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Journal articles on the topic 'Multitemporale'

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1

Geri, F., M. Giordano, A. Nucci, D. Rocchini, and A. Chiarucci. "Multitemporal analysis of forest landscape in the province of Siena (Italy) using historical maps." Forest@ - Rivista di Selvicoltura ed Ecologia Forestale 5, no. 1 (2008): 82–91. http://dx.doi.org/10.3832/efor0508-0050082.

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Santoro, A., and M. Agnoletti. "Multi-temporal analysis of energetic fluxes in the Maremma (Italy) landscape between XIX and XX century." Forest@ - Rivista di Selvicoltura ed Ecologia Forestale 7, no. 1 (2010): 199–222. http://dx.doi.org/10.3832/efor0632-007.

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3

Sabrina, Rahma Nafila Fitri, and Sudaryatno Sudaryatno. "MULTITEMPORAL ANALYSIS FOR TROPHIC STATE MAPPING IN BATUR LAKE AT BALI PROVINCE BASED ON HIGH-RESOLUTION PLANETSCOPE IMAGERY." International Journal of Remote Sensing and Earth Sciences (IJReSES) 17, no. 2 (2021): 149. http://dx.doi.org/10.30536/j.ijreses.2020.v17.a3381.

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Remote sensing data for analyzing and evaluating trophic state ecosystem problems seen in Batur Lake isan approach that is suitable for water parameters that cannot be observed terrestrially. As the multitemporal spatial data used in this study were extensive, it was necessary to consider the effectiveness and efficiency of the processing and analysis, therefore R Studio was used as a data processing tool. Theresearch aims to(1) map the trophic state of Batur Lake multitemporally usingPlanetScope Imagery;(2) assess the accuracy of the trophic state model and applyitto anothertemporal data as a
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Schoenebeck, Uta V. "Erkundung ohne Proben. Altlastenerfassung und- Erstbewertung durch multitemporale Karten-und Luftbildauswertung. Von Hans-Walter Borries. Vogel Buchverlage, 1992. 372 Seiten, zahlreiche Bilder. DM 88,-. ISBN. 3-8023-0474-8." Biologie in unserer Zeit 23, no. 4 (1993): 225. http://dx.doi.org/10.1002/biuz.19930230410.

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Pereira dos Santos, Arthur, Henzo Henrique Simionatto, and Elson Mendonca Felici. "VARIAÇÃO DO ÍNDICE NDVI E DA TEMPERATURA DA SUPERFÍCIE TERRESTRE NA MALHA URBANA DO MUNICÍPIO DE PARACATU –MG ENTRE 1985 E 2005." COLLOQUIUM EXACTARUM 12, no. 2 (2020): 119–29. http://dx.doi.org/10.5747/ce.2020.v12.n2.e323.

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This research aimed to evaluate, multitemporally, through the index of vegetation by normalized difference (NDVI) and the surface temperature (LST), the expansion of the urban fabric of the municipality of Paracatu (MG), which came to present, during the analyzed period , between 1985 and 2005, urbanization rate above Brazil. A multitemporal layout was prepared containing the results obtained and statistical analyzes were performed to verify if there was a significant difference between the years. There wasa variation of more than 2 ºC in the averages and maximum of your LST. Regarding the var
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Gris, Darlene, Helen Rezende de Figueiredo, and Antonio Conceição Paranhos Filho. "ANÁLISE MULTITEMPORAL EM ÁREAS DE NASCENTE NA ZONA URBANA DE IGUATEMI (MS)." Revista de Geociências do Nordeste 6, no. 2 (2020): 155–65. http://dx.doi.org/10.21680/2447-3359.2020v6n2id19766.

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Áreas úmidas são ecossistemas muito importantes para preservação da água e da vida, fornecendo diversos serviços ecossistêmicos. São ambientes frequentemente associados a áreas de nascentes, com espécies e outras características bastante particulares. Esse trabalho objetivou analisar as áreas úmidas na região urbana de Iguatemi (MS) quanto aos tipos de nascentes e as alterações sofridas pelas ações antrópicas durante o período de 1985 e 2017. Para tanto, foram realizadas técnicas de delimitação de bacia hidrográfica utilizando imagens de radar SRTM, bem como uma análise multitemporal a partir
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Yi, José L. R., Yosio E. Shimabukuro, and José A. Quintanilha. "Identificação e mapeamento de áreas de milho na região sul do Brasil utilizando imagens MODIS." Engenharia Agrícola 27, no. 3 (2007): 753–63. http://dx.doi.org/10.1590/s0100-69162007000400019.

