Validation of MODIS Vegetation Continuous Fields for monitoring deforestation and forest degradation: two cases in Mexico     

Yan Gao  Adrian Ghilardi  Jaime Paneque-Galvez  Margaret Skutsch  Jean François Mas 《国际地球制图》2016,31(9):1019-1031

This study assesses whether MODIS Vegetation Continuous Fields percent tree cover (PTC) data can detect deforestation and forest degradation. To assess the usefulness of PTC for detecting deforestation, we used a data set consisting of eight forest and seven non-forest categories. To evaluate forest degradation, we used data from two temperate forest types in three conservation states: primary (dense), secondary (moderately degraded) and open (heavily degraded) forest. Our results show that PTC can differentiate temperate forest from non-forest categories (p = 0.05) and thus suggests PTC can adequately detect deforestation in temperate forests. In contrast, single-date PTC data does not appear to be adequate to detect forest degradation in temperate forests. As for tropical forest, PTC can partially discriminate between forest and non-forest categories.  相似文献   

A Survey of the Spatio-Temporal Data Model   总被引：1，自引：0，他引：1  

Wu Qunyong  Sun Mei  Cui Lei 《地球科学进展》2016,31(10):1001-1011

Traditional GIS(Geographic Information System)mostly can only describe the transient state data and does not have the ability to deal with the temporal dynamic data. When the data changes, new data will take the place of the old data, namely the transient state change into another, and the old data will disappear. Therefore, it is unable to make an analysis of the updating changes of the data and predict the development trend of the future. In this case, TGIS (Temporal Geographic Information System) emerges and expands the time dimension on the basis of traditional GIS. Spatio-temporal data model is the key to TGIS. Spatio-temporal data modeling is not only related to dynamic expression of spatio-temporal objects, but also gives an important support for spatio-temporal analysis and reasoning. This paper summarized the theories and applications status at home and abroad of spatio-temporal data model in detail, illustrated family tree of spatio-temporal data model for the nearly fifty years, discussed improvement and application status of Base State with Amendments Model, Event-based Spatio-temporal Data Model, Object-oriented Data Model and other spatio-temporal data models, and raised the existing problems of spatio-temporal data model. The current existing problems mainly includes: ①There are a lot of spatio-temporal data models put forward, but some of them only focus on semantic design and neglect the verified; ②Most of existing spatio-temporal data model are for vector data, only the Event-based Spatio-temporal Data Model is raster data structure; ③At present, the expression the time-space information of geographic entity is relative separated with spatio-temporal data model; ④Spatio-temporal data model is mainly used in cadastral management, land use and forestry data updating, less application in other fields. In the end, the future development direction was put forward of spatio-temporal data model. In the time of big data and “Internet plus”, it is necessary to explore the big data spatio-temporal data model that supports multiple data formats.  相似文献   

白缘(鱼央)5S rDNA的扩增分析及其在染色体上的FISH定位     

张伟伟  付元帅  邵燕  王宝琴  石东里  张兰 《海洋学报》2016,38(6):82-88

本文分别对雌雄白缘(鱼央)的5S rDNA进行了PCR扩增和序列分析,并采用双色荧光原位杂交(FISH)技术,以白缘(鱼央)的5S rDNA序列和小麦的45S rDNA为探针,对其在白缘(鱼央)雌雄中期染色体上进行了FISH定位研究。结果表明,白缘(鱼央)5S rDNA序列无雌雄差异;5S rDNA的保守区序列为117 bp;5S rDNA和45S rDNA分别被定位于白缘(鱼央)的性染色体和第5号染色体上。同时从GenBank中获得了22种鱼的5S rDNA,运用DNAman软件构建了23种鱼的系统发育树,对白缘(鱼央)的进化地位进行了初步研究。本研究为阐明白缘(鱼央)在鱼类系统进化中的位置、重复序列在脊椎动物性染色体上的分布状况以及与性别决定与分化的关系,提供了资料积累和分析依据。  相似文献   

