Greenness Index from Phenocams Performs Well in Linking Climatic Factors and Monitoring Grass Phenology in a Temperate Prairie Ecosystem     

ZHOU Yuke 《资源与生态学报(英文版)》2019,10(5):481-493

Near-surface remote sensing (e.g., digital cameras) has played an important role in capturing plant phenological metrics at either a focal or landscape scale. Exploring the relationship of the digital image-based greenness index (e.g., Gcc, green chromatic coordinate) with that derived from satellites is critical for land surface process research. Moreover, our understanding of how well Gcc time series associate with environmental variables at field stations in North American prairies remains limited. This paper investigated the response of grass Gcc to daily environmental factors in 2018, such as soil moisture (temperature), air temperature, and solar radiation. Thereafter, using a derivative-based phenology extraction method, we evaluated the correspondence between key phenological events (mainly including start, end and length of growing season, and date with maximum greenness value) derived from Gcc, MODIS and VIIRS NDVI (EVI) for the period 2015-2018. The results showed that daily Gcc was in good agreement with ground-level environmental variables. Additionally, multivariate regression analysis identified that the grass growth in the study area was mainly affected by soil temperature and solar radiation, but not by air temperature. High frequency Gcc time series can respond immediately to precipitation events. In the same year, the phenological metrics retrieved from digital cameras and multiple satellites are similar, with spring phenology having a larger relative difference. There are distinct divergences between changing rates in the greenup and senescence stages. Gcc also shows a close relationship with growing degree days (GDD) derived from air temperature. This study evaluated the performance of a digital camera for monitoring vegetation phenological metrics and related climatic factors. This research will enable multiscale modeling of plant phenology and grassland resource management of temperate prairie ecosystems.  相似文献   

基于NS2的TCPW性能改进算法研究     

邢苏珍  吴卫东 《中国海洋大学学报(自然科学版)》2008,(Z1)

TCP Westwood(TCPW)和Vegas都是基于测量的TCP New-Reno增强算法。TCPW针对ACK流直接估算可用带宽,在慢启动和线性递增部分依然采用传统Reno的盲目递增的机制,导致发送端较为频繁的重传。对这几种算法原理进行分析阐述,并提出1种改进方法,更精确的测量估计带宽,通过网络仿真工具NS2进行验证,明显去除TCP全局同步现象,增强网络性能。  相似文献   

地形位指数模型改进及其在植被覆盖评价中的应用     

张玉  张道军 《地理学报》2022,77(11):2757-2772

地形作为影响植被覆盖的重要因素,对植被恢复评价以及生态修复规划意义重大。地形位作为测度地形因子综合效应的指标,具有单一地形因子难以比拟的优势。然而,现有地形位指数算法以整个研究区为参照,未考虑空间异质性,难以反映植被生长的局部环境特征。基于地理学第三定律对地理环境相似的强调,融合“空间位置邻近”和“环境特征相似”,对传统地形位模型进行改进：(1)引入局部窗口算法,以突出局部地形特征;(2)在不同生境因子组合下测算地形位指数,以排除环境差异对地形位作用的干扰。案例研究表明,新模型有效提升了地形位指数对植被覆盖水平的解释力度;当考虑生境因子组合,且采用最优窗口时,局部窗口地形位指数与植被覆盖度之间的相关性最高。此外,通过观察不同生境组合下的地形位指数发现,在高热少水阴坡和高热少水阳坡条件下,植被覆盖度与局部窗口地形位指数具有更高相关性;可见,越是水资源相对匮乏区域,植被覆盖对局部窗口地形位的响应越敏感。本文有望为植被恢复评价与规划提供新的指标。  相似文献   

基于均值变点法提取地形起伏度的影响因素分析——以黄河流域(山西段)为例     

宁婷  崔伟  马晓勇 《测绘通报》2022,(2):159-163

地形起伏度因子在宏观尺度生态评估中具有重要作用。均值变点法是确定地形起伏度最佳分析窗口的常用方法,但其影响因素尚缺乏研究。本文以黄河流域(山西段)为例,基于DEM数据和均值变点法提取了研究区地形起伏度,并探讨了分析窗口样本数量、DEM分辨率和地貌类型3种因素的影响。结果表明：(1)分析窗口样本数量对最佳分析窗口取值有明显影响。随着样本数量的增加,变点所在的最佳分析窗口面积也不断增加。(2)DEM分辨率对最佳分析窗口取值有一定影响。分析窗口面积取值范围一致时,基于30 m ASTER GDEM计算得到的最佳分析窗口面积小于基于90 m SRTM DEM的最佳分析窗口面积。(3)地貌类型对最佳分析窗口取值的影响不大。当分析窗口样本数量一致时,不同地貌类型区及整个研究区最佳分析窗口相同或接近。总体而言,分析窗口样本数量是最关键的影响因素。  相似文献   