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O presente trabalho teve como proposta avaliar a identificação e o mapeamento das áreas de milho da região noroeste do Estado do Rio Grande do Sul a partir de dados multitemporais do sensor MODIS (Moderate Resolution Imaging Spectroradiometer) a bordo do satélite Earth Observing System - EOS-AM (Terra). O algoritmo de classificação supervisionada Spectral Angle Mapper (SAM) foi aplicado com sucesso em uma série multitemporal de imagens EVI pré-processadas. Verificou-se que as áreas classificadas como milho na imagem coincidiam plenamente com áreas mais extensas ou contínuas (> 90 ha) de mil
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Jaque-Castillo, Edilia, Viviana Huiliñir, and Alfonso Fernández. "Presiones de borde en los Sistemas Naturales Protegidos: efectos sobre su conservación. Parque Nacional Laguna del Laja, Chile." Espacios 3, no. 5 (2017): 55. http://dx.doi.org/10.25074/07197209.5.349.

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<p>Se describen los cambios de cobertura del suelo en el entorno del área protegida Parque Nacional Laguna del Laja (37°22’LS – 37°28’LS, 71°16’LO – 71°26’LO) en la Región del Biobío y los efectos en su conservación. A través del análisis multitemporal de imágenes satelitales Landsat ETM+, TM, Y MSS años 1975, 1986, 2000, 2006 respectivamente, e imágenes satelitales Aster del año 2007. Dichas imágenes fueron corregidas utilizando el software ENVI 4.2© apoyado con la información del catastro de Bosque Nativo (Conama Conaf, 1997) y levantamiento en terreno. Todos estos antecedentes permiti
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Octariady, J., A. Hikmat, E. Widyaningrum, R. Mayasari, and M. K. Fajari. "VERTICAL ACCURACY COMPARISON OF DIGITAL ELEVATION MODEL FROM LIDAR AND MULTITEMPORAL SATELLITE IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 419–23. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-419-2017.

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Digital elevation model serves to illustrate the appearance of the earth's surface. DEM can be produced from a wide variety of data sources including from radar data, LiDAR data, and stereo satellite imagery. Making the LiDAR DEM conducted using point cloud data from LiDAR sensor. Making a DEM from stereo satellite imagery can be done using same temporal or multitemporal stereo satellite imagery. How much the accuracy of DEM generated from multitemporal stereo stellite imagery and LiDAR data is not known with certainty. The study was conducted using LiDAR DEM data and multitemporal stereo sate
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10

Huang, Liang, Qiuzhi Peng, and Xueqin Yu. "Change Detection in Multitemporal High Spatial Resolution Remote-Sensing Images Based on Saliency Detection and Spatial Intuitionistic Fuzzy C-Means Clustering." Journal of Spectroscopy 2020 (March 23, 2020): 1–9. http://dx.doi.org/10.1155/2020/2725186.

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In order to improve the change detection accuracy of multitemporal high spatial resolution remote-sensing (HSRRS) images, a change detection method of multitemporal remote-sensing images based on saliency detection and spatial intuitionistic fuzzy C-means (SIFCM) clustering is proposed. Firstly, the cluster-based saliency cue method is used to obtain the saliency maps of two temporal remote-sensing images; then, the saliency difference is obtained by subtracting the saliency maps of two temporal remote-sensing images; finally, the SIFCM clustering algorithm is used to classify the saliency dif
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11

Fosbury, Adam M. "Estimation with Multitemporal Measurements." Journal of Guidance, Control, and Dynamics 33, no. 5 (2010): 1518–26. http://dx.doi.org/10.2514/1.47984.

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12

Zhu, Wei, Qian Du, and James E. Fowler. "Multitemporal Hyperspectral Image Compression." IEEE Geoscience and Remote Sensing Letters 8, no. 3 (2011): 416–20. http://dx.doi.org/10.1109/lgrs.2010.2081661.

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13

Zhang, Xiaokang, Wenzhong Shi, Zhiyong Lv, and Feifei Peng. "Land Cover Change Detection from High-Resolution Remote Sensing Imagery Using Multitemporal Deep Feature Collaborative Learning and a Semi-supervised Chan–Vese Model." Remote Sensing 11, no. 23 (2019): 2787. http://dx.doi.org/10.3390/rs11232787.