Longleaf Pine (Pinus palustris Mill.) Morphology and Climate/Growth Responses Along a Physiographic Gradient in North Carolina     

Thomas W. Patterson  Lindsay W. Cummings  Paul A. Knapp 《The Professional geographer》2016,68(2):238-248

Geographic differences in tree morphology and climate and growth responses of longleaf pine have been documented, yet how these differences vary at a larger scale has not. In this study, we documented changes in tree morphology and climate and radial growth responses of six longleaf pine (Pinus palustris Mill.) stands in three physiographic regions in North Carolina. We sampled from more than fifteen trees per stand and compared site- and regional-level total and latewood ring width values to temperature, precipitation, and drought. All morphological characteristics expressed a strong west–east gradient. Climate and radial growth response was strongest for the Sandhills region and then Piedmont and Coastal Plain regions. The distinct morphological characteristic gradient did not covary with climate and radial growth response, suggesting that additional environmental influences affect needle length, trunk diameter, and height.  相似文献   

Prediction of Seaward Slope Recession in Berm Breakwaters Using M5' Machine Learning Approach     

Alireza Sadat Hosseini  Mehdi Shafieefar 《海洋工程》2016,(1):19-32

In the design process of berm breakwaters, their front slope recession has an inevitable rule in large number of model tests, and this parameter being studied. This research draws its data from Moghim’s and Shekari’s experiment results. These experiments consist of two different 2D model tests in two wave flumes, in which the berm recession to different sea state and structural parameters have been studied. Irregular waves with a JONSWAP spectrum were used in both test series. A total of 412 test results were used to cover the impact of sea state conditions such as wave height, wave period, storm duration and water depth at the toe of the structure, and structural parameters such as berm elevation from still water level, berm width and stone diameter on berm recession parameters. In this paper, a new set of equations for berm recession is derived using the M5'' model tree as a machine learning approach. A comparison is made between the estimations by the new formula and the formulae recently given by other researchers to show the preference of new M5'' approach.  相似文献   

基于离散元模拟的二元颗粒柱坍塌特性研究     

崔溦  魏杰  张贵科  李宏璧 《岩土力学》2021,(1):280-290

常见的地质灾害如滑坡、泥石流、岩崩等通常都涉及不同形状的颗粒物质运动,这些形状不同的颗粒又多具有不同的尺寸和含量。基于典型的颗粒柱坍塌试验,首先根据试验方法确定了离散元模拟所需的各项参数,然后采用随机多面体方法生成了可控制长细比的大颗粒,利用离散元法就不同大颗粒含量下形态变化对二元颗粒柱坍塌特性的影响开展研究,研究结果表明:(1)利用离散元法可以较好地重现室内试验中小球和多面体组成的二元颗粒系统的颗粒柱坍塌过程;(2)在不同长细比的不规则大颗粒和小球组成的二元颗粒柱系统中,当大颗粒含量高于临界含量值20%时,二元颗粒柱坍塌持续的时间随非球形大颗粒长细比的增加而增加;(3)在不同长细比的不规则大颗粒和小球组成的二元颗粒柱中,当大颗粒含量高于临界含量值20%时,在相同百分比的大颗粒含量下,大颗粒长细比的增加会提高大颗粒平均配位数以及降低颗粒的运动能力,大颗粒间形成更强的互锁作用,降低了颗粒柱的整体流动性,使其最终堆积高度更高、最大跑出距离更短以及更小的归一化动能峰值。(4)在不同长细比的不规则大颗粒和小球组成的二元颗粒柱中,小颗粒可以较为明显降低大颗粒间摩擦及互锁作用,增加流动性,降低大骨料形态对坍塌过程的影响。  相似文献   

