[HTML][HTML] A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations

S Chen, Y Yang, F Deng, Y Zhang, D Liu… - Atmospheric …, 2022 - amt.copernicus.org
Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect
has become a more concerning climatic and environmental issue. A high-spatial-resolution …

Monthly analysis of wetlands dynamics using remote sensing data

G Kaplan, U Avdan - ISPRS International Journal of Geo-Information, 2018 - mdpi.com
As wetlands are one of the world's most important ecosystems, their vulnerability
necessitates the constant monitoring and mapping of their changes. Satellite-based remote …

Assessment of badland susceptibility and its governing factors using a random forest approach. Application to the Upper Llobregat River Basin and Catalonia (Spain)

O Torra, M Hürlimann, C Puig-Polo… - Environmental …, 2023 - Elsevier
Badlands are considered hotspots of sediment production, contributing to large fractions of
the sediment budget of catchments and river basins. The erosion rates of these areas can …

A new approach for understanding urban microclimate by integrating complementary predictors at different scales in regression and machine learning models

L Alonso, F Renard - Remote Sensing, 2020 - mdpi.com
Climate change is a major contemporary phenomenon with multiple consequences. In
urban areas, it exacerbates the urban heat island phenomenon. It impacts the health of the …

Mapping and monitoring wetland dynamics using thermal, optical, and SAR remote sensing data

G Kaplan, ZY Avdan, U Avdan - … management: Assessing risk …, 2019 - books.google.com
Wetlands are transition zone where the flow of water, the cycling of carbon and nutrients,
and the energy to form a unique ecosystem are characterized by its hydrology, soils, and …

Influence of the mapping unit for regional landslide early warning systems: comparison between pixels and polygons in Catalonia (NE Spain)

RM Palau, M Hürlimann, M Berenguer… - Landslides, 2020 - Springer
This work presents a prototype landslide early warning system (LEWS) adapted to real-time
performance over the region of Catalonia (NE Spain). The system uses high-resolution …

Thermal unmixing based downscaling for fine resolution diurnal land surface temperature analysis

J Wang, O Schmitz, M Lu, D Karssenberg - ISPRS journal of …, 2020 - Elsevier
Due to the limitation in the availability of airborne imagery data that are high in both spatial
and temporal resolution, land surface temperature (LST) dense in both space and time can …

Estimation of daily and instantaneous near-surface air temperature from MODIS data using machine learning methods in the Jingjinji Area of China

C Wang, X Bi, Q Luan, Z Li - Remote Sensing, 2022 - mdpi.com
Meteorologically observed air temperature (T a) is limited due to low density and uneven
distribution that leads to uncertain accuracy. Therefore, remote sensing data have been …

A bayesian kriging regression method to estimate air temperature using remote sensing data

Z Zhang, Q Du - Remote Sensing, 2019 - mdpi.com
Surface air temperature (Ta) is an important physical quantity, usually measured at ground
weather station networks. Measured Ta data is inadequate to characterize the complex …

Comparison of linear, generalized additive models and machine learning algorithms for spatial climate interpolation

J Bonsoms, M Ninyerola - Theoretical and Applied Climatology, 2024 - Springer
Geospatial atmospheric data is the input variable of a wide range of hydrological and
ecological spatial models, many of which are oriented towards improving the socioeconomic …