共查询到19条相似文献，搜索用时 906 毫秒
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农作物长势综合监测——以印度为例 总被引：2，自引：0，他引：2
提出农作物长势综合监测方法,利用卫星遥感得到的NDVI时间序列数据,综合采用实时监测、过程监测和时间序列聚类监测方法,明确不同方法适用的监测尺度及监测目的,对不同范围农作物长势进行监测。改进了Crop Watch全球农情遥感速报系统运行化作物长势监测方法,克服了原有作物长势监测中实时监测方法无法反映相同区域苗情在整个生长过程中的连续变化情况的缺点。实现对相同区域作物长势连续变化的定量描述,可对作物长势进行更准确的判断。利用官方发布的作物单产变幅数据,对单产变幅较大的12个作物主产省区作物长势监测结果的准确性进行判断,结果表明:6个邦的实时监测和聚类监测方法所得结果一致,都符合作物单产变化的实际状况;4个邦的聚类监测方法所得结果对作物长势监测更为准确,更符合该区域作物单产的实际变化;1个邦实时监测结果对作物长势监测比聚类监测方法更为准确;只有1个邦采用两种方法对作物长势的监测存在误差,聚类监测方法在对农作物生长过程的连续监测及空间分布的定量化表述方面,比实时监测更为准确。3种方法可以综合使用,实现业务化运行的农作物长势监测。 相似文献
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区域作物生长过程的遥感提取方法 总被引：16，自引：3，他引：16
提出利用时序NDVI数据提取作物生长过程方法。遥感数据在采集过程中受云、大气因子的影响 ,以及混合像元问题 ,造成时序植被指数值变得没有规律 ,对比性不强。采用基于最小二次方拟合的谐函数分析方法 ,依据作物轮作规律和生长周期性特征 ,用主要频率的正弦、余弦谐函数重建时序图像 ,去除了影像中云污染的影响。以中国的旱地为例 ,考虑到像元内旱地对NDVI值的贡献率 ,计算区域内旱地像元加权平均值来反映其作物生长过程。同时与区域所有像元的平均值、旱地平均值等统计方法的结果进行对比分析 ,表明区域内旱地的加权平均值能够削弱旱地比例和地域间的差异 ,突出耕地上作物的生长过程特征。通过与地面实测数据分析 ,平滑前后的作物生长过程与叶面积指数相关性增加 5 %— 11% ,采用区域加权平均的方法得到的作物生长过程 ,比旱地平均和NDVI平均的结果与叶面积指数的相关性增加 14 %— 17%。 相似文献
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遥感和生长模型相结合的小麦长势监测研究现状与展望 总被引：9，自引：0，他引：9
遥感影像的信息波段及其组合可以反映农作物生长的空间信息，可对小麦进行长势监测和产量估算，具有及时性和广域性。生长模型是集气候、土壤、品种和栽培措施等因素为一体的，对作物的物候发育、光合生产、器官建成、同化物积累与分配以及产量与品质形成等生理过程及其与环境和技术因子关系综合量化的动态数学模型，具有机理性和预测性。将二者结合用于长势监测不但具有理论研究价值，还具有广泛的应用前景。本文在简要概述小麦生长模型和长势遥感监测研究进展的基础上，总结了生长模型和遥感相结合的小麦长势监测应用的研究进展，并提出一些今后研究设想。 相似文献
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农业遥感研究应用进展与展望 总被引：22，自引：0，他引：22
得益于中国自主遥感卫星、无人机遥感和物联网等技术的发展,中国农业遥感研究与应用在过去20年取得了显著进步,中国农业遥感信息获取呈现出天地网一体化的趋势;农业定量遥感在关键参数遥感反演技术方法与应用方面取得进展;作物面积、长势、产量、灾害遥感监测的理论与技术方法取得突破,农业遥感技术应用领域不断拓展。本文从农业遥感信息获取、农业定量遥感、农业灾害遥感、作物遥感识别与制图、作物长势遥感监测与产量预测、农业土地资源遥感等方面对中国农业遥感科研与应用进行了总结综述。 相似文献
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作物长势监测是农情监测的核心内容之一,处在不同生育期的作物长势存在显著差异。为了提高大范围作物长势遥感监测的精度,利用2001―2015年间获取的MOD09A1数据,以山东省冬小麦为研究对象,在逐年提取冬小麦抽穗期基础上,探讨研究区近15 a间冬小麦抽穗期长势时空格局。研究表明,与归一化差值植被指数(normalized difference vegetation index,NDVI)相比,基于增强型植被指数(enhanced vegetation index,EVI)提取的冬小麦抽穗期与地面观测数据有更好的一致性。研究区冬小麦抽穗期主要集中在4月中、下旬,并从南向北、自西向东逐渐推迟;与NDVI,EVI和归一化差值红外指数(normalized difference infrared index,NDII)相比,产品改进–NDVI(product improve–NDVI,PI_NDVI)更能反映冬小麦的实际长势。基于该指数监测冬小麦长势,2001―2015年间山东省冬小麦抽穗期长势整体呈上升趋势;但年际间波动较大,相同年份不同区域的冬小麦长势存在明显差异;而大部分区域长势状况比较一致,与多年平均状况持平。研究结果与已有的相关研究较为一致,基于遥感进行大范围和长时间作物长势监测的思路可以为以后研究提供一定的参考。 相似文献
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山体滑坡是不可逆转的自然灾害,实时监测滑坡绝对位移和相对位移,掌握滑坡形变的规律和趋势,可减少经济损失,保障经济发展。三维激光扫描技术是监测山体滑坡的主要方法之一,其关键是去除地表植被、建筑物等其他地物点云信息对地表模型的干扰,获得扫描区域高精度的DEM,进而得到准确的监测信息。因此本文重点分析并去除滑坡体各种干扰地物点云信息。 相似文献
