Publication Date:
2022-08-17
Description:
Abstract
Description:
The dataset is composed of Hyspex (VNIR/SWIR) hyperspectral imagery acquired during airplane overflights on 01. Oktober, 2015 within the Demmin Research Area. The acquisition conditions were cloud free. The dataset includes two mosaics generated based on 9 HySpex flight lines. The dataset also includes Level 2A EnMAP-like imagery simulated using the end-to-end Simulation tool (EeteS). Additionally a soil database focussed on the soil organic carbon content (SOC) with geographic coordinates, texture and spectral information is included.
Description:
Methods
Description:
Nine flight stripes were acquired during an EnMAP GFZ/FUB flight campaign operated by the GFZ using the HySpex VNIR-1600 and HySpex SWIR 320m-e (“HySpex, Norsk Elektro Optikk,” 2015) imaging spectrometers over the DEMMIN test field on 01 October 2015 (10:07-11:01 local time). Over the nine flight stripes, three are located in the Western part of the area over the village of Borrentin and Nossendorf, and six in the Eastern part of the area over the villages of Alt-Tellin, Jarmen and Sassen covering mainly agricultural fields (figure 1). For this campaign the HySpex imaging system was mounted on the Cessna 207T aircraft of the “Freie Universität Berlin” (FUB). The HySpex hyperspectral imaging system is based on two separated push-broom hyperspectral cameras HySpex VNIR-1600 and HySpex SWIR 320m-e which cover the wavelength domain from 0.4-1.0 µm and 1.0-2.5 µm respectively, with a spectral resolution of 3.7 nm (VNIR-1600) and 6.0 nm (SWIR-320m-e). Both sensors were flown with a field of view expander which results in field of view of 33.2° for the VNIR and 26.4° for the SWIR. The position and attitude of the airplane were measured with an AEROcontrol-IId inertial measurement unit (IMU) with available data rates of 256 Hz in combination with a Novatel OEM4 - g2 GPS receiver. The HySpex sensors (VNIR, SWIR) and DGPS/IMU sensors were arranged on an active stabilization platform (SM2000 ).
The entire airborne campaign was conducted at a mean altitude of 2500m which results in a mean ground sampling distance (GSD) of 1.9 m for the VNIR and 3.8 m for the SWIR. After the preprocessing of the HySpex data (georectification, sensor co-registration, atmospheric correction, mosaicking) the hyperspectral data cube consists of a total of 408/390 bands resampled to 4m pixel resolution. The overflight encompassed an area of approximately 23000 ha.
Description:
Other
Description:
The Environmental Mapping and Analysis Program (EnMAP) is a German hyperspectral satellite mission that aims at monitoring and characterizing the Earth’s environment on a global scale. EnMAP serves to measure and model key dynamic processes of the Earth’s ecosystems by extract-ing geochemical, biochemical and biophysical parameters, which provide information on the status and evolution of various terrestrial and aquatic ecosystems. In the frame of the EnMAP preparatory phase, pre-flight campaigns including airborne and in-situ measurements in different environments and for several application fields are being conducted. The main purpose of these campaigns is to support the development of scientific applications for EnMAP. In addition, the acquired data are input in the EnMAP end-to-end simulation tool (EeteS) and are employed to test data pre-processing and calibration-validation methods. The campaign data are made freely available to the scientific community under a Creative Commons Attribution 4.0 International License. An overview of all available data is provided in in the EnMAP Flight Campaigns Metadata Portal (http://www.enmap.org/?q=flights).
Keywords:
Hyperspectral Imagery
;
Soil
;
Landuse
;
Agricultur
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agriculture 〉 agricultural method
;
Earth Remote Sensing Instruments 〉 Passive Remote Sensing 〉 Spectrometers/Radiometers 〉 Hyperspectral Spectrometers/Radiometers
;
EARTH SCIENCE 〉 AGRICULTURE 〉 SOILS 〉 SOIL CHEMISTRY
;
EARTH SCIENCE 〉 BIOSPHERE 〉 VEGETATION
;
land 〉 world 〉 Europe 〉 Western Europe
;
pedosphere 〉 soil
Type:
Dataset
,
Dataset
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