Academic literature on the topic 'Multitemporal processing'
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Journal articles on the topic "Multitemporal processing"
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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 (March 24, 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 SpatialBigData;and (3) understand the trophic state impacton the water quality of Batur Lake based on physical factors andthelake’s chemical concentration (sulfur concentration). Theresearch showsthatthetrophic state of Batur Lake isin good condition,with an ultraoligotrophic state as the majority class,based on the mean Trophic State Index (TSI) value of9.49. The standard errorsof each trophic state parameter were0.010 for total phosphor, 0.609 for chlorophyll-a, and 0.225 for Secchi Disk Transparency (SDT). The multitemporal model demonstratesthat the correlation between the increase oftrophic state and mass fish death cases in Batur Lake is existent.
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Shu, Chang, and Lihui Sun. "Automatic target recognition method for multitemporal remote sensing image." Open Physics 18, no. 1 (June 5, 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 multitemporal remote sensing image. The automatic segmentation of the image target is introduced. The effectiveness of the segmentation technology is verified through the kernel function bandwidth algorithm. Linear feature extraction is used to extract the segmented image. The image extraction processing is described, which includes image profile analysis, image preprocessing, image feature analysis, the region of interest localization, image enhancement processing, recognition processing, and result output. According to the theory of pattern recognition, three different feature recognition images are given, which are partial separable recognition, weakly separable recognition, and fully separable recognition, and then, a new image recognition method is designed. To verify the practical application effect of the recognition method, the proposed method is compared with the traditional recognition method. Experimental results show that the proposed method can accurately identify the specified objects from the massive remote sensing image data and has a high potential for development. This article has an important guiding significance for image recognition.
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Esmaeili, Mostafa, Mahdi Motagh, and Andy Hooper. "Application of Dual-Polarimetry SAR Images in Multitemporal InSAR Processing." IEEE Geoscience and Remote Sensing Letters 14, no. 9 (September 2017): 1489–93. http://dx.doi.org/10.1109/lgrs.2017.2717846.
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Pavelka, Karel, Paulina Raeva, and Karel Pavelka. "Evaluating the Performance of Airborne and Ground Sensors for Applications in Precision Agriculture: Enhancing the Postprocessing State-of-the-Art Algorithm." Sensors 22, no. 19 (October 10, 2022): 7693. http://dx.doi.org/10.3390/s22197693.
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The main goals of the following paper are to evaluate the performance of two multispectral airborne sensors and compare their image data with in situ spectral measurements. Moreover, the authors aim to present an enhanced workflow for processing multitemporal image data using both commercial and open-source solutions. The research was provoked by the need for a relevant comparison between airborne and ground sensors for vegetation analysis and monitoring. The research team used an eBee fixed-wing platform and the multiSPEC 4c and Sequoia sensors. The authors carried out field measurements using a handheld spectrometer by Trimble—GreenSeeker. There were two flight campaigns which took place near the village of Tuhan in the Czech Republic. The results from the first campaign were discouraging, showing less possibility in the correlation between the aerial and field data. The second campaign resulted in a very high percentage of correlation between both types of data. The researchers present the image processing steps and their enhanced photogrammetric workflow for multitemporal data which helps experts and nonprofessionals to reduce their processing time.
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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 (July 11, 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 employed to further suppress the speckle; (3) the final output of each patch is obtained by a guided filter using both the original speckled data and the filtering result of step 3; and (4) an aggregation step is used to tackle the multiple estimations problem for each pixel. The despeckling experiments conducted on both simulated and real multitemporal SAR datasets reveal the pleasing performance of the proposed method in both suppressing speckle and retaining details, when compared with both advanced single-temporal and multitemporal SAR despeckling techniques.
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Sefrin, Oliver, Felix M. Riese, and Sina Keller. "Deep Learning for Land Cover Change Detection." Remote Sensing 13, no. 1 (December 28, 2020): 78. http://dx.doi.org/10.3390/rs13010078.
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Land cover and its change are crucial for many environmental applications. This study focuses on the land cover classification and change detection with multitemporal and multispectral Sentinel-2 satellite data. To address the challenging land cover change detection task, we rely on two different deep learning architectures and selected pre-processing steps. For example, we define an excluded class and deal with temporal water shoreline changes in the pre-processing. We employ a fully convolutional neural network (FCN), and we combine the FCN with long short-term memory (LSTM) networks. The FCN can only handle monotemporal input data, while the FCN combined with LSTM can use sequential information (multitemporal). Besides, we provided fixed and variable sequences as training sequences for the combined FCN and LSTM approach. The former refers to using six defined satellite images, while the latter consists of image sequences from an extended training pool of ten images. Further, we propose measures for the robustness concerning the selection of Sentinel-2 image data as evaluation metrics. We can distinguish between actual land cover changes and misclassifications of the deep learning approaches with these metrics. According to the provided metrics, both multitemporal LSTM approaches outperform the monotemporal FCN approach, about 3 to 5 percentage points (p.p.). The LSTM approach trained on the variable sequences detects 3 p.p. more land cover changes than the LSTM approach trained on the fixed sequences. Besides, applying our selected pre-processing improves the water classification and avoids reducing the dataset effectively by 17.6%. The presented LSTM approaches can be modified to provide applicability for a variable number of image sequences since we published the code of the deep learning models. The Sentinel-2 data and the ground truth are also freely available.
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Kim, Taeheon, and Youkyung Han. "Integrated Preprocessing of Multitemporal Very-High-Resolution Satellite Images via Conjugate Points-Based Pseudo-Invariant Feature Extraction." Remote Sensing 13, no. 19 (October 6, 2021): 3990. http://dx.doi.org/10.3390/rs13193990.
