Photogrammetrie Fernerkundung Geoinformation最新文献_第3页

Multi-temporal Analysis of RapidEye Data to Detect Natural Vegetation Phenology During Two Growing Seasons in the Northern Negev, Israel 以色列内盖夫北部两个生长季节自然植被物候的RapidEye数据多时相分析

Photogrammetrie Fernerkundung Geoinformation Pub Date : 2015-05-01 DOI: 10.1127/PFG/2015/0258

Stefanie Elste, C. Gläßer, I. Walther, Christian Götze

引用次数: 4

Georeferencing Multi-source Geospatial Data Using Multi-temporal TerraSAR-X Imagery: a Case Study in Qixing Farm, Northeast China 基于多时相TerraSAR-X影像的多源地理空间数据参考——以东北七星农场为例

Photogrammetrie Fernerkundung Geoinformation Pub Date : 2015-05-01 DOI: 10.1127/PFG/2015/0262

Q. Zhao, C. Hütt, V. Lenz-Wiedemann, Y. Miao, Fei Yuan, Fusuo Zhang, G. Bareth

引用次数: 7

Development of Multi-Temporal Landslide Inventory Information System for Southern Kyrgyzstan Using GIS and Satellite Remote Sensing 基于GIS和卫星遥感的吉尔吉斯斯坦南部多时相滑坡调查信息系统开发

Photogrammetrie Fernerkundung Geoinformation Pub Date : 2015-05-01 DOI: 10.1127/PFG/2015/0261

D. Golovko, S. Roessner, R. Behling, H. Wetzel, B. Kleinschmit

{"title":"Development of Multi-Temporal Landslide Inventory Information System for Southern Kyrgyzstan Using GIS and Satellite Remote Sensing","authors":"D. Golovko, S. Roessner, R. Behling, H. Wetzel, B. Kleinschmit","doi":"10.1127/PFG/2015/0261","DOIUrl":"https://doi.org/10.1127/PFG/2015/0261","url":null,"abstract":"Summary: In Southern Kyrgyzstan, landslides regularly endanger human lives and infrastructure. They are a very dynamic phenomenon with significant variations of the process activity in different years. This creates a need for the development of new methods of dynamic and spatially differentiated landslide hazard assessment at a regional scale. Because of the large size of the study area (over 12,000 km²), remote sensing data are a valuable and reliable source of detailed and consistent spatial information for landslide investigations in Southern Kyrgyzstan. The paper demonstrates how GIS and remote sensing techniques are used for the acquisition, verification and homogenization of heterogeneous multi-source landslide data with the goal of generating a multi-temporal landslide inventory. Special emphasis is placed on the spatial data consistency, the documentation of temporal information and the possibility to document repeated slope failures within the same slope. The multi-temporal landslide inventory is an integral part of a landslide inventory information system, which is implemented in the QGIS environment and provides self-customized functionality for data queries and spatial analysis including the derivation of landslide attributes. The information system contains additional spatial base data such as a spatially consistent multi-temporal archive of satellite images and topographic maps.","PeriodicalId":56096,"journal":{"name":"Photogrammetrie Fernerkundung Geoinformation","volume":"2006 1","pages":"157-172"},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86926679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 19

Enhancement of Lidar Planimetric Accuracy using Orthoimages 利用正射影增强激光雷达平面测量精度

Photogrammetrie Fernerkundung Geoinformation Pub Date : 2015-05-01 DOI: 10.1127/PFG/2015/0260

K. Bakuła, W. Dominik, W. Ostrowski

引用次数: 2

An Algorithm to Generate a Simplified Railway Network through Generalization 一种泛化生成简化铁路网的算法

Photogrammetrie Fernerkundung Geoinformation Pub Date : 2015-02-01 DOI: 10.1127/PFG/2015/0255

Paul Czioska, F. Thiemann, Monika Sester, R. Giese, Hermann Vogt

引用次数: 0

Comparison of two Statistical Methods for the Derivation of the Fraction of Absorbed Photosynthetic Active Radiation for Cotton 棉花吸收光合有效辐射比值的两种统计方法的比较

Photogrammetrie Fernerkundung Geoinformation Pub Date : 2015-02-01 DOI: 10.1127/PFG/2015/0250

