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Temporal Resolution, a Key Factor in Environmental Risk Assessment

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 50774

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Special Issue Editors

Dr. Adrian Ursu

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Guest Editor

Faculty of Geography and Geology, University “Alexandru Ioan Cuza”, 700506 Iași, Romania
Interests: land use/land cover changes; image processing; satellite image analysis; digital mapping; natural and environmental risk assessment through remote sensing; urban sprawl and remote sensing; heritage and remote sensing
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Dr. Cristian Constantin Stoleriu

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Guest Editor

Department of Geography, Faculty of Geography and Geology, Alexandru Ioan Cuza University of Iași, 700505 Iași, Romania
Interests: biogeography; hydrology; GIS; remote sensing; geo-informatics; phytogeography; hydrological processes; environmental studies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

During current times, the world has access to a vast database of satellite imagery, covering the entire surface of the globe, while spanning over 40 years of our timeline. Considering the large number of different types of satellites orbiting the Earth, the available data is not always homogeneous and comparable, but each space mission has managed to collect large packages of systematic data. In the recent years, the spatial analysis instruments have diversified and evolved significantly from a technological point of view, so we currently benefit from satellite images with better spatial, spectral and temporal resolutions. Therefore, we can now easily evaluate the impact of natural or anthropic events on the environment and society, and we can easily estimate the repercussions and provide appropriate solutions. Good temporal resolution and good quality of satellite images allows scientists to evaluate the effects of: droughts, hails, hurricanes, tornadoes, floods, deforestation, forest fires, mining accidents, pollution, Hazmat accidents, land use change, social events, urbanization, wars etc. Furthermore, having a consistent long-term database of satellite images provides researchers the opportunity to analyse the phenomena from a historic perspective, and it is possible to evaluate long term changes in natural local parameters, in relation to the recent changes of the environment at global scale. This special issue focuses on TIME, as the determinant factor in the analysis of various phenomena, at various spatial scales.

Dr. Adrian Ursu
Dr. Cristian Constantin Stoleriu
Guest Editors

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Keywords

Time series data and projections
Rapid evaluation of the extreme events impact on the environment and society
Climate change
Environmental Risks
Land use and land cover change
Multispectral, hyperspectral and LiDAR data from a temporal perspective
Ecosystems monitoring from RS data
History and Heritage

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22 pages, 5294 KiB

Open AccessArticle

Normalized Sand Index for Identification of Bare Sand Areas in Temperate Climates Using Landsat Images, Application to the South of Romania

by Cristian Vasilică Secu, Cristian Constantin Stoleriu, Cristian Dan Lesenciuc and Adrian Ursu

Remote Sens. 2022, 14(15), 3802; https://doi.org/10.3390/rs14153802 - 7 Aug 2022

Cited by 5 | Viewed by 4831

Abstract

The expansion of bare sand surfaces indicates a tendency towards desertfication in certain periods as a result of the improper agricultural use of sand soils and of the significant changes in the climate in the past 30 years. The Normalised Sand Index (NSI) is a new index used to identify bare sand areas and their spatio-temporal evolution in SW Romania. Landsat scenes (1988, 2001, 2019), spectral and soil texture analysis (36 samples), covariates (e.g., soil map), and field observations allowed for the validation of the results. The performance of the NSI was compared with indices from the sand index family (e.g., Normalized Differential Sand Areas Index) and supervised classifications (e.g., Maximum Likelihood Classification) based on 47 random control square areas for which the soil texture is known. A statistical analysis of the NSI showed 23.6% (27,310.14 hectares) of bare sands in 1988, followed by an accelerated increase to 47.2% (54,737.73 hectares) in 2001 because of economic and land-use changes, and a lower increase by 2019, which reached 52.5% (60,852.42 hectares) due to reforestation programs. Compared to the NSI, the bare sand areas obtained with the tested indicator were almost 20% higher. The traditional classification shows smaller areas of bare sands but uses a higher complexity of land use classes, while the producer accuracy values are lower than those of the NSI. The new index has achieved a correct spatial delimitation of soils in the interdune-dune and major riverbed-interfluvial areas, but it is limited to the transition Arenosols-Chernozems by humus content and agrotechnical works. The new spectral index favours bare sand monitoring and is a fast and inexpensive method of observing the desertification trend of temperate sandy agroecosystems in the context of climate change. Full article