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This paper presents a novel approach for automatically detecting land cover changes from multitemporal high-resolution remote sensing images in the deep feature space. This is accomplished by using multitemporal deep feature collaborative learning and a semi-supervised Chan–Vese (SCV) model. The multitemporal deep feature collaborative learning model is developed to obtain the multitemporal deep feature representations in the same high-level feature space and to improve the separability between changed and unchanged patterns. The deep difference feature map at the object-level is then extracte
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14

Shu, Chang, and Lihui Sun. "Automatic target recognition method for multitemporal remote sensing image." Open Physics 18, no. 1 (2020): 170–81. http://dx.doi.org/10.1515/phys-2020-0015.

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AbstractThe traditional target recognition method for the remote sensing image is difficult to accurately identify the specified targets from the massive remote sensing image data. Based on the theory of multitemporal recognition, an automatic target recognition method for the remote sensing image is proposed in this article. The proposed recognition method includes four modules: automatic segmentation of multitemporal remote sensing image, automatic target extraction of multitemporal remote sensing image, automatic processing of multitemporal remote sensing image, and automatic recognition of
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15

Anderson, Liana Oighenstein, Luiz Eduardo Oliveira e. Cruz de Aragão, André de Lima, and Yosio Edemir Shimabukuro. "Detecção de cicatrizes de áreas queimadas baseada no modelo linear de mistura espectral e imagens índice de vegetação utilizando dados multitemporais do sensor MODIS/TERRA no estado do Mato Grosso, Amazônia brasileira." Acta Amazonica 35, no. 4 (2005): 445–56. http://dx.doi.org/10.1590/s0044-59672005000400009.

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O objetivo desta pesquisa foi avaliar os dados do sensor MODIS para detectar e monitorar cicatrizes de áreas recém queimadas. Utilizamos imagens da reflectância de superfície do sensor MODIS: produto MOD09 (dia 5 de outubro) e produto MOD13A1 (meses de outubro e novembro). Foi avaliada também uma série temporal de um ano dos índices de vegetação (IV) EVI e NDVI (produto MOD13A1). Uma imagem do sensor ETM+ (dia 5 de outubro) foi utilizada como base para a delimitação dos polígonos amostrais e avaliação dos dados MODIS devido a sua melhor resolução espacial. A metodologia focou na aplicação do m
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16

Small, Christopher. "Multitemporal analysis of urban reflectance." Remote Sensing of Environment 81, no. 2-3 (2002): 427–42. http://dx.doi.org/10.1016/s0034-4257(02)00019-6.

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17

Sigurdsson, Jakob, Magnus O. Ulfarsson, Johannes R. Sveinsson, and Jose M. Bioucas-Dias. "Sparse Distributed Multitemporal Hyperspectral Unmixing." IEEE Transactions on Geoscience and Remote Sensing 55, no. 11 (2017): 6069–84. http://dx.doi.org/10.1109/tgrs.2017.2720539.

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18

Shen, Hongda, Zhuocheng Jiang, and W. Pan. "Efficient Lossless Compression of Multitemporal Hyperspectral Image Data." Journal of Imaging 4, no. 12 (2018): 142. http://dx.doi.org/10.3390/jimaging4120142.

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Hyperspectral imaging (HSI) technology has been used for various remote sensing applications due to its excellent capability of monitoring regions-of-interest over a period of time. However, the large data volume of four-dimensional multitemporal hyperspectral imagery demands massive data compression techniques. While conventional 3D hyperspectral data compression methods exploit only spatial and spectral correlations, we propose a simple yet effective predictive lossless compression algorithm that can achieve significant gains on compression efficiency, by also taking into account temporal co
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19

Lefsky, M. A., W. B. Cohen, and T. A. Spies. "An evaluation of alternate remote sensing products for forest inventory, monitoring, and mapping of Douglas-fir forests in western Oregon." Canadian Journal of Forest Research 31, no. 1 (2001): 78–87. http://dx.doi.org/10.1139/x00-142.

