Assimilating ASCAT normalized backscatter and slope into the land surface model ISBA-A-gs using a Deep Neural Network as the observation operator: Case studies at ISMN stations in western Europe

Building Resilience: Analyzing Beira’s Drainage Network and Flood Management: The impact of failure mechanisms on flooding in informal settlements

Paving the way for Green: A study on the effect of residential gardens in The Hague on local climate

Novel use of advanced scatterometer (ASCAT) for forest fire monitoring

Geometrical Mangrove Models: Quantifying frontal surface area distribution for Avicennia marina vegetation: an important parameter for estimating wave attenuation

Procedural Modelling of Tree Growth Using Multi-temporal Point Clouds

The New Dutch Waterline: The (Hi)story of the Landscape

Sensitivity Assessment of Sentinel-1 SAR Closure Phase to Vegetation and Soil Moisture Dynamics: A Case Study for Regions in Southern France

Towards constraining soil and vegetation dynamics in land surface models: Modeling ASCAT backscatter incidence-angle dependence with a Deep Neural Network

Bio Cyber Physical Architecture: Use of Computational methods in Ecological buildings and Landscapes

Preferential hydrodynamic, geomorphological, and vegetation ecology conditions for turtle nesting: Al Wajh Bank, Saudi Arabia

The impact of extreme events on mudflats - The Guyana case

Towards including dynamic vegetation parameters in the EUMETSAT H SAF ASCAT soil moisture products

An Approach to Map Visibility in The Built Environment from Airborne LiDAR Point Clouds

Spectral Wave Dissipation by Vegetation: A new frequency distributed dissipation model in SWAN

Revitalizing Philipsburg: Towards a sustainable, densified, and vibrant neighbourhood.

Influence of Climate and Vegetation on Root Zone Storage Capacity: A case study in Australia

Automatic construction of 3D tree models in multiple levels of detail from airborne LiDAR data

Satellite-Based Analysis of Vegetation Trends in Europe

Predicting rainfall induced slope stability using Random Forest regression and synthetic data