(This article belongs to the Special Issue Temporal Resolution, a Key Factor in Environmental Risk Assessment)

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20 pages, 3998 KiB

Open AccessArticle

Using UAV Survey, High-Density LiDAR Data and Automated Relief Analysis for Habitation Practices Characterization during the Late Bronze Age in NE Romania

by Alin Mihu-Pintilie, Casandra Brașoveanu and Cristian Constantin Stoleriu

Remote Sens. 2022, 14(10), 2466; https://doi.org/10.3390/rs14102466 - 20 May 2022

Cited by 4 | Viewed by 2397

Abstract

The characterization of prehistoric human behavior in terms of habitation practices using GIS cartography methods is an important aspect of any modern geoarchaeological approach. Furthermore, using unmanned aerial vehicle (UAV) surveys to identify archaeological sites with temporal resolution during the spring agro-technical works and automated mapping of the geomorphological features based on LiDAR-derived DEM can provide valuable information about the human–landscape relationships and lead to accurate archaeological and cartographic products. In this study, we applied a GIS-based landform classification method to relief characterization of 362 Late Bronze Age (LBA) settlements belonging to Noua Culture (NC) (cal. 1500/1450-1100 BCE) located in the Jijia catchment (NE Romania). For this purpose, we used an adapted version of Topographic Position Index (TPI) methodology, abbreviated DEV, which consists of: (1) application of standard deviation of TPI for the mean elevation (DEV) around each analyzed LBA site (1000 m buffer zone); (2) classification of the archaeological site’s location using six slope position classes (first method), or ten morphological classes by combining the parameters from two small-DEV and large-DEV neighborhood sizes (second method). The results indicate that the populations belonging to Noua Culture preferred to place their settlements on hilltops but close to the steep slope and on the small hills/local ridges in large valleys. From a geoarchaeological perspective, the outcomes indicate a close connection between occupied landform patterns and habitation practices during the Late Bronze Age and contribute to archaeological predictive modelling in the Jijia catchment (NE Romania). Full article

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21 pages, 9001 KiB

Open AccessArticle

Managing Flood Hazard in a Complex Cross-Border Region Using Sentinel-1 SAR and Sentinel-2 Optical Data: A Case Study from Prut River Basin (NE Romania)

by Cătălin I. Cîmpianu, Alin Mihu-Pintilie, Cristian C. Stoleriu, Andrei Urzică and Elena Huţanu

Remote Sens. 2021, 13(23), 4934; https://doi.org/10.3390/rs13234934 - 4 Dec 2021

Cited by 4 | Viewed by 2817

Abstract

In this study, an alternative solution for flood risk management in complex cross-border regions is presented. In these cases, due to different flood risk management legislative approaches, there is a lack of joint cooperation between the involved countries. As a main consequence, LiDAR-derived digital elevation models and accurate flood hazard maps obtained by means of hydrological and hydraulic modeling are missing or are incomplete. This is also the case for the Prut River, which acts as a natural boundary between European Union (EU) member Romania and non-EU countries Ukraine and Republic of Moldova. Here, flood hazard maps were developed under the European Floods Directive (2007/60/EC) only for the Romanian territory and only for the 1% exceeding probability (respectively floods that can occur once every 100 years). For this reason, in order to improve the flood hazard management in the area and consider all cross-border territories, a fully remote sensing approach was considered. Using open-source SAR Sentinel-1 and Sentinel-2 data characterized by an improved temporal resolution, we managed to capture the maximum spatial extent of a flood event that took place in the aforementioned river sector (middle Prut River course) during the 24 and 27 June 2020. Moreover, by means of flood frequency analysis, the development of a transboundary flood hazard map with an assigned probability, specific to the maximum flow rate recorded during the event, was realized. Full article

(This article belongs to the Special Issue Temporal Resolution, a Key Factor in Environmental Risk Assessment)

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21 pages, 58799 KiB

Open AccessArticle

Spatio-Temporal Analysis of Ecological Vulnerability and Driving Factor Analysis in the Dongjiang River Basin, China, in the Recent 20 Years

by Jiao Wu, Zhijun Zhang, Qinjie He and Guorui Ma

Remote Sens. 2021, 13(22), 4636; https://doi.org/10.3390/rs13224636 - 17 Nov 2021