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This research evaluates the utility of several remote sensing data types for the purpose of mapping forest structure and related attributes at a regional scale. Several sensors were evaluated, including (i) single date Landsat Thematic Mapper (TM); (ii) multitemporal Landsat TM; (iii) Airborne Data Acquisition and Registration (ADAR), a sensor with high spatial resolution; (iv) Airborne Visible-Infrared Imaging Spectrometer (AVIRIS), a sensor with high spectral resolution; and (v) Scanning Lidar Imager Of Canopies By Echo Recovery (SLICER), a lidar sensor that directly measures the height and
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20

Feng, Quanlong, Jianyu Yang, Dehai Zhu, et al. "Integrating Multitemporal Sentinel-1/2 Data for Coastal Land Cover Classification Using a Multibranch Convolutional Neural Network: A Case of the Yellow River Delta." Remote Sensing 11, no. 9 (2019): 1006. http://dx.doi.org/10.3390/rs11091006.

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Coastal land cover classification is a significant yet challenging task in remote sensing because of the complex and fragmented nature of coastal landscapes. However, availability of multitemporal and multisensor remote sensing data provides opportunities to improve classification accuracy. Meanwhile, rapid development of deep learning has achieved astonishing results in computer vision tasks and has also been a popular topic in the field of remote sensing. Nevertheless, designing an effective and concise deep learning model for coastal land cover classification remains problematic. To tackle
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Magalhães, Ivo Augusto Lopes, Everton de Carvalho, Aguinaldo Silva, and Beatriz Lima de Paula. "ANÁLISE DA DINAMICA HIDROGEOMORFOLÓGICA NO RIO MIRANDA, ESTADO DE MATO GROSSO DO SUL POR MEIO DE IMAGENS LANDSAT SENSORES TM E OLI." Revista Cerrados 17, no. 01 (2020): 53–69. http://dx.doi.org/10.22238/rc24482692201917015369.

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Atualmente no Brasil, os estudos sobre as dinâmicas hidrogeomorfológicas por meio de dados de sensoriamento remoto ainda são escassos. Em rios com extensos percursos e áreas inóspitas faz jus o uso de técnicas de sensoriamento remoto para análise e monitoramento ambiental. Diante do exposto, o objetivo deste estudo foi analisar as mudanças na geomorfologia fluvial do rio Miranda no estado de Mato Grosso do Sul, MS por meio de séries de imagens multitemporais dos Sensores Tematic Mapper do satélite Landsat – 5 e OLI do Satélite Landsat- 8. A planície de inundação do rio Miranda apresenta aproxi
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OLIVEIRA, A. P. G., C. L. MIOTO, F. B. DALMAS, et al. "Multitemporal Analysis of the Vegetation Cover of the São Gabriel do Oeste, MS." Anuário do Instituto de Geociências - UFRJ 40, no. 3 (2017): 254–65. http://dx.doi.org/10.11137/2017_3_254_265.

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23

Perros, Nikolas, Dionissios Kalivas, and Rigas Giovos. "Spatial Analysis of Agronomic Data and UAV Imagery for Rice Yield Estimation." Agriculture 11, no. 9 (2021): 809. http://dx.doi.org/10.3390/agriculture11090809.

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In this study, a spatial analysis of agronomic and remote sensing data is carried out to derive accurate rice crop yield estimation. The variability of a series of vegetation indices (VIs) was calculated from remote sensing data obtained via a commercial UAS platform (e-Bee) at four dates (per stage of development), and the development of estimation models was conducted. The study area is located in the region of Chalastra (municipality of Thessaloniki, North Greece) and the primary data were obtained during the 2016 growing season. These data include ultra-high resolution remote sensing multi
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Sun, Jing, and Suwit Ongsomwang. "Multitemporal Land Use and Land Cover Classification from Time-Series Landsat Datasets Using Harmonic Analysis with a Minimum Spectral Distance Algorithm." ISPRS International Journal of Geo-Information 9, no. 2 (2020): 67. http://dx.doi.org/10.3390/ijgi9020067.

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An understanding of historical and present land use and land cover (LULC) information and its changes, such as urbanization and urban growth, is critical for city planners, land managers and resource managers in any rapidly changing landscape. To deal with this situation, the development of a new supervised classification method for multitemporal LULC mapping with long-term reliable information is necessary. The ultimate goal of this study was to develop a new classification method using harmonic analysis with a minimum spectral distance algorithm for multitemporal LULC mapping. Here, the Jian
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Duong, N. D., N. M. Phuong, and N. B. Thi. "DEVELOPMENT OF PHENOLOGY BASED ALGORITHM FOR CROPLAND AND CROP TYPE MAPPING WITH MULTITEMPORAL LANDSAT IMAGE DATA - CASE STUDY IN THE NORTHWEST OF VIETNAM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W7 (March 1, 2019): 11–17. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w7-11-2019.

