Mapping flood events using remote sensing in an arid zone river, central Australia

Identifying permanent water and temporary water in flood disasters efficiently has mainly relied on change detection method from multi-temporal remote sensing imageries, but estimating the water type in flood disaster events from only post-flood remote sensing imageries still remains challenging. Research progress in recent years has demonstrated the excellent potential of multi-source data fusion and deep learning algorithms in improving flood detection, while this field has only been studied initially due to the lack of large-scale labelled remote sensing images of flood events. Here, we present new deep learning algorithms and a multi-source data fusion driven flood inundation mapping approach by leveraging a large-scale publicly available Sen1Flood11 dataset consisting of roughly 4831 labelled Sentinel-1 SAR and Sentinel-2 optical imagery gathered from flood events worldwide in recent years. Specifically, we proposed an automatic segmentation method for surface water, permanent water, and temporary water identification, and all tasks share the same convolutional neural network architecture. We utilize focal loss to deal with the class (water/non-water) imbalance problem. Thorough ablation experiments and analysis confirmed the effectiveness of various proposed designs. In comparison experiments, the method proposed in this paper is superior to other classical models. Our model achieves a mean Intersection over Union (mIoU) of 52.99%, Intersection over Union (IoU) of 52.30%, and Overall Accuracy (OA) of 92.81% on the Sen1Flood11 test set. On the Sen1Flood11 Bolivia test set, our model also achieves very high mIoU (47.88%), IoU (76.74%), and OA (95.59%) and shows good generalization ability.

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A Study of Desertification Using Remote Sensing Techniques in Basra Governorate, South Iraq

Iraqi Journal of Science ◽

10.24996/ijs.2021.62.3.22 ◽

2021 ◽

pp. 912-926

Author(s):

Fadel Abbas Zwain ◽

Thair Thamer Al-Samarrai ◽

Younus I. Al-Saady

Keyword(s):

Remote Sensing ◽

Land Degradation ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Arid Zone ◽

Sand Dunes ◽

Risk Index ◽

Anthropogenic Factors ◽

Landsat Images

Iraq territory as a whole and south of Iraq in particular encountered rapid desertification and signs of severe land degradation in the last decades. Both natural and anthropogenic factors are responsible for the extent of desertification. Remote sensing data and image analysis tools were employed to identify, detect, and monitor desertification in Basra governorate. Different remote sensing indicators and image indices were applied in order to better identify the desertification development in the study area, including the Normalized difference vegetation index (NDVI), Normalized Difference Water Index (NDWI), Salinity index (SI), Top Soil Grain Size Index (GSI) , Land Surface Temperature (LST) , Land Surface Soil Moisture (LSM), and Land Degradation Risk Index (LDI) which was used for the assessment of degradation severity .Three Landsat images, acquired in 1973, 1993, and 2013, were used to evaluate the potential of using remote sensing analysis in desertification monitoring. The approach applied in this study for evaluating this phenomenon was proven to be an effective tool for the recognition of areas at risk of desertification. The results indicated that the arid zone of Basra governorate encounters substantial changes in the environment, such as decreasing surface water, degradation of agricultural lands (as palm orchards and crops), and deterioration of marshlands. Additional changes include increased salinization with the creeping of sand dunes to agricultural areas, as well as the impacts of oil fields and other facilities.

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Pleistocene settlement in the Australian arid zone: occupation of an inland riverine landscape in the central Australian ranges

Antiquity ◽

10.1017/s0003598x00086257 ◽

1998 ◽

Vol 72 (275) ◽

pp. 34-45 ◽

Cited By ~ 23

Author(s):

Peter B. Thorley

Keyword(s):

Environmental Change ◽

Arid Zone ◽

River Catchment ◽

Central Australia

Recent excavations at the Kulpi Mara Rockshelter in the Palmer River catchment of central Australia have produced radiocarbon determinations spanning an archaeological sequence of 30,000 years. These results enable re-assessment of models addressing the how, where and when of arid zone colonisation, and human adjustments to environmental change in the later Pleistocene. Whilst the evidence supports early occupation of the central arid zone during wetter conditions, doubts are raised about the continuity of occupation during the height of glacial aridity.

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Reflecting on siliceous rocks in central Australia: Using advanced remote sensing to map ancient “tool‐stone” resources

Geoarchaeology ◽

10.1002/gea.21776 ◽

2020 ◽

Vol 35 (3) ◽

pp. 400-415

Author(s):

Wallace Boone Law ◽

Megan M. Lewis ◽

Bertram Ostendorf ◽

Peter Hiscock

Keyword(s):

Remote Sensing ◽

Siliceous Rocks ◽

Central Australia

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Zooplankton diversity and assemblages in arid zone rivers of the Lake Eyre Basin, Australia

Marine and Freshwater Research ◽

10.1071/mf05101 ◽

2006 ◽

Vol 57 (1) ◽

pp. 49 ◽

Cited By ~ 26

Author(s):

