Abstract
How to obtain the “truth” of land surface parameter as reference value to validate the remote sensing retrieved parameter in heterogeneous scene and coarse-resolution pixel is one of the most challenging topics in environmental studies. In this paper, a distributed sensor network system named CPP-WSN was established to capture the spatial and temporal variation of land surface parameters at coarse-resolution satellite pixel scale around the Huailai Remote Sensing Station, which locates in the North China Plain. The system consists of three subnetworks that are RadNet, SoilNet, and VegeNet. Time series observations of typical land surface parameters, including UVR, PAR, SWR, LWR, albedo, and land surface temperature (LST) from RadNet, multