Landsat-8 Sensor Characterization and Calibration

Landsat-8 was launched on 11 February 2013 with two new Earth Imaging sensors to provide a continued data record with the previous Landsats. For Landsat-8, pushbroom technology was adopted, and the reflective bands and thermal bands were split into two instruments. The Operational Land Imager (OLI) is the reflective band sensor and the Thermal Infrared Sensor (TIRS), the thermal. In addition to these fundamental changes, bands were added, spectral bandpasses were refined, dynamic range and data quantization were improved, and numerous other enhancements were implemented. As in previous Landsat missions, the National Aeronautics and Space Administration (NASA) and United States Geological Survey (USGS) cooperated in the development, launch and operation of the Landsat- 8 mission. One key aspect of this cooperation was in the characterization and calibration of the instruments and their data. This Special Issue documents the efforts of the joint USGS and NASA calibration team and affiliates to characterize the new sensors and their data for the benefit of the scientific and application users of the Landsat archive. A key scientific use of Landsat data is to assess changes in the land-use and land cover of the Earth's surface over the now 43-year record. In order to perform these analyses and avoid confusing sensor changes with Earth surface changes, a solid understanding of the sensors' performance, consistent geolocation and radiometry are essential. Particularly with the significant changes in the Landsat-8 sensors relative to previous Landsat missions, this characterization becomes all the more important

Interpretasi Lahan Sawah Di Kecamatan Limboto Barat Menggunakan Citra Landsat 8 Oli (Interpretation of Paddy Fields in West Limboto Subdistrict Using Landsat 8 Oli)

- One of the issues of national food security is the availability of staple food in the form of rice in a sustainability. The availability of paddy fields in West Limboto subdistrict, which is one of the rice producing areas in Gorontalo Regency needs to be interpreted to be known if there is land conversion in the future. Calculation of rice fields can be interpreted using remote sensing data. The purpose of this research is to interpreationt the extent of paddy field located in West Limboto subdistrict. Landsat 8 OLI (Operational Land Imager) acquired November 20, 2015 is the data used in this study. GPS measuring instrument is used as a tool for checking the coordinates of sample points that will be in the fiel d check. The method by digital image processing landsat 8 OLI using supervised classification algorithm maximum likelihood. Landsat 8 layer stacking process then do corrected geometric. Unsupervised classification is performed as an initial interpretation stage to classify land cover and also as sample point extraction. Total 18 sample points were taken that were used for ground data. Reclassified using supervised method processing after finished ground data. The results show that the paddy fields about 886,66 ha spread in 8 villages. Keywords: paddy fields, supervised, mapping, west limboto, Gorontal

INTERPRETASI LAHAN SAWAH DI KECAMATAN LIMBOTO BARAT MENGGUNAKAN CITRA LANDSAT 8 OLI (Interpretation of Paddy Fields in West Limboto Subdistrict Using Landsat 8 OLI)

Abstract - One of the issues of national food security is the availability of staple food in the form of rice in a sustainability. The availability of paddy fields in West Limboto subdistrict, which is one of the rice producing areas in Gorontalo Regency needs to be interpreted to be known if there is land conversion in the future. Calculation of rice fields can be interpreted using remote sensing data. The purpose of this research is to interpreationt the extent of paddy field located in West Limboto subdistrict. Landsat 8 OLI (Operational Land Imager) acquired November 20, 2015 is the data used in this study. GPS measuring instrument is used as a tool for checking the coordinates of sample points that will be in the fiel d check. The method by digital image processing landsat 8 OLI using supervised classification algorithm maximum likelihood. Landsat 8 layer stacking process then do corrected geometric. Unsupervised classification is performed as an initial interpretation stage to classify land cover and also as sample point extraction. Total 18 sample points were taken that were used for ground data. Reclassified using supervised method processing after finished ground data. The results show that the paddy fields about 886,66 ha spread in 8 villages. Keywords: paddy fields, supervised, mapping, west limboto, gorontalo Abstrak – Salah satu isu ketahanan pangan nasional adalah ketersediaan bahan makanan pokok berupa beras secara berkelanjutan. Ketersediaan lahan sawah di Kecamatan Limboto Barat yang merupakan salah satu wilayah penghasil beras di Kabupaten Gorontalo perlu diinterpretasi agar dapat diketahui bila terjadi alih fungsi lahan pada masa mendatang. Penghitungan luas lahan sawah dapat diinterpretasi menggunakan data penginderaan jauh yaitu citra landsat 8. Tujuan penelitian ini adalah untuk menginterpretasi luasan lahan sawah yang terdapat di Kecamatan Limboto Barat. Citra landsat 8 OLI (Operational Land Imager) perekaman 20 November 2015 merupakan data yang digunakan dalam penelitian ini. Alat ukur berupa GPS digunakan sebagai alat bantu untuk pengecekan koordinat titik sampel yang akan di cek lapangan. Metode penelitian dilakukan dengan teknik pengolahan citra digital landsat 8 OLI menggunakan klasifikasi supervised algoritma maximum likelihood. Citra landsat 8 dilakukan proses layer stacking kemudian dikoreksi geometrik. Klasifikasi tak terbimbing (unsupervised) dilakukan sebagai tahap interpretasi awal untuk mengklasifikasi tutupan lahan dan juga sebagai pengambilan titik sampel. Sebanyak 18 titik sampel diambil yang digunakan untuk cek lapangan. Reklasifikasi metode terbimbing (supervised) dilakukan dari hasil data lapangan. Hasil yang diperoleh menunjukkan luas lahan sawah sekitar 886,66 ha yang tersebar di 8 desa. Kata kunci: sawah, landsat, supervised, pemetaan, limboto barat, gorontal