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Multitemporal very-high-resolution (VHR) satellite images are used as core data in the field of remote sensing because they express the topography and features of the region of interest in detail. However, geometric misalignment and radiometric dissimilarity occur when acquiring multitemporal VHR satellite images owing to external environmental factors, and these errors cause various inaccuracies, thereby hindering the effective use of multitemporal VHR satellite images. Such errors can be minimized by applying preprocessing methods such as image registration and relative radiometric normalization (RRN). However, as the data used in image registration and RRN differ, data consistency and computational efficiency are impaired, particularly when processing large amounts of data, such as a large volume of multitemporal VHR satellite images. To resolve these issues, we proposed an integrated preprocessing method by extracting pseudo-invariant features (PIFs), used for RRN, based on the conjugate points (CPs) extracted for image registration. To this end, the image registration was performed using CPs extracted using the speeded-up robust feature algorithm. Then, PIFs were extracted based on the CPs by removing vegetation areas followed by application of the region growing algorithm. Experiments were conducted on two sites constructed under different acquisition conditions to confirm the robustness of the proposed method. Various analyses based on visual and quantitative evaluation of the experimental results were performed from geometric and radiometric perspectives. The results evidence the successful integration of the image registration and RRN preprocessing steps by achieving a reasonable and stable performance.
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Liu, Bin, Zhengyu Yang, Jiaqing Wu, and Jie Gu. "OLAP analysis of user energy consumption based on multitemporal distribution characteristics." Journal of Physics: Conference Series 2290, no. 1 (June 1, 2022): 012045. http://dx.doi.org/10.1088/1742-6596/2290/1/012045.
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Abstract With the development of databases, online transaction processing (OLTP) can no longer meet the needs of end users for database query and analysis, and the simple query of large databases by SQL can not meet the requirements of end user analysis. Therefore, online analytical processing (OLAP) is proposed. concept. On the one hand, we explained the basic knowledge of OLAP, including OLAP multidimensional data concept, multidimensional data structure, multidimensional data analysis, characteristics, etc. On the other hand, we established an OLAP analysis model of the multi-temporal and spatial distribution characteristics of user energy consumption, which is refined provide support for the analysis of user energy consumption behavior.
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Amitrano, Donato, Raffaella Guida, and Giuseppe Ruello. "Multitemporal SAR RGB Processing for Sentinel-1 GRD Products: Methodology and Applications." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12, no. 5 (May 2019): 1497–507. http://dx.doi.org/10.1109/jstars.2019.2904035.
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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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<p><strong>Abstract.</strong> 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 crop water requirements in Tunisia based on multitemporal Sentinel-2 data. Using this multitemporal information, a thorough analysis of the different culture types over time is possible, from which a set of additional multitemporal features is deduced for crop type classification. In this paper, the contribution of those features is analyzed, showing a classification accuracy enhanced by 10<span class="thinspace"></span>% with the multitemporal features. Furthermore, relying on existing methods and FAO standards for the estimation of crop water needs, the methodology aims to estimate the specific crop water consumption. The results of the water estimates are validated against delimited areas where estimates of the water consumption are available from the authorities. Finally, as the study is conducted within the framework of an international technical cooperation, the methodology aims to be reproducible and sustainable for local authorities. The particularity of the results presented here is that they are achieved through automatic processing and using exclusively Open Source solutions, deployable on simple workstations.</p>
Dissertations / Theses on the topic "Multitemporal processing"
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Renzullo, Luigi John. "Radiometric processing of multitemporal sequences of satellite imagery for surface reflectance retrievals in change detection studies." Thesis, Curtin University, 2004. http://hdl.handle.net/20.500.11937/2075.
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A relative, lie-value image normalisation (LVIN) procedure was investigated as a means of estimating surface reflectances from sequences of Landsat TM and ETM+ imagery, and standardising image data for change detection studies when there are uncertainties in sensor calibration and atmospheric parameters over time. The basis of the LVIX procedure is that for an A-date sequence, the digital numbers (DNs) of N-1 overpass images can be mapped to the reflectance values of a reference image for a set of pseudo- invariant targets (PITs) common to all images in the sequence. The robust M-estimator was employed to provide the transformation function that achieved the mapping. The investigation also showed that in some instances the LVIN procedure could incorporate the modelled Path DN-the modelled DN for a target of zero surface reflectance. A lack of surface validation data was a limitation in the investigation. However, a qualitative evaluation of the LVIN procedure was possible by examining the pre- and post-normalisation image histograms. In a comparison with the results of the 6S radiative transfer code, it war observed that when both overpass and reference images were acquired with the same sensor, the LVIK procedure appeared t o correct for atmospheric effects; and when overpass and reference images were with different sensors, the LVIN procedure also corrected for between-sensor differences. Moreover, it was demonstrated for the more "temporally-invariant" PITs that the procedure retrieved surface reflectances that were on average within ±0.02 reflectance units.The ability of the LVIK procedure to standardise sequences of image data was further demonstrated in the study of vegetation change. The normalised difference vegetation index (NDVI) was calculated from LVIN estimates of surface reflectance for a selection of sites around the township of Mt. Barker, Western Australia. NDVI data had characteristics consistent with data that have been corrected for atmospheric effects. A modification to the LVIN procedure was also proposed based on an investigation of some empirically-derived vegetation reflectance relationships. Research into the robustness of the relationships for a greater range of vegetation types is recommended.
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Laben, Craig A. "A comparison of methods for forming multitemporal composites from NOAA advanced very high resolution radiometer data /." Online version of thesis, 1993. http://hdl.handle.net/1850/12137.
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Renzullo, Luigi John. "Radiometric processing of multitemporal sequences of satellite imagery for surface reflectance retrievals in change detection studies." Curtin University of Technology, Department of Applied Physics, 2004. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=15737.