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全球农情遥感速报系统20年 总被引：2，自引：0，他引：2
面向国家粮食安全的重大战略需求,1998年中国科学院建立了"中国农情遥感速报系统"(CropWatch),持续运行20年后,现已发展成为"全球农情遥感速报系统"(CropWatch)。本文重点论述了2013年建立参与式全球农情遥感监测云平台(CropWatch-Cloud)以来,所采用的农情监测体系、可定制的农情监测云平台理念以及CropWatch-Cloud在国内外的应用推广情况,介绍了技术方法与农情信息服务方式的创新与进步带来的国际影响力的提升。系统总结了全球农情遥感速报系统发展的农情监测指标、农情预警能力、作物长势综合监测方法以及众源数据支持的作物面积监测方法,论文进一步阐述了CropWatch未来的发展方向,借助众源地理信息、大数据技术等的发展,打通从地块—村—镇—县—市—省—国家—全球的体系化全链条监测,满足从农户到政府决策部门对农情信息的差异化需求。 相似文献
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Abstract Recent investigations demonstrated that inter‐year NOAA‐AVHRR NDVI variations at the middle of the rainy season can provide information on annual crop yields in Sahelian countries. This line of research is presently extended to the consideration of multitemporal NDVI data for several years (1986-1991) pre‐processed by a proven methodology. The investigation was conducted using NDVI and crop yield data from the sahelian sub‐districts of Niger. The results confirm that geographically standardized NDVI data are efficient for crop yield forecasting, but notable differences exist in this prediction capability depending on the beginning of the season. Late beginnings of the growing (rainy) season (after the end of June) allow optimum forecasting only after mid‐August, while early beginnings lead to anticipate the forecasting capability but also to decrease its accuracy. The importance of these findings in the context of an early warning system is finally discussed. 相似文献
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M. B. Potdar K. R. Manjunath N. L. Purohit 《Journal of the Indian Society of Remote Sensing》1999,27(4):205-215
Attempt has been made to develop spectro meteorological yield models using normalized difference vegetation index (NDVI) derived from NOAA AVHRR data over the crop growth period and monthly rainfall data for predicting yield of mustard crop. The AVHRR data spanning seven crop growing seasons, the rain gauze station-level rainfall data and crop yield data determined from crop cutting experiments (CCE) conducted by state Directorate of Economics and Statistics (DES) are the basic input data. A methodology has been developed to normalize the multi-temporal NDVIs for the minimisation of atmospheric effects, which is found to reduce the noise in NDVI due to varying atmospheric conditions from season to season and improve the predictability of statistical multiple linear regression yield models developed for nine geographically large districts of Rajasthan state. The spectro meteorological yield models had been validated by comparing the predicted district level yields with those estimated from the crop cutting experiments. 相似文献