Land use dynamics in Sagara River Catchment in Dodoma Region, Tanzania

Abstract Context and background: The Sagara hills provide key ecosystem services to the communities in Kongwa and Mpwapwa districts in Dodoma region. In particular, the hills provide watershed services which is vital in a challenging semi-arid condition. However, the current situation suggests that the watershed services are at risk due to anthropogenic activities.  Goal and Objectives: This study assesses the dynamics of land use and land cover changes in Sagara catchment and its implication to watershed services for the surrounding communities. Methodology: Remote sensing and Geographical Information System (GIS) techniques were used to analyze changes in land use and land cover in the catchment between 2013 and 2021.  The study used two categories of data: Landsat 8 layers and reference data. Landsat 8 layers were used as input data for change detection and quantification of vegetation cover and other land uses at Sagara hills, while field data and higher resolution Google Earth Pro Historical images were used to create reference data for training the classifier and accuracy assessment. Results: Results show that the built area increased from 249.4 ha in 2013 to 504.2 ha in 2021 with a net gain of 254.8 ha.  Farmland increased with a net gain of 3108.1 ha whereby the farmland area was 10900.7 ha in 2013, but increased to 14008 ha in 2021. It was further observed that there were significant changes in vegetation cover from 2013 to 2021. The woodland forest which was a dominant vegetation in 2013 with an area of 24187.5 ha has been reduced to 12439 ha. This means in 9years; 11,748 ha of forest have been lost due destructive human activities. Grassland area was also observed to decrease from 995.1 ha in 2013 to 751.9 ha in 2021 with a net loss of 243.2 ha. Closed bushes and thickets which increased significantly by 2021 has become the dominant vegetation. Bare land was also observed to have increased. This is attributed to poor farming methods which resulted into soil erosion and loss of land productivity in the catchment

Observations and Recommendations for the Calibration of Landsat 8 OLI and Sentinel 2 MSI for Improved Data Interoperability

Combining data from multiple sensors into a single seamless time series, also known as data interoperability, has the potential for unlocking new understanding of how the Earth functions as a system. However, our ability to produce these advanced data sets is hampered by the differences in design and function of the various optical remote-sensing satellite systems. A key factor is the impact that calibration of these instruments has on data interoperability. To address this issue, a workshop with a panel of experts was convened in conjunction with the Pecora 20 conference to focus on data interoperability between Landsat and the Sentinel 2 sensors. Four major areas of recommendation were the outcome of the workshop. The first was to improve communications between satellite agencies and the remote-sensing community. The second was to adopt a collections-based approach to processing the data. As expected, a third recommendation was to improve calibration methodologies in several specific areas. Lastly, and the most ambitious of the four, was to develop a comprehensive process for validating surface reflectance products produced from the data sets. Collectively, these recommendations have significant potential for improving satellite sensor calibration in a focused manner that can directly catalyze efforts to develop data that are closer to being seamlessly interoperable

Lithological and hydrothermal alteration mapping of epithermal, porphyry and tourmaline breccia districts in the Argentine Andes using ASTER imagery