Full textAbstract:
A relative, lie-value image normalisation (LVIN) procedure was investigated as a means of estimating surface reflectances from sequences of Landsat TM and ETM+ imagery, and standardising image data for change detection studies when there are uncertainties in sensor calibration and atmospheric parameters over time. The basis of the LVIX procedure is that for an A-date sequence, the digital numbers (DNs) of N-1 overpass images can be mapped to the reflectance values of a reference image for a set of pseudo- invariant targets (PITs) common to all images in the sequence. The robust M-estimator was employed to provide the transformation function that achieved the mapping. The investigation also showed that in some instances the LVIN procedure could incorporate the modelled Path DN-the modelled DN for a target of zero surface reflectance. A lack of surface validation data was a limitation in the investigation. However, a qualitative evaluation of the LVIN procedure was possible by examining the pre- and post-normalisation image histograms. In a comparison with the results of the 6S radiative transfer code, it war observed that when both overpass and reference images were acquired with the same sensor, the LVIK procedure appeared t o correct for atmospheric effects; and when overpass and reference images were with different sensors, the LVIN procedure also corrected for between-sensor differences. Moreover, it was demonstrated for the more "temporally-invariant" PITs that the procedure retrieved surface reflectances that were on average within ±0.02 reflectance units.The ability of the LVIK procedure to standardise sequences of image data was further demonstrated in the study of vegetation change. The normalised difference vegetation index (NDVI) was calculated from LVIN estimates of surface reflectance for a selection of sites around the township of Mt. Barker, Western Australia. NDVI data had characteristics consistent with data that have been corrected for atmospheric effects. A modification to the LVIN procedure was also proposed based on an investigation of some empirically-derived vegetation reflectance relationships. Research into the robustness of the relationships for a greater range of vegetation types is recommended.
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Marchesi, Silvia. "Advanced Pre-Processing and Change-Detection Techniques for the Analysis of Multitemporal VHR Remote Sensing Images." Doctoral thesis, Università degli studi di Trento, 2011. https://hdl.handle.net/11572/368788.
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Remote sensing images regularly acquired by satellite over the same geographical areas (multitemporal images) provide very important information on the land cover dynamic. In the last years the ever increasing availability of multitemporal very high geometrical resolution (VHR) remote sensing images (which have sub-metric resolution) resulted in new potentially relevant applications related to environmental monitoring and land cover control and management. The most of these applications are associated with the analysis of dynamic phenomena (both anthropic and non anthropic) that occur at different scales and result in changes on the Earth surface. In this context, in order to adequately exploit the huge amount of data acquired by remote sensing satellites, it is mandatory to develop unsupervised and automatic techniques for an efficient and effective analysis of such kind of multitemporal data.
In the literature several techniques have been developed for the automatic analysis of multitemporal medium/high resolution data. However these techniques do not result effective when dealing with VHR images. The main reasons consist in their inability both to exploit the high geometrical detail content of VHR data and to model the multiscale nature of the scene (and therefore of possible changes). In this framework it is important to develop unsupervised change-detection(CD) methods able to automatically manage the large amount of information of VHR data, without the need of any prior information on the area under investigation. Even if these methods usually identify only the presence/absence of changes without giving information about the kind of change occurred, they are considered the most interesting from an operational perspective, as in the most of the applications no multitemporal ground truth information is available.
Considering the above mentioned limitations, in this thesis we study the main problems related to multitemporal VHR images with particular attention to registration noise (i.e. the noise related to a non-perfect alignment of the multitemporal images under investigation). Then, on the basis of the results of the conducted analysis, we develop robust unsupervised and automatic change-detection methods. In particular, the following specific issues are addressed in this work:
1. Analysis of the effects of registration noise in multitemporal VHR images and definition of a method for the estimation of the distribution of such kind of noise useful for defining:
a. Change-detection techniques robust to registration noise (RN); the proposed techniques are able to significantly reduce the false alarm rate due to RN that is raised by the standard CD techniques when dealing with VHR images.
b. Effective registration methods; the proposed strategies are based on a multiscale analysis of the scene which allows one to extract accurate control points for the registration of VHR images.
2. Detection and discrimination of multiple changes in multitemporal images; this techniques allow one to overcome the limitation of the existing unsupervised techniques, as they are able to identify and separate different kinds of change without any prior information on the study areas.
3. Pre-processing techniques for optimizing change detection on VHR images; in particular, in this context we evaluate the impact of:
a. Image transformation techniques on the results of the CD process;
b. Different strategies of image pansharpening applied to the original multitemporal images on the results of the CD process.
For each of the above mentioned topic an analysis of the state of the art is carried out, the limitations of existing methods are pointed out and the proposed solutions to the addressed problems are described in details. Finally, experimental results conducted on both simulated and real data are reported in order to show and confirm the validity of all the proposed methods.
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Marchesi, Silvia. "Advanced Pre-Processing and Change-Detection Techniques for the Analysis of Multitemporal VHR Remote Sensing Images." Doctoral thesis, University of Trento, 2011. http://eprints-phd.biblio.unitn.it/533/1/PhD-Thesis-Marchesi_Final_April2011.pdf.
Full textAbstract:
Remote sensing images regularly acquired by satellite over the same geographical areas (multitemporal images) provide very important information on the land cover dynamic. In the last years the ever increasing availability of multitemporal very high geometrical resolution (VHR) remote sensing images (which have sub-metric resolution) resulted in new potentially relevant applications related to environmental monitoring and land cover control and management. The most of these applications are associated with the analysis of dynamic phenomena (both anthropic and non anthropic) that occur at different scales and result in changes on the Earth surface. In this context, in order to adequately exploit the huge amount of data acquired by remote sensing satellites, it is mandatory to develop unsupervised and automatic techniques for an efficient and effective analysis of such kind of multitemporal data.
In the literature several techniques have been developed for the automatic analysis of multitemporal medium/high resolution data. However these techniques do not result effective when dealing with VHR images. The main reasons consist in their inability both to exploit the high geometrical detail content of VHR data and to model the multiscale nature of the scene (and therefore of possible changes). In this framework it is important to develop unsupervised change-detection(CD) methods able to automatically manage the large amount of information of VHR data, without the need of any prior information on the area under investigation. Even if these methods usually identify only the presence/absence of changes without giving information about the kind of change occurred, they are considered the most interesting from an operational perspective, as in the most of the applications no multitemporal ground truth information is available.
Considering the above mentioned limitations, in this thesis we study the main problems related to multitemporal VHR images with particular attention to registration noise (i.e. the noise related to a non-perfect alignment of the multitemporal images under investigation). Then, on the basis of the results of the conducted analysis, we develop robust unsupervised and automatic change-detection methods. In particular, the following specific issues are addressed in this work:
1. Analysis of the effects of registration noise in multitemporal VHR images and definition of a method for the estimation of the distribution of such kind of noise useful for defining:
a. Change-detection techniques robust to registration noise (RN); the proposed techniques are able to significantly reduce the false alarm rate due to RN that is raised by the standard CD techniques when dealing with VHR images.
b. Effective registration methods; the proposed strategies are based on a multiscale analysis of the scene which allows one to extract accurate control points for the registration of VHR images.
