PyLUSAT: An open-source Python toolkit for GIS-based land use suitability analysis

Chen, Changjie; Judge, Jasmeet; Hulse, David

doi:10.1016/j.envsoft.2022.105362

Cited by 10 publications

(5 citation statements)

References 48 publications

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“…The built environment was assessed within quarter-mile buffers of both the residential locations and trip destinations. We calculated built-environment variables in five dimensions ("5Ds") using Geographic Information System tools (Chen et al, 2022). Household density represents the density dimension.…”

Section: Built Environment Factors Tour Attributes and Socioeconomic ...mentioning

confidence: 99%

Non-linear effects of built environment factors on mode choice: A tour-based analysis

Fang,

Yan,

Tao

et al. 2024

JTLU

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Understanding the connections between the built environment and travel mode choice is a major research topic in transportation. However, existing studies usually examine the relationship through trip-based analyses rather than tour-based approaches. A tour consists of multiple trips that originate and end at the same place, which is increasingly considered the more appropriate analysis unit for travel behaviors. Applying a tour-based approach, this study employs random forest to investigate the non-linear impacts of built environment factors and tour attributes on different mode combinations of a tour. We find that tour attributes and connectivity-related variables (e.g., block size and intersection density) have a strong association with the use of active travel modes when their values are within a certain threshold. In addition, capturing mode change behaviors offers more nuanced understanding of how various built environment variables shape people’s decision to combine modes in a tour.

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Section: Built Environment Factors Tour Attributes and Socioeconomic ...mentioning

confidence: 99%

Non-linear effects of built environment factors on mode choice: A tour-based analysis

Fang,

Yan,

Tao

et al. 2024

JTLU

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“…A collection of Python libraries [54,55] has recently built up with EarthPy that is specially tailored for geo-information processing [56]. Aside from general applications in diverse branches of data science and ML [57][58][59][60], Python can be applied for RS data processing using its spatial libraries [61].…”

Section: Related Workmentioning

confidence: 99%

Satellite Image Processing by Python and R Using Landsat 9 OLI/TIRS and SRTM DEM Data on Côte d’Ivoire, West Africa

Lemenkova

Debeir

2022

J. Imaging

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In this paper, we propose an advanced scripting approach using Python and R for satellite image processing and modelling terrain in Côte d’Ivoire, West Africa. Data include Landsat 9 OLI/TIRS C2 L1 and the SRTM digital elevation model (DEM). The EarthPy library of Python and `raster’ and `terra’ packages of R are used as tools for data processing. The methodology includes computing vegetation indices to derive information on vegetation coverage and terrain modelling. Four vegetation indices were computed and visualised using R: the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index 2 (EVI2), Soil-Adjusted Vegetation Index (SAVI) and Atmospherically Resistant Vegetation Index 2 (ARVI2). The SAVI index is demonstrated to be more suitable and better adjusted to the vegetation analysis, which is beneficial for agricultural monitoring in Côte d’Ivoire. The terrain analysis is performed using Python and includes slope, aspect, hillshade and relief modelling with changed parameters for the sun azimuth and angle. The vegetation pattern in Côte d’Ivoire is heterogeneous, which reflects the complexity of the terrain structure. Therefore, the terrain and vegetation data modelling is aimed at the analysis of the relationship between the regional topography and environmental setting in the study area. The upscaled mapping is performed as regional environmental analysis of the Yamoussoukro surroundings and local topographic modelling of the Kossou Lake. The algorithms of the data processing include image resampling, band composition, statistical analysis and map algebra used for calculation of the vegetation indices in Côte d’Ivoire. This study demonstrates the effective application of the advanced programming algorithms in Python and R for satellite image processing.

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“…• Deep chestnut soils: These soils have developed in areas with little rain, as the vegetation cover is in the form of short weeds and is rich in calcareous materials, minerals and calcareous materials, and occupied an area (141.18 km2) and a percentage (53.8%) of the total area (Chen et al, 2022). • Cracked rocky soil: They are cracked rugged, shallow, shallow rocky soils that are newly formed, with a dark brown color that tends to several changes in the sloping areas and increases slightly at the feet of the mountainous slopes, forming an area (65.13 km2) and a percentage (24.6%) of the total area (Benedek & Ivan, 2018).…”

Section: Characteristics Of Soil: (Characteristics)mentioning

confidence: 99%

Correlational relationships between morphometric and hydrological variables of the norther mountion Bekhir Basins, a comparative study (SCS-CN) using modern technologies

Al-Fatlawy¹,

Zamili²

2022

ijhs

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The research aims to reveal the analysis of the hydrological characteristics of the northern mountain Bekhair Basin within the Sulaymaniyah belt, and its area is estimated (264.22 km2). Its rocky and sedimentary formations date back to the triple and quadruple periods of sandstone, limestone and gypsum rocks located astronomically between two latitudes. (37o01’00”-37o08’00”) north And longitudes (42o20’00”-42o50’00”) east, while administratively in Dohuk Governorate it extends from Dohuk to Zakho, along the village of Fishkhabur at the Iraqi-Turkish border, and lies within the semi-arid climate that is characterized by high temperatures and its average during the month of July (34, 33.7) centigrade respectively for the two stations of Dohuk - Zakho and the annual rainfall amounted to (512.7, 559) mm respectively The hydrological characteristics of the basins were studied showing the possibility of generating water flow in the study area, in addition to the possibility of constructing additional dams to store water and benefit from it for the daily uses of shepherds and drinking Animals in the Chided period.

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PyLUSAT: An open-source Python toolkit for GIS-based land use suitability analysis

Cited by 10 publications

References 48 publications

Non-linear effects of built environment factors on mode choice: A tour-based analysis

Non-linear effects of built environment factors on mode choice: A tour-based analysis

Satellite Image Processing by Python and R Using Landsat 9 OLI/TIRS and SRTM DEM Data on Côte d’Ivoire, West Africa

Correlational relationships between morphometric and hydrological variables of the norther mountion Bekhir Basins, a comparative study (SCS-CN) using modern technologies

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