The area of interest is located on the eastern flank of the Andean Cordillera, San Juan province, Argentina. The 3600 km2 area is characterized by Siluro-Devonian to Neogene sedimentary and igneous rocks and unconsolidated Quaternary sediments. Epithermal, porphyry-related, and magmatic-hydrothermal breccia-hosted ore deposits, common in this part of the Frontal Cordillera, are associated with various types of hydrothermal alteration assemblages. Kaolinite – alunite-rich argillic, quartz – illite-rich phyllic, epidote – chlorite – calcite-rich propylitic and silicic are the most common hydrothermal alteration assemblages in the study area. VNIR, SWIR and TIR ASTER data were used to characterize geological features on a portion of the Frontal Cordillera. Red-green-blue band combinations, band ratios, logical operations, mineral indices and principal component analysis were applied to successfully identify rock types and hydrothermal alteration zones in the study area. These techniques were used to enhance geological features to contrast different lithologies and zones with high concentrations of argillic, phyllic, propylitic alteration mineral assemblages and silicic altered rocks. Alteration minerals detected with portable short-wave infrared spectrometry in hand specimens confirmed the capability of ASTER to identify hydrothermal alteration assemblages. The results from field control areas confirmed the presence of those minerals in the areas classified by ASTER processing techniques and allowed mapping the same mineralogy where pixels had similar information. The current study proved ASTER processing techniques to be valuable mapping tools for geological reconnaissance of a large area of the Argentinean Frontal Cordillera, providing preliminary lithologic and hydrothermal alteration maps that are accurate as well as cost and time effective

Comparison between satellite-based and cosmic ray probe soil moisture estimates : a case study in the Cathedral Peak catchment.

Master of Science in Environmental Hydrology. University of KwaZulu-Natal, Pietermaritzburg 2015.Abstract available in PDF file

Analisis Strategi Pengelolaan Ekosistem Terumbu Karang Berbasis Resiliensi (Studi Kasus di Teluk Doreri, Kabupaten Manokwari)

