Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011

Tulbure, Mirela G.; Broich, Mark

doi:10.1016/j.isprsjprs.2013.01.010

Cited by 169 publications

(109 citation statements)

References 35 publications

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“…Unsupervised classification approaches have been the most common technique in the past for mapping wetlands (Ozesmi and Bauer, 2002). Of the many supervised classification methods available, maximum likelihood has been used most frequently (Mather, 1985;Ozesmi and Bauer, 2002), however classification trees have become increasingly popular, and typically produce superior results (Baker et al, 2006;Breiman, 2001;Friedl and Brodley, 1997;Tulbure and Broich, 2013). Thresholds can also be used for land cover mapping, with an advantage of lower overall investment for the user; once developed, a classification can be generated virtually instantaneously (Chuvieco, 2016;Friedl and Brodley, 1997).…”

Section: Introductionmentioning

confidence: 99%

Three decades of Landsat-derived spring surface water dynamics in an agricultural wetland mosaic; Implications for migratory shorebirds

Schaffer‐Smith

Swenson

Barbaree

et al. 2017

Remote Sensing of Environment

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Satellite measurements of surface water offer promise for understanding wetland habitat availability at broad spatial and temporal scales; reliable habitat is crucial for the persistence of migratory shorebirds that depend on wetland networks. We analyzed water extent dynamics within wetland habitats at a globally important shorebird stopover site for a 1983-2015 Landsat time series, and evaluated the effect of climate on water extent. A range of methods can detect open water from imagery, including supervised classification approaches and thresholds for spectral bands and indices. Thresholds provide a time advantage; however, there is no universally superior index, nor single best threshold for all instances. We used random forest to model the presence or absence of water from >6200 reference pixels, and derived an optimal water probability threshold for our study area using receiver operating characteristic curves. An optimized mid-infrared (1.5-1.7 μm) threshold identified open water in the Sacramento Valley of California at 30-m resolution with an average of 90% producer's accuracy, comparable to approaches that require more intensive user input. SLC-off Landsat 7 imagery was integrated by applying a customized interpolation that mapped water in missing data gaps with 99% user's accuracy. On average we detected open water on ~26000 ha (~3% of the study area) in early April at the peak of shorebird migration, while water extent increased five-fold after the migration rush. Over the last three decades, late March water extent declined by ~1300 ha per year, primarily due to changes in the extent and timing of agricultural flood-irrigation. Water within shorebird habitats was significantly associated with an index of water availability at the peak of migration. Our approach can be used to optimize thresholds for time series analysis and near-real-time mapping in other regions, and requires only marginally more time than generating a confusion matrix.

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Section: Introductionmentioning

confidence: 99%

Three decades of Landsat-derived spring surface water dynamics in an agricultural wetland mosaic; Implications for migratory shorebirds

Schaffer‐Smith

Swenson

Barbaree

et al. 2017

Remote Sensing of Environment

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“…[13,25], we converted digital numbers (DN) to Top of Atmosphere (TOA) reflectance, according to previous research [29]. Bands 1-5 and 7 from the TM/ETM+, and bands 2-7 from the OLI, were processed.…”

Section: Collection Of Feature Variablesmentioning

confidence: 99%

“…Some comparative analyses between these water indices have been conducted [23,24], but the best water indices cannot be determined. The other method is classification based on a combination of spectral bands and other variables (e.g., water indices, shape features) [25]. These classification methods include Support Vector Machines (SVM), Maximum Likelihood (ML) and Decision Tree (DT), et al [26,27].…”

Section: Introductionmentioning

confidence: 99%

“…But, the performance of Random Forest (RF), an improved implementation of DT, is superior to a traditional DT [26,27]. Therefore, some studies employed the RF to classify the continuous remote images [13,25,28]. For example, Tulbure et al adopted RF to produce continuous surface water time series at a subcontinental scale in an Australian semi-arid region, the Murray-Darling Basin [13].…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal Change of Lake Water Extent in Wuhan Urban Agglomeration Based on Landsat Images from 1987 to 2015

et al. 2017

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Abstract:Urban lakes play an important role in urban development and environmental protection for the Wuhan urban agglomeration. Under the impacts of urbanization and climate change, understanding urban lake-water extent dynamics is significant. However, few studies on the lake-water extent changes for the Wuhan urban agglomeration exist. This research employed 1375 seasonally continuous Landsat TM/ETM+/OLI data scenes to evaluate the lake-water extent changes from 1987 to 2015. The random forest model was used to extract water bodies based on eleven feature variables, including six remote-sensing spectral bands and five spectral indices. An accuracy assessment yielded a mean classification accuracy of 93.11%, with a standard deviation of 2.26%. The calculated results revealed the following: (1) The average maximum lake-water area of the Wuhan urban agglomeration was 2262.17 km 2 from 1987 to 2002, and it decreased to 2020.78 km 2 from 2005 to 2015, with a loss of 241.39 km 2 (10.67%). (2) The lake-water areas of loss of Wuhan, Huanggang, Xianning, and Xiaogan cities, were 114.83 km 2 , 44.40 km 2 , 45.39 km 2 , and 31.18 km 2 , respectively, with percentages of loss of 14.30%, 11.83%, 13.16%, and 23.05%, respectively. (3) The lake-water areas in the Wuhan urban agglomeration were 226.29 km 2 , 322.71 km 2 , 460.35 km 2 , 400.79 km 2 , 535.51 km 2 , and 635.42 km 2 under water inundation frequencies of 5%-10%, 10%-20%, 20%-40%, 40%-60%, 60%-80%, and 80%-100%, respectively. The Wuhan urban agglomeration was approved as the pilot area for national comprehensive reform, for promoting resource-saving and environmentally friendly developments. This study could be used as guidance for lake protection and water resource management.