Russell J. Shiel ◽

Justin F. Costelloe ◽

Julian R. W. Reid ◽

Peter Hudson ◽

Joan Powling

Keyword(s):

Seasonal Changes ◽

Arid Zone ◽

Early Summer ◽

Taxon Richness ◽

Ecosystem Structure ◽

Regression Analyses ◽

Flood Events ◽

Assemblage Composition ◽

Boom And Bust ◽

Three Rivers

The responses of zooplankton assemblages in arid zone rivers to seasonal changes, flow events, drying and water quality changes are fundamental to our understanding of these unregulated rivers. For three years the zooplankton and littoral microfauna in three rivers in the Lake Eyre Basin were studied. A diverse assemblage was discovered with a total of 398 identifiable taxa being recorded, consisting of 72 protist, 227 rotifer and 93 microcrustacean taxa. Zooplankton diversity was highest in a boom phase during, or in the summer following, a large flood. The rotifer assemblage dominated during, or soon after, periods of flow. However, during the winter and early summer, there was a decline in rotifer taxon richness and abundance accompanied by an increase in microcrustacean taxon richness and abundance. The winter samples occurred during the recession of a large flood and the early summer samples during periods of no flow. These changes suggested the involvement of a strong annual cycle of ecosystem structure evident within the longer term patterns of boom and bust driven by the timing and size of flood events. Multivariate and regression analyses found that salinity was a significant and independent driver of assemblage composition.

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Quaternary pollen analysis in the arid zone of Australia: Dalhousie Springs, Central Australia

Review of Palaeobotany and Palynology ◽

10.1016/0034-6667(90)90149-d ◽

1990 ◽

Vol 64 (1-4) ◽

pp. 331-341 ◽

Cited By ~ 21

Author(s):

W.E Boyd

Keyword(s):

Pollen Analysis ◽

Arid Zone ◽

Central Australia

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CONSISTENCY IN REMOTE SENSING-BASED URBAN MAPPING FOR GROWTH AND MOBILITY ANALYSIS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w16-461-2019 ◽

2019 ◽

Vol XLII-4/W16 ◽

pp. 461-462

Author(s):

L. Møller-Jensen ◽

A. N. Allotey

Keyword(s):

Remote Sensing ◽

Census Data ◽

Urban Expansion ◽

Growth Dynamics ◽

Transport Infrastructure ◽

Flood Events ◽

Mobility Analysis ◽

Digital Road Maps ◽

Road Maps ◽

Initial Results

Abstract. This extended abstract presents initial results from a study that focus on the accuracy of satellite-based maps of Accra’s urban expansion as well as their comparability and ability to provide a basis for assessing urban spatial growth dynamics. Within the study we have analysed five different satellite-derived maps of urban development in Accra and compared the results and underlying methods. It is discussed how these maps can be operationalized and, combined with census data and digital road maps, used for calculating how flood events that disable parts of the transport infrastructure impact the overall mobility of the Accra population.

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Estimation of antecedent wetness conditions for flood modelling in northern Morocco

Hydrology and Earth System Sciences ◽

10.5194/hess-16-4375-2012 ◽

2012 ◽

Vol 16 (11) ◽

pp. 4375-4386 ◽

Cited By ~ 52

Author(s):

Y. Tramblay ◽

R. Bouaicha ◽

L. Brocca ◽

W. Dorigo ◽

C. Bouvier ◽

...

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Initial Conditions ◽

Remote Sensing Data ◽

Data Availability ◽

Flood Events ◽

Catchment Scale ◽

Ungauged Catchments ◽

Sensing Data ◽

Event Based

Abstract. In northern Morocco are located most of the dams and reservoirs of the country, while this region is affected by severe rainfall events causing floods. To improve the management of the water regulation structures, there is a need to develop rainfall–runoff models to both maximize the storage capacity and reduce the risks caused by floods. In this study, a model is developed to reproduce the flood events for a 655 km2 catchment located upstream of the 6th largest dam in Morocco. Constrained by data availability, a standard event-based model combining a SCS-CN (Soil Conservation Service Curve Number) loss model and a Clark unit hydrograph was developed for hourly discharge simulation using 16 flood events that occurred between 1984 and 2008. The model was found satisfactory to reproduce the runoff and the temporal evolution of floods, even with limited rainfall data. Several antecedent wetness conditions estimators for the catchment were compared with the initial condition of the model. Theses estimators include an antecedent discharge index, an antecedent precipitation index and a continuous daily soil moisture accounting model (SMA), based on precipitation and evapotranspiration. The SMA model performed the best to estimate the initial conditions of the event-based hydrological model (R2 = 0.9). Its daily output has been compared with ASCAT and AMSR-E remote sensing data products, which were both able to reproduce with accuracy the daily simulated soil moisture dynamics at the catchment scale. This same approach could be implemented in other catchments of this region for operational purposes. The results of this study suggest that remote sensing data are potentially useful to estimate the soil moisture conditions in the case of ungauged catchments in Northern Africa.

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