Cited by 12 | Viewed by 2707

Abstract

The global ecological environment faces many challenges. Landsat thematic mapper time-series, digital elevation models, meteorology, soil types, net primary production data, socio-economic data, and auxiliary data were collected in order to construct a comprehensive evaluation system for ecological vulnerability (EV) using multi-source remote sensing data. EV was divided into five vulnerability levels: potential I, slight II, mild III, moderate IV, and severe V. Then, we analyzed and explored the spatio-temporal patterns and driving mechanisms of EV in the region over the past 20 years. Our research results showed that, from 2001 to 2019, the DRB was generally characterized as being in the severe vulnerability class, with higher upstream and downstream EV classes and a certain amount of reduction in the midstream EV classes. Moreover, EV in the DRB continues to decrease. The spatio-temporal EV patterns in the DRB were significantly influenced by the relative humidity, average annual temperature, and vegetation cover over the past 20 years. Our work can provide a basis for decision-making and technical support for ecosystem protection, ecological restoration, and ecological management in the DRB. Full article

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20 pages, 12110 KiB

Open AccessArticle

Mapping the Impact of COVID-19 Lockdown on Urban Surface Ecological Status (USES): A Case Study of Kolkata Metropolitan Area (KMA), India

by Manob Das, Arijit Das, Paulo Pereira and Asish Mandal

Remote Sens. 2021, 13(21), 4395; https://doi.org/10.3390/rs13214395 - 31 Oct 2021

Cited by 7 | Viewed by 4340

Abstract

An urban ecosystem’s ecological structure and functions can be assessed through Urban Surface Ecological Status (USES). USES are affected by human activities and environmental processes. The mapping of USESs are crucial for urban environmental sustainability, particularly in developing countries such as India. The COVID-19 pandemic caused unprecedented negative impacts on socio-economic domains; however, there was a reduction in human pressures on the environment. This study aims to assess the effects of lockdown on the USES in the Kolkata Metropolitan Area (KMA), India, during different lockdown phases (phases I, II and III). The land surface temperature (LST), normalized difference vegetation index (NDVI), and wetness and normalized difference soil index (NDSI) were assessed. The USES was developed by combining all of the biophysical parameters using Principal Component Analysis (PCA). The results showed that there was a substantial USES spatial variability in KMA. During lockdown phase III, the USES in fair and poor sustainability areas decreased from 29% (2019) to 24% (2020), and from 33% (2019) to 25% (2020), respectively. Overall, the areas under poor USES decreased from 30% to 25% during lockdown periods. Our results also showed that the USES mean value was 0.49 in 2019but reached 0.34 during the lockdown period (a decrease of more than 30%). The poor USES area was mainly concentrated in built-up areas (with high LST and NDSI), compared to the rural fringe areas of KMA (high NDVI and wetness). The mapping of USES are crucial in different biophysical environmental conditions, and they can be very helpful for the assessment of urban sustainability. Full article

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25 pages, 4602 KiB

Open AccessArticle

Evaluating the Territorial Impact of Built-Up Area Expansion in the Surroundings of Bucharest (Romania) through a Multilevel Approach Based on Landsat Satellite Imagery

by Ilinca-Valentina Stoica, Daniela Zamfir and Marina Vîrghileanu

Remote Sens. 2021, 13(19), 3969; https://doi.org/10.3390/rs13193969 - 3 Oct 2021

Cited by 12 | Viewed by 3452

Abstract

Assessing the relentless expansion of built-up areas is one of the most important tasks for achieving sustainable planning and supporting decision-making on the regional and local level. In this context, techniques based on remote sensing can play a crucial role in monitoring the fast rhythm of urban growth, allowing the regular appraisal of territorial dynamics. The main aim of the study is to evaluate, in a multi-scalar perspective, the built-up area expansion and the spatio–temporal changes in Ilfov County, which overlaps the surroundings of Bucharest, capital of Romania. Our research focuses on processing multi-date Landsat satellite imagery from three selected time references (2000, 2008, 2018) through the supervised classification process. Further on, the types of built-up area dynamics are explored using LDTtool, a landscape metrics instrument. The results reveal massive territorial restructuring in the 18 years, as the new built-up developments occupy a larger area than the settlements’ surface in 2000. The rhythm of the transformations also changed over time, denoting a significant acceleration after 2008, when 75% of the new development occurred. At the regional level, the spatial pattern has become more and more complex, in a patchwork of spatial arrangements characterized by the proliferation of low density areas interspersed with clusters of high density developments and undeveloped land. At the local level, a comparative assessment of the administrative territorial units’ pathway was conducted based on the annual growth of built-up areas, highlighting the most attractive places and the main territorial directions of development. In terms of the specific dynamics of built-up areas, the main change patterns are “F—NP increment by gain”, followed by “G—Aggregation by gain”, both comprising around 80% of the total number of cells. The first type was prevalent in the first period (2000–2008), while the second is identified only after 2008, when it became the most represented, followed in the hierarchy by the previously dominant category. The spatial pattern differentiations were further explored in three complementary case studies investigated in correlation with socioeconomic data, revealing a heterogeneous landscape. Full article