Pengelolaan terumbu karang berbasis resiliensi merupakan paradigma baru dan telah menjadi konsep kunci untuk mendukung kemampuan sistem terumbu karang dalam menghadapi tekanan lokal dan dampak perubahan iklim. Pengelolaan berbasis resiliensi mencakup dua aspek penting, yaitu penilaian potensi resiliensi secara spasial dan perencanaan atau strategi pengelolaan yang sesuai dengan kondisi resiliensi sistem terumbu karang. Sejauh ini penelitian-penelitian untuk menentukan indikatorindikator penilaian resiliensi telah mengalami kemajuan yang berarti, namun masih terbatas dalam kerangka kerja untuk merumuskan strategi pengelolaan berdasarkan kondisi resiliensi ekosistem terumbu karang. Penelitian ini mengkombinasikan pendekatan-pendekatan yang berbeda dalam penilaian resiliensi ekosistem terumbu karang, yaitu penilaian potensi rezime/status terumbu karang, penilaian potensi resiliensi dan penilaian potensi tekanan/stres dalam satu kerangka kerja (framework) untuk menentukan tindakan dan strategi pengelolaan ekosistem terumbu karang di kawasan Teluk Doreri, Kabupaten Manokwari. Tujuan penelitian ini adalah: 1) menganalisis status dan potensi rezim-rezim terumbu yang ada di ekosistem terumbu karang; 2) menganalisis potensi resiliensi ekologi terumbu karang; 3) menganalisis potensi tekanan aktivitas manusia terhadap terumbu karang; 4) memodelkan skenario perubahan tekanan terhadap resiliensi dan status terumbu karang; 5) merumuskan strategi pengelolaan yang mendukung resiliensi dan keberlanjutan ekosistem terumbu karang. Penelitian ini akan berkontribusi dalam mengisi kekosongan basis data terumbu karang, menyediakan informasi tentang kondisi terkini resiliensi ekosistem terumbu karang, serta berkontribusi dalam penyempurnaan kerangka kerja yang mengakomodir aspek penilaian resiliensi dalam perencanaan pengelolaan terumbu karang. Penelitian ini menerapkan metode deskriptif dengan observasi lapangan, studi dokumentasi, studi pustaka dan pemodelan statistik sebagai sumber datanya. Variabelvariabel yang digunakan dikelompokkan dalam 3 kelompok variabel, yaitu variabel proses, variabel tekanan dan variabel habitat bentik. Data dikumpulkan dengan menerapkan pendekatan lapangan (observasi dan wawancara), analisis laboratorium dan analisis spasial. Potensi rezim terumbu karang dinilai dengan menerapkan statistik deskriptif (mean±SE), analisis PSI (phase shift index), korelasi PCA, hierarchical cluster, dan K-means cluster. Pola spasial perubahan terumbu karang diperoleh melalui pemrosesan citra satelit Landsat multisensor dan multitemporal. Analisis potensi resiliensi relatif dan potensi tekanan mengikuti metode perhitungan menurut Maynard et al. (2015) yang meliputi proses kompilasi, normalisasi, pengaturan skala satu arah, perhitungan nilai rata-rata, perhitungan nilai potensi relatif dan penentuan ranking lokasi/site. Penentuan tindakan pengelolaan dilakukan melalui kueri nilai potensi resiliensi dan tekanan terhadap kriteria pengelolaan. Analisis persepsi masyarakat dilakukan melalui penerapan metode tabulasi yang didahului proses editing dan coding. Metode hybrid A’WOT diterapkan untuk analisis prioritas strategi pengelolaan ekosistem terumbu karang. Hasil menunjukkan bahwa rata-rata persentase karang hidup di Teluk Doreri 46,75%, dimana tergolong cukup baik, namun demikian ada potensi perkembangan rezim abiotik dan alga yang diperkuat dengan pola spasial tren pengurangan tutupan karang hidup yang cukup tajam dalam kurun waktu 15 tahun terakhir. Potensi resiliensi ekosistem terumbu karang umumnya masih cukup baik berdasarkan indikator-indikator proses resiliensi, namun terdapat kelemahan pada aspek indikator biomassa dan kehadiran kelompok fungsional ikan herbivora. Hampir 50% lokasi yang disurvei menghadapi potensi tekanan atau stress yang tinggi, bahkan 70% lokasi mengalami tekanan tinggi khusus dalam bentuk tekanan penangkapan. Hasil queri terhadap kriteria-kriteria penentuan area target dan tindakan pengelolaan menunjukkan bahwa pengelolaan perikanan dan penegakan hukum adalah prioritas yang utama, disamping juga pemantauan pemutihan karang (bleaching) dan dukungan pemulihan. Prioritas strategi utama adalah meningkatkan keterpaduan antar sektor dan stakeholder dalam pengelolaan terumbu karang, membangun perilaku dan partisipasi aktif masyakat dalam pelestarian dan pengelolaan ekosistem terumbu karang, dan meningkatkan pemantauan kondisi terumbu karang dan efektifitas penegakan hukum. Berdasarkan hasil disarankan program pemantauan jangka panjang juga perlu dilakukan untuk memperoleh tren indikator-indikator proses resiliensi dan tantangan resiliensi. Disamping itu perlu upaya untuk meningkatkan kesadaran, pemahaman, serta dukungan dan partisipasi masyarakat dalam pengelolaan ekosistem terumbu karang mulai dari proses perencanaan sampai pengawasan dan evaluasi

Using multispectral imagery and monitored key parameters to optimise the efficient management of vineyards ("Vitis vinifera" L.)

