Revista de Teledeteccion最新文献

{"title":"Monitorización de las concentraciones atmosféricas de metano y óxido nitroso a partir del Metop/IASI","authors":"O. García, M. Schneider, B. Ertl, E. Sepúlveda, C. Borger, C. Diekmann, F. Hase, F. Khosrawi, A. Cansado, M. Aullé","doi":"10.4995/raet.2020.13290","DOIUrl":"https://doi.org/10.4995/raet.2020.13290","url":null,"abstract":"Future of the Earth-atmosphere system will depend, to a large extent, on our capability of understanding all the processes driving climate change and, in this context, of outstanding importance are the monitoring and the investigation of greenhouse gases (GHGs), as main drivers of the Earth’s climate change. With this idea the project INMENSE (IASI for Surveying Methane and Nitrous Oxide in the Troposphere) was born, which aims to improve our current understanding of the atmospheric budgets of two of the most important well-mixed greenhouse gases, methane (CH4) and nitrous oxide (N2O). To this end, INMENSE has generated a new global observational data set of middle/upper tropospheric concentrations of CH4 and N2O from the space-based remote sensor IASI (Infrared Atmospheric Sounding Interferometer), on board the meteorological satellites EUMETSAT/Metop. In this work the INMENSE IASI CH4 and N2O products are presented, characterized and comprehensively validated by using a multiplatform reference database (aircraft vertical profiles, ground-based in-situ and remote-sensing observations). This extensive validation exercise suggests that the IASI CH4 and N2O products shows a precision between 1-3% and a bias of 2% as well as they are consistent temporally and spatially. Finally, the CH4 and N2O IASI observations over the Iberian Peninsula have been compared to MOCAGE chemical transport simulations, assessing the degree of agreement between both datasets. ","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2020-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45421238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seguimiento del fenómeno blanco de la laguna de la Cruz (Cuenca, España)","authors":"M. Ruiz, S. Morales, J. M. Soria","doi":"10.4995/raet.2020.14137","DOIUrl":"https://doi.org/10.4995/raet.2020.14137","url":null,"abstract":"In the present study, a five-year follow-up was performed by remote sensing of the calcium carbonate precipitation in La Gitana karstic lake also known as La Cruz (located on the province of Cuenca, Spain). The important role that calcium carbonate precipitation plays in the ecology of the lake is well known for its influence on the vertical migrations of phytoplankton, the concentration of bioavailable phosphorus and, therefore, the eutrophication and quality of the waters. Whiting take place between the months of July and August, and it can be studied at this time through its optical properties, with the main objective of offering updated data on a phenomenon traditionally studied and establishing possible relationships between abiotic factors such as temperature and/or rainfall. The atmospheric temperature data collected by the meteorological station suggest a possible relationship between the appearance of the white phenomenon and a pulse of previous maximum temperatures. On the other hand, no apparent relationship was found between rainfall and water whiting.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70599142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clasificación de usos y cubiertas del suelo y análisis de cambios en los alrededores de la Reserva Ecológica Manglares Churute (Ecuador) mediante una serie de imágenes Sentinel-1","authors":"D.A. Vélez-Alvarado, J. Álvarez-Mozos","doi":"10.4995/raet.2020.14099","DOIUrl":"https://doi.org/10.4995/raet.2020.14099","url":null,"abstract":"Management practices adopted in protected natural areas often ignore the relevance of the territory surrounding the actual protected land (buffer area). These areas can be the source of impacts that threaten the protected ecosystems. This paper reports a case study where a time series of Sentinel-1 imagery was used to classify the land-use/land-cover and to evaluate its change between 2015 and 2018 in the buffer area around the Manglares Churute Ecological Reserve (REMCh) in Ecuador. Sentinel-1 scenes were processed and ground-truth data were collected consisting of samples of the main land-use/land-cover classes in the region. Then, a Random Forests (RF) classification algorithm was built and optimized, following a five-fold cross validation scheme using the training dataset (70% of the ground truth). The remaining 30% was used for validation, achieving an Overall Accuracy of 84%, a Kappa coefficient of 0.8 and successful class performance metrics for the main crops and land use classes. Results were poorer for heterogeneous and minor classes, nevertheless the performance of the classification was deemed sufficient for the targeted change analysis. Between 2015 and 2018, an increase in the area covered by intensive land uses was evidenced, such as shrimp farms and sugarcane, which replaced traditional crops (mainly rice and banana). Even though such changes only affected the land area around the natural reserve, they might affect its water quality due to the use of fertilizers and pesticides that easily. Therefore, it is recommended that these buffer areas around natural protected areas be taken into account when designing adequate environmental protection measures and polices.