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<p><strong>Abstract.</strong> Cropland mapping is very important for food security, policy development, land use planning, and environmental protection. Scientists have developed methods and techniques for cropland mapping with remote sensing image data. Both single date and multitemporal image data are used for generation of cropland and crop type maps. Multitemporal image data has advantages over single date image data from reliability and accuracy point of view because multitemporal image data allows to eliminate seasonality of vegetation. In this paper, the authors presen
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Ullah, Sana, Zhengkang Zuo, Feizhou Zhang, et al. "GPM-Based Multitemporal Weighted Precipitation Analysis Using GPM_IMERGDF Product and ASTER DEM in EDBF Algorithm." Remote Sensing 12, no. 19 (2020): 3162. http://dx.doi.org/10.3390/rs12193162.

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To obtain the high-resolution multitemporal precipitation using spatial downscaling technique on a precipitation dataset may provide a better representation of the spatial variability of precipitation to be used for different purposes. In this research, a new downscaling methodology such as the global precipitation mission (GPM)-based multitemporal weighted precipitation analysis (GMWPA) at 0.05° resolution is developed and applied in the humid region of Mainland China by employing the GPM dataset at 0.1° and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m DEM-b
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Dodt, Jürgen, and Christiane Lechtenbörger. "Farbkompositen — ein Hilfsmittel zur multitemporalen Kartenauswertung." KN - Journal of Cartography and Geographic Information 54, no. 5 (2004): 213–18. http://dx.doi.org/10.1007/bf03545076.

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Hollaus, Markus, and Norbert Pfeifer. "Multitemporales, flugzeuggetragenes Laserscanning für die Forstwirtschaft." Schweizerische Zeitschrift fur Forstwesen 168, no. 3 (2017): 134–41. http://dx.doi.org/10.3188/szf.2017.0134.

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Multi-temporal airborne laserscanning data for forestry applications During the last decade airborne laserscanning (ALS) data has been established as a suitable data source for three-dimensional description of forests and for deriving forest parameters. For the study area Vorarlberg, Austria, the potential of multi-temporal ALS data (data from 2004 and 2011) was analyzed for deriving the amount of harvests in terms of area and stem volume. The data were used as well to assess the site index with the aid of the changes in top heights. The analyses have shown that harvested areas could be detect
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Ma, Xiaoshuang, and Penghai Wu. "Multitemporal SAR Image Despeckling Based on a Scattering Covariance Matrix of Image Patch." Sensors 19, no. 14 (2019): 3057. http://dx.doi.org/10.3390/s19143057.

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This paper presents a despeckling method for multitemporal images acquired by synthetic aperture radar (SAR) sensors. The proposed method uses a scattering covariance matrix of each image patch as the basic processing unit, which can exploit both the amplitude information of each pixel and the phase difference between any two pixels in a patch. The proposed filtering framework consists of four main steps: (1) a prefiltering result of each image is obtained by a nonlocal weighted average using only the information of the corresponding time phase; (2) an adaptively temporal linear filter is empl
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Han, Youkyung, Anjin Chang, Seokkeun Choi, Honglyun Park, and Jaewan Choi. "An Unsupervised Algorithm for Change Detection in Hyperspectral Remote Sensing Data Using Synthetically Fused Images and Derivative Spectral Profiles." Journal of Sensors 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/9702612.

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Multitemporal hyperspectral remote sensing data have the potential to detect altered areas on the earth’s surface. However, dissimilar radiometric and geometric properties between the multitemporal data due to the acquisition time or position of the sensors should be resolved to enable hyperspectral imagery for detecting changes in natural and human-impacted areas. In addition, data noise in the hyperspectral imagery spectrum decreases the change-detection accuracy when general change-detection algorithms are applied to hyperspectral images. To address these problems, we present an unsupervise
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Zhang, Xiang, Xinming Tang, Xiaoming Gao, and Hui Zhao. "Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by Means of Alpha Model with Multisensor SAR Data." Advances in Meteorology 2018 (2018): 1–17. http://dx.doi.org/10.1155/2018/7914581.

