover types and between continents. The NDVI seasonal patterns for each land cover type were roughly similar between the Central Plains and the Pampas during the growing season. The largest differences were observed during the winter and spring, when the NDVI of all land cover types in the Central Plains remained at lower values than in the Pampas. This was probably caused by the high annual thermal amplitude in the Central Plains that results in a much more restricted growing season. As a result of these differences in the shape of the NDVI curve, the mean annual NDVI in the Central Plains was lower than in the Pampas for all land cover types but the maximum NDVI did not differ importantly. In both regions, row crops delayed the date of the NDVI peak, small grain crops advanced it and pastures did not change it importantly, compared with rangelands. The interannual variability of the NDVI attributes was higher for small grains than for row crops in both regions. However, small grains crops were consistently more variable between years in the Central Plains than in the Pampas. The opposite occurred with pastures and rangelands, which were more variable in the Pampas than in the Central Plains. This paper confirms and generalizes previous findings that showed important imprints of land use on ecosystem functioning in temperate ecosystems. Our results support the idea that the changes in land cover that have occurred in the Central Plains and the Pampas leaded to similar changes in the way that ecosystems absorb solar radiation and in the patterns of carbon uptake.  相似文献