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20 pages, 14853 KiB

Open AccessArticle

Rapid glacier Shrinkage and Glacial Lake Expansion of a China-Nepal Transboundary Catchment in the Central Himalayas, between 1964 and 2020

by Yan Zhong, Qiao Liu, Liladhar Sapkota, Yunyi Luo, Han Wang, Haijun Liao and Yanhong Wu

Remote Sens. 2021, 13(18), 3614; https://doi.org/10.3390/rs13183614 - 10 Sep 2021

Cited by 7 | Viewed by 3833

Abstract

Climate warming and concomitant glacier recession in the High Mountain Asia (HMA) have led to widespread development and expansion of glacial lakes, which reserved the freshwater resource, but also may increase risks of glacial lake outburst floods (GLOFs) or debris floods. Using 46 moderate- and high-resolution satellite images, including declassified Keyhole and Landsat missions between 1964 and 2020, we provide a comprehensive area mapping of glaciers and glacial lakes in the Tama Koshi (Rongxer) basin, a highly glacierized China-Nepal transnational catchment in the central Himalayas with high potential risks of glacier-related hazards. Results show that the 329.2 ± 1.9 km² total area of 271 glaciers in the region has decreased by 26.2 ± 3.2 km² in the past 56 years. During 2000–2016, remarkable ice mass loss caused the mean glacier surface elevation to decrease with a rate of −0.63 m a⁻¹, and the mean glacier surface velocity slowed by ~25% between 1999 and 2015. The total area of glacial lakes increased by 9.2 ± 0.4 km² (~180%) from 5.1 ± 0.1 km² in 1964 to 14.4 ± 0.3 km² in 2020, while ice-contacted proglacial lakes have a much higher expansion rate (~204%). Large-scale glacial lakes are developed preferentially and experienced rapid expansion on the east side of the basin, suggesting that in addition to climate warming, the glacial geomorphological characters (aspect and slope) are also key controlling factors of the lake growing process. We hypothesize that lake expansion will continue in some cases until critical local topography (i.e., steepening icefall) is reached, but the lake number may not necessarily increase. Further monitoring should be focused on eight rapidly expanding proglacial lakes due to their high potential risks of failure and relatively high lake volumes. Full article

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17 pages, 7965 KiB

Open AccessArticle

The Relative Contributions of Climate and Grazing on the Dynamics of Grassland NPP and PUE on the Qinghai-Tibet Plateau

by Huilin Yu, Qiannan Ding, Baoping Meng, Yanyan Lv, Chang Liu, Xinyu Zhang, Yi Sun, Meng Li and Shuhua Yi

Remote Sens. 2021, 13(17), 3424; https://doi.org/10.3390/rs13173424 - 28 Aug 2021

Cited by 27 | Viewed by 2837

Abstract

Net primary productivity (NPP) and precipitation-use efficiency (PUE) are crucial indicators in understanding the responses of vegetation to global change. However, the relative contributions of climate change and human interference to the dynamics of NPP and PUE remain unclear. During the past few decades, the impacts of climate change and human activities on alpine grasslands on the Qinghai-Tibet Plateau (QTP) have been intensifying. The aims of the study were to investigate the spatiotemporal patterns of grassland NPP and PUE on the QTP during 2000–2017 and quantify how much of the variance in NPP and PUE can be attributed to the climatic factors (precipitation and temperature) and grazing intensity. The results showed that: (1) grassland NPP significantly increased with a rate of 0.6 g C m⁻² year⁻¹ over the past 18 years, mainly induced by the increased temperature and the enhanced precipitation. The temperature was the dominant factor for NPP interannual variation in mid-eastern QTP, and precipitation restrained vegetation growth most in the southwest and northeast. (2) The PUE was higher on the eastern and western parts of the plateau, but lower at the center. Regarding grassland types, the PUE of alpine steppe (0.19 g C m⁻² mm⁻¹) was significantly lower than those of alpine meadow (0.31 g C m⁻² mm⁻¹) and desert steppe (0.32 g C m⁻² mm⁻¹). (3) Precipitation was significantly and negatively correlated with PUE and contributed the most to the temporal variation of grassland PUE on the QTP (52.7%). (4) Furthermore, we found that the grazing activities had the lowest contributions to both NPP and PUE interannual variation, compared to temperature and precipitation. Thus, it is suggested that climate variability rather than grazing activities dominated vegetation changes on the QTP. Full article