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The objective of this research is to optimize the Alpha approximation model for soil moisture retrieval using multitemporal SAR data. The Alpha model requires prior knowledge of soil moisture range to constrain soil moisture estimation. The solution of the Alpha model is an undetermined problem due to the fact that the number of observation equations is less than the number of unknown parameters. This research primarily focused on the optimization of Alpha model by employing multisensor and multitemporal SAR data. The disadvantage of the Alpha model can be eliminated by the combination of mult
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Mesev, V. "MULTISCALE AND MULTITEMPORAL URBAN REMOTE SENSING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B2 (July 25, 2012): 17–21. http://dx.doi.org/10.5194/isprsarchives-xxxix-b2-17-2012.

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Biday,. "Radiometric Correction of Multitemporal Satellite Imagery." Journal of Computer Science 6, no. 9 (2010): 1027–36. http://dx.doi.org/10.3844/jcssp.2010.1027.1036.

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Candra, Danang Surya. "Deforestation detection using multitemporal satellite images." IOP Conference Series: Earth and Environmental Science 500 (July 4, 2020): 012037. http://dx.doi.org/10.1088/1755-1315/500/1/012037.

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35

IVASHCHUK, VLADIMIR D., and VITALY N. MELNIKOV. "MULTITEMPORAL GENERALIZATION OF THE SCHWARZSCHILD SOLUTION." International Journal of Modern Physics D 04, no. 02 (1995): 167–73. http://dx.doi.org/10.1142/s0218271895000119.

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The n-time generalization of the Schwarzschild solution is considered. The equations of geodesics for the metric are integrated. The multitemporal analogues of Newton’s laws for the extended objects described by the solution are suggested. The scalar-vacuum generalization of the solution is also presented.
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De Castro, Cristina, Fabio Grandi, and Maria Rita Scalas. "SCHEMA VERSIONING FOR MULTITEMPORAL RELATIONAL DATABASES." Information Systems 22, no. 5 (1997): 249–90. http://dx.doi.org/10.1016/s0306-4379(97)00017-3.

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37

Haertel, V., Y. E. Shimabukuro, and R. Almeida-Filho. "Fraction images in multitemporal change detection." International Journal of Remote Sensing 25, no. 23 (2004): 5473–89. http://dx.doi.org/10.1080/01431160412331269751.

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Broncano-Mateos, Carlos Javier, Carlos Pinilla, Rub�n Gonzalez-Crespo, and Andr�s Castillo-Sanz. "Relative Radiometric Normalization of Multitemporal images." International Journal of Interactive Multimedia and Artificial Intelligence 1, no. 3 (2010): 53. http://dx.doi.org/10.9781/ijimai.2010.139.

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Helgason, Sigurdur. "Integral geometry and multitemporal wave equations." Communications on Pure and Applied Mathematics 51, no. 9-10 (1998): 1035–71. http://dx.doi.org/10.1002/(sici)1097-0312(199809/10)51:9/10<1035::aid-cpa5>3.0.co;2-e.

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Shirzaei, Manoochehr. "A seamless multitrack multitemporal InSAR algorithm." Geochemistry, Geophysics, Geosystems 16, no. 5 (2015): 1656–69. http://dx.doi.org/10.1002/2015gc005759.

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La, Hien Phu, Yang Dam Eo, Soo Bong Lee, Wan Yong Park, and Jee Hee Koo. "Image simulation from multitemporal landsat images." GIScience & Remote Sensing 52, no. 5 (2015): 586–608. http://dx.doi.org/10.1080/15481603.2015.1062676.

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42

Byeungwoo Jeon and D. A. Landgrebe. "Decision fusion approach for multitemporal classification." IEEE Transactions on Geoscience and Remote Sensing 37, no. 3 (1999): 1227–33. http://dx.doi.org/10.1109/36.763278.

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Dubois, C., F. Stoffner, A. C. Kalia, M. Sandner, M. Labiadh, and M. Mimouni. "COPERNICUS SENTINEL-2 DATA FOR THE DETERMINATION OF GROUNDWATER WITHDRAWAL IN THE MAGHREB REGION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-1 (September 26, 2018): 37–44. http://dx.doi.org/10.5194/isprs-annals-iv-1-37-2018.

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&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; Agriculture plays an important role in the economy of the Maghreb region. Most of the water needed for irrigation comes from pumping of the aquifers. A controlled pumping of the groundwater resources does not exist yet, thus, estimating the total water consumption for agricultural use only with in situ data is nearly impossible. In order to overcome this lack of information, Copernicus data are used for determining the groundwater withdrawal through agriculture in the Maghreb region. This paper presents an approach for estimating and monitoring c
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Henits, L., C. Jürgens, and L. Mucsi. "Seasonal multitemporal land-cover classification and change detection analysis of Bochum, Germany, using multitemporal Landsat TM data." International Journal of Remote Sensing 37, no. 15 (2016): 3439–54. http://dx.doi.org/10.1080/01431161.2015.1125558.

