Study of the urban heat island (UHI) using remote sensing data/techniques: a systematic review.

Urban Heat Islands (UHI) consist of the occurrence of higher temperatures in urbanized areas when compared to rural areas. During the warmer seasons, this effect can lead to thermal discomfort, higher energy consumption, and aggravated pollution effects. The application of Remote Sensing (RS) data/techniques using thermal sensors onboard satellites, drones, or aircraft, allow for the estimation of Land Surface Temperature (LST). This article presents a systematic review of publications in Scopus andWeb of Science (WOS) on UHI analysis using RS data/techniques and LST, from 2000 to 2020. The selection of articles considered keywords, title, abstract, and when deemed necessary, the full text. The process was conducted by two independent researchers and 579 articles, published in English, were selected. Qualitative and quantitative analyses were performed. Cfa climate areas are the most represented, as the Northern Hemisphere concentrates the most studied areas, especially in Asia (69.94%); Landsat products were the most applied to estimates LST (68.39%) and LULC (55.96%); ArcGIS (30.74%) was most used software for data treatment, and correlation (38.69%) was the most applied statistic technique. There is an increasing number of publications, especially from 2016, and the transversality of UHI studies corroborates the relevance of this topic.This work was funded by National Funds through the FCT-Foundation for Science and Technology and FEDER, under the projects UIDB/04683/2020 and PT2020 Program for financial support to CIMO UIDB/00690/2020. This work was funded by National Funds through the FCT-Foundation for Science and Technology and FEDER, under the projects UIDB/04683/2020 and PT2020 Program for financial support to CIMO UIDB/00690/2020.info:eu-repo/semantics/publishedVersio

Detection and Monitoring of Marine Pollution Using Remote Sensing Technologies

Recently, the marine habitat has been under pollution threat, which impacts many human activities as well as human life. Increasing concerns about pollution levels in the oceans and coastal regions have led to multiple approaches for measuring and mitigating marine pollution, in order to achieve sustainable marine water quality. Satellite remote sensing, covering large and remote areas, is considered useful for detecting and monitoring marine pollution. Recent developments in sensor technologies have transformed remote sensing into an effective means of monitoring marine areas. Different remote sensing platforms and sensors have their own capabilities for mapping and monitoring water pollution of different types, characteristics, and concentrations. This chapter will discuss and elaborate the merits and limitations of these remote sensing techniques for mapping oil pollutants, suspended solid concentrations, algal blooms, and floating plastic waste in marine waters

Correção atmosférica de imagens termais utilizando perfis verticais de alta resolução simulados por um modelo de mesoescala