2. Detection and discrimination of multiple changes in multitemporal images; this techniques allow one to overcome the limitation of the existing unsupervised techniques, as they are able to identify and separate different kinds of change without any prior information on the study areas.
3. Pre-processing techniques for optimizing change detection on VHR images; in particular, in this context we evaluate the impact of:
a. Image transformation techniques on the results of the CD process;
b. Different strategies of image pansharpening applied to the original multitemporal images on the results of the CD process.
For each of the above mentioned topic an analysis of the state of the art is carried out, the limitations of existing methods are pointed out and the proposed solutions to the addressed problems are described in details. Finally, experimental results conducted on both simulated and real data are reported in order to show and confirm the validity of all the proposed methods.
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Nascimento, Sergio Roberto Vital do. "Geoprocessamento aplicado a gest?o de informa??es territoriais do munic?pio de Grossos-RN :estudo multitemporal do uso e ocupa??o do solo." Universidade Federal do Rio Grande do Norte, 2004. http://repositorio.ufrn.br:8080/jspui/handle/123456789/16787.
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The present work was carried through in the Grossos city - RN and had as main objectives the elaboration of an physicist-ambient, socioeconomic survey and execution a multisecular evaluation of 11 years, between 1986 and 1996, using remote sensing products, to evaluate the modifications of the land use, aiming at the generation of an information database to implementation a geographical information system (GIS) to management the this city. For they had been in such a way raised given referring the two Demographic Censuses carried through by the IBGE (1991 and 2000) and compared, of this form was possible to the accomplishment of an evaluation on the demographic aspects (degree of urbanization, et?ria structure, educational level) and economic (income, habitation, vulnerability, human development). For the ambient physical survey the maps of the natural resources had been confectioned (simplified geology, hydrography, geomorphologi, veget covering, ground association, use and occupation), based in comments of field and orbital products of remote sensoriamento (images Spot-HRVIR, Landsat 5-TM and IKONOS - II), using itself of techniques of digital picture processing. The survey of these data and important in the identification of the potentialities and fragilities of found ecosystems, therefore allows an adequate planning of the partner-economic development by means of an efficient management. The project was part of a partnership between the Grossos city hall the municipal City hall of Grossos - RN and the Geoscience post-graduate program of the UFRN, more specifically the Geomatica laboratory LAGEOMA
O presente trabalho foi realizado no Munic?pio de Grossos RN e teve como principais objetivos ? elabora??o de um levantamento s?cio-econ?mico, f?sico-ambiental e execu??o uma avalia??o multitemporal de 11 anos, entre o per?odo de 1986 e 1996, utilizando-se de produtos de sensores orbitais, para avaliar as modifica??es ocorridas na utiliza??o e ocupa??o do solo, visando a gera??o de uma base informacional para implementa??o de um Sistema de Informa??es Geogr?ficas (SIG) voltado para a gest?o ambiental do referido Munic?pio. Para tanto foram levantados dados referentes a dois Censos Demogr?ficos realizados pelo IBGE (1991 e 2000) e comparados, desta forma foi poss?vel ? realiza??o de uma avalia??o sobre os aspectos demogr?ficos (grau de urbaniza??o, estrutura et?ria, n?vel educacional) e econ?micos (renda, habita??o, vulnerabilidade, desenvolvimento humano). Para o levantamento f?sico ambiental foram confeccionados os mapas dos recursos naturais (geologia simplificada, hidrografia, geomorfologia, cobertura vegetal, associa??o de solos, uso e ocupa??o), baseados em observa??es de campo e produtos orbitais de sensoriamento remoto (imagens SPOT-HRVIR, Landsat 5-TM e IKONOS - II), utilizando-se de t?cnicas de processamento de imagens digitais. O levantamento destes dados e importante na identifica??o das potencialidades e fragilidades dos ecossistemas encontrados, pois permite um planejamento adequado do desenvolvimento s?cio-econ?mico por meio de um gerenciamento eficaz. O projeto fez parte de uma parceria entre a Prefeitura municipal de GrossosRN e o Programa de P?s-gradua??o em Geoci?ncias da UFRN, mais especificamente o Laborat?rio de Geom?tica LAGEOMA
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Esquerdo, Julio Cesar Dalla Mora 1977. "Utilização de perfis multi-temporais do NDVI/AVHRR no acompanhamento da safra de soja no oeste do Parana." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/257089.