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Le Breton-Miller, Isabelle, and Danny Miller. "Commentary: Family Firms and the Advantage of Multitemporality." Entrepreneurship Theory and Practice 35, no. 6 (2011): 1171–77. http://dx.doi.org/10.1111/j.1540-6520.2011.00496.x.

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In this commentary, we argue the need for multitemporality (MT)—the ability to achieve enduring success by meeting both short– and long–term challenges—and we show how many family firms are in a superior position to do that. We situate Lumpkin and Brigham's (L&amp;B's) long–term orientation (LTO) components within a multitemporal frame in part by relating them to their primary mechanisms of intertemporality. We then extend L&amp;B's LTO conception by moving from an organizational mindset to its effective actualization via multitemporal facilitators as they manifest in family firms, arguing als
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Li, Jiaying, Weidong Wang, Zheng Han, Yange Li, and Guangqi Chen. "Exploring the Impact of Multitemporal DEM Data on the Susceptibility Mapping of Landslides." Applied Sciences 10, no. 7 (2020): 2518. http://dx.doi.org/10.3390/app10072518.

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Digital elevation models (DEMs) are fundamental data models used for susceptibility assessment of landslides. Due to landscape change and reshaping processes, a DEM can show obvious temporal variation and has a significant influence on assessment results. To explore the impact of DEM temporal variation on hazard susceptibility, the southern area of Sichuan province in China is selected as a study area. Multitemporal DEM data spanning over 17 years are collected and the topographic variation of the landscape in this area is investigated. Multitemporal susceptibility maps of landslides are subse
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Aktar, Mumu, Md Al Mamun, and Md Ali Hossain. "Statistical Similarity Based Change Detection for Multitemporal Remote Sensing Images." Journal of Electrical and Computer Engineering 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/3123967.

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Change detection (CD) of any surface using multitemporal remote sensing images is an important research topic since up-to-date information about earth surface is of great value. Abrupt changes are occurring in different earth surfaces due to natural disasters or man-made activities which cause damage to that place. Therefore, it is necessary to observe the changes for taking necessary steps to recover the subsequent damage. This paper is concerned with this issue and analyzes statistical similarity measure to perform CD using remote sensing images of the same scene taken at two different dates
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Park, Honglyun, Jaewan Choi, Wanyong Park, and Hyunchun Park. "Modified S2CVA Algorithm Using Cross-Sharpened Images for Unsupervised Change Detection." Sustainability 10, no. 9 (2018): 3301. http://dx.doi.org/10.3390/su10093301.

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This study aims to reduce the false alarm rate due to relief displacement and seasonal effects of high-spatial-resolution multitemporal satellite images in change detection algorithms. Cross-sharpened images were used to increase the accuracy of unsupervised change detection results. A cross-sharpened image is defined as a combination of synthetically pan-sharpened images obtained from the pan-sharpening of multitemporal images (two panchromatic and two multispectral images) acquired before and after the change. A total of four cross-sharpened images were generated and used in combination for
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Azabdaftari, A., and F. Sunar. "SOIL SALINITY MAPPING USING MULTITEMPORAL LANDSAT DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 17, 2016): 3–9. http://dx.doi.org/10.5194/isprsarchives-xli-b7-3-2016.

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Soil salinity is one of the most important problems affecting many areas of the world. Saline soils present in agricultural areas reduce the annual yields of most crops. This research deals with the soil salinity mapping of Seyhan plate of Adana district in Turkey from the years 2009 to 2010, using remote sensing technology. In the analysis, multitemporal data acquired from LANDSAT 7-ETM&amp;lt;sup&amp;gt;+&amp;lt;/sup&amp;gt; satellite in four different dates (19 April 2009, 12 October 2009, 21 March 2010, 31 October 2010) are used. As a first step, preprocessing of Landsat images is applied.
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Chandran, Aneesh, and Swathy Ramadas. "CLEARMiner: Mining of Multitemporal Remote Sensing Images." International Journal of Computer Applications Technology and Research 4, no. 1 (2015): 48–52. http://dx.doi.org/10.7753/ijcatr0401.1009.

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