288 p.[ES] Según la ESA (Agencia Espacial Europea), la teledetección es una forma de recoger y analizar datos para obtener información sobre un objeto, sin que el instrumento utilizado para ello esté en contacto directo con el mismo. Esta herramienta ha demostrado su utilidad en un amplio abanico de campos, incluida la agricultura, ámbito en el que se ha generalizado el uso de imágenes multiespectrales, y podría convertirse en una importante herramienta no sólo para gestionar el cultivo, sino también en la lucha contra el cambio climático. Esta información puede utilizarse sola o combinada con otros datos para obtener mejores resultados, aportando información útil sobre el estado del viñedo. Cuatro elementos son esenciales en la teledetección: una plataforma, un objeto a medir, un sensor y la forma de utilizar y almacenar la información obtenida. En la actualidad, existen varias plataformas para obtener información: satélites, drones, aviones, vehículos terrestres, etc. De tal manera que, dependiendo de la plataforma y del sensor, se obtendrán datos con diferentes características de resolución espacial, temporal, espectral y radiométrica y, por tanto, el coste será diferente en función de la tecnología utilizada. Las aplicaciones de la teledetección en la agricultura son una innovación reconocida y con un potencial cada vez mayor. Esta herramienta se puede emplear para diversos usos de forma muy diversa. Así, en agricultura, la información disponible suele ser tratada empleando índices de vegetación. De igual modo, se puede emplear una sola imagen en un momento determinado del ciclo fenológico (en viticultura suele ser el envero, que está relacionado con el máximo de vegetación) o también es posible emplear todas las imágenes disponibles y trabajar con series temporales. En viticultura, los estudios de investigación muestran que las técnicas de teledetección permiten evaluar la variabilidad del viñedo (Vitis vinifera L.) y controlar la calidad y producción de uva, además, esta herramienta se ha empleado exitosamente para estimar diversos parámetros críticos del viñedo, como el índice de área foliar (LAI). En la presente tesis doctoral, se emplearon las imágenes obtenidas de los satélites Sentinel-2 para comprobar si tenían relación con los parámetros agronómicos y enológicos de varias parcelas situadas en la Denominación de Origen Rueda, Valladolid. Para ello se analizó una serie temporal de imágenes, confirmando que el estado fenológico de envero es un buen momento para el empleo de las imágenes. Se tomaron datos de campo en cada parcela y se mostró que las imágenes de satélite eran capaces de clasificar las parcelas en función de su desarrollo vegetativo, encontrando diferencias significativas en diversos parámetros agronómicos y de calidad de la uva. Adicionalmente, se realizó un ensayo similar en pistacho para comprobar su aplicabilidad, observando diferencias significativas en el rendimiento. Finalmente, se emplearon imágenes Landsat-8 en diversas parcelas de Galicia de las que se disponía de datos de campo relacionados con las poblaciones de levaduras para comprobar si la vegetación, identificada empleando en NDVI de las imágenes, estaba relacionada con la riqueza de especies de levaduras, encontrando diferencias significativas con respecto a las parcelas y el NDVI. Por otra parte, se desarrolló un ensayo experimental en el que se arrancó un viñedo, marcando los píxeles del satélite sobre la superficie del viñedo y coordinando las labores con las pasadas de los satélites Sentinel-2, para comprobar el efecto de la reducción de vegetación sobre la información espectral captada por los satélites (a través del NDVI) en un cultivo como el viñedo, sometido a la problemática de los píxeles mixtos. Se midió minuciosamente en laboratorio la vegetación arrancada para comprobar la superficie exacta de vegetación extraída de la parcela, encontrando que para un viñedo en espaldera como el del estudio, cada 20% de reducción en la cantidad de vegetación supuso una reducción en el NDVI de alrededor del 6%. Adicionalmente, antes de los arranques, se tomaron ortofotografías con UAV y cámaras multiespectrales para desarrollar un método novedoso para estimar el área foliar del viñedo (LAI) empleando las sombras de las plantas proyectadas sobre el suelo del viñedo. Con este fin, se planeó la hora del vuelo con exactitud, para maximizar las sombras, posibilitando a los pilotos no sólo el empleo de un nuevo método de bajo coste con una precisión similar a métodos más costosos, sino también otorgando una mayor flexibilidad a la hora de realizar los trabajos, ya que con este nuevo método los pilotos no necesitan volar el dron al mediodía solar. Finalmente, se realizaron dos estudios de campo exhaustivos en dos viñedos: uno en la DO Rueda y otro en la DO Ribera del Duero, en España. Se creó una malla de muestreo para tratar de captar la variabilidad espacial de los viñedos y se emplearon las imágenes de los satélites Sentinel-2 de todo un año para construir una serie temporal y aplicar un análisis funcional basado en componentes principales (f-PCA). Los resultados muestran que con dos componentes principales se explica la mayor parte de la variabilidad del viñedo y que, a partir de la tercera componente, la relación con los parámetros de campo no está clara. Por otra parte, se encontró que el empleo del f-PCA permitió alcanzar resultados mejores que simplemente una imagen de envero y cada componente principal fue capaz de explicar la variabilidad ocasionada por distintas variables del viñedo. En la presente tesis doctoral: i) se cuantifica la relación entre la información espectral obtenida de las imágenes y los parámetros del viñedo, ii) se implementan herramientas para establecer unidades de manejo diferenciado en viñedo, incluyendo aquellas derivadas de imágenes Sentinel-2, iii) se verifica que las diferencias se trasladan a los vinos elaborados de esas unidades diferenciadas, iv) las herramientas empleadas permiten monitorizar de manera dinámica los viñedos, v) son herramientas basadas en teledetección, accesibles para los productores y de bajo coste y vi) aportan conocimiento práctico, que puede ser empleado por el sector. Además, se refuerzan los resultados a nivel global dado que los experimentos incluyeron diversos cultivares de vid, en diferentes localidades y situaciones de cultivo. La idea más relevante de la presente tesis doctoral es que el gran reto de esta "era digital en la viticultura" es disponer de profesionales con la suficiente formación para aprovechar las enormes oportunidades que brinda este tipo de tecnología y ofrecer soluciones prácticas a los agricultores y viticultores.