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Orientador: Jurandir Zullo JuniorTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola
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Resumo: O principal problema levantado nesta tese é que a ocupação do espaço rural para a produção agropecuária se efetiva sem a devida preocupação com os recursos naturais disponíveis, em especial o solo, e sem o conhecimento das características sócio-econômicas dos produtores. Uma das evidências para essa constatação é que ainda não há estudos suficientes sobre as dinâmicas ambientais e sociais do uso do solo, ocorrendo uma supervalorização da dimensão econômica na exploração dos mesmos. Objetivou-se realizar um estudo do meio físico, através de suas potencialidades e limitações, em sobreposição aos indicadores sócio-econômicos, com vistas a avaliar uma proposta metodológica de planejamento rural para o desenvolvimento sustentável. A partir daí procurou-se quantificar a adequabilidade do uso do solo dos municípios de Aguaí, Mogi Guaçú e Estiva Gerbi, Estado de São Paulo, para os anos de 1981, 1990 e 1997, compondo um banco de dados espaciais multitemporais. A avaliação sócio-econômica foi feita por meio da análise da dinâmica de ocupação e uso dos recursos naturais pelos agricultores, agrupados em setores censitários do IBGE, cujas variáveis e tipologia, georeferrenciadas, compuseram o banco de dados de atributos. A metodologia foi desenvolvida a partir da elaboração do Mapa de Adequabilidade do Uso do Solo dos municípios, empregando-se os Mapas de Aptidão Agrícola e de Uso e Cobertura do Solo, segundo o Método de Avaliação de Aptidão Agrícola, utilizando-se imagens dos satélites Landsat 2 (MSS) e Landsat 5 (TM). Foram também analisadas as transformações no uso dos solos pela tabulação cruzada e índices de exatidão global e Kappa, que indicam o grau de evolução nas mudanças ocorridas no espaço analisado. A caracterização sócio-econômica e tecnológica dos setores censitários foi efetivada por meio da Análise Fatorial de Correspondências Múltiplas (ACM) e da Classificação Hierárquica Ascendente, com os dados do Censo Agropecuário 1995/96. Os resultados da análise física multitemporal permitiram delimitar o histórico agroambiental do uso dos solos, representando a evolução e expansão agropecuária, em relação ao uso e adequabilidade dos mesmos. A análise espaço-temporal do uso intensivo do solo e da adequabilidade indicou uma forte evolução no sentido do aumento da ocupação dos solos, tanto para um uso adequado, quanto para uma sobreutilização. Nos três municípios, percebe-se que, com a intensificação da modernização da agricultura, as terras subutilizadas vão diminuindo, gradativamente de 1981 a 1997, apontando seu decréscimo na direção do desmatamento e/ou substituições das pastagens, para a introdução de culturas anuais e/ou permanentes, de maior valor comercial. Por outro lado, áreas que deveriam estar como reservas para preservação permanente acabam também sendo apropriadas por cultivos mais intensivos, ocorrendo, novamente, uma sobreutilização do solo. Foram definidos quatro tipos de agricultores nos municípios: modernos e diversificados citrícolas capitalizados, criadores descapitalizados de animais e familiares com produção vegetal diversificada. Como resultado final, obteve-se um conjunto de mapas, que traduzem o conhecimento integral dos espaços rurais e a ocupação do território. A metodologia proposta mostrou-se apropriada para o subsídio ao planejamento sócio-ambiental, propiciando elementos para um diagnóstico atualizado e eficaz, no estabelecimento de políticas públicas voltadas ao desenvolvimento rural sustentado
Abstract: The main problem raised in this thesis is that the occupation of the agricultural space for the farming, effectives production without the proper concern with the available natural resources, in special the ground, and without the knowledge of the social and economical characteristics of the producers. One of the causes for this confirmation is that it does not have enough studies yet on the environmental and social dynamic of the use of the land, occurring a supervaluation of the economic dimension in the exploration of agricultural ground. It was aimed to carry through a study of its potentialities and limitations, in overlapping to the social and economical index, with sights to evaluate a methodological proposal of agricultural planning for the sustainable development. Since then, it was tried to quantify the adequateness of the use of lands of the cities of Aguaí, Mogi Guaçú and Estiva Gerbi, State of São Paulo, for the years of 1981, 1990 and 1997, composing a multisecular space data base. The social and economical evaluation was made by the analysis of the dynamics of occupation and use of the natural resources for the agriculturists, grouped in tax sectors of the IBGE, whose georeferenced variable and typology had composed the bank of attributes. The methodology had as base the elaboration of the Map of Adequateness of the Use of Lands of the cities, using the Maps of Agricultural Aptitude and the Use and Covering of the Ground, according to Method of Classification of Agricultural Aptitude, using images of the satellites Landsat 2 (MSS), Landsat (5 TM) and Landsat 7 (ETM+). Also the transformations in the use of lands for the cross tabulation and index of global exactness and Kappa had been analyzed, that indicate the degree of evolution in the occured changes in the analyzed space. The social, economical and technological characterization of the tax sectors was accomplished by means of the Factorial Analysis of Correspondence (ACM) and the Ascending Hierarchic Classification, with the data of 1995/96 Farming Census. The results of the multisecular physical analysis had allowed to delimit the agro-environmental description of the use of the land, being represented the evolution and farming expansion in relation to the use and adequateness of lands. The analysis space-weather of the intensive use of the ground and the adequateness, indicated one strong evolution in the direction of the increase of the occupation of lands, as much for an adjusted use as for an over-use. In the three cities, it was perceived gradually that, with the intensification of the modernization of agriculture, the underutilized lands diminished, from 1981 to 1997, pointing its decrease in the direction of the deforestation and/or substitutions of the pastures with respect to the introduction of annual and/or permanent cultures of higher commercial value. On the other hand, lands that would have to remain as reserves for permanent preservation also finishing being appropriate for more intense cultivation, occurring, again, an over-use of the lands. Four types of agriculturists in the cities had been defined: modern and diversified, capitalized citrus producers, undercapitalized animal breeders, diversified familial vegetal production. As final result, a set of maps was gotten, aiming at the integral knowledge of the agricultural spaces and the occupation of the territory. The methodology proposal revealed appropriate for the subsidy to the spcial and environmental planning, propitiating elements for a fast, brought up to date and efficient diagnosis, in the establishment of directed public politics to the supported agricultural development
Doutorado
Planejamento e Desenvolvimento Rural Sustentável
Doutor em Engenharia Agrícola
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Lobry, Sylvain. "Modèles Markoviens pour les images SAR : application à la détection de l'eau dans les images satellitaires SWOT et analyse multi-temporelle de zones urbaines." Electronic Thesis or Diss., Paris, ENST, 2017. http://www.theses.fr/2017ENST0056.
