Analysis of the Urban Geometry’s Effects on Nocturnal Urban Heat Islands Using Remote Sensing and GIS (Case Study: Golestan town, District 22 of Tehran)

Oke’s model is one of the most successful models presented to simulate maximum nocturnal urban heat island’s intensity (UHI) based on the urban canyons’ aspect ratio parameter. The aspect ratio parameter is known as one of the indicators of urban geometry. Since this simulation requires various spatial and descriptive analyzes (especially topological analyzes), the use of geospatial information systems is inevitable. In this study, the efficiency of Oke’s model is evaluated using regression analysis and land surface temperature (LST) calculated from ASTER data and single-channel algorithm (SCA), and a local model is presented to simulate the maximum nocturnal urban heat island intensity of the area of study. The coefficient of determination and correlation calculated based on regression analysis are 0.74 and 0.86, respectively. These quantities show a relatively strong linear relationship between the urban geometry index and nocturnal urban heat island’s intensity and the significant effect of urban geometry on nocturnal urban heat island intensity. The root mean squared error (RMSE) and the mean absolute error (MAE) of the presented local model are ±0.80 and 0.67, respectively, showing the acceptable accuracy of the presented local model in simulation of UHI intensity. Two-variable regression analysis shows a greater effect of the height of buildings on UHI intensity’s changes compared to the width of the streets. The sign of the coefficients above shows this effect is increasing in terms of the height of the buildings and decreasing in terms of the width of the streets

Downscaling landsat land surface temperature over the urban area of Florence

A new downscaling algorithm for land surface temperature (LST) images retrieved from Landsat Thematic Mapper (TM) was developed over the city of Florence and the results assessed against a high-resolution aerial image. The Landsat TM thermal band has a spatial resolution of 120 m, resampled at 30 m by the US Geological Survey (USGS) agency, whilst the airborne ground spatial resolution was 1 m. Substantial differences between Landsat USGS and airborne thermal data were observed on a 30 m grid: therefore a new statistical downscaling method at 30 m was developed. The overall root mean square error with respect to aircraft data improved from 3.3 °C (USGS) to 3.0 °C with the new method, that also showed better results with respect to other regressive downscaling techniques frequently used in literature. Such improvements can be ascribed to the selection of independent variables capable of representing the heterogeneous urban landscape

Thermally enhanced spectral indices to discriminate burn severity in Mediterranean forest ecosystems

P. 1-8Fires are a problematic and recurrent issue in Mediterranean forest ecosystems. Accurate discrimination of burn severity level is fundamental for the rehabilitation planning of affected areas. Though fieldwork is still necessary for measuring post-fire burn severity, remote sensing based techniques are being widely used to predict it because of their computational simplicity and straightforward application. Among them, spectral indices classification (especially difference Normalized Burn Ratio–dNBR- based ones) may be considered the standard remote sensing based method to distinguish burn severity level. In this work we show how this methodology may be improved by using land surface temperature (LST) to enhance the standard spectral indices. We considered a large wildfire in August 2012 in North Western Spain. The Composite Burn Index (CBI) was measured in 111 field plots and grouped into three burn severity levels. Relationship between Landsat 7 Enhanced Thematic Mapper (ETM+) LST-enhanced spectral indices and CBI was evaluated by using the normalized distance between two burn severity levels and spectral dispersion graphs. Inclusion of LST in the spectral index equation resulted in higher discrimination between burn severity levels than standard spectral indices (0.90, 8.50, and 17.52 NIR-SWIR Temperature version 1 vs 0.60, 2.83, and 6.46 NBR). Our results demonstrate the potential of LST for improving burn severity discrimination and mapping. Future research, however, is needed to evaluate the performance of the proposed LST-enhanced spectral indices in other fire regimes, and forest ecosystems.S

Analisis Perubahan Distribusi Urban Heat Island (UHI) di Kota Surabaya Menggunakan Citra Satelit Landsat Multitemporal

Surabaya merupakan kota terbesar kedua di Indonesia setelah Jakarta, dimana jumlah penduduk kota Surabaya setiap tahunnya selalu mengalami kenaikan. Peningkatan populasi penduduk di wilayah perkotaan dapat mengubah pola ruang kawasan perkotaan. Pengunaan lahan akan bergeser dari keperluan pertanian menjadi keperluan tempat tinggal, kawasan bisini/industri dan aktivitas lainnya. Perubahan tutupan lahan ini akan berdampak pada kondisi iklim dan cuaca di kawasan perkotaan sehingga menyebabkan terjadinya fenomena Urban Heat Island (UHI). Pemantauan fenomena ini diperlukan di perkotaan yang mengalami perkembangan pesat, termasuk di Kota Surabaya. Pada penelitian ini akan dianalisis perubahan distribusi Urban Heat Island (UHI) di Kota Surabaya pada tahun 2002, 2014, dan 2019 menggunakan Citra Landsat 7 (ETM+) dan Citra Landsat 8 (OLI/TIRS). Langkah awal yang dilakukan berupa perhitungan Land Surface Temperature (LST) dengan metode Single-Channel Algorithm, kemudian dilakukan analisis distribusi UHI dengan metode Ambang Batas dan Hot Spot Analysis (Getis-Ord Gi*). Hasilnya didapatkan nilai suhu permukaan rata-rata Kota Surabaya untuk tahun 2002, 2014, dan 2019 secara berurutan sebesar 29,094°C; 26,889°C; dan 27,130°C. Uji korelasi Pearson Product Moment dilakukan antara LST dengan suhu lapangan, diperoleh hasi koefisien korelasi (Rxy) sebesar 0,449. Terakhir, dari peta distribusi UHI metode Ambang Batas, luas area yang terdampak UHI selalu mengalami penurunan dari tahun 2002 ke 2014, dan 2014 ke 2019 dengan luas penurunan masing-masing sebesar 0,760 km2 dan 7,995 km2. Hal yang sama juga terjadi untuk metode Hot Spot Analysis, dengan luas penurunan pada tahun 2002 ke 2014, dan 2014 ke 2019 sebesar 2,027 km2 dan 31,168 km2

The Impact of Spatial Form of Urban Architecture on the Urban Thermal Environment: A Case Study of the Zhongshan District, Dalian

The correlation of spatial variation in land surface temperature with building height and density in Zhongshan District, Dalian, China, is investigated over the period 2003-2013. We utilize remote sensing data and multisource land-use data, which we evaluate using a combination of a single-window algorithm and correlation analysis. The results show that: 1) during 2003-2013, the number of high surface temperature regions increased by 4339 grid cells (out of a total of 53 601), with most of the high-temperature grid cells distributed along Jiefang Road and Zhongnan Road in the northern part of Zhongshan District. Ninety-eight percent of grid cells had temperature ranges of 293-309 K in July 2003, 296-310 K in August 2003, 295-308 K in July 2008, 296-311 K in August 2008, 305-314 K in July 2013, and 303-318 K in August 2013; 2) during 2003-2008, the number of low-rise buildings increased by 140%, and the number of multistory buildings increased by 100%. During 2008-2013, the number of buildings in all height categories remained relatively unchanged, with the exception of an 11% decrease in the number of low-rise buildings; 3) surface temperature showed weak correlation with building height (0.314, 0.346, and 0.361 in 2003, 2008, and 2013, respectively) but moderate correlation with building density (0.511, 0.533, and 0.563, respectively)