Yady Tatiana Solano Correa

Pontificia Universidad Javeriana - Cali · Departamento de Electrónica y Ciencias de la Computación

Preprocessing Synthetic Aperture Radar (SAR) data is a crucial initial stage in leveraging SAR data for remote sensing applications. Terrain correction, both radiometric and geometric, and the detection of layover/shadow areas hold significant importance when SAR data are collected over mountainous regions. This study aims at investigating the impa...

This book brings together early career researchers, non-governmental organisations and industry practitioners, indigenous and local communities, and government agency workers to interrogate the concept of water security. By collating multicultural perspectives, diverse contributions, and illustrative media, we challenge the current anthropocentric,...

High Resolution (HR) Satellite Image Time Series (SITS) are a valuable data source for analyzing Land Cover Change (LCC) due to their large amount of spatial, spectral, and temporal information. However, most existing LCC detection methods focus on binary Change Detection (CD) within a single year and fail to provide detailed information about the...

Conventional agricultural practices, such as the use of agrochemicals, implementation of monocultures, and the expansion of crops in strategic ecosystems, have significant impacts in Andean basins, directly increasing nutrient inputs to waterways, and contributing to ecological fragility and socioeconomic vulnerability. This complex dynamic is rela...

Land Use and Land Cover (LULC) classification using remote sensing data is a challenging problem that has evolved with the update and launch of new satellites in orbit. As new satellites are launched with higher spatial and spectral resolution and shorter revisit times, LULC classification has evolved to take advantage of these improvements. Howeve...

Particulate matter, PM 10 and PM 2 . 5 , represents common air pollutants in cities and constitute a considerable threat to public health impacting daily activity of people living in city. In large cities, the main sources of PM 10 and PM 2 . 5 are diesel engine exhaust, brake dust, and particulate matter from vehicle tires. These particles can be...

At the international level, the term “water security” (WS) has gained increasing attention in recent decades. At the operational level, WS is assessed using tools that define the concept using a variety of dimensions and sub-dimensions, with qualitative and quantitative indicators and parameters. The breadth of tools and concepts is an obstacle to...

Insect outbreaks affect forests, causing the deaths of trees and high economic loss. In this study, we explored the detection of European spruce bark beetle (Ips typographus, L.) outbreaks at the individual tree crown level using multispectral satellite images. Moreover, we explored the possibility of tracking the progression of the outbreak over t...

Norway spruce pathogenic fungi causing root, butt and stem rot represent a substantial problem for the forest sector in many countries. Early detection of rot presence is important for efficient management of the forest resources but due to its nature, which does not generate evident exterior signs, it is very difficult to detect without invasive m...

Key Points: • The concept of "water security" (WS) is hard to operationalize due to its intrinsic complexity. • Data gathering is not an end in itself but to strengthen the relationship between the data-information-stakeholders nexus. • We propose a framework to help practitioners to design effective and sys-temic Data Gathering Strategies for Wate...

Over the last two decades, several data sets have been developed to assess flood risk at the global scale. In recent years, some of these data sets have become detailed enough to be informative at national scales. The use of these data sets nationally could have enormous benefits in areas lacking existing flood risk information and allow better flo...

Availability of multitemporal (MT) images, such as the sentinel-2 (S2) ones, offers accurate spatial, spectral and temporal information to effectively monitor vegetation, more specifically agriculture. Agricultural practices can benefit from temporally dense satellite image time series (SITS) for accurate understanding of the phenological evolution...

Wind disturbances represent the main source of damage in European forests, affecting them directly (windthrows) or indirectly due to secondary damages (insect outbreaks and forest fires). The assessment of windthrows damages is very important to establish adequate management plans and remote sensing can be very useful for this purpose. Many types o...

This paper presents an approach for large-scale precise mapping of agricultural fields based on the analysis of Satellite Image Time Series (SITS) acquired by ESA Sentinel-2 (S2) satellite constellation. The approach has been developed in the framework of the ESA SEOM - Scientific Exploitation of Operational Missions - S2-4Sci Land and Water projec...

This paper presents an approach for precision agriculture large scale applications based on the analysis of big data consisting in Satellite Image Time Series (SITS) acquired by ESA Sentinel-2 (S2) satellite constellation. The approach has been developed in the framework of the ESA SEOM - Scientific Exploitation of Operational Missions - S2-4Sci La...