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“…Some examples are the Shuttle Radar Topography Mission (SRTM) applied in the Three Gorges reservoir in China (WANG et al, 2005), optical sensors such as Landsat (COLLISCHONN;CLARKE, 2016;RAN;LU, 2012) and MODIS (GAO;BIRKETT;LETTENMAIER, 2012;OVAKOGLOU et al, 2016). The spatiotemporal monitoring of surface water bodies is also possible using remote sensors as the applications in wetlands (TULBURE;BROICH, 2013), in large reservoirs around the globe (GAO; BIRKETT; LETTENMAIER, 2012), nearshore bathymetry (PACHECO et al, 2015) and near real-time monitoring in Africa (PEKEL, et al, 2014). In the case of optical sensors, the volume can be obtained by multiplication of the inundated surface area (estimated from the image) by the depth determined with limnimetric stations, radar altimetry or GPS.…”

Section: Introductionmentioning

confidence: 99%

Characterization of reservoirs for water supply in Northeast Brazil using high resolution remote sensing

Nascimento¹,

Neto

2017

RBRH

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This paper reports the application of information acquired by aerial survey to characterize water supply reservoirs in the Pajeú River Basin (Pernambuco State/Brazil). The survey was carried out with digital cameras of high spatial resolution and laser relief profiling (LiDAR technology). Two areas were selected to apply the remote sensing products. Small reservoirs in the Quixaba Creek Basin were identified based on their topographic characteristics. Given that the small reservoirs are "depressions" in the terrain, they can be "filled", resulting in a new Digital Terrain Model (DTM). The difference between the filled DTM and the original DTM makes it possible to identify the reservoirs. A summary of the results is: 61 reservoirs were correctly detected; 18 reservoirs were not detected; 13 reservoirs were detected erroneously. In another application, the storage capacity of the reservoirs belonging to the hydrosystems of Pajeú River Basin was estimated. The storage in these reservoirs and maximum surface area were estimated using DTM and geoprocessing tools. From the total of 31 reservoirs evaluated, eight were completely empty at the time of the LiDAR data collection. The official registers reported 83.83 million m 3 for the storage capacity of these eight reservoirs, whereas our applications estimated the value at 70.23 million m 3 . This difference is explained by the loss of volume in the reservoirs due to the process of sediment transport.Keywords: LiDAR; Semiarid; Water resources; Storage capacity. RESUMOEste artigo apresenta a aplicação de produtos adquiridos por levantamento aéreo para caracterização de reservatórios de abastecimento de água na Bacia do Rio Pajeú (Pernambuco/Brasil). O levantamento foi feito com câmeras digitais de alta resolução espacial e perfilamento de relevo a laser (tecnologia LiDAR). Foram selecionadas duas áreas para aplicação dos produtos de sensoriamento remoto. Pequenos reservatórios na Bacia do Riacho Quixaba foram identificados com base em suas características topográficas. Considerando que os pequenos reservatórios são "depressões" no terreno, eles podem ser "preenchidos" resultando em um novo MDT. A diferença entre o MDT preenchido e o MDT original torna possível a identificação dos reservatórios. O resumo dos resultados é: 61 reservatórios foram corretamente detectados; 18 reservatórios não foram detectados; 13 reservatórios foram detectados erroneamente. Em outra aplicação, foi estimada a capacidade de armazenamento dos reservatórios pertencentes aos hidrossistemas da Bacia do Rio Pajeú. O armazenamento nos reservatórios e a área superficial máxima foram estimados utilizando o MDT e ferramentas de geoprocessamento.

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Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011

Cited by 169 publications

References 35 publications

Three decades of Landsat-derived spring surface water dynamics in an agricultural wetland mosaic; Implications for migratory shorebirds

Three decades of Landsat-derived spring surface water dynamics in an agricultural wetland mosaic; Implications for migratory shorebirds

Spatio-Temporal Change of Lake Water Extent in Wuhan Urban Agglomeration Based on Landsat Images from 1987 to 2015

Characterization of reservoirs for water supply in Northeast Brazil using high resolution remote sensing

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