Stefanie Elste, C. Gläßer, I. Walther, Christian Götze
of these ecosystems. Phenology has proven to be a very suitable tool for this because it comprises “the study of the timing of recurring biological events, the causes of their timing with regard to biotic and abiotic forces, and the interrelation among phases of the same or different species” (Lieth 1974). Due to the spatial coverage as well as financial and time related savings, remote sensing techniques proved to be very suitable for these kinds of analyses. For example until now especially dense
{"title":"Multi-temporal Analysis of RapidEye Data to Detect Natural Vegetation Phenology During Two Growing Seasons in the Northern Negev, Israel","authors":"Stefanie Elste, C. Gläßer, I. Walther, Christian Götze","doi":"10.1127/PFG/2015/0258","DOIUrl":"https://doi.org/10.1127/PFG/2015/0258","url":null,"abstract":"of these ecosystems. Phenology has proven to be a very suitable tool for this because it comprises “the study of the timing of recurring biological events, the causes of their timing with regard to biotic and abiotic forces, and the interrelation among phases of the same or different species” (Lieth 1974). Due to the spatial coverage as well as financial and time related savings, remote sensing techniques proved to be very suitable for these kinds of analyses. For example until now especially dense","PeriodicalId":56096,"journal":{"name":"Photogrammetrie Fernerkundung Geoinformation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89051259","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}
Q. Zhao, C. Hütt, V. Lenz-Wiedemann, Y. Miao, Fei Yuan, Fusuo Zhang, G. Bareth
{"title":"Georeferencing Multi-source Geospatial Data Using Multi-temporal TerraSAR-X Imagery: a Case Study in Qixing Farm, Northeast China","authors":"Q. Zhao, C. Hütt, V. Lenz-Wiedemann, Y. Miao, Fei Yuan, Fusuo Zhang, G. Bareth","doi":"10.1127/PFG/2015/0262","DOIUrl":"https://doi.org/10.1127/PFG/2015/0262","url":null,"abstract":"","PeriodicalId":56096,"journal":{"name":"Photogrammetrie Fernerkundung Geoinformation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86830660","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}
D. Golovko, S. Roessner, R. Behling, H. Wetzel, B. Kleinschmit
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.
{"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":null,"pages":null},"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}
{"title":"Enhancement of Lidar Planimetric Accuracy using Orthoimages","authors":"K. Bakuła, W. Dominik, W. Ostrowski","doi":"10.1127/PFG/2015/0260","DOIUrl":"https://doi.org/10.1127/PFG/2015/0260","url":null,"abstract":"","PeriodicalId":56096,"journal":{"name":"Photogrammetrie Fernerkundung Geoinformation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84395141","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}
Paul Czioska, F. Thiemann, Monika Sester, R. Giese, Hermann Vogt
don Tube. Since this type of map lacks a lot of additional cartographic information, it has become also common to show the geometry of the route as an overlay on a real map, so that the user is able to locate stations and the travelled route in between. A dynamic enhancement of this type of map is the so called Live Map, where, in addition to the tracks, the positions of the moving vehicles are drawn in real-time. The position information can be gathered either directly from GPS or indirectly calculated through spatiotemporal interpolation on the given track, like it can be seen for example at the German “DB Zugradar”, www.bahn.de/zugradar (Fig. 1). A basic requirement for the routing of the trains is a graph structure of the track network.
{"title":"An Algorithm to Generate a Simplified Railway Network through Generalization","authors":"Paul Czioska, F. Thiemann, Monika Sester, R. Giese, Hermann Vogt","doi":"10.1127/PFG/2015/0255","DOIUrl":"https://doi.org/10.1127/PFG/2015/0255","url":null,"abstract":"don Tube. Since this type of map lacks a lot of additional cartographic information, it has become also common to show the geometry of the route as an overlay on a real map, so that the user is able to locate stations and the travelled route in between. A dynamic enhancement of this type of map is the so called Live Map, where, in addition to the tracks, the positions of the moving vehicles are drawn in real-time. The position information can be gathered either directly from GPS or indirectly calculated through spatiotemporal interpolation on the given track, like it can be seen for example at the German “DB Zugradar”, www.bahn.de/zugradar (Fig. 1). A basic requirement for the routing of the trains is a graph structure of the track network.","PeriodicalId":56096,"journal":{"name":"Photogrammetrie Fernerkundung Geoinformation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80264363","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}
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.
光合有效辐射吸收分数(FAPAR)是模拟生物量增加和农业产量的重要输入，可基于光学遥感数据计算。本研究对乌兹别克斯坦费尔干纳河谷灌溉棉花FAPAR的两种基于遥感的方法进行了测试和比较:(i)基于归一化植被指数(NDVI)的FAPAR重新标度(“百分位法”)和(ii)基于NDVI的经验回归方法。在重标度方法中，将整个研究区棉田NDVI分布的上、下百分位数与固定的FAPAR最小值(裸土)和最大值联系起来，得出FAPAR。NDVI来自于2011年全年获得的6.5 m RapidEye数据。对于回归方法，FAPAR数据是在植被季节从棉田现场收集的。百分位方法的RMSE为0.10，而回归的RMSE仅略好于0.07。因此，对于需要经验回归的田间数据，百分位数法可以作为一种快速简便的替代方法来推导棉花田的FAPAR。
{"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":null,"pages":null},"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}
K. Yu, M. Gnyp, Lei Gao, Y. Miao, Xin-ping Chen, G. Bareth
{"title":"Estimate leaf chlorophyll of rice using reflectance indices and partial least squares","authors":"K. Yu, M. Gnyp, Lei Gao, Y. Miao, Xin-ping Chen, G. Bareth","doi":"10.1127/PFG/2015/0253","DOIUrl":"https://doi.org/10.1127/PFG/2015/0253","url":null,"abstract":"","PeriodicalId":56096,"journal":{"name":"Photogrammetrie Fernerkundung Geoinformation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75197304","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}
{"title":"Multitemporale und kantenbasierte Analyseverfahren zur Detektion agrarischer Landnutzungsdynamiken auf Teneriffa","authors":"Sebastian Günthert, Simone Naumann, A. Siegmund","doi":"10.1127/PFG/2015/0244","DOIUrl":"https://doi.org/10.1127/PFG/2015/0244","url":null,"abstract":"","PeriodicalId":56096,"journal":{"name":"Photogrammetrie Fernerkundung Geoinformation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87984171","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}
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.
{"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":null,"pages":null},"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}
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