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70599072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estrategia para la verificación de declaraciones PAC a partir de imágenes Sentinel-2 en Navarra","authors":"M. González-Audícana, S. López, I. Sola, J. Álvarez-Mozos","doi":"10.4995/raet.2020.14128","DOIUrl":"https://doi.org/10.4995/raet.2020.14128","url":null,"abstract":"In June 2018, the European Commission approved a modification of the Common Agricultural Policy (CAP) that, among other measures, proposed the use of Copernicus data for the verification process of farmers’ declarations. In recent years, several research efforts have been conducted to develop operational tools to accomplish this aim, among this the Interreg-POCTEFA PyrenEOS project. This article describes the methodological strategy proposed in the PyrenEOS project, which is based on the identification of the most probable crop using the Random Forests algorithm. Originally, the strategy builds a training sample from the CAP declarations file based on their NDVI time series. In addition, a series of rules are proposed to establish the level of uncertainty in the classification, and the criteria used to represent each parcel in the verification map with a simple colour coding (traffic light), where green represents correctly declared parcels, red indicates that the declaration is dubious, and orange corresponds to parcels with a high classification uncertainty. This verification strategy has been applied to two Agricultural Regions of Navarre, during an agricultural campaign where valuable field inspections were available, with a sampling intensity of 7% of the declared parcels. The results obtained, report overall accuracies close to 80% when the most probable crop was considered, and 90% when the two most probable crops were considered. This proves it is possible to identify correctly declared parcels (green parcels) with an error below 1%. Orange and red parcels should be considered for further analysis and inspection by technicians from the paying agencies, though they represent a small percentage of declarations (~6% of parcels), and include most of the wrong declarations.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44466253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photogrammetry and image processing techniques for beach monitoring","authors":"E. Sánchez-García, Á. Balaguer-Beser, J. Pardo-Pascual","doi":"10.4995/raet.2020.14107","DOIUrl":"https://doi.org/10.4995/raet.2020.14107","url":null,"abstract":"The land-water boundary varies according to the sea level and the shape of a beach profile that is continuously modelled by incident waves. Attempting to model the response of a landscape as geomorphologically volatile as beaches requires multiple precise measurements to recognize responses to the actions of various geomorphic agents. It is therefore essential to have monitoring systems capable of systematically recording the shoreline accurately and effectively. New methods and tools are required to efficiently capture, characterize, and analyze information – and so obtain geomorphologically significant indicators. This is the aim of the doctoral thesis, focusing on the development of tools and procedures for coastal monitoring using satellite images and terrestrial photographs. The work brings satellite image processing and photogrammetric solutions to scientists, engineers, and coastal managers by providing results that demonstrate the usefulness of these viable and lowcost techniques. Existing and freely accessible public information (satellite images, video-derived data, or crowdsourced photographs) can be converted into high quality data for monitoring morphological changes on beaches and thus help achieve a sustainable management of coastal resources.