排序方式： 共有68条查询结果，搜索用时 15 毫秒
21.
MODIS的增强型植被指数（EVI）时间序列数据早已广泛应用于植被观测、生态环境和全球气象变化等研究领域,但即使EVI时间序列数据已经经过严格的预处理,其中仍然存在着一些噪声。因此,本文开发了一种简单有效的方法来重构EVI时间序列数据,减少EVI时间序列数据中的噪声,尤其是一些由大气云层和冰雪覆盖产生的噪声。新方法的理论来源于图论,利用拉普拉斯矩阵的关系对EVI中选定的邻域窗口的像元权重进行赋值,得到中心像元的拟合。新方法已应用于2016—2018年的MODIS MOD13A1产品,并与S-G滤波法、谐波函数法、双逻辑斯蒂拟合法和非对称高斯函数法进行了比较。结果表明,在荒漠、草原和林地中,新方法留一验证测试的绝对差值最小,相较于其他方法效果较优;在拟合不同植被类型的EVI时间序列数据时,图论邻点方法呈现出更好的细节拟合曲线;其在5类植被类型中的RMSE值分别为200.59、46.58、63.48、165.47和40.95,在5种方法中均为最小值,在获取高保真和高质量的EVI时间序列数据方面优势更明显有效。本文的方法研究可以给植被遥感时序数据的去噪和生态环境的研究提供有益借鉴。 相似文献
22.
《International Journal of Digital Earth》2013,6(3):219-236
Abstract This paper investigates the contribution of multi-temporal enhanced vegetation index (EVI) data to the improvement of object-based classification accuracy using multi-spectral moderate resolution imaging spectral-radiometer (MODIS) imagery. In object-oriented classification, similar pixels are firstly grouped together and then classified; the produced result does not suffer the speckled appearance and closer to human vision. EVI data are from the MODIS sensor aboard Terra spacecraft. 69 EVI data (scenes) were collected during the period of three years (2001–2003) in a mountainous vegetated area. These data sets were used to study the phenology of the land cover types. Different land cover types show distinct fluctuations over time in EVI values and this information might be used to improve object-oriented land cover classification. Two experiments were carried out: one was only with single date MODIS multispectral data, and the other one including also the 69 EVI images. Eight classes were distinguished: temperate forest, tropical dry forest, grassland, irrigated agriculture, rain-fed agriculture, orchards, lava flows and human settlement. The two classifications were evaluated with independent verification data, and the results showed that with multi-temporal EVI data, the classification accuracy was improved 5.2%. Evaluated by McNemar's test, this improved was significant, with significance level p=0.01. 相似文献
23.
伏牛山地区森林植被动态变化对水热条件的响应 总被引：2，自引：2，他引：0
利用环境一号卫星不同时相多光谱数据,提取伏牛山地区不同森林植被类型。借助S-G滤波算法重构2000-2013年MODIS EVI时间序列影像,并结合气温和降水数据,运用线性回归、相关性分析和ANUSPLIN插值等方法分析伏牛山地区不同森林植被类型变动对水热条件的响应方式。结果表明：① 伏牛山地区植被覆盖较高,EVI平均值为0.48,14年来总体呈上升趋势,但不同森林植被类型变化存在明显差异,其中占比例最大的落叶阔叶林的上升趋势最为明显。② 14年来伏牛山地区气温呈升高趋势,气温距平升高速度约为0.27℃/10a,降水距平百分率呈波动增加趋势。③ 伏牛山地区不同森林植被类型EVI变化和气温、降水的相关性存在明显差异,其中常绿阔叶林EVI与气温的相关性最高,常绿落叶混交林与气温的相关性最弱;除常绿落叶混交林与降水主要呈弱正相关外,其余森林植被类型与降水主要呈弱负相关。④ 伏牛山地区森林植被对气温和降水的响应总体上滞后性不明显,仅在局部区域内常绿落叶混交林与气温和降水存在半个月滞后期。 相似文献
24.
