1,525 research outputs found

    Burnt area mapping in insular Southeast Asia using medium resolution satellite imagery

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    Burnt area mapping in humid tropical insular Southeast Asia using medium resolution (250-500m) satellite imagery is characterized by persisting cloud cover, wide range of land cover types, vast amount of wetland areas and highly varying fire regimes. The objective of this study was to deepen understanding of three major aspects affecting the implementation and limits of medium resolution burnt area mapping in insular Southeast Asia: 1) fire-induced spectral changes, 2) most suitable multitemporal compositing methods and 3) burn scars patterns and size distribution. The results revealed a high variation in fire-induced spectral changes depending on the pre-fire greenness of burnt area. It was concluded that this variation needs to be taken into account in change detection based burnt area mapping algorithms in order to maximize the potential of medium resolution satellite data. Minimum near infrared (MODIS band 2, 0.86μm) compositing method was found to be the most suitable for burnt area mapping purposes using Moderate Resolution Imaging Spectroradiometer (MODIS) data. In general, medium resolution burnt area mapping was found to be usable in the wetlands of insular Southeast Asia, whereas in other areas the usability was seriously jeopardized by the small size of burn scars. The suitability of medium resolution data for burnt area mapping in wetlands is important since recently Southeast Asian wetlands have become a major point of interest in many fields of science due to yearly occurring wild fires that not only degrade these unique ecosystems but also create regional haze problem and release globally significant amounts of carbon into the atmosphere due to burning peat. Finally, super-resolution MODIS images were tested but the test failed to improve the detection of small scars. Therefore, super-resolution technique was not considered to be applicable to regional level burnt area mapping in insular Southeast Asia.Laaja valikoima erilaisia maankäyttöluokkia, pilvisyys ja kosteikkoalueiden suuri määrä luovat erityispiirteet paloalueiden kartoitukselle Kaakkois-Aasian saariston kostean troppisissa olosuhteissa keskiresoluutioisilla (250m-500m) satelliittikuva-aineistoilla. Tämän tutkimuksen tavoitteena oli syventää ymmärrystä keskiresoluutioisen paloaluekartoituksen toteutukseen ja rajoituksiin Kaakkois-Aasian saaristossa vaikuttavista tekijöistä. Tutkimuksen tulokset paljastivat suurta vaihtelua tulipalojen aiheuttamissa heijastussäteilyn muutoksissa riippuen palaneen alueen vehreydestä ennen tulipaloa. Johtopäätöksenä todettiin että keskiresoluutioisten satelliittikuvien koko potentiaalin hyödyntämiseksi paloalueiden kartoituksessa tämä vaihtelu tulisi ottaa huomioon paloalueiden havainnointialgoritmeissa jotka perustuvat heijastussäteilyn muutosten seurantaan. Tähän ajatukseen perustuvaa paloalueiden kartoitusta myös kokeiltiin aineistoilla jotka oli tutkimuksissa todettu parhaiten tarkoitukseen sopiviksi. Paloalueiden muoto- ja kokojakauman analyysiin sekä käytännön testeihin perustuen keskiresoluutioinen paloalueiden kartoitus todettiin käyttökelpoiseksi Kaakkois-Aasian saariston kosteikkoalueilla. Muilla alueilla sen sijaan paloalueiden pieni koko uhkasi vakavasti sen käyttökelpoisuutta. Keskiresoluutioisten satelliittikuva-aineistojen käyttökelpoisuus paloalueiden kartoitukseen kosteikkoalueilla on kuitenkin merkittävää sillä viime aikoina Kaakkois-Aasian kosteikkoalueet ovat monilla tieteenaloilla nousseet kiinnostuksen kohteeksi vuosittain esiintyvien tulipalojen takia. Vuosittaiset tulipalot eivät ainoastaan heikennä näitä ainutlaatuisia ekosysteemejä vaan lähinnä palavan turpeen johdosta myös aiheuttavat pahoja alueellisia savusumuongelmia ja vapauttavat maailmanlaajuisesti merkittäviä määriä hiilidioksidia ilmakehään. Tämän tutkimuksen tulokset osaltaan luovat pohjaa yhä tarkempien alueellisten paloalueiden kartoitusmenetelmien kehittämiselle. Näillä menetelmillä kerättävä tieto paloalueiden laajuudesta ja sijainneista antaa muiden alojen tutkijoille yhä paremmat mahdollisuudet arvioida Kaakkois-Aasian saariston kosteikkoalueiden tulipalojen paikallisia, alueellisia ja maailmanlaajuisia vaikutuksia

    A contribution for a global nurned area map

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    The goal of this work was to develop methodologies for burned area mapping at 1 km resolution using SPOT-VEGETATION (VGT) images from tropical (Southeastern Africa and Brazil), temperate (Iberian Peninsula) and boreal (Eastern Siberia / Northeastern China) regions. For each study area seven months of daily images were used in order to map the areas burned during the entire fire season. Linear discriminant analysis or classification trees were applied, depending on the study area, to monthly composite images derived from the daily images, and monthly burned area maps were produced. The final VGT 1 km burned area maps were validated with burned area maps derived from 30 m Landsat imagery, using linear regression. Twenty-four Landsat scenes were used in the validation of the maps produced for the four study areas. The accuracy of the VGT maps was variable, dependent on vegetation type and on the spatial pattern of the burned areas