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Afin d’obtenir une meilleure couverture, à la fois spatiale et temporelle de leurs mesures les hydrologues utilisent des données spatiales en plus de celles acquises sur place. Fruit d’une collaboration entre les agences spatiales française (le CNES) et américaine (JPL, NASA), la future mission SWOT a notamment pour but de fournir des mesures de hauteur des surfaces d’eau continentales en utilisant l’interférométrie radar à synthèse d’ouverture (SAR). Dans cette thèse, nous nous intéressons au problème de la détection de l’eau dans les images d’amplitude SWOT qui est ici un prérequis au traitement interférométrique. Dans cette optique, nous proposons d’utiliser une méthode dédiée à la détection des larges cours d’eau ainsi qu’un traitement spécifique pour la détection de rivières fines. La première méthode est basée sur un champ de Markov (MRF) pour la classification, conjointement à une estimation des paramètres de classes qui ne peuvent être supposés constants dans le cas de SWOT. L’estimation des paramètres peut également être modélisée par des champs de Markov. La seconde méthode s’appuie sur une détection de segments au niveau pixellique complétée par une connexion de ces segments. Afin d’étudier l’extension aux séries multi-temporelles, nous proposons des méthodes de traitement adaptées aux données SAR de zones urbaines. Ces zones présentent de forts rétro-diffuseurs, ayant une radiométrie largement supérieure à celle des autres points dans l’image. Les modèles présentés prennent explicitement en compte la présence de ces forts rétro-diffuseurs en considérant les images comme une somme de deux composantes (le fond et les cibles fortes). Différents termes de régularisation peuvent alors être utilisés pour chacune de ces deux composantes. Modélisés comme des champs de Markov, ils peuvent alors être optimisés exactement par recherche de coupure minimale dans un graphe. Nous présentons des applications en détection de cibles fortes, régularisation et détection de changement dans ces sériesTo obtain a better coverage both spatially and temporally, hydrologists use spaceborne data in addition to data acquired in situ. Resulting from a collaboration between NASA’s Jet Propulsion Laboratory (JPL) and the French Space Agency (CNES), the upcoming SWOT mission will provide global continental water elevation measures using Synthetic Aperture Radar (SAR) interferometry. In this dissertation, we address the problem of water detection in SWOT amplitude images, which is to be performed before the interferometric processing. To this end, we propose to use a method dedicated to the detection of large water bodies and a specific algorithm for the detection of narrow rivers. The first method is based on Markov Random Fields (MRF). The classification is regularized and the class parameters, which cannot be assumed constant in the case of SWOT, are jointly estimated. The second method is based on segment detection at the pixel level, completed by a connection step. To study the extension to multi-temporal data, we propose methods adapted to the processing of series of SAR images of urban areas. These areas feature strong scatterers, having a radiometry orders of magnitude higher than the other points in the image. The proposed models explicitly account for the presence of these strong scatterers by considering the images as a sum of two components (the background and the strong scatterers). Different regularization terms can then be applied to each of these components. Modeled as MRF, they can then be optimized exactly using graph cuts. We present applications for strong scatterers detection, regularization and change detection
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Smecca, Graziano. "La Geomatica nello studio multitemporale di una struttura architettonica: il Pavaglione di Lugo." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.
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Questo lavoro di tesi ha sviluppato alcuni tecniche della Geomatica inerenti allo studio multitemporale di una struttura architettonica. E' stato preso in esame il Pavaglione di Lugo, struttura di grande interesse architettonico e di notevole rilevanza urbanistica.
In questo lavoro sono stati affrontati due obiettivi, il primo riguardante la realizzazione di un modello 3D che consentisse di analizzare la struttura esistente, ed ha rappresentato la base per il successivo obiettivo, ovvero la ricostruzione virtuale di un oggetto non più esistente: l'obelisco. Entrambi gli obiettivi sono stati pienamente raggiunti con risultati soddisfacenti.
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Moretto, J. "Linking River Channel Forms and Processes in Gravel Bed Rivers: Time, Space, Remote Sensing and Uncertainty." Doctoral thesis, Università degli studi di Padova, 2014. http://hdl.handle.net/11577/3423802.
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The “modern” fluvial morphology, is the results of a series of events characterized by both natural and human dynamics. Recognizing the process responsible for particular morphology is not a simple analysis, it can be more difficult or impossible if the data collected have too low resolution or too high uncertainty in relation to the spatial and temporal scale assessed.
This work aims to analyse and optimize different data and collection methods, derived from different time, space and resolution scales, with a good equilibrium between time-consuming and results at low uncertainty.
Different gravel bed reaches were analysed as study area: Brenta, Piave, Tagliamento River (Italy) and Feshie River (Scotland).
Three geomorphic analyses were applied at different spatial and temporal scale. A planimetric approach through a multitemporal analysis over the last 30 years on the Brenta River. A volumetric approach through a revised colour bathymetry; hybrid digital terrain models (HDTM) building and comparison of different digital elevation models (DoD) was used to study relevant flood events that occurred in the North-East Italian rivers (Brenta, Piave and Tagliamento). A highly detailed resolution, derived from Terrestrial Laser Scanner (TLS) to study its uncertainty, was applied on the Feshie River and to some laboratory experiments.
Results show that on the Brenta River, lower active channel narrowing happened from 1981 to 1990 even if relatively important floods occurred. The active channel was likely at its minimum extent due to still relevant human impacts. Partial recovery of the active channel width was detected from 1990 to 2011 due to less gravel mining and human pressure.
The proposed methodology for producing high-resolution Digital Terrain Models (DTMs) in wet areas has an uncertainty comparable to LiDAR (Light Detection And Ranging) data in dry areas. The bathymetric model calibration only requires a dGPS survey in the wet areas contemporary to aerial images acquisition. Detailed and automatic erosion - deposition analyses starting from a DoD are possible thanks to the “principal erosion deposition analyser” script developed.
Density, angle of incidence and laser intensity seem to be the most uncertain influencing factors in DTMs building from TLS point clouds. A new TLS filter developed provides semi-automatic point cloud classifications to filter the vegetation.