基于Ts-EVI特征空间的春旱遥感监测——以河北省为例 总被引：2，自引：0，他引：2
春季干旱是影响我国农业生产的重要自然灾害。以河北省为研究区,采用Ts-EVI构建的特征空间,以温度植被干旱指数TVDI作为土壤水分估算因子对2005年4～5月的春旱发生与发展进行遥感监测,主要得出以下结论:(1)表层土壤相对湿度RSM_(10)与TVDI的相关性均通过了α=0.001水平的置信度的t检验而表现出显著相关性,基于Ts-EVI特征空间构建的TVDI可以较好地估算土壤表层水分状况。(2)TVDI与不同土壤深度RSM的相关性在不同时期存在一定的差异,4月上旬～4月中旬以10 cm深度处的相关性最高,20 cm处次之;4月下旬～5月下旬以20 cm土壤深度处的相关性最好,10 cm处次之。(3)在不统计云覆盖地区旱情的情况下,2005年4月上旬河北省春旱面积为15 014.4 km~2;4月中旬～5月下旬的春旱面积分别为43 350.4 km~2、13 889.3km~2、71 664.3 km~2、12 864.8 km~2和44381.5 km~2。 相似文献
25.
基于MODIS/EVI的内蒙古高原西部植被变化 总被引：1，自引：0，他引：1
内蒙古高原西部生态环境脆弱,是全球变化的敏感地带.为了解该区域植被覆盖的时空动态变化,根据2000—2012年MODIS/EVI影像,使用趋势分析和标准差分析方法,研究了近13年内蒙古高原西部植被生长状况及其空间格局动态变化.同时,根据《1:100万植被类型图》把研究区分为荒漠区、草原区、草甸区和灌丛区,以研究不同植被类型下的EVI变化情况.结果显示:内蒙古高原西部植被覆盖退化面积大于改善面积;植被退化区主要分布在内蒙古农牧交错带北部边缘,包含乌兰察布、呼和浩特、包头等市及大通河、疏勒河、黑河等河谷地带;植被增加区域分布在河西地区、河套地区和阿巴嘎旗附近;研究区植被稳定性存在明显的地域差异,波动较高的区域位于阴山南部、祁连山南北和阿巴嘎旗,与植被覆盖退化或者增加的区域基本吻合;仅荒漠区植被覆盖水平上升,草甸、草原区植被覆盖退化严重. 相似文献
26.
基于长江中下游流域120个气象站点1971-2015年日值气温数据,2006-2015年ERA-Interim土壤湿度再分析资料和2006-2015年MODIS卫星遥感植被指数产品MOD13A3,研究了在考虑全球变暖背景下,长江中下游流域春、夏、秋、冬4个季节平均气温在三峡大坝运行前后的变化,采用百分比阈值方法量化最高和最低气温并进行MK突变检验,并分析三峡大坝运行后的长江中下游流域四季土壤湿度和增强型植被指数（EVI）的变化。结果表明：长江中下游流域四季平均气温在三峡大坝运行以后出现明显变化,江南地区主要出现增温现象,江北地区主要出现降温现象;MK突变检验结果显示,江南地区的高温日和江北的低温日均在2006年左右发生突变,与三峡大坝完全运行的时间相符;长江中下游流域土壤湿度在三峡大坝运行后出现南湿北干的变化趋势;EVI在江南地区诸多区域出现显著增加趋势,其中冬季最突出（33.06%）,而江北地区诸多区域则出现显著减小趋势,其中夏季最明显（5.11%）,EVI与平均气温的空间变化在春、夏、冬3个季节显著相关。 相似文献
27.
2001-2010年秦岭森林物候时空变化遥感监测 总被引：1，自引：1，他引：0
植被物候是陆地生态系统对全球气候变化响应的最佳指示器,研究其时空变化对深入理解陆面水热过程、碳循环过程及预测陆地生态系统的时空变化具有重要意义。本文采用2001-2010年MODIS MOD09A1产品,通过引入MOD09A1的时间控制层DOY(Day of Year)提高EVI的时间精度;采用最大变化速率法和阈值法相结合提取秦岭森林物候期。结果表明,随着水热条件变化,由低海拔至高海拔,东南向西北,生长季始期(Start of Growth Season, SOG)逐渐推迟,集中在第81~120 d(即从3月下旬-4月末);生长季末期(End of Growth Season, EOG)逐渐提前,集中在第270~311 d(10月初-11月上旬);生长季长度(Length of Growth Season, LOG)逐渐缩短,集中在150~230 d。秦岭森林物候期与海拔关系密切,海拔每升高100 m,SOG推迟2 d,EOG提前1.9 d,LOG缩短3.9 d。2001-2010年,森林SOG提前、EOG延后和LOG延长主要分布于秦岭中高海拔区;SOG延后、EOG提前和LOG缩短主要分布在海拔1000 m以下部分区域。高海拔区物候的年际变化要比低海拔区复杂,2000 m以上区域SOG提前、EOG提前、LOG缩短。上述研究结果量化了不同海拔梯度森林的物候差异,揭示了近10年秦岭森林物候的时空格局,可为秦岭地区生态环境评价和保护提供科学依据。 相似文献
28.