A estimativa da temperatura da superfície terrestre ( LST ) por sensoriamento remoto no infravermelho termal (TIR) é dependente d a realização de uma correção atmosférica apropriada que , em geral, necessita de perfis atmosféricos como dados de entrada. Dados globais de reanálise são uma alternativa prática para a obtenção desses perfis, mas podem apresentar limitações. Nesse contexto, o presente estudo teve como objetivo analisar a utilização do modelo numérico Weather Research and Forecasting (WRF) para gerar perfis verticais de alta resolução , refinando dados de reanálise , visando a correção atmosférica no TIR para o cálculo de valores de LST. Para tal, foram realizadas simulações com o modelo WRF com dados de reanálise do NCEP Climate Forecast System Version 2 (CFSv2) como condições iniciais e utilizando duas grades aninhadas com resoluções horizontais de 12 km (G12) e 3 km (G03). Para estimar a LST, foram empregados: o método da inversão direta da Equação de Transferência Radiativa (RTE) , o modelo MODTRAN e valores de radiância da banda 10 do Landsat 8 TIRS. A pesquisa avaliou o desempenho do modelo através dos perfis verticais, dos parâmetros atmosféricos de correção (transmitância atmosférica e radiâncias upwelling e downwelling ) e dos valores de LST, utilizando como referência dados de radiossondagens in situ , no sul do Brasil . Adicionalmente, foi executada uma análise de sensibilidade a dois esquemas de parametrização de camada limite planetária . Os resultados indicam que o modelo WRF simula de maneira satisfatória os perfis atmosféricos que, por consequência, geram parâmetros de correção e LST com baixos erros. Contudo, não existe melhora significativa nas métricas estatísticas entre os perfis extraídos diretamente da reanálise CFSv2 e os simulados pelo WRF . Em alguns casos, a utilização de um perfil de grade mais refinada resultou, até mesmo, em maiores erros. Os valores gerais de RMSE para a LST foram: 0,55 K ( CFSv2), 0,79 K ( WRF G12 ) e 0,82 K ( WRF G03 ). A escolha do esquema de camada limite mostrou - se caso - dependente. Conclui - se que não há necessidade especial de refinar a resolução dos perfis de reanálise visando estimativa de LST, por meio do método da RTE .The Land Surface Temperature (LST) retrieval from thermal infrared (TIR) remote sensing depends on performing an appropriate atmospheric correction. In general, this approach requires atmospheric profiles as input data. Global reanalysis data are a practical alternative to obtain these profiles, but they may have limitations. In this con text, this study aimed to assess the use of the Weather Research and Forecasting (WRF) numerical model to generate high - resolution vertical profiles, downscaling reanalysis data , to be applied in TIR atmospheric correction for LST retrieval . WRF simulations were carried out using NCEP Climate Forecast System Version 2 (CFSv2) reanalysis as initial conditions and two nested grids with horizontal resolutions of 12 km (G12) and 3 km (G03) . To retrieve the LST, we used: the Radiative Transfer Equation (RTE) based method , the MODTRAN model, and radiance values from Landsat 8 TIRS10 band . Th is research evaluated the model performance through vertical profiles, atmospheric correction parameters (atmospheric transmittance and upwelling and downwelling radiances) , and LST values, using in situ radiosonde data ( in Southern Brazil ) as reference. Moreover, a sensitivity analysis to two planetary boundary layer parameterization schemes was performed . The results indicate that the WRF model satisfactor il y simulates the atmospheric profiles that, consequently, generate correction param eters and LST with low errors. However, there is no significant improvement in statistical metrics between profiles extracted directly from the CFSv2 reanalysis and those simulated by WRF . In some cases, the use of a finer grid profile resulted even in larger errors. The LST overall RMSE values were: 0.55 K (CFSv2), 0.79 K (WRF G12) , and 0.82 K (WRF G03) . The boundary layer scheme choice proved to be case - dependent. We concluded that there is no special need to increase the resolution of reanalysis profiles in order to retrieve LST using the RTE - based method

Estimating daily evapotranspiration based on a model of evaporative fraction (EF) for mixed pixels

Currently, applications of remote sensing evapotranspiration (ET) products are limited by the coarse resolution of satellite remote sensing data caused by land surface heterogeneities and the temporal-scale extrapolation of the instantaneous latent heat flux (LE) based on satellite overpass time. This study proposes a simple but efficient model (EFAF) for estimating the daily ET of remotely sensed mixed pixels using a model of the evaporative fraction (EF) and area fraction (AF) to increase the accuracy of ET estimate over heterogeneous land surfaces. To accomplish this goal, we derive an equation for calculating the EF of mixed pixels based on two key hypotheses. Hypothesis 1 states that the available energy (AE) of each sub-pixel is approximately equal to that of any other sub-pixels in the same mixed pixel within an acceptable margin of error and is equivalent to the AE of the mixed pixel. This approach simplifies the equation, and uncertainties and errors related to the estimated ET values are minor. Hypothesis 2 states that the EF of each sub-pixel is equal to that of the nearest pure pixel(s) of the same land cover type. This equation is designed to correct spatial-scale errors for the EF of mixed pixels; it can be used to calculate daily ET from daily AE data. The model was applied to an artificial oasis located in the midstream area of the Heihe River using HJ-1B satellite data with a 300&thinsp;m resolution. The results generated before and after making corrections were compared and validated using site data from eddy covariance systems. The results show that the new model can significantly improve the accuracy of daily ET estimates relative to the lumped method; the coefficient of determination (R2) increased to 0.82 from 0.62, the root mean square error (RMSE) decreased to 1.60 from 2.47&thinsp;MJ&thinsp;m−2(decreased approximately to 0.64 from 0.99&thinsp;mm) and the mean bias error (MBE) decreased from 1.92 to 1.18&thinsp;MJ&thinsp;m−2 (decreased from approximately 0.77 to 0.47&thinsp;mm). It is concluded that EFAF can reproduce daily ET with reasonable accuracy; can be used to produce the ET product; and can be applied to hydrology research, precision agricultural management and monitoring natural ecosystems in the future.</p

NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms

The 2017–2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a “Designated Targeted Observable” (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380–2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3–5 μm; TIR: 8–12 μm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. This effort synthesizes the findings of more than 130 scientists

Land Surface Temperature (LST) estimated from Landsat images: applications in burnt areas and tree-grass woodlands (dehesas)

A lo largo de los últimos 40 años, las diferentes misiones del proyecto Landsat han proporcionado una gran cantidad de información espectral sobre la superficie terrestre. Las imágenes obtenidas por estos satélites se caracterizan por una resolución espacial de tipo medio, bandas espectrales situadas en diferentes regiones del espectro electromagnético (ópticas y térmicas) y una amplia cobertura terrestre. Si bien las bandas del óptico han sido utilizadas con éxito en numerosas aplicaciones, el uso del térmico ha sido mucho más limitado, a pesar de la gran importancia que representa el parámetro de la temperatura de superficie para numerosas aplicaciones ambientales, especialmente para aquellas relacionadas con la modelización de los flujos de energía en el sistema suelo-vegetación-atmósfera y con el cambio global. En este contexto, el objetivo principal de la presente investigación es explorar el potencial de la temperatura de superficie terrestre (siglas en inglés - LST), derivada de imágenes Landsat, en el estudio de ecosistemas heterogéneos, concretamente (i) áreas afectadas por los incendios forestales y (ii) ecosistemas de dehesa,formaciones constituidas por los árboles dispersos y pastizal/cultivos. En primer lugar, en el marco del proyecto BIOSPEC “Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of Global Change” (http://www.lineas.cchs.csic.es/biospec) se comparan las diferentes metodologías disponibles para la estimación de la LST a partir de la banda térmica de Landsat. Los mejores resultados, en condiciones atmosféricas caracterizadas por niveles medios de contenido de vapor, se obtuvieron usando el método mono-banda (en inglés - SingleChannel) (Jiménez-Muñoz et al., 2009), con un error de estimación <1º K. En el siguiente paso de la investigación la información sobre la distribución de LST derivada del sensor Thematic Mapper se utilizó en el análisis de la severidad del fuego en una zona forestal de Las Hurdes(Extremadura, España), y en el estudio de los efectos ocasionados por los diferentes tratamientos post-incendio en una zona quemada, esta vez localizada en los Montes de Zuera (Zaragoza, España). En relación con la severidad del fuego analizada en diferentes fechas post-incendio, se han detectado diferencias estadísticamente significativas entre los valores de LST correspondientes a las categorías de severidad establecidas a partir del índice espectral ΔNBR (Key y Benson, 2006).Los niveles de LST más elevados se observaron en las zonas donde la severidad del fuego fue mayor, debido a la menor emisividad de los productos de combustión y los cambios en el balance de energía relacionados con la ausencia de vegetación. En cuanto a las consecuencias de los tratamientos de madera quemada en la regeneración vegetal, se han observado diferencias estadísticamente significativas entre las áreas intervenidas y no intervenidas. En este sentido, en las áreas no intervenidas se registraron valores de LST ~1 K más bajos y niveles de recubrimiento vegetal ~10% más altos que en las intervenidas. En otro ámbito de aplicación, los datos de LST obtenidos mediante imágenes de Landsat-5 TM (período 2009-2011), se utilizaron en el análisis de los patrones espacio-temporales de la LST y su relación con el grado de ocupación de la fracción arbórea en ecosistemas de dehesa. Se ha detectado una relación negativa entre la LST y la cobertura arbórea, con diferencias a nivel estacional debido al dinamismo del ciclo fenológico del pastizal