[EN] According to ESA (European Space Agency), remote sensing is a way of collecting and analysing data to obtain information about an object, without the instrument used to collect the data being in direct contact with said object. This tool has proven useful in a wide range of fields, including agriculture, where the use of multispectral imagery has become widespread and could become an important tool to manage vineyards and fight against climate change. Furthermore, these images can be used alone or combined with other data for better results, providing helpful information on the state of crops. Four elements are essential in remote sensing: a platform, a target object, a sensor, and a way to use and store the information obtained. Nowadays, there are several platforms for obtaining information, such as satellites, drones, aircraft, and ground vehicles. Thus, data will be obtained with different spatial, temporal, spectral and radiometric resolution characteristics depending on the platform and sensor. Consequently, the cost will be different depending on the technology used. Remote sensing applications in agriculture are a recognised innovation with increasing potential. This tool can be used for various applications in a wide range of fields. In agriculture, the available information can be processed using vegetation indices. Similarly, it is possible to use a single image at a specific moment of the phenological cycle (usually veraison, which is related to the maximum amount of vegetation), or it is also possible to use all available images and work with time series. In viticulture, research studies show that remote sensing techniques allow the assessment of vineyard (Vitis vinifera L.) variability and the control of grape quality and quantity. Remote sensing has been successfully used to estimate several vineyard parameters, such as leaf area index (LAI). In this PhD thesis, Sentinel-2 satellite imagery was used to check if they were related to the agronomic and oenological parameters of several vineyards located in the Appellation of Origin Rueda, Valladolid. For this purpose, a time series of images was analysed, confirming that the phenological stage of veraison is a good moment for the use of the images. Field data was taken in each vineyard, and it was found that the satellite images were able to classify the vineyards according to their vegetative development, finding significant differences in several agronomic and quality parameters. In addition, a similar experiment was carried out on pistachio to check the applicability of the method, observing significant differences in yield. Finally, Landsat-8 images were used on several vineyards in Galicia. Field data related to yeast populations was compared using NDVI as an indicator of the amount of vineyard vegetation. As a result, significant differences were found concerning the plots and NDVI. On the other hand, to study the effect of mixed pixels in vineyards, an experimental trial was carried out in a vineyard where vines were progressively removed. Thus, satellite pixels were marked on the surface, and the removals were synchronized with the Sentinel-2 satellites imagery. The effect of the reduction of vegetation on the spectral information captured by the satellites was analysed (using NDVI). Then, the removed vegetation was carefully measured in the laboratory to check the exact leaf area, finding that for a trellised vineyard, every 20% reduction in the amount of vegetation meant a reduction of around 6% in NDVI. Additionally, before each vine removal, orthophotographs were taken with UAV and multispectral cameras to develop a novel method for estimating the leaf area of the vineyard (LAI) using the shadows of the plants projected on the ground. The flight time was carefully planned to maximise shadows, enabling pilots not only to use a new low-cost method with similar accuracy to other more expensive methods but also by providing flexibility when carrying out the work, as with this new method, pilots do not need to fly the drone in the solar midday. Finally, two comprehensive field studies were conducted in separate vineyards: one in the DO Rueda and the other in the DO Ribera del Duero in Spain. A sampling grid was created to try to capture the spatial variability of the vineyards, and Sentinel-2 imagery taken over the course of one year was employed to construct a time series and apply a functional principal component analysis (f-PCA). The results show that the two principal components explain most of the variability in the vineyard, and that from the third component onwards, the relationship between the components and the field parameters is not clear. On the other hand, it was found that f-PCA allowed better results than solely a veraison image, and each principal component explained the variability caused by different variables in the vineyard. In this doctoral thesis: i) the relationship between the spectral information obtained from the images and the vineyard parameters is quantified, ii) tools are implemented to establish differentiated vineyard management units, including those derived from Sentinel-2 images, iii) it is verified that the differences are transferred to the wines produced from these differentiated units, iv) the tools allow dynamic monitoring of the vineyards, v) they are remote sensing-based tools accessible to producers and low cost, and vi) they provide knowledge and present a useful product for the sector. The great challenge of this "digital era in viticulture" is to have professionals with sufficient training to take advantage of the immense opportunities of this technology and to offer practical solutions to farmers and winegrowers