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19 pages, 4481 KiB

Open AccessArticle

Variation Tendency of Coastline under Natural and Anthropogenic Disturbance around the Abandoned Yellow River Delta in 1984–2019

by Zhipeng Sun and Xiaojing Niu

Remote Sens. 2021, 13(17), 3391; https://doi.org/10.3390/rs13173391 - 26 Aug 2021

Cited by 6 | Viewed by 2119

Abstract

The coast around the Abandoned Yellow River Delta underwent significant changes under anthropogenic disturbance. This study aims to reveal the variation of the coastline, tidal flat area, and intertidal zone slope before, during, and after extensive reclamation during the period of 1984–2019 using satellite remote sensing images. In order to eliminate the influence of the varying water level, a new coastline correction algorithm had been proposed under the condition of insufficient accurate slope and water level data. The influence of seawalls on slope estimation were considered in it. The spatiotemporal evolution of coast had been analyzed and confirmed to be reasonable by comparing with the observed data. The results show that the coast can be roughly divided into a north erosion part and a south deposition part. Affected by reclamation, their tidal flat area in 2019 is reduced to only 43 and 27% of original area in 1984, respectively, which results in a continuous decrease in the tidal flat width. The adjustment of the tidal flat profile makes the slopes steeper in the erosion part, while the slopes in the deposition part remain stable. The reclamation has stimulated a cumulative effect as the disappearance of the intertidal zone, which may lead to the destruction of biological habitats. Full article

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17 pages, 4727 KiB

Open AccessArticle

Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data

by Chong Liu, Huabing Huang, Fengming Hui, Ziqian Zhang and Xiao Cheng

Remote Sens. 2021, 13(14), 2742; https://doi.org/10.3390/rs13142742 - 13 Jul 2021

Cited by 4 | Viewed by 3296

Abstract

The timing of lake ice-off regulates biotic and abiotic processes in Arctic ecosystems. Due to the coarse spatial and temporal resolution of available satellite data, previous studies mainly focused on lake-scale investigations of melting/freezing, hindering the detection of subtle patterns within heterogeneous landscapes. To fill this knowledge gap, we developed a new approach for fine-resolution mapping of Pan-Arctic lake ice-off phenology. Using the Scene Classification Layer data derived from dense Sentinel-2 time series images, we estimated the pixel-by-pixel ice break-up end date information by seeking the transition time point when the pixel is completely free of ice. Applying this approach on the Google Earth Engine platform, we mapped the spatial distribution of the break-up end date for 45,532 lakes across the entire Arctic (except for Greenland) for the year 2019. The evaluation results suggested that our estimations matched well with both in situ measurements and an existing lake ice phenology product. Based on the generated map, we estimated that the average break-up end time of Pan-Arctic lakes is 172 ± 13.4 (measured in day of year) for the year 2019. The mapped lake ice-off phenology exhibits a latitudinal gradient, with a linear slope of 1.02 days per degree from 55°N onward. We also demonstrated the importance of lake and landscape characteristics in affecting spring lake ice melting. The proposed approach offers new possibilities for monitoring the seasonal Arctic lake ice freeze–thaw cycle, benefiting the ongoing efforts of combating and adapting to climate change. Full article

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22 pages, 14265 KiB

Open AccessArticle

Drought Extent and Severity on Arable Lands in Romania Derived from Normalized Difference Drought Index (2001–2020)

by Radu-Vlad Dobri, Lucian Sfîcă, Vlad-Alexandru Amihăesei, Liviu Apostol and Simona Țîmpu