To overcome the limited capability of most state-of-the-art change detection (CD) methods in modeling spatial context of multispectral high spatial resolution (HR) images and exploiting all spectral bands jointly, this letter presents a novel unsupervised deep-learning-based CD method that can effectively model contextual information and handle the...

Satellite image time series (SITS), such as those by Sentinel-2 (S2) satellites, provides a large amount of information due to their combined temporal, spatial, and spectral resolutions. The high revisit frequency and spatial resolution of S2 result in: 1) increase in the probability of acquiring cloud-free images and 2) availability of detailed in...

Information regarding both the spatial distribution and the quantity of vegetation components is of great relevance in different fields. Of particular interest is the detection of Non-Photosynthetic Vegetation (NPV) against Photosynthetic Vegetation (PV) and Bare Soil (BS). In-situ approaches exist that identify NPV, but are time and cost expensive...

Change Detection (CD) is an important application of remote sensing. Recent technological evolution resulted in the availability of optical multispectral sensors that provide High spatial Resolution (HR) images with many spectral bands. Such characteristics allow for new applications of CD, however present new challenges on the proper exploitation...

Crop-type classification has been attracting a lot of attention in recent years. In particular since the launch of the Sentinel-2 (S2) satellite which combines a large amount of spectral and spatial information, compared to previous satellite generations. In the literature, several methods exist that perform crop classification in time series, but...

The availability of multitemporal images acquired by several very high geometrical resolution (VHR) optical sensors makes it possible to build VHR image time series (TS) of images acquired over the same geographical area with a temporal resolution better than the one achievable when considering a single VHR sensor. However, such TS include images s...

One of the most common approaches to unsupervised change detection (CD) in multispectral images is change vector analysis (CVA). CVA computes the multispectral difference image and exploits its statistical distribution in (hyper-) spherical coordinates by means of two steps: 1) magnitude and 2) direction thresholding. The two steps require assumpti...

Satellite Image Time Series (SITS), such as the ones acquired by the new Sentinel-2 (S2), combine a large amount of information compared to previous satellite generations since a better trade-off in terms of spatial/spectral/temporal resolutions is guaranteed. The specific characteristic of acquiring images under overlapped orbits, offered by S2, r...

This paper proposes an approach for the detection of changes in multitemporal Very High Resolution (VHR) optical images acquired by different multispectral sensors. The proposed approach, which is inspired by a recent framework developed to support the design of change-detection systems for single-sensor VHR remote sensing images, addresses and int...

Multitemporal data analysis is a hot topic in remote sensing. This articlereviews literature about: (i) unsupervised bitemporal image analysis, (ii) (semi-)supervised bitemporal image analysis, and (iii) image time series analysis. The first one mainly exploits multitemporal image comparison techniques for detecting the presence/absence of changes....

The classification of land covers is one of the most relevant tasks carried on to understand the state of a certain region. Additional studies about the biodiversity, hydrology, human impact, modeling dynamics, and phenology in the study area, can be carried on. In these cases, a wide temporal series of images need to be considered in order to get...

When dealing with optical images, the most common approach to unsupervised change detection is Change Vector Analysis (CVA) which computes the multispectral difference image and exploits its statistical distribution in (hyper-)spherical coordinates. The latter step usually requires assumptions on both the model of class distributions and the number...

This paper presents the results obtained after applying different radiometric indices over sugarcane crops located in a Colombian Andean area, analyzing their possible correlation with ENSO phenomena. The study was performed over Landsat images acquired during a 28-year period. Given the change of sensor on-board Landsat satellites during the above...

The availability of multitemporal images acquired by several very high geometrical resolution (VHR) optical sensors makes it possible to build VHR image Time-Series (TS) with a temporal resolution better than the one achievable when considering a single sensor. However, such TS include images showing different characteristics from the geometrical,...

This work aims at developing an approach to the detection of changes in multisensor multitemporal VHR optical images. The main steps of the proposed method are: i) multisensor data homogenization; and ii) change detection in multisensor multitemporal VHR optical images. The proposed approach takes advantage of: the conversion to physical quantities...

This study presents the implementation of image processing techniques in satellite bands of the visible and infrared spectrum for the differentiation of land cover in the Colombian Andes, which is dominated by high mountain systems, to do this, we extracted features through texture analysis methods, principal component analysis, discrete cosine tra...