    MAPPING BURNT AREAS USING THE SEMI-AUTOMATIC OBJECT-BASED IMAGE ANALYSIS METHOD

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    Forest and land fires in Indonesia take place almost every year, particularly in the dry season and in Sumatra and Kalimantan. Such fires damage the ecosystem, and lower the quality of life of the community, especially in health, social and economic terms. To establish the location of forest and land fires, it is necessary to identify and analyse burnt areas. Information on these is necessary to determine the environmental damage caused, the impact on the environment, the carbon emissions produced, and the rehabilitation process needed. Identification methods of burnt land was made both visually and digitally by utilising satellite remote sensing data technology. Such data were chosen because they can identify objects quickly and precisely. Landsat 8 image data have many advantages: they can be easily obtained, the archives are long and they are visible to thermal wavelengths. By using a combination of visible, infrared and thermal channels through the semi-automatic object-based image analysis (OBIA) approach, the study aims to identify burnt areas in the geographical area of Indonesia. The research concludes that the semi-automatic OBIA approach based on the red, infrared and thermal spectral bands is a reliable and fast method for identifying burnt areas in regions of Sumatra and Kalimantan

    Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

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    Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status

    Development of a global burned area mapping algorithm for moderate spatial resolution optical sensors

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    La tesis doctoral titulada “Development of a global burned area mapping algorithm for moderate spatial resolution optical sensors” propone el desarrollo de un algoritmo de detección de área quemada global para sensores ópticos de resolución espacial moderada. El trabajo ha sido financiado y desarrollado bajo los proyectos Fire Disturbance (FireCCI) del programa Climate Change Initiative (CCI) de la European Space Agency (ESA) y el Copernicus Climate Change Service (C3S) de la European Commission (EC). El autor de este trabajo también ha recibido financiación del Ministerio de Ciencia, Innovación y Universidades, a través de una beca FPU. Cuando se propuso esta tesis solo había un único producto global de área quemada que ofrecía una serie temporal larga y consistente. Se trataba del producto MCD64A1 de la National Aeronautics and Space Administration (NASA) que se generaba operacionalmente y que proveía información de área quemada a nivel global a 500 m desde noviembre del 2000. Por la parte europea solo había dos productos, el FireCCI41 y el GIO_GL1_BA, pero se trataba de productos que o bien ofrecían una serie temporal demasiado reducida (FireCCI41) o bien una serie con baja fiabilidad. En cualquier caso, los tres productos, incluido el MCD64A1, presentaban limitaciones que les hacían estar lejos de cumplir los requerimientos establecidos por los usuarios en términos de errores de comisión y omisión. Es en este contexto donde se plantea esta tesis que pretende avanzar en el conocimiento de los algoritmos de área quemada globales y la generación de productos globales que cumplan o se acerquen de forma más significativa a las expectativas de los usuarios. Para este propósito, se ha utilizado información proveniente de sensores que no se habían utilizado hasta el momento para generar productos de área quemada globales. Esta información incluye las bandas de alta resolución a 250 m del Moderate Resolution Imaging Spectroradiometer (MODIS), las bandas del Ocean and Land Colour Instrument (OLCI) y del SYNERGY, así como fuegos activos de MODIS y del Visible Infrared Imaging Radiometer Suite (VIIRS). En este último caso, ha sido la primera vez que se utilizan globalmente para generar este tipo de productos. Así, se han desarrollado cuatro algoritmos y se han generado sus respectivos productos de área quemada a escala global. Cada uno de ellos ha jugado un papel complementario al resto, ya sea a modo de versión mejorada o como adaptación de un mismo algoritmo a distintos sensores. Todos los productos derivados han sido validados globalmente y se han llevado a cabo comparaciones exhaustivas con otros productos existentes. Además, para confirmar la estabilidad de los patrones espacio temporales, los productos se han aplicado para dar respuesta a distintas preguntas científicas relacionadas con las anomalías en las tendencias del área quemada en distintas partes del mundo. Para explicar todo este proceso la tesis se ha estructurado en ocho capítulos: introducción, seis publicaciones en revistas internacionales y unas conclusiones

    Separability Analysis of Sentinel-2A Multi-Spectral Instrument (MSI) Data for Burned Area Discrimination

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    : Biomass burning is a global phenomenon and systematic burned area mapping is of increasing importance for science and applications. With high spatial resolution and novelty in band design, the recently launched Sentinel-2A satellite provides a new opportunity for moderate spatial resolution burned area mapping. This study examines the performance of the Sentinel-2A Multi Spectral Instrument (MSI) bands and derived spectral indices to differentiate between unburned and burned areas. For this purpose, five pairs of pre-fire and post-fire top of atmosphere (TOA reflectance) and atmospherically corrected (surface reflectance) images were studied. The pixel values of locations that were unburned in the first image and burned in the second image, as well as the values of locations that were unburned in both images which served as a control, were compared and the discrimination of individual bands and spectral indices were evaluated using parametric (transformed divergence) and non-parametric (decision tree) approaches. Based on the results, the most suitable MSI bands to detect burned areas are the 20 m near-infrared, short wave infrared and red-edge bands, while the performance of the spectral indices varied with location. The atmospheric correction only significantly influenced the separability of the visible wavelength bands. The results provide insights that are useful for developing Sentinel-2 burned area mapping algorithms
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