基于MODIS的沿海带状植被NDVI/EVI季节变化研究——以江苏沿海互花米草盐沼为例 总被引：3，自引：0，他引：3
植被指数的时空变化是目前全球变化研究的热点问题。该文以江苏沿海互花米草盐沼为例,运用MODIS数据探索沿海带状植被NDVI/EVI的季节变化规律。结果表明,互花米草的返青(出苗)、抽穗、种子成熟等主要物候期在VI曲线上均能得到很好体现。本研究可为监测互花米草盐沼扩展趋势、加强管理、趋利避害提供基础数据,同时也为沿海其它带状植被监测提供借鉴。 相似文献
29.
Hamideh Nouri Pamela Nagler Sattar Chavoshi Borujeni Armando Barreto Munez Sina Alaghmand Behnaz Noori Alejandro Galindo Kamel Didan 《水文研究》2020,34(15):3183-3199
Urban green spaces (UGS), like most managed land covers, are getting progressively affected by water scarcity and drought. Preserving, restoring and expanding UGS require sustainable management of green and blue water resources to fulfil evapotranspiration (ET) demand for green plant cover. The heterogeneity of UGS with high variation in their microclimates and irrigation practices builds up the complexity of ET estimation. In oversized UGS, areas too large to be measured with in situ ET methods, remote sensing (RS) approaches of ET measurement have the potential to estimate the actual ET. Often in situ approaches are not feasible or too expensive. We studied the effects of spatial resolution using different satellite images, with high-, medium- and coarse-spatial resolutions, on the greenness and ET of UGS using Vegetation Indices (VIs) and VI-based ET, over a 780-ha urban park in Adelaide, Australia. We validated ET with the ground-based ET method of Soil Water Balance. Three sets of imagery from WorldView2, Landsat and MODIS, and three VIs including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Enhanced Vegetation Index 2 (EVI2), were used to assess long-term changes of VIs and ET calculated from the different imagery acquired for this study (2011–2018). We found high correspondence between ET-MODIS and ET-Landsat (R2 > 0.99 for all VIs). Landsat-VIs captured the seasonal changes of greenness better than MODIS-VIs. We used artificial neural network (ANN) to relate the RS-ET and ground data, and ET-MODIS (EVI2) showed the highest correlation (R2 = 0.95 and MSE =0.01 for validation). We found a strong relationship between RS-ET and in situ measurements, even though it was not explicable by simple regressions; black box models helped us to explore their correlation. The methodology used in this research makes a strong case for the value of remote sensing in estimating and managing ET of green spaces in water-limited cities. 相似文献
30.
Remotely sensed observations of seasonal greenness dynamics represent a valuable tool for studying vegetation phenology at regional and ecosystem-level scales. We investigated the seasonal variability of forests in Italy, examining the different mechanisms of phenological response to biophysical drivers. For each point of the Italian National Forests Inventory, we processed a multitemporal profile of the MODIS Enhanced Vegetation Index. Then we applied a multivariate approach for the purpose of (i) classifying the Italian forests into phenological clusters (i.e. pheno-clusters), (ii) identifying the main phenological characteristics and the forest compositions of each pheno-cluster and (iii) exploring the role of climate and physiographic variables in the phenological timing of each cluster. Results identified four pheno-clusters, following a clear elevation gradient and a distinct separation along the Mediterranean-to-temperate climatic transition of Italy. The “High-elevation coniferous” and the “High elevation deciduous” resulted mainly affected by elevation, with the former characterized by low annual productivity and the latter by high seasonality. To the contrary, the “Low elevation deciduous” showed to be mostly associated to moderate climate conditions and a prolonged growing season. Finally, summer drought was the main driving variable for the “Mediterranean evergreen”, characterized by low seasonality. The discrimination of vegetation phenology types can provide valuable information useful as a baseline framework for further studies on forests ecosystem and for management strategies. 相似文献