The geomorphic approaches presented provide an adequate topographical description of the rivers to explore channel adjustments due to natural and human causes at different spatial and temporal scales. The study represents a valuable tool for any fluvial engineering, river topography description, river management, ecology and restoration purposes.La “moderna” morfologia fluviale, è il risultato di una serie di eventi caratterizzati da differenti dinamiche, naturali ed antropiche. Riconoscere i processi responsabili di una particolare morfologia, può divenire complesso se i dati disponibili presentano bassi livelli di risoluzione o eccessiva incertezza in funzione della scala temporale e spaziale analizzata. Questo lavoro si è focalizzato ad analizzare ed ottimizzare differenti tipi di dati e metodologie di rilievo in differenti tratti fluviali a fondo ghiaioso dell’Italia Nord-Orientale e della Scozia: Fiume Brenta, Piave e Tagliamento (Italia) e Fiume Feshie (Scozia). Tre differenti metodologie geomorfometriche sono state applicate a diverse scale spaziali e temporali. Un approccio planimetrico attraverso un’analisi multitemporale degl’ultimi 30 anni in un tratto del Fiume Brenta. Un approccio volumetrico attraverso una rivisitata applicazione di batimetria da colore, con costruzione di modelli digitali del terreno “ibridi” (HDTM) e comparazione di modelli di elevazione (DoD) per lo studio di un intenso evento di piena, avvenuto nei fiumi italiani considerati. Rilievi in laboratorio e nel Fiume Feshie ad alta risoluzione, tramite laser scanner terrestre (TLS), sono stati eseguiti per studiarne l’incertezza ed individuare metodologie di classificazione spaziale delle nuvole di punti. I risultati, mostrano che dal 1981 al 1990 nel Fiume Brenta persiste ancora un processo di restringimento dell’alveo attivo. L’impatto umano è ancora presente. L’alveo attivo presenta la sua minima estensione. Dal 1990 al 2011, sembra che un parziale recupero della larghezza dell’alveo attivo sia in atto. Minor pressione da estrazione di ghiaia e da impatto umano, caratterizzano questo periodo. La metodologia proposta per produrre DTM ad alta risoluzione in presenza di aree bagnate ha dimostrato un’incertezza comparabile con il LiDAR nelle aree secche. La calibrazione dei modelli batimetrici, richiede un rilievo dGPS nelle aree bagnate in “contemporaneo” con l’acquisizione delle foto aeree. Grazie allo script sviluppato (PrEDA), sono possibili più dettagliate e automatiche analisi dell’erosione e della deposizione. Densità, angolo di incidenza ed intensità laser sembrano essere i fattori che maggiormente influenzano l’incertezza nella realizzazione di modelli di elevazione da TLS. Il filtro sviluppato per nuvole TLS è in grado di fornire semi-automatici filtraggi della vegetazione. Gli approcci geomorfometrici presentati, forniscono adeguate descrizioni topografiche dei sistemi fluviali; utili ad esplorare aggiustamenti dei canali dovuti a cause naturali o antropiche in differenti scale spaziali e temporali. Lo studio proposto, può rappresentare un valido supporto alla topografia in ambito fluviale, alla progettazione di interventi di ingegneria fluviale, ad una adeguata gestione fluviale, considerando aspetti ecologici e di riqualificazione fluviale.
Book chapters on the topic "Multitemporal processing"
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Perissin, Daniele. "Interferometric SAR Multitemporal Processing: Techniques and Applications." In Multitemporal Remote Sensing, 145–76. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47037-5_8.
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Eklundh, Lars, and Per Jönsson. "TIMESAT for Processing Time-Series Data from Satellite Sensors for Land Surface Monitoring." In Multitemporal Remote Sensing, 177–94. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47037-5_9.
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Aiazzi, Bruno, Francesca Bovolo, Lorenzo Bruzzone, Andrea Garzelli, Davide Pirrone, and Claudia Zoppetti. "Change Detection in Multitemporal Images Through Single- and Multi-scale Approaches." In Mathematical Models for Remote Sensing Image Processing, 325–55. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66330-2_8.
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Janoth, Jürgen, Markus M. Eisl, Erwin M. Bakker, Rogier van Sterkenburg, Roberta Borgia, Salvo Sabina, and Fabio Volpe. "MMIPPS - A Software Package for Multitemporal and Multispectral Image Processing on Parallel Systems." In Parallel Computation, 398–407. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-49164-3_38.
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Copăcenaru, Olimpia, Adrian Stoica, Antonella Catucci, Laura De Vendictis, Alessia Tricomi, Savvas Rogotis, and Nikolaos Marianos. "Copernicus Data and CAP Subsidies Control." In Big Data in Bioeconomy, 265–90. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_20.
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AbstractThis chapter integrates the results of three pilots developed within the framework of the Horizon 2020 DataBio project. It aims to provide a broad picture of how products based on Earth Observation techniques can support the European Union’s Common Agricultural Policy requirements, whose fulfillments are supervised by National and Local Paying Agencies operating in Romania, Italy and Greece. The concept involves the use of the same data sources, mainly multitemporal series of Copernicus Sentinel-2 imagery, but through three different Big Data processing chains, tailored to each paying agency’s needs in terms of farm compliance assessment. Particularities of each workflow are presented together with examples of the results and their accuracy, calculated by validation against independent sources. Business value aspects for each use case are also discussed, emphasizing the way in which the automation of the CAP requests verification process through satellite technologies has increased the efficiency and reduced cost and time resources for the subsidy process. We end the chapter by highlighting the benefits of continuous satellite tracking as a substitute, but also complementary to the classical field control methods, and also the enormous potential of Earth Observation-based products for the agri-food market.
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"Processing of multitemporal data and change detection." In Advances in Photogrammetry, Remote Sensing and Spatial Information Sciences: 2008 ISPRS Congress Book, 245–66. CRC Press, 2008. http://dx.doi.org/10.1201/9780203888445-24.
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Gong, Jianya, Qiming Zhou, Guorui Ma, and Haigang Sui. "Processing of multitemporal data and change detection." In Advances in Photogrammetry, Remote Sensing and Spatial Information Sciences, 227–47. CRC Press, 2008. http://dx.doi.org/10.1201/9780203888445.ch17.
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Senthilnath, J., and X. S. Yang. "Multitemporal remote sensing image classification by nature- inspired techniques." In Bio-Inspired Computation and Applications in Image Processing, 187–219. Elsevier, 2016. http://dx.doi.org/10.1016/b978-0-12-804536-7.00009-0.
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Murugan, Mahalakshmi, Rohini Selvaraj, and Sureshkumar Nagarajan. "Assessment of land use land cover change detection in multitemporal satellite images using machine learning algorithms." In Cognitive Systems and Signal Processing in Image Processing, 27–45. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-12-824410-4.00006-4.