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多时相MODIS影像水田信息提取研究 总被引：5，自引：0，他引：5
水稻种植及其分布信息是土地覆被变化、作物估产、甲烷排放、粮食安全和水资源管理分析的重要数据源。基于遥感的水田利用监测中,通常采用时序NDVI植被指数法和影像分类法分别进行AVHRR和TM影像的水田信息获取。针对8天合成MODIS陆地表面反射比数据的特点和水稻生长特征,选取水稻种植前的休耕期、秧苗移植期、秧苗生长期和成熟期等多时相MODIS地表反射率影像数据,通过归一化植被指数、增强植被指数及利用对土壤湿度和植被水分含量较敏感的短波红外波段计算得到的陆表水指数进行水田信息获取。将提取结果与基于ETM＋影像的国土资源调查水田数据,通过网格化计算处理并进行对比分析,结果表明,利用MODIS影像的8天合成地表反射率数据,进行区域甚至全国的水田利用监测是可行的。 相似文献
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Susanna Azzali 《国际地球制图》2013,28(3):15-26
A method to correlate crop production in Zambia to the yearly evolution of the Normalized Difference Vegetation Index (NDVI) is proposed. The method consists of the analysis of remote sensing data together with meteorological data and simulated crop production to obtain indicators of crop production. The accuracy of these indicators is assessed with statistical data. The main objective was to assess whether the NDVI‐time series extracted from NOAA‐AVHRR‐images , having a pixel resolution of 73 km may give reliable information on crop production in Zambia where agricultural areas cover just 1% of the land area. The mean NDVI‐value of several pixels, e.g. for one province or other administrative units, relates to the dominant type of vegetation in the area under consideration. It is shown that the 7.3 km NDVI‐data give reliable indications on crop production in Zambia, when small areas (200–450 km2 large ) are considered where agricultural land use is intensive. This implies that preliminary analysis is required to localize the agricultural areas. This has been done by means of high resolution satellite images i.e. LANDSAT‐MultiSpectral Scanner. Consequently, the NDVI‐time series of the ‘agricultural ‘ pixels are used to calculate crop growth indicators which can be applied to assess the crop production. 相似文献
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V. K. Pandey S. N. Panda N. S. Raghuwanshi S. Sudhakar 《Journal of the Indian Society of Remote Sensing》2006,34(2):143-152
Delineation of Banikdih Agricultural watershed in Eastern India was carried out and various watershed parameters were extracted
using Geographic Information System (GIS) and Remote Sensing. Digital Elevation Model (DEM) was developed with a contour interval
of 10 m in the scale of 1:25000 using ARC/INFO modules. Sub watershed, drainage, slope, aspect, flow direction, soil series,
soil texture, and soil class maps were independently generated and they were properly registered and integrated for analysis.