Remote Sens. 2021, 13(8), 1478; https://doi.org/10.3390/rs13081478 - 12 Apr 2021

Cited by 24 | Viewed by 4544

Abstract

The aim of this study was to evaluate the frequency and severity of drought over the arable lands of Romania using the Normalized Difference Drought Index (NDDI). This index was obtained from the Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensor of the Terra satellite. The interval between March and September was investigated to study the drought occurrence from the early stage of crop growth to its harvest time. The study covered a long period (2001–2020), hence it is able to provide a sound climatological image of crop vegetation conditions. Corine Land Cover 2018 (CLC) was used to extract the arable land surfaces. According to this index, the driest year was 2003 with 25.6% of arable land affected by drought. On the contrary, the wettest year was 2016, with only 10.8% of arable land affected by drought. Regarding the multiannual average of the period 2001–2020, it can be seen that drought is not a phenomenon that occurs consistently each year, therefore only 11.7% of arable land was affected constantly by severe and extreme drought. The correlation between NDDI and precipitation amount was also investigated. Although the correlations at weekly or monthly levels are more complicated, the annual regional mean NDDI is overall negatively correlated with annual rainfall. Thus, from a climatic perspective, we consider that NDDI is a reliable and valuable tool for the assessment of droughts over the arable lands in Romania. Full article

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24 pages, 22444 KiB

Open AccessArticle

Predicting Future Urban Flood Risk Using Land Change and Hydraulic Modeling in a River Watershed in the Central Province of Vietnam

by Huu Duy Nguyen, Dennis Fox, Dinh Kha Dang, Le Tuan Pham, Quan Vu Viet Du, Thi Ha Thanh Nguyen, Thi Ngoc Dang, Van Truong Tran, Phuong Lan Vu, Quoc-Huy Nguyen, Tien Giang Nguyen, Quang-Thanh Bui and Alexandru-Ionut Petrisor

Remote Sens. 2021, 13(2), 262; https://doi.org/10.3390/rs13020262 - 13 Jan 2021

Cited by 39 | Viewed by 6817

Abstract

Flood risk is a significant challenge for sustainable spatial planning, particularly concerning climate change and urbanization. Phrasing suitable land planning strategies requires assessing future flood risk and predicting the impact of urban sprawl. This study aims to develop an innovative approach combining land use change and hydraulic models to explore future urban flood risk, aiming to reduce it under different vulnerability and exposure scenarios. SPOT-3 and Sentinel-2 images were processed and classified to create land cover maps for 1995 and 2019, and these were used to predict the 2040 land cover using the Land Change Modeler Module of Terrset. Flood risk was computed by combining hazard, exposure, and vulnerability using hydrodynamic modeling and the Analytic Hierarchy Process method. We have compared flood risk in 1995, 2019, and 2040. Although flood risk increases with urbanization, population density, and the number of hospitals in the flood plain, especially in the coastal region, the area exposed to high and very high risks decreases due to a reduction in poverty rate. This study can provide a theoretical framework supporting climate change related to risk assessment in other metropolitan regions. Methodologically, it underlines the importance of using satellite imagery and the continuity of data in the planning-related decision-making process. Full article

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12 pages, 1818 KiB

Open AccessTechnical Note

Sensitivity of Spectral Indices on Burned Area Detection using Landsat Time Series in Savannas of Southern Burkina Faso

by Jinxiu Liu, Eduardo Eiji Maeda, Du Wang and Janne Heiskanen

Remote Sens. 2021, 13(13), 2492; https://doi.org/10.3390/rs13132492 - 25 Jun 2021

Cited by 15 | Viewed by 3463

Abstract

Accurate and efficient burned area mapping and monitoring are fundamental for environmental applications. Studies using Landsat time series for burned area mapping are increasing and popular. However, the performance of burned area mapping with different spectral indices and Landsat time series has not been evaluated and compared. This study compares eleven spectral indices for burned area detection in the savanna area of southern Burkina Faso using Landsat data ranging from October 2000 to April 2016. The same reference data are adopted to assess the performance of different spectral indices. The results indicate that Burned Area Index (BAI) is the most accurate index in burned area detection using our method based on harmonic model fitting and breakpoint identification. Among those tested, fire-related indices are more accurate than vegetation indices, and Char Soil Index (CSI) performed worst. Furthermore, we evaluate whether combining several different spectral indices can improve the accuracy of burned area detection. According to the results, only minor improvements in accuracy can be attained in the studied environment, and the performance depended on the number of selected spectral indices. Full article

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