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Santos, Helane Cristina Aguiar, Carlos Rodrigo Tanajura Caldeira, Yanna Karoline Santos da Costa, Thamyres Marques da Silva, Tabilla Verena da Silva Leite, Valdeides Marques Lima, Olavo Pimentel Silva, Rafaela da Silva Guerino, Jefferson dos Santos Martins, and Marcos Augusto de Souza Gonçalves. "Multitemporal analysis of land use and occupation with a focus on agriculture, livestock and pebble extraction in the municipality of Ourém/PA, from 2016 to 2020." In Exploring the Field of Agricultural and Biological Sciences. Seven Editora, 2024. http://dx.doi.org/10.56238/sevened2023.001-014.
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The studies of the forms of use and coverage of the earth's surface are essential to provide subsidies for the environmental monitoring of a given area. The present work aimed to analyze the dynamics of land use and land cover in the municipality of Ourém/PA in the period from 2016 to 2020, generating representative information of the landscape dynamics, influenced by the physical and socioeconomic aspects inherent to this municipality. Land use and land cover classes were quantified and mapped with Google Earth Engine from 2016 to 2020. Data processing was performed using the ArcgisPro software to classify land use and land cover classes and to make maps. With the products generated, an image was selected for each year, in order to determine the areas for each thematic class of urban area, vegetation, agriculture and livestock, and pebble extraction, so that it was possible to quantify the class measurements. The results of each year were compared and a thematic map was prepared with the images selected to determine the use and occupation of the land in the municipality. The results revealed that the agriculture and pasture classes are predominant during the analyzed period, with a slight reduction in vegetation cover and a slight increase in the area of agriculture and pasture. Therefore, the identification and analysis of the classes of use and occupation provide both the understanding of these modes of use and the degradation to the environment, understanding the function of Man as a potential cause of this degradation.
Conference papers on the topic "Multitemporal processing"
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Huot, Etienne, Jean-Paul Rudant, Nicholas Classeau, B. Flasque, P. Guillope, Isabelle L. Herlin, Marc Sigelle, and W. Stroobants. "Image processing for multitemporal SAR images." In Remote Sensing, edited by Francesco Posa. SPIE, 1998. http://dx.doi.org/10.1117/12.331352.
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Amitrano, Donato, Gerardo Di Martino, Antonio Iodice, Daniele Riccio, and Giuseppe Ruello. "RGB SAR product exploiting multitemporal: General processing and applications." In 2017 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp). IEEE, 2017. http://dx.doi.org/10.1109/multi-temp.2017.8035221.
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Arthur, Daniel T. J., M. M. Khan, and L. C. Barclay. "Image processing for pathological visualization in multitemporal convoluted TIRI." In 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI). IEEE, 2012. http://dx.doi.org/10.1109/bhi.2012.6211685.
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Datta, Urmila. "Multimodal change monitoring using multitemporal satellite images." In Image and Signal Processing for Remote Sensing XXVII, edited by Lorenzo Bruzzone, Francesca Bovolo, and Jon Atli Benediktsson. SPIE, 2021. http://dx.doi.org/10.1117/12.2600099.
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Halimi, Abderrahim, Nicolas Dobigeon, Jean-Yves Toumeret, Steve McLaughlin, and Paul Honeine. "Unmixing multitemporal hyperspectral images accounting for endmember variability." In 2015 23rd European Signal Processing Conference (EUSIPCO). IEEE, 2015. http://dx.doi.org/10.1109/eusipco.2015.7362665.
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Datta, Urmila. "Infrastructure monitoring using SAR and multispectral multitemporal images." In Image and Signal Processing for Remote Sensing XXVI, edited by Claudia Notarnicola, Fabio Bovenga, Lorenzo Bruzzone, Francesca Bovolo, Jon Atli Benediktsson, Emanuele Santi, and Nazzareno Pierdicca. SPIE, 2020. http://dx.doi.org/10.1117/12.2573894.
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Dinguirard, Magdeleine C., Patrice J. Henry, and Madeleine Bodilis. "SPOT multitemporal calibration over stable desert areas." In Recent Advances in Sensors, Radiometric Calibration, and Processing of Remotely Sensed Data. SPIE, 1993. http://dx.doi.org/10.1117/12.161572.
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Fang, Leyuan, Shutao Li, and Jianwen Hu. "Multitemporal image change detection with compressed sparse representation." In 2011 18th IEEE International Conference on Image Processing (ICIP 2011). IEEE, 2011. http://dx.doi.org/10.1109/icip.2011.6116218.
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Tanizaki, Fumihiro, Michiharu Niimi, Sei-ichiro Kamata, and Eiji Kawaguchi. "Radiance transformation of multitemporal LANDSAT image for land cover classification." In Visual Communications and Image Processing '95, edited by Lance T. Wu. SPIE, 1995. http://dx.doi.org/10.1117/12.206704.
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Huo, Dongming, Jingxiong Zhang, Jiabing Sun, and Gaohuan Liu. "Bayesian networks for mapping salinity using multitemporal Landsat TM imagery." In Multispectral Image Processing and Pattern Recognition, edited by Xubang Shen and Jianguo Liu. SPIE, 2001. http://dx.doi.org/10.1117/12.441695.
Full textReports on the topic "Multitemporal processing"
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Groeneveld, Davis, and Williams. L51974 Automated Detection of Encroachment Events Using Satellite Remote Sensing. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), August 2002. http://dx.doi.org/10.55274/r0011300.
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As an integral part of the ongoing effort to develop an operational capability of remote sensing based pipeline encroachment monitoring, this investigation focused on the development of automated target detection using synthetic aperture radar (RADARSAT) and optical (QUICKBIRD, EROS) satellite imagery. Specifically, the study aimed at meeting the following objectives: To develop automated target detection algorithms for optical and radar imagery that replicate detection rates obtained through visual image interpretation; To investigate the utility of newly available high-resolution optical satellite imagery for encroachment monitoring; To reduce false alarms through the processing of multitemporal radar images; and To identify and prioritize areas of future research and development required for the operational application of the technology.