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47890067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Análisis espacio temporal y climático del humedal altoandino de Chalhuanca (Perú) durante el periodo 1986-2016","authors":"A. Pauca-Tanco, C. Ramos-Mamani, C. Luque-Fernández, C. Talavera-Delgado, J. F. Villasante-Benavides, J. P. Quispe-Turpo, L. Villegas-Paredes","doi":"10.4995/raet.2020.13325","DOIUrl":"https://doi.org/10.4995/raet.2020.13325","url":null,"abstract":"The high Andean wetlands are considered fragile ecosystems that provide ecosystem services for the maintenance of Andean biodiversity and economy. However, currently the global threat of climate change puts them at serious risk, which is why the objective of this study is to determine the spatial-temporal and climatic variation of the high Andean wetlands of Chalhuanca (Peru), during the period 1986-2016. Landsat scenes were obtained during dry season in the years 1986, 1991, 1996, 2001, 2006, 2011, 2016, and using remote sensing techniques the area and vegetation index (NDVI) of the wetlands were calculated. For precipitation, maximum and minimum temperature, an analysis of moving averages, linear trends and the Mann-Kendall non-parametric statistical test was carried out, and finally the interaction between the variables was evaluated by using correlation and regression. The results show that the wetland area has increased by 12 ha/year. As for the NDVI, an increase of the average values for the evaluated period has been detected, being 0.26 the average of minimum values. Analysis of climate data shows that precipitation, maximum and minimum temperature have increased by 32 mm/dec, 0.3 °C/dec and 0.6 °C/dec respectively, with the maximum and minimum temperature being significant (α<0.05). Finally, correlation and regression analyses show that the wetland area-precipitation, NDVI-precipitation and wetland-NDVI relationships are significant for α<0.01, while the wetland-temperature and NDVI-temperature relationships were significant for α<0.05.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2020-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48625201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generación de datos de cambio de coberturas vegetales en la sabana de Bogotá mediante el uso de series temporales con imágenes Landsat e imágenes sintéticas MODIS-Landsat entre los años 2007 y 2013","authors":"M. A. Zaraza-Aguilera, L. M. Manrique-Chacón","doi":"10.4995/raet.2019.12280","DOIUrl":"https://doi.org/10.4995/raet.2019.12280","url":null,"abstract":"Currently, new tools have been implemented that merge high-resolution temporal and spatial images for detection of change land cover. With the purpose of evaluate this type of techniques we generated a time series with Landsat satellite imagery and a time series with simulated images Landsat-MODIS, with the purpose of determining which of the two methods provides the best results in the change quantification in the Sabana of Bogota between 2007 and 2013. The processing consists of (i) Time Series with images Landsat trough BFAST, (ii) getting synthetic images through the ESTARFM algorithm; (iii) time series through BFAST with the use of simulated images. In the time series process, the series incorporating synthetic images and images corrected by the gaps generated the best accuracy indexes (global accuracy: 88.16% y Kappa: 76.52%) with respect to the series that incorporated only the images Landsat (global accuracy: 83% y Kappa: 65.18%); it indicates that densification of time series allow to get the best results in the quantification of changes and dynamics of land cover. The methodology applied represents an advance about generation of synthetic images and monitoring and detection of changes in land cover through time series. This is one of the first studies realized in the country that includes this type of process.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2019-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42686013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluando el desempeño de índices espectrales para identificar humedales alto andinos","authors":"J. Aponte-Saravia, J. E. Ospina-Noreña","doi":"10.4995/RAET.2019.10580","DOIUrl":"https://doi.org/10.4995/RAET.2019.10580","url":null,"abstract":"High Andean wetlands are habitats critical to life forms that have adapted to these extreme high mountain ecosystems, and for living beings that inhabit the lower parts of the basin; they are spaces that contain high diversity of flora and fauna characteristic of these places and are strongly associated with the water component. There lies the importance of identifying and monitoring ecosystems, using easy applicable methods and allowing results every two weeks approximately, they are inexpensive and highly reliable. Methods of monitoring in short periods, they are economically profitable and provide reliable information, they correspond to the evaluations by satellite images, specifically applying the methods of spectral indices. Thereby, the objective of the research was to evaluate the performance of six indices, considered to be the most used to identify high Andean wetlands (humidity index at surface level, normalized difference water index, normalized difference vegetation index, enhanced vegetation index, index of vegetation to the surface and tasseled CAP vegetation), in periods of low precipitation, using imagery Landsat 8 OLI. Comparing the performance of those indexes in the identification of wetlands through cross-validation and bootstrap statistical learning, the index that showed better performance was tasseled CAP vegetation, revealing the lowest value of the average of the mean square error of iterations between the test failure rate and training. The index tasseled CAP vegetation, shows greater reliability to identify and evaluate high Andean wetlands.