Avaliação de métodos single channel na estimativa da temperatura da superfície terrestre no hemisfério sul a partir de dados orbitais no infravermelho termal

Diversos métodos tem sido propostos para estimar a Temperatura da Superfície Terrestre (LST) a partir de dados do infravermelho termal obtidos por satélites. Esses esforços são uma tentativa de minimizar os erros impostos na solução não-linear da transferência radiativa no sistema superfície-atmosfera. Além disso, a correção atmosférica em dados termais é um dos fatores fundamentais para obter LST acurada. Os métodos Single Channel (SC) permitem derivar a LST a partir da radiância medida em uma banda. Assim, consistem em uma oportunidade para estimar LST de longo prazo com os dados termais da série Landsat, com quase 40 anos de registro. Contudo, a maioria dos SC é desenvolvida e projetada para as condições atmosféricas e de superfície do Hemisfério Norte. Nesse contexto, essa dissertação objetivou avaliar o desempenho dos algoritmos Generalized Single Channel (GSC), Improved Single Channel (ISC) e Surface Temperature product (produto ST) na estimativa da LST em uma região litorânea do Hemisfério Sul. Para tanto, um campo de dunas composto por 99,53% de quartzo foi selecionado e dados do Landsat 8 TIRS foram utilizados. Inicialmente, para fundamentar a avaliação, investigou-se a aplicabilidade de perfis verticais de diferentes resoluções espaciais e horizontais, derivados de produtos de reanálise NCEP, na correção atmosférica, bem como, os impactos gerados na estimativa da LST. Os resultados mostraram que os perfis NCEP CFSv2 de resoluções originais e os perfis NCEP FNL utilizados pela Calculadora de Parâmetros de Correção Atmosférica (ACPC) da NASA foram os mais adequados para a correção atmosférica. Considerando as vantagens da ACPC, ela também foi utilizada para estimar os dados atmosféricos empregados nos algoritmos GSC e ISC na avaliação. O algoritmo ISC (RMSE de 0,69 K) apresentou o melhor desempenho na estimativa da LST, seguido do GSC (RMSE de 2,5 K) e do produto ST (RMSE de 4,24 K). De modo geral, concluiu-se que o ISC se mostrou o mais adequado para calcular a LST, podendo ser aplicado em estudos de balanço de energia, onde um erro de até 2 K é aceitável. Confirmou-se, portanto, a importância da análise dos métodos SC no presente trabalho, justificada pela sua aplicação em dados de radiância de sensores termais com uma banda, principalmente para estudos com séries temporais de LST da série Landsat, além de situações de mau funcionamento de canais espectrais.Several methods have been proposed to estimate the Land Surface Temperature (LST) from thermal infrared data obtained by satellites. These efforts are an attempt to minimize errors imposed in the nonlinear solution of radiative transfer in the surface- atmosphere system. Furthermore, atmospheric correction in thermal data is one of the key factors to obtain accurate LST. Single Channel (SC) methods allow to retrieve the LST from the measured radiance in one band. Thus, they provide an opportunity to estimate long-term LST with the Landsat thermal data series, with almost 40 years of record. However, most SCs are developed and designed for the atmospheric and surface conditions of the Northern Hemisphere. In this context, this dissertation aimed to evaluate the performance of the Generalized Single Channel (GSC), Improved Single Channel (ISC) and Surface Temperature product (ST product) algorithms in estimating LST in a coastal region of the Southern Hemisphere. For that, a dune field composed of 99.53% quartz was selected and Landsat 8 TIRS data were used. Initially, to support the evaluation, the applicability of vertical profiles of different spatial and horizontal resolutions, derived from NCEP reanalysis products, in atmospheric correction, as well as the impacts generated in the LST estimation, was investigated. The results showed that the original resolution NCEP CFSv2 profiles and the NCEP FNL profiles used by NASA's Atmospheric Correction Parameters Calculator (ACPC) were the most suitable for atmospheric correction. Considering the advantages of ACPC, it was also used to estimate the atmospheric data used in the GSC and ISC algorithms in the evaluation. The ISC algorithm (RMSE of 0.69 K) presented the best performance in retrieving the LST, followed by the GSC (RMSE of 2.5 K) and the ST product (RMSE of 4.24 K). In general, it was concluded that the ISC proved to be the most suitable to calculate the LST, and can be applied in energy balance studies, where an error of up to 2 K is acceptable. Therefore, the importance of the analysis of SC methods in the present work was confirmed, justified by their application in radiance data from thermal sensors with one band, mainly for studies with time series of LST from Landsat series, in addition to situations of channel malfunction