航空重力数据谐波小波滤波中卷积运算的处理     

田颜锋  李姗姗  吴星  叶修松 《海洋测绘》2010,30(2):4-6

数据的滤波提取是航空重力测量数据处理的一个重要环节。谐波小波滤波器在频域具有良好的盒形谱特征,可以较好地实现信号的滤波。但谐波小波滤波器是一个连续函数,航空重力测量采集的信号是离散的,无法直接进行卷积运算。讨论了谐波小波用于航空重力数据滤波处理时的卷积运算处理方法,给出了谐波小波频域卷积的算法实现过程和仿真算例。  相似文献   

大气红外窗区(10.5-11.5μm和11.5-12.5μm)辐射传输的敏感性试验   总被引：1，自引：0，他引：1  

魏丽  钟强 《高原气象》1988,(3)

大气窗区卫星红外遥感的辐射资料可应用于地表温度的确定,但必须考虑大气影响。为此,本文利用辐射传输模式和中纬度及青藏高原模式大气,用数值模拟的方法研究了大气和地表状态(大气温、湿廓线、地表温度与高度)的改变对大气顶红外窗区射出辐射的影响以及射出辐射对发射方向(天顶角)依赖关系。主要结论见正文小结。  相似文献   

气候变化对中国木本植物物候的可能影响   总被引：76，自引：1，他引：76  

张福春 《地理学报》1995,50(5):402-410

本文根据我国的３０年的物候资料和气候资料的统计分析，论证了气温是影响中国木本植物物候的主要因子，在此基础上建立了物候与年平均气温的线性统计模式，又利用此模式分析计算了未来全球年平均气温升高０．５－２．０℃和未来大气中ＣＯ２浓度倍增而增暖情况下，我国主要木本植物物候期的大致变幅。  相似文献   

STUDY ON CORRELATIVE EARTHQUAKES AND SEISMIC WINDOW NETWORK IN TIANSHAN REGION     

Wang Gulling Ao Xueming 《内陆地震》1991,(4)

In this paper , by using the seismic data of strong earthquake (M≥7) which have occurred since 1900,correlative features of strong earthquake activity in Tianshan region which crosses China and USSR have been studied . Meanwhile , we selected 15 seismic windows (11 in China , 4 in USSR) by censusing , systematically researching and statistically examing seismic data of regional seismic network which are in Chian and USSR.The anomalous features of seismic window and seismic window network , prediction index and prediction plan have been studied . In the same time ,its prediction efficency have been evaluated . Several examples of successful earthquake prediction are given out in this paper .Finally ,the possible physical mechanism of the results are discussed.  相似文献   

漳州-华安“地震窗”及其机制          下载免费PDF全文

吕浩江  杨志辉 《地震地质》1989,11(2):33-38

漳州-华安是一个中强地震活动区,现今小震活动频繁。本文分析该区历史和现今地震活动特点,发现该区地震活动性涨落与闽台强震活动存在一定的相关性,因而得出该区是一个“地震窗”的认识。进而对“地震窗”的形成条件进行讨论,认为该区“地震窗”的形成是与其深部热作用所产生的向上垂直作用力紧密相关  相似文献   

Archaeomagnetic secular variation in the UK during the past 4000 years and its application to archaeomagnetic dating     

I. Zananiri  C.M. Batt  D.H. Tarling 《Physics of the Earth and Planetary Interiors》2007,160(2):97-107

This paper examines the limitations and deficiencies of the current British archaeomagnetic calibration curve and applies several mathematical approaches in an attempt to produce an improved secular variation curve for the UK for use in archaeomagnetic dating. The dataset compiled is the most complete available in the UK, incorporating published results, PhD theses and unpublished laboratory reports. It comprises 620 archaeomagnetic (directional) data and 238 direct observations of the geomagnetic field, and includes all relevant information available about the site, the archaeomagnetic direction and the archaeological age. A thorough examination of the data was performed to assess their quality and reliability. Various techniques were employed in order to use the data to construct a secular variation (SV) record: moving window with averaging and median, as well as Bayesian statistical modelling. The SV reference curve obtained for the past 4000 years is very similar to that from France, most differences occurring during the early medieval period (or Dark Ages). Two examples of dating of archaeological structures, medieval and pre-Roman, are presented based on the new SV curve for the UK and the implications for archaeomagnetic dating are discussed.  相似文献