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49639709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estudio de bofedales en los Andes ecuatorianos a través de la comparación de imágenes Landsat-8 y Sentinel-2","authors":"Carlos Jara, J. Delegido, J. Ayala, P. Lozano, A. Armas, V. Flores","doi":"10.4995/RAET.2019.11715","DOIUrl":"https://doi.org/10.4995/RAET.2019.11715","url":null,"abstract":"The objective of the present study was to compare the Landsat-8 and Sentinel-2 images to calculate the wetland´s extension, distribution and degree of conservation, in Reserva de Producción de Fauna Chinborazo (RPFCH) protected area located in the Andean region of Ecuador. This process was developed with in situ work in 16 wetlands, distributed in different conservation levels. The Landsat-8 and Sentinel-2 images were processed through a radiometric calibration (restoration of lost lines or píxels and correction of the stripe of the image) and an atmospheric correction (conversion of the digital levels to radiance values), to later calculate the Vegetation spectral indexes: NDVI, SAVI (L = 0.5) where L is a constant of the soil brightness component, EVI2 (improved vegetation index 2), NDWI (standard difference water index), WDRI (wide dynamic range vegetation index) and the Red Edge model that only this one has in Sentinel-2 in this study. Making a classification of the Bofedal ecosystem in satellite images by applying Random Forest, the most important variables with Landsat-8 were EVI2 (37.72%) and SAVI with L = 0.5 (30.97%), while with Sentinel-2 the most important variables correspond to the Red Edge (38.54%) and WDRI (27.06%). With the indices calculated, two categories of analysis were determined: a) wetland integrated by the levels: intervened [1], moderately conserved [2] and conserved [3] and b) other than wetland [4] integrated by areas that do not correspond to this ecosystem. Landsat-8 shows that the percentage of correct classifications of píxels belonging to the wetland category corresponds to: [1] 72.76%, [2] 58.38%, [3] 68.42%, while for the category other [4] were correct 95.15%. With Sentinel-2, the percentage of correct classifications corresponds to [1] 95.00%, [2] 82.60%, [3] 96.25%, while for the category other [4] the correct answers were 98.13%. In this way with Landsat-8 the wetland corresponds to 21.708,54 ha (41.21%), while with Sentinel-2 the wetland represents a total of 20,518 ha (38.95%), of the 52,560 ha that belong to the RPFCH, concluding that Sentinel-2, due to its better spatial resolution, and the incorporation of its new bands in Red Edge, obtains better results in image classification.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45680670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Methods for tree cover extraction from high resolution orthophotos and airborne LiDAR scanning in Spanish dehesas","authors":"I. Borlaf-Mena, Mihai A. Tanase, A. Gómez-Sal","doi":"10.4995/RAET.2019.11320","DOIUrl":"https://doi.org/10.4995/RAET.2019.11320","url":null,"abstract":"Dehesas are high value agroecosystems that benefit from the effect tree cover has on pastures. Such effect occurs when tree cover is incomplete and homogeneous. Tree cover may be characterized from field data or through visual interpretation of remote sensing data, both time-consuming tasks. An alternative is the extraction of tree cover from aerial imagery using automated methods, on spectral derivate products (i.e. NDVI) or LiDAR point clouds. This study focuses on assessing and comparing methods for tree cover estimation from high resolution orthophotos and airborne laser scanning (ALS). RGB image processing based on thresholding of the ‘Excess Green minus Excess Red’ index with the Otsu method produced acceptable results (80%), lower than that obtained by thresholding the digital canopy model obtained from the ALS data (87%) or when combining RGB and LiDAR data (87.5%). The RGB information was found to be useful for tree delineation, although very vulnerable to confusion with the grass or shrubs. The ALS based extraction suffered for less confusion as it differentiated between trees and the remaining vegetation using the height. These results show that analysis of historical orthophotographs may be successfully used to evaluate the effects of management changes while LiDAR data may provide a substantial increase in the accuracy for the latter period. Combining RGB and Lidar data did not result in significant improvements over using LIDAR data alone.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49234363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}