Landsat-8 cloud-free observations in wet tropical areas: a case study in South East Asia

Laborde, Henri; Douzal, Vincent; Piña, Hugo Antonio Ruiz; Morand, Serge; Cornu, J. F.

doi:10.1080/2150704x.2017.1297543

Cited by 18 publications

(12 citation statements)

References 13 publications

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“…Land use and land cover changes (LULCC) have been the subject of recent studies focusing on landscape changes [1,2], land degradation/deforestation [3,4], and landscape fragmentation [5,6]. Human activity is the main driver of LULCC in the world [7]; as a result, human activities have substantially affected 75% of the Earth's land surface, mostly related to agricultural activities [8].…”

Section: Introductionmentioning

confidence: 99%

Assessing Land Use and Land Cover Changes in the Direct Influence Zone of the Braço Norte Hydropower Complex, Brazilian Amazonia

Guerrero

Escobar-Silva

Chaves

et al. 2020

Forests

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Over the decades, hydropower complexes have been built in several hydrographic basins of Brazil including the Amazon region. Therefore, it is important to understand the effects of these constructions on the environment and local communities. This work presents a land use and land cover change temporal analysis considering a 33-year period (1985–2018) in the direct influence zone of the Braço Norte Hydropower Complex, Brazilian Amazonia, using the Collection 4.1 level 3 of the freely available MapBiomas dataset. Additionally, we have assessed the Brazilian Amazon large-scale deforestation process acting as a land use and land cover change driver in the study area. Our findings show that the most impacted land cover was forest formation (from 414 km2 to 287 km2, a reduction of 69%), which primarily shifted into pasturelands (increase of 664%, from 40 km2 to 299 km2). The construction of the hydropower complex also triggered indirect impacts such as the presence of urban areas in 2018 and the consequent increased local demand for crops. Together with the ongoing large-scale Amazonian deforestation process, the construction of the complex has intensified changes in the study area as 56.42% of the pixels were changed between 1985 and 2018. This indicates the importance of accurate economic and environmental impact studies for assessing social and environmental consequences of future construction in this unique region. Our results reveal the need for adopting special policies to minimize the impact of these constructions, for example, the creation of Protected Areas and the definition of locally-adjusted parameters for the ecological-economic zoning considering environmental and social circumstances derived from the local actors that depend on the natural environment to subsist such as indigenous peoples, riverine population, and artisanal fishermen.

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Section: Introductionmentioning

confidence: 99%

Assessing Land Use and Land Cover Changes in the Direct Influence Zone of the Braço Norte Hydropower Complex, Brazilian Amazonia

Guerrero

Escobar-Silva

Chaves

et al. 2020

Forests

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“…The use of remote sensing to delineate flood map are promising [40][41][42][43]. Despite that, clouds are always the main problem for optical-based satellite systems to capture images [44,45], especially during the rainy season while flooding is happening [46,47]. Microwave satellites can overcome this problem as its signal can penetrate cloud and light to moderate rain [42,48], but limited available microwave satellites prevent near-real-time flood mapping [42,48].…”

Section: Introductionmentioning

confidence: 99%

Application of Satellite Rainfall Products for Flood Inundation Modelling in Kelantan River Basin, Malaysia

et al. 2019

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The advent of satellite rainfall products can provide a solution to the scarcity of observed rainfall data. The present study aims to evaluate the performance of high spatial-temporal resolution satellite rainfall products (SRPs) and rain gauge data in hydrological modelling and flood inundation mapping. Four SRPs, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) - Early, - Late (IMERG-E, IMERG-L), Global Satellite Mapping of Precipitation-Near Real Time (GSMaP-NRT), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks- Cloud Classification System (PERSIANN-CCS) and rain gauge data were used as the primary input to a hydrological model, Rainfall-Runoff-Inundation (RRI) and the simulated flood level and runoff were compared with the observed data using statistical metrics. GSMaP showed the best performance in simulating hourly runoff with the lowest relative bias (RB) and the highest Nash-Sutcliffe efficiency (NSE) of 4.9% and 0.79, respectively. Meanwhile, the rain gauge data was able to produce runoff with −12.2% and 0.71 for RB and NSE, respectively. The other three SRPs showed acceptable results in daily discharge simulation (NSE value between 0.42 and 0.49, and RB value between −23.3% and −31.2%). The generated flood map also agreed with the published information. In general, the SRPs, particularly the GSMaP, showed their ability to support rapid flood forecasting required for early warning of floods.

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“…Li et al (2018) studied the acquisition probability differences in cloud coverage of the available Landsat observations over mainland Southeast Asia. Laborde et al (2017) analyzed the Landsat 8 cloud-free observations in South East Asia. Xiao et al (2018) analyzed the spatio-temporal differences in cloud cover of Landsat-8 OLI across China.…”

Section: Introductionmentioning

confidence: 99%

The Spatial and Temporal Availability Differences of Cloud-Free Landsat Images Over Three Gorges Reservoir Area

Bai

Tan

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Availability analysis of cloud-free optical remote sensing data is a prerequisite for remote sensing applications. In this study, spatio-temporal availability differences of cloud-free Landsat TM, ETM+, and OLI sensors images over Three Gorges Reservoir Area (TGRA) were analyzed from 1986 to 2019 based on the Google Earth Engine (GEE). The results show that: 1) in Summer, especially in August, the probabilities of obtaining Landsat images with no more than 30% cloud cover (CC) is higher. 2) the northeast of TGRA has higher probability of acquiring cloudless images than the southwest. 3) In TGRA, annual monitoring which require at least one cloud-free observation in a year largely unaffected by CC, but when considering seasonal monitoring, cloud contaminate will become a limitation, and monthly monitoring in this area is basically not feasible even if the three sensors data are combined. The results of this paper will provide important references for the research of using optical data in this area, and although the research area is relatively small, the analysis method and the program developed in this paper have no restrictions on the area.

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Landsat-8 cloud-free observations in wet tropical areas: a case study in South East Asia

Cited by 18 publications

References 13 publications

Assessing Land Use and Land Cover Changes in the Direct Influence Zone of the Braço Norte Hydropower Complex, Brazilian Amazonia

Assessing Land Use and Land Cover Changes in the Direct Influence Zone of the Braço Norte Hydropower Complex, Brazilian Amazonia

Application of Satellite Rainfall Products for Flood Inundation Modelling in Kelantan River Basin, Malaysia

The Spatial and Temporal Availability Differences of Cloud-Free Landsat Images Over Three Gorges Reservoir Area

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