The watershed was digitally delineated using AVSWAT model that couples hydrological model and GIS with appropriate threshold
value of cell size. Subsequently, stream characteristics through the interface were generated. Indian Remote Sensing Satellite
IRS-1D LISS-III data pertaining to the period of October 29, 1998 and October 23, 2000 was used to develop land use/land cover
thematic map using ERDAS- 8.4 version image processing software. Eight major land use/land cover classes namely water body,
lowland paddy, upland paddy, fallow land, upland crop (non-paddy crops), settlement, open mixed forest, and wasteland were
segregated through digital image processing techniques using maximum likelihood algorithm. The information generated would
be of immense help in hydrological modeling of watershed for prediction of runoff and sediment yield, thereby providing necessary
inputs for developing suitable developmental management plans with sound scientific basis. 相似文献
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Rice crop occupies an important aspect of food security and also contributes to global warming via GHGs emission. Characterizing rice crop using spatial technologies holds the key for addressing issues of global warming and food security as different rice ecosystems respond differently to the changed climatic conditions. Remote sensing has become an important tool for assessing seasonal vegetation dynamics at regional and global scale. Bangladesh is one of the major rice growing countries in South Asia. In present study we have used remote sensing data along with GIS and ancillary map inputs in combination to derive seasonal rice maps, rice phenology and rice cultural types of Bangladesh. The SPOT VGT S10 NDVI data spanning Aus, Aman and Boro crop season (1st May 2008 to 30th April 2009) were used, first for generating the non-agriculture mask through ISODATA clustering and then to generate seasonal rice maps during second classification. The spectral rice profiles were modelled and phenological parameters were derived. NDVI growth profiles were modelled and crop calendar was derived. To segregate the rice cultural types of Bangladesh into IPCC rice categories, we used elevation, irrigated area, interpolated rainfall maps and flood map through logical modelling in GIS. The results indicated that the remote sensing derived rice area was 9.99 million ha as against the reported area of 11.28 million ha. The wet and dry seasons accounted for 64% and 36 % of the rice area, respectively. The flood prone, drought prone and deep water categories account for 7.5%, 5.56% and 2.03%, respectively. The novelty of current findings lies in the spatial outcome in form of seasonal and rice cultural type maps of Bangladesh which are helpful for variety of applications. 相似文献
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中国农情遥感速报系统 总被引：49，自引：3，他引：49
介绍了中国农情遥感速报系统的建设情况 ,系统内容包括农作物长势监测、农作物种植面积监测、农作物单产预测与粮食产量估算、作物时空结构监测和粮食供需平衡预警等。简要介绍了 1998年以来中国农情遥感速报系统在监测内容与监测范围、监测频率、技术发展以及质量控制与过程检验体系建立等方面的进展 ,并就中国农情遥感速报系统的发展方向提出了展望。 相似文献
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With the availability of high frequent satellite data, crop phenology could be accurately mapped using time-series remote sensing data. Vegetation index time-series data derived from AVHRR, MODIS, and SPOT-VEGETATION images usually have coarse spatial resolution. Mapping crop phenology parameters using higher spatial resolution images (e.g., Landsat TM-like) is unprecedented. Recently launched HJ-1 A/B CCD sensors boarded on China Environment Satellite provided a feasible and ideal data source for the construction of high spatio-temporal resolution vegetation index time-series. This paper presented a comprehensive method to construct NDVI time-series dataset derived from HJ-1 A/B CCD and demonstrated its application in cropland areas. The procedures of time-series data construction included image preprocessing, signal filtering, and interpolation for daily NDVI images then the NDVI time-series could present a smooth and complete phenological cycle. To demonstrate its application, TIMESAT program was employed to extract phenology parameters of crop lands located in Guanzhong Plain, China. The small-scale test showed that the crop season start/end derived from HJ-1 A/B NDVI time-series was comparable with local agro-metrological observation. The methodology for reconstructing time-series remote sensing data had been proved feasible, though forgoing researches will improve this a lot in mapping crop phenology. Last but not least, further studies should be focused on field-data collection, smoothing method and phenology definitions using time-series remote sensing data. 相似文献