S. Lex, Sarah Asam, F. Löw, C. Conrad

{"title":"Comparison of two Statistical Methods for the Derivation of the Fraction of Absorbed Photosynthetic Active Radiation for Cotton","authors":"S. Lex, Sarah Asam, F. Löw, C. Conrad","doi":"10.1127/PFG/2015/0250","DOIUrl":"https://doi.org/10.1127/PFG/2015/0250","url":null,"abstract":"The fraction of absorbed photosynthetic active radiation (FAPAR) is an important input for modelling biomass increase and agricultural yield and can be calculated based on optical remote sensing data. In this study two remote sensing based approaches to derive the FAPAR for irrigated cotton in Fergana valley, Uzbekistan, are tested and compared: (i) FAPAR rescale from the normalized difference vegetation index (NDVI) (“percentile approach”), and (ii) an empirical regression approach based on NDVI. In the rescaling approach FAPAR was derived by relating upper and lower percentiles derived from the NDVI distribution of cotton fields from the entire study area to fixed FAPAR minima (bare soil) and maxima. NDVI was derived from multi-temporal 6.5 m RapidEye data acquired throughout 2011. For the regression approach FAPAR data was collected in situ from cotton fields during the vegetation season. The percentile approach delivered an RMSE of 0.10 whilst regression was only slightly better with an RMSE of 0.07. Hence, the percentile approach could be concluded as being a fast and easy alternative to field data demanding empirical regressions for the derivation of FAPAR on cotton fields.","PeriodicalId":56096,"journal":{"name":"Photogrammetrie Fernerkundung Geoinformation","volume":"26 1","pages":"55-67"},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73451743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Estimate leaf chlorophyll of rice using reflectance indices and partial least squares 利用反射率指数和偏最小二乘估算水稻叶片叶绿素

Photogrammetrie Fernerkundung Geoinformation Pub Date : 2015-02-01 DOI: 10.1127/PFG/2015/0253

K. Yu, M. Gnyp, Lei Gao, Y. Miao, Xin-ping Chen, G. Bareth

引用次数: 18

Multitemporale und kantenbasierte Analyseverfahren zur Detektion agrarischer Landnutzungsdynamiken auf Teneriffa 天啊

Photogrammetrie Fernerkundung Geoinformation Pub Date : 2015-02-01 DOI: 10.1127/PFG/2015/0244

Sebastian Günthert, Simone Naumann, A. Siegmund

引用次数: 0

Themenheft Fernerkundung für Agrarmonitoring 用于农业监测的主题索引

Photogrammetrie Fernerkundung Geoinformation Pub Date : 2015-02-01 DOI: 10.1127/pfg/2015/0254

F. Beyer, Thomas Jarmer, Bastian Siegmann, Fabian Löw, Ulrich Michel, Wolfgang Kresse

引用次数: 0

Identific ation of Agricultural Crop Types in Northern Israel using Multitemporal RapidEye Data 利用多时相快速眼数据识别以色列北部农作物类型

Photogrammetrie Fernerkundung Geoinformation Pub Date : 2015-02-01 DOI: 10.1127/PFG/2015/0249

F. Beyer, T. Jarmer, B. Siegmann

{"title":"Identific ation of Agricultural Crop Types in Northern Israel using Multitemporal RapidEye Data","authors":"F. Beyer, T. Jarmer, B. Siegmann","doi":"10.1127/PFG/2015/0249","DOIUrl":"https://doi.org/10.1127/PFG/2015/0249","url":null,"abstract":"Summary: Accurate land use / land cover classifi-cation (LU/LC) of agricultural crops still repre-sents a major challenge for multispectral remotesensing. In order to obtain reliable classificationaccuracies on the basis of multispectral satellitedata,mergingcropclassesinratherbroadclassesisoftennecessary.Withregardtotherising availabil-ity and the improving spatial resolution of satellitedata, multitemporal analyses become increasinglyimportant for remote sensing investigations. Forthe separation of spectrally similar crops, multi-datesatelliteimagesinclude differentgrowthchar-acteristics duringthephenologicalperiod.Thepre-sent study aims at investigating a way to performhighlyaccurateclassificationswithnumerousagri-cultural classesusing multitemporalRapidEyedata. The Jeffries-Matusita separability (JM) wasused for applying a pre-procedure in order to findthe best multitemporal setting of all available im-ages withinone crop cycle, consisting of twoculti-vation periods P1 with 16 agricultural classes andP2 with 27 agricultural classes. Only one criticalclass pairing occurred for both P1 and P2 takinginto account the best multitemporal dataset. Themaximum likelihood (ML) classifier and the sup-port vector machine (SVM) were compared usingthemostsuitable multitemporalimages.Bothalgo-rithms achieved very high overall accuracies(OAA)of over 90%. SVM was slightly better witha classification accuracy of P1-OAA = 96.13% andP2-OAA=94.01%. MLprovidedaresult of OAA =94.83% correctly classified pixels for P1 and OAA= 93.28% for P2. Theprocessingtimeof ML,how-ever, was significantly shorter compared to SVM,infact by a factor of five.","PeriodicalId":56096,"journal":{"name":"Photogrammetrie Fernerkundung Geoinformation","volume":"30 1","pages":"21-32"},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86986396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8