Methodenentwicklung; Validierung; Mikrowellen-Fernerkundung; Radar; Radiometrie; Schnee; Vegetation; Boden; Strahlungstransport; Schneedichte; Bodenpermittivität; Bodenfeuchte; Vegetationsdichte; Vegetationsstruktur
Schwank Mike, Naderpour Reza, Mätzler Christian (2018), “Tau-Omega”- and Two-Stream Emission Models Used for Passive L-Band Retrievals: Application to Close-Range Measurements over a Forest, in Remote Sensing
, 10(12), 1868-1868.
Naderpour Reza, Schwank Mike (2018), Snow Wetness Retrieved from L-Band Radiometry, in Remote Sensing
, 10(3), 359-359.
Schwank Mike, Naderpour Reza (2018), Snow Density and Ground Permittivity Retrieved from L-Band Radiometry: Melting Effects, in Remote Sensing
, 10(3), 354-354.
Naderpour Reza, Schwank Mike, Mätzler Christian (2017), Davos-Laret Remote Sensing Field Laboratory: 2016/2017 Winter Season L-Band Measurements Data-Processing and Analysis, in Remote Sensing
, 9(11), 1185-1185.
Naderpour Reza, Schwank Mike, Matzler Christian, Lemmetyinen Juha, Steffen Konrad (2017), Snow Density and Ground Permittivity Retrieved From L-Band Radiometry: A Retrieval Sensitivity Analysis, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
, 10(7), 3148-3161.
Radiation, heat and mass fluxes through the terrestrial surface layer are affected by snow and vegetation. Knowing the states of these surface covers is particularly relevant with regard to the exchange of water between land and atmosphere. At the large scale, this exchange is a driving mechanism to be considered, e.g., in global climate change scenario development to quantify mitigation strategies. Accordingly, global information on snow and vegetation states are important to know. The further exploitation of remote microwave signals provided by emerging space-born active and passive sensors (radars and radiometers), bears the potential to obtain information on snow and vegetation that is complementary to corresponding existing data-products as provided e.g. from optical sensors. In this context the proposed project Active/Passive Microwave Remote Sensing in Application to ”Vegetation & Soil” and “Snow & Soil” (MicroVegSnow) will support the extended exploitation of active and passive microwave data measured over vegetated and snow covered areas. Due to the already existing infrastructure built up at the FZJ (Forschungszentrum Jülich GmbH, Germany) and the expertise in radiative transfer modelling, snow physics, hydrology, parameter estimation and inversion available in both host institutes (FZJ and the WSL (Swiss Federal Institute for Forest, Snow and Landscape Research, Switzerland)) MicroVegSnow is proposed as a joint project. The MicroVegSnow project includes the topic areas ”Vegetation & Soil” and “Snow & Soil”, which are handled by the FZJ and the WSL, respectively. The overall objective of the MicroVegSnow project is to explore the microwave radiative transfer that determines remote active and passive microwave signals of footprints comprising vegetation and snow. To this aim, the overarching research concept includes: i) tower-based active and passive microwave measurements over vegetated and snow-covered footprints accompanied by simultaneous in-situ measurements; ii) the development and the validation of radiative transfer forward models to simulate corresponding microwave signals; and iii) the development and the assessment of retrieval schemes needed to derive information on snow and vegetation states from remote microwave signals. The microwave remote sensing field campaigns i) associated with the topic area ”Vegetation & Soil” are planned to be conducted at the TERENO test-site Selhausen near Jülich during the growing periods 2015 and 2016. During the winters 2014/15 and 2015/2016 corresponding field campaigns i) will be performed at a test-site near Davos (WSL/SLF) in support of the topic area “Snow & Soil”.The research outcome of the MicroVegSnow project will increase our understanding of active and passive microwave remote sensing in application to vegetation, snow, and soil. This is the basis to optimally exploit available and future microwave remote sensing data measured over vegetated and snow covered terrains.