A new ArcGIS toolset for automated mapping of land surface temperature with the use of LANDSAT satellite data

Walawender, Jakub P.; Hajto, Monika J.; Iwaniuk, P.

doi:10.1109/igarss.2012.6350405

Cited by 37 publications

(34 citation statements)

References 15 publications

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“…The two Landsat (OLI and ETM+) scenes were obtained in digital number (DN), and were converted to reflectance values. All Landsat ETM+ images acquired from 2003 have scan-line errors (striping problem) and were corrected for scanline errors using the Landsat toolbox in ArcGIS 10.2 before being converted to reflectance (Walawender et al 2012). The Landsat ETM+ bands were then converted to Top-Of-Atmosphere spectral radiances and then to at-sensor reflectance using the reflectance rescaling coefficients provided in the image's metadata files.…”

Section: Field Data Collectionmentioning

confidence: 99%

Developing detailed age-specific thematic maps for coffee (Coffea arabica L.) in heterogeneous agricultural landscapes using random forests applied on Landsat 8 multispectral sensor

Chemura

Mutanga

2016

Geocarto International

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Coffee is a commodity of international trade significance, and its value chain can benefit from age-specific thematic maps. This study aimed to assess the potential of Landsat 8 OLI to develop these maps. Using field-collected samples with the random forest classifier, splitting coffee into three age classes (Scheme A) was compared with running the classification with one compound coffee class (Scheme B). Higher overall classification accuracy was obtained in Scheme B (90.3% for OLI and 86.8% for ETM+) than in Scheme A (86.2% for OLI and 81.0% for ETM+). The NIR band of OLI was the most important band in intra-class discrimination of coffee. Landsat 8 OLI mapped area closely matched farm records (R 2 = 0.88) compared to that of Landsat 7 ETM+ (R 2 = 0.78). It was concluded that Landsat 8 OLI data can be used to produce age-specific thematic maps in coffee production areas although disaggregating coffee classes reduces overall accuracy.

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Section: Field Data Collectionmentioning

confidence: 99%

Developing detailed age-specific thematic maps for coffee (Coffea arabica L.) in heterogeneous agricultural landscapes using random forests applied on Landsat 8 multispectral sensor

Chemura

Mutanga

2016

Geocarto International

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“…Landsat-8 is an optical sensor with a spatial resolution of 15 m (band 8), 30 m (band 1-7 and 9) and 100 m (band 10-11, TIRS). Surface temperature grids in°C were generated in three steps in ArcMap (version 10.1, ESRI, Redlands, USA) using a toolbox for automated mapping (Walawender et al 2012):…”

Section: Remote Sensingmentioning

confidence: 99%

A combined-method approach to trace submarine groundwater discharge from a coastal karst aquifer in Ireland

Schuler

Stoeckl

Schnegg³

et al. 2019

Hydrogeol J

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Knowledge about the hydraulic connections between submarine groundwater discharge (SGD) and its terrestrial coastal catchment is relevant with regard to the management of marine and coastal waters in karst areas. This study applies different methods and monitoring approaches to trace SGD between the Burren Limestone Plateau and Galway Bay in western Ireland, via an excavated sinkhole shaft and deep conduit. Areas of potential SGD were first delineated based on sea surface temperature anomalies using Landsat satellite images. Two fluorescent dyes and solid wood chips were then used as tracers. Solid wood chips were tested as potential means to circumvent the problem of high dispersion in the sea, impacting on the fluorescent dyes to yield readings below the detection limits. Sampling was conducted at 10 different terrestrial locations and in the sea at Galway Bay. Offshore sampling was conducted in transects over a period of four successive days onboard of a vessel using an automated field fluorometer and a conductivity-temperature-depth sensor. No wood chips were recovered in the sea but both fluorescent dyes were successfully sampled. The estimated travel times are in the order of 100 to 354 m/h, and localised tracer readings correlate well in space and time with low conductivity readings. By confirming hydraulic connections between the two karst features and Galway Bay, the study substantiates the hypothesised importance of Variscan veins with regard to regional groundwater flow in the region.

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“…For each city, we selected a Landsat image of a summertime cloud-free day, and derived the LST in the geospatial computing environment of Google Earth Engine (Gorelick et al, 2017) using the methodology described in Walawender et al (2012) (Walawender et al, 2012). A novel aspect of our methodology is the clustering technique used to characterize the LST.…”

Section: A Preprint -September 9 2019mentioning

confidence: 99%

Paradoxical impact of sprawling intra-Urban Heat Islets: Reducing mean surface temperatures while enhancing local extremes

Shreevastava¹,

Bhalachandran²,

McGrath³

et al. 2019

Preprint

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Cities are at the forefront of climate change impacts and face a growing burden of adaptation to ensuing natural hazards. Extreme heat is a particularly challenging hazard as persistent heatwaves are locally exacerbated by the Urban Heat Island (UHI) effect. As a result, there is an increasing scientific interest in the influence of diverse urban morphologies on UHI. However, as the temperatures within cities are highly spatially heterogeneous, bulk quantification metrics such as UHI Intensity may hamper understanding. Here, we use remotely sensed Land Surface Temperature (LST) data for 78 diverse cities to develop a novel multi-scale framework of quantifying spatial heterogeneity in the Surface UHI. We identify heat clusters emerging within the SUHI using percentile-based thermal thresholds and refer to them collectively as \textit{intra-Urban Heat Islets}. We first develop a Lacunarity based metric ($\Lambda_{score}$) to quantify the spatial organization of heat islets at various degrees of sprawl and densification. Using probabilistic models, we condense the size, spacing, and intensity information about heterogeneous clusters into distributions that can be described using single scaling exponents. This allows for a seamless comparison of the heat islet characteristics across cities at varying spatial scales. From the size distribution analysis, we observe the emergence of two distinct classes wherein the dense cities (positive $\Lambda_{score}$) follow a Pareto size distribution, whereas the sprawling cities (negative $\Lambda_{score}$) show an exponential tempering of Pareto tail. This indicates a significantly reduced probability of encountering large heat islets for sprawling cities. Contrastingly, however, Heat Islet Intensity modeled as exponential distributions reveal that a sprawling configuration is favorable for reducing the mean temperature of a city. However, for the same mean SUHI intensity, it also results in higher local thermal extremes. This poses a paradox for urban designers in adopting expansion versus densification as a growth trajectory to mitigate the UHI.

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A new ArcGIS toolset for automated mapping of land surface temperature with the use of LANDSAT satellite data

Cited by 37 publications

References 15 publications

Developing detailed age-specific thematic maps for coffee (Coffea arabica L.) in heterogeneous agricultural landscapes using random forests applied on Landsat 8 multispectral sensor

Developing detailed age-specific thematic maps for coffee (Coffea arabica L.) in heterogeneous agricultural landscapes using random forests applied on Landsat 8 multispectral sensor

A combined-method approach to trace submarine groundwater discharge from a coastal karst aquifer in Ireland

Paradoxical impact of sprawling intra-Urban Heat Islets: Reducing mean surface temperatures while enhancing local extremes

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