Thermal remote sensing of water under flooded vegetation: New observations of inundation patterns for the ‘Small’ Lake Chad

Leblanc, Marc; Lemoalle, Jacques; Bader, Jean‐Claude; Tweed, Sarah; Mofor, Linus

doi:10.1016/j.jhydrol.2011.04.023

Cited by 76 publications

(65 citation statements)

References 52 publications

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“…The only sources found providing significant observation-based time series of area for Lake Chad are [4,10]. Their results differ significantly.…”

Section: Approx Dates L Chad Area Change (Km 2 ) L Chad Area Changementioning

confidence: 77%

“…The wet season lasts from June to October, although due to the time lag of water flowing through the Chari and Logone River systems, the annual flooding occurs during the dry season [10]. The lake rises about 1-2 m during the annual flooding season [4] and provides livelihoods to fishermen who are most productive following the floods, to "recession farmers" who farm in the rich soils of the receding floodwaters, and to those who raise livestock [1].…”

Section: Lake Chad and Environmentmentioning

confidence: 99%

“…Grove, 1996 [9] 1960s-mid 1980s −22,500 −90% UNEP, 2006 [11] 1963-2001 −22,598 −99% Gao et al, 2011 [6] 1971-2011 N/A More than −90% Leblanc et al, 2011 [10] 1986-2001 (+) 3500 * (+) 33% * * difference between 1st data point (May 1986) and last data point (May 2001).…”

Section: Approx Dates L Chad Area Change (Km 2 ) L Chad Area Changementioning

confidence: 99%

“…Leblanc et al (2011) [10] used 5 km resolution Land Surface Temperature (LST) data from the Meteosat satellites operated by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). Using this data, Leblanc et al [10] developed a monthly record of the lake area from 1986 to 2001, differentiating water vs. non-water using a 2-cluster unsupervised classification process. Note that this lumps dry soil, wet soil, and dry vegetation classes into a single non-water class, and water and flooded vegetation into a single water class.…”

Section: Approx Dates L Chad Area Change (Km 2 ) L Chad Area Changementioning

confidence: 99%

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Lake Chad Total Surface Water Area as Derived from Land Surface Temperature and Radar Remote Sensing Data

et al. 2018

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Lake Chad, located in the middle of the African Sahel belt, underwent dramatic decreases in the 1970s and 1980s leaving less than ten percent of its 1960s surface water extent as open water. In this paper, we present an extended record (dry seasons 1988-2016) of the total surface water area of the lake (including both open water and flooded vegetation) derived using Land Surface Temperature (LST) data (dry seasons [2000][2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014][2015][2016] from the NASA Terra MODIS sensor and EUMETSAT Meteosat-based LST measurements (dry seasons 1988-2001) from an earlier study. We also examine the total surface water area for Lake Chad using radar data (dry seasons 2015-2016) from the ESA Sentinel-1a mission. For the limited number of radar data sets available to us (18 data sets), we find on average a close match between the estimates from these data and the corresponding estimates from LST, though we find spatial differences in the estimates using the two types of data. We use these spatial differences to adjust the record (dry seasons 2000-2016) from MODIS LST. Then we use the adjusted record to remove the bias of the existing LST record (dry seasons 1988-2001) derived from Meteosat measurements and combine the two records. From this composite, extended record, we plot the total surface water area of the lake for the dry seasons of 1988-1989 through 2016-2017. We find for the dry seasons of 1988-1989 to 2016-2017 that the maximum total surface water area of the lake was approximately 16,800 sq. km (February and May, 2000), the minimum total surface water area of the lake was approximately 6400 sq. km (November, 1990), and the average was approximately 12,700 sq. km. Further, we find the total surface water area of the lake to be highly variable during this period, with an average rate of increase of approximately 143 km 2 per year.

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“…The only sources found providing significant observation-based time series of area for Lake Chad are [4,10]. Their results differ significantly.…”

Section: Approx Dates L Chad Area Change (Km 2 ) L Chad Area Changementioning

confidence: 77%

Section: Lake Chad and Environmentmentioning

confidence: 99%

Section: Approx Dates L Chad Area Change (Km 2 ) L Chad Area Changementioning

confidence: 99%

Section: Approx Dates L Chad Area Change (Km 2 ) L Chad Area Changementioning

confidence: 99%

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Lake Chad Total Surface Water Area as Derived from Land Surface Temperature and Radar Remote Sensing Data

et al. 2018

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“…Meteosat II, GOES, GMS) may often be able to bypass clouds with their high temporal resolution allowing for the mapping of open water at ∼1 km spatial resolution. In the specific case of flooding events occurring in semi-arid and arid regions, such as the Pakistan flood studied here, water under flooded vegetation can also be mapped using composite data from the thermal bands of these weather satellites (Leblanc et al, 2003(Leblanc et al, , 2011. Amongst the most promising potential developments in remote sensing of surface water is the future Surface Water and Ocean Topography (SWOT) mission.…”

Section: A Complement To Other Mapping Techniquesmentioning

confidence: 99%

Use of ENVISAT ASAR Global Monitoring Mode to complement optical data in the mapping of rapid broad-scale flooding in Pakistan

O’Grady

Leblanc

Gillieson

2011

Hydrol. Earth Syst. Sci.

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Abstract. Envisat ASAR Global Monitoring Mode (GM) data are used to produce maps of the extent of the flooding in Pakistan which are made available to the rapid response effort within 24 h of acquisition. The high temporal frequency and independence of the data from cloud-free skies makes GM data a viable tool for mapping flood waters during those periods where optical satellite data are unavailable, which may be crucial to rapid response disaster planning, where thousands of lives are affected. Image differencing techniques are used, with pre-flood baseline image backscatter values being deducted from target values to eliminate regions with a permanent flood-like radar response due to volume scattering and attenuation, and to highlight the low response caused by specular reflection by open flood water. The effect of local incidence angle on the received signal is mitigated by ensuring that the deducted image is acquired from the same orbit track as the target image. Poor separability of the water class with land in areas beyond the river channels is tackled using a region-growing algorithm which seeks threshold-conformance from seed pixels at the center of the river channels. The resultant mapped extents are tested against MODIS SWIR data where available, with encouraging results.

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Variability of Lake Chad

Fougou¹,

Lemoalle²

2022

Congo Basin Hydrology, Climate, and Biogeochemistry

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Thermal remote sensing of water under flooded vegetation: New observations of inundation patterns for the ‘Small’ Lake Chad

Cited by 76 publications

References 52 publications

Lake Chad Total Surface Water Area as Derived from Land Surface Temperature and Radar Remote Sensing Data

Lake Chad Total Surface Water Area as Derived from Land Surface Temperature and Radar Remote Sensing Data

Use of ENVISAT ASAR Global Monitoring Mode to complement optical data in the mapping of rapid broad-scale flooding in Pakistan

Variability of Lake Chad

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