Land Surface Monitoring Based on Satellite Imagery

This book focuses attention on significant novel approaches developed to monitor land surface by exploiting satellite data in the infrared and visible ranges. Unlike in situ measurements, satellite data provide global coverage and higher temporal resolution, with very accurate retrievals of land parameters. This is fundamental in the study of climate change and global warming. The authors offer an overview of different methodologies to retrieve land surface parameters— evapotranspiration, emissivity contrast and water deficit indices, land subsidence, leaf area index, vegetation height, and crop coefficient—all of which play a significant role in the study of land cover, land use, monitoring of vegetation and soil water stress, as well as early warning and detection of forest fires and drought

SATELLITE MICROWAVE MEASUREMENT OF LAND SURFACE PHENOLOGY: CLARIFYING VEGETATION PHENOLOGY RESPONSE TO CLIMATIC DRIVERS AND EXTREME EVENTS

The seasonality of terrestrial vegetation controls feedbacks to the climate system including land-atmosphere water, energy and carbon (CO2) exchanges with cascading effects on regional-to-global weather and circulation patterns. Proper characterization of vegetation phenology is necessary to understand and quantify changes in the earthÆs ecosystems and biogeochemical cycles and is a key component in tracking ecological species response to climate change. The response of both functional and structural vegetation phenology to climatic drivers on a global scale is still poorly understood however, which has hindered the development of robust vegetation phenology models. In this dissertation I use satellite microwave vegetation optical depth (VOD) in conjunction with an array of satellite measures, Global Positioning System (GPS) reflectometry, field observations and flux tower data to 1) clarify vegetation phenology response to water, temperature and solar irradiance constraints, 2) demonstrate the asynchrony between changes in vegetation water content and biomass and changes in greenness and leaf area in relation to land cover type and climate constraints, 3) provide enhanced assessment of seasonal recovery of vegetation biomass following wildfire and 4) present a method to more accurately model tropical vegetation phenology. This research will establish VOD as a useful and informative parameter for regional-to-global vegetation phenology modeling, more accurately define the drivers of both structural and functional vegetation phenology, and help minimize errors in phenology simulations within earth system models. This dissertation also includes the development of Gross Primary Productivity (GPP) and Net Primary Productivity (NPP) vegetation health climate indicators as part of a NASA funded project entitled Development and Testing of Potential Indicators for the National Climate Assessment; Translating EOS datasets into National Ecosystem Biophysical Indicators

Pansharpened landsat 8 thermal-infrared data for improved land surface temperature characterization in a heterogeneous urban landscape

Challenges associated with adolescents are prevalent in South African societies. During the adolescence stage, children may become involved in deviant behaviour. Although a significant number of studies have focused on the factors that contribute to adolescents’ deviant behaviour, including parental factors, there is paucity of research specifically in rural communities. This study explores the contribution of parental factors to adolescents’ deviant behaviour in rural communities in South Africa. Guided by the qualitative approach, the present study makes use of semi-structured interviews to collect data and thematic analysis to analyse data