Automated discrimination of upland and wetland using terrain derivatives

Hogg, Adam; Todd, Kent

doi:10.5589/m07-049

Cited by 34 publications

(28 citation statements)

References 20 publications

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“…A terrain derivative such as the topographic index, which is frequently used in simpler models that do not consider hydrological data (Chirico et al 2005), is therefore not included in the analysis. Evapotranspiration and relative humidity are highly correlated with (often calculated using) temperature and rainfall and therefore also excluded from the analysis (Creed et al 2003;Hogg and Todd 2007). The most important and independent topographic and climatic factors to predict the occurrence of wetlands in Rwanda are summarized in Table 1a.…”

Section: Data Preparationmentioning

confidence: 99%

“…Thus, slope and elevation appear to be consistent variables for the prediction of wetlands (Creed et al 2003;Hogg and Todd 2007).…”

Section: Functional Wetlands Surfaces Characterization Driversmentioning

confidence: 99%

“…The overall accuracy reaching 86.22 %-93 % with field-based dataset is a clear improvement compared to studies using topographic derivatives only. Hogg and Todd (2007) reached only 84 % of accuracy in characterizing wetlands in southern Ontario using a very high-resolution DEM (2 m 9 2 m pixel size) at detailed scales.…”

Section: Model Performance and Accuracymentioning

confidence: 99%

“…Digital elevation models (DEM) are readily accessible nowadays, and automated procedures exist to compute terrain derivatives (slope, curvature, topographic index, variance in slope, etc.) which can discern real depression features from spurious ones (Hogg and Todd 2007;Temme et al 2006;Yamazaki et al 2012).…”

Section: Introductionmentioning

confidence: 99%

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Regional climate sensitivity of wetland environments in Rwanda: the need for a location-specific approach

2015

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Wetlands are sustaining large communities of people in Rwanda where 10 % of its land surface consists of many local wetlands. Sustainable future management of these numerous wetlands requires a reliable inventory of their location and a dynamic quantitative characterization that allows assessment of their climate change sensitivity. The aim of this study was to assess the importance of climatic factors for determining wetland location at different regional scales. Wetland locations were analyzed and statistically modeled using their location factors with logistic regression. Wetland location probability was determined using topographic (elevation, slope), hydrological (contributing area) and climatic (temperature and rainfall) location factors. A wetland location probability map was made that demonstrated a calibration accuracy of 87.9 % correct at national level compared to an existing inventory, displaying even better fits at subnational level (reaching up to 98 % correct). A validation accuracy of 86.2 % was obtained using an independently collected dataset. A sensitivity analysis was applied to the threshold values used as cutoff value between wetland/non-wetland, demonstrating a robust performance. The developed models were used in a sensitivity scenario analysis to assess future wetland location probability to changes in temperature and rainfall. In particular, wetlands in the central regions of Rwanda demonstrate a high sensitivity to changes in temperature (1 % increase causes a net probable wetland area decline by 12.4 %) and rainfall (?1 % causes a net increase by 1.6 %). This potentially significant impact on wetland number and location probability indicates that climate-sensitive future planning of wetland use is required in Rwanda.

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Section: Data Preparationmentioning

confidence: 99%

“…Thus, slope and elevation appear to be consistent variables for the prediction of wetlands (Creed et al 2003;Hogg and Todd 2007).…”

Section: Functional Wetlands Surfaces Characterization Driversmentioning

confidence: 99%

Section: Model Performance and Accuracymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Regional climate sensitivity of wetland environments in Rwanda: the need for a location-specific approach

2015

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“…Automatic drainage extraction methods generate good results when associated with Geographic Information Systems (GIS) (Fernández, 2011;Hogg and Todd, 2007;Ribeiro and Ferreira, 2014). However, on mild slopes and diffuse flow areas, the combination of these methods might present less realistic representations (Fuller et al, 2006;Oksanena and Sarjakoskia, 2005).…”

Section: Introductionmentioning

confidence: 99%

Watershed Spatial Discretization for the Analysis of Land Use Change in Coastal Regions

2017

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Abstract:In this study, we present a methodology to discretize a non-assessed basin based on terrain analysis using the SRTM digital elevation model (DEM) and a high resolution surface model (DSM) with a drainage network semi-automatic extraction process. The Juqueriquerê River Basin was used for the case study, which has the most representative non-urbanized plains of the northern coastline of São Paulo State, Brazil. The low-lying region is featured by elevations close to the sea level, mild slopes, and shallow water tables. It is also influenced by tidal variation and orographic rains. Therefore, frequent flooding occurs, even in vegetated areas. Two conflicting land use scenarios, proposed by the City Master Plan (CMP) of Caraguatatuba and the Ecological-Economical Zoning (EEZ), were compared to analyze the flood vulnerability increase and geotechnical risk caused by the urbanization process. The drainage extraction techniques showed better results on high resolution DSM for low-lying regions than the SRTM DEM and determined with accuracy the locations of flood potentiality in the plains. The watershed spatial discretization allowed us to show the effects of the two different land use approaches, considering the flood vulnerability and geotechnical risk of each sub-basin.Keywords: Digital terrain models; Hydro processing; Urbanization; Flood vulnerability; Land use. Resumo:Neste estudo, apresentamos uma metodologia para discretizar uma bacia não monitorada baseada na análise do terreno, usando o modelo digital de elevação (DEM) SRTM e o digital de superfície (DSM) de alta resolução em um processo de extração de redes de drenagem semiautomático. A bacia do rio Juqueriquerê foi usada como estudo de caso, que possui as planícies não urbanizadas mais representativas do litoral norte do estado de São Paulo, Brasil. A região de baixa altitude é caracterizada por elevações próximas ao nível do mar, declividades suaves e lençóis freáticos rasos. A região é também influenciada pela variação das marés e chuvas orográficas. Por isso, inundações freqüentes acontecem, mesmo em áreas vegetadas. Dois cenários conflitantes no uso de solo, propostos pelo Plano Diretor Municipal de Caraguatatuba

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Geo-Information Tools in Implementing Nature-Based Solutions from High Altitude Wetlands: From Mapping to Decision-Making Support for Disaster Risk Reduction

Srivastava

Agarwal

2020

Nature-Based Solutions for Resilient Ecosystems and Societies

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Automated discrimination of upland and wetland using terrain derivatives

Cited by 34 publications

References 20 publications

Regional climate sensitivity of wetland environments in Rwanda: the need for a location-specific approach

Regional climate sensitivity of wetland environments in Rwanda: the need for a location-specific approach

Watershed Spatial Discretization for the Analysis of Land Use Change in Coastal Regions

Geo-Information Tools in Implementing Nature-Based Solutions from High Altitude Wetlands: From Mapping to Decision-Making Support for Disaster Risk Reduction

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