基于梯度提升算法的岩性识别方法     

王恒  姜亚楠  张欣  仲鸿儒  陈庆轩  高世臣 《吉林大学学报(地球科学版)》2021,51(3):940-950

传统的岩性识别方法如岩屑录井、钻井取心及测井资料解释等技术,对录井质量的依赖程度较高,识别精度与效率低,泛化能力差。随着计算机技术的迅速发展,将测井资料与计算机技术相结合开展岩性研究已成为岩性识别的有效手段。本文提出了一种基于梯度提升算法XGBoost和LightGBM的岩性识别方法。以苏里格气田苏东41-33区块下碳酸盐岩储层为例进行测试验证,采用该方法结合测井资料中的声波时差、自然伽马、光电吸收截面指数、密度、深侧向电阻率和补偿中子等6种参数进行岩性识别,并与KNN （K近邻分类器）、朴素贝叶斯和支持向量机等传统算法进行对比,结果表明,3种传统算法的岩性识别准确率分别为78.45%、74.43%和78.72%,基于梯度提升算法XGBoost和LightGBM的识别准确率分别达到了98.90%和98.72%,远高于传统算法。  相似文献   

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management   总被引：1，自引：0，他引：1  

Zizheng Guo  Yu Shi  Faming Huang  Xuanmei Fan  Jinsong Huang 《地学前缘(英文版)》2021,12(6):243-261

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.  相似文献   

我国中东部平原地区临界气温条件下降水相态判别分析   总被引：1，自引：0，他引：1  

陈双  谌芸  何立富  郭云谦 《气象》2019,45(8):1037-1051

基于2001—2013年地面观测和探空资料,对地面气温位于0～2℃(以下称临界气温)我国降雪的时空分布及其与降雨的垂直热力特征进行了研究,引入了决策树判别方法对上述条件下雪和雨进行了判别分析,结果表明:临界气温下降雪出现频率总体高于降雨、雨夹雪出现频率,且在我国华北南部至江南北部的中东部地区分布较多,年均可达7.69～15.38站次;临界气温下,降水相态为雨或雪对应的平均温度廓线最大差异位于650 hPa附近,且地面气温较低时,平均温度差异更明显,平均湿度廓线差异则主要位于低层,且在地面气温较高时,平均湿度差异更明显;临界气温下,降水相态为雨时,地面上空存在暖层样本占比,较降水相态为雪时更高,且降雨时暖层主要位于中层,降雪时暖层则主要位于低层,降雨时其暖层强度显著大于降雪时暖层强度;在临界气温下雨雪判别分析中,地面气温能显著提升判别准确率,湿球温度能在一定程度上提升判别准确率,基于云顶温度、中层融化参数、低层湿球温度构建的决策树判别模型,判别准确率达到91.86%,能较好地解决临界气温下雨和雪的判别问题。  相似文献   

气温变化对西峰黄土高原地温与梨树发育期的影响   总被引：2，自引：0，他引：2  

郭江勇  林纾  马鹏里 《干旱区地理》2007,30(6):852-857

用西北地区140站1961-2000年的气温资料和西峰黄土高原1971-2005年5,10,15,20cm地温和1984-2005年梨树发育期资料,分析了西北地区春季、夏季、秋季、冬季和年气温的变化事实,再用相关计算和典型年份对比,分析了地温的时间变化规律及其对梨树发育期的影响。结果表明,西北地区20世纪60年代冬季增温,其余降温,70年代均降温,80年代冬季增温,其余降温,90年代均增温,冬季的最明显。西峰10cm地温各季节呈持续升高的趋势,春季增温最明显为0.058℃/a,变幅也最大,冬季增温幅度次之为0.039℃/a,再是秋季为0.032℃/a,夏季增温幅度最小为0.029℃/a,上升趋势均通过0.05和0.01的信度检验。冬季、春季地温与梨树的各发育期均为负相关,即地温高,发育期早,地温低,发育期迟。冬季地温与梨树发育期相关最显著的是叶变始期和开花始期,相关系数为-0.41～-0.52,信度为0.05,春季地温与之相关最显著的是开花始期,相关系数为-0.68～-0.69,信度达0.001。春季地温对梨树发育期的影响具有明显的持续性和滞后性,冬季地温对梨树发育期影响有阶段性,春季地温对梨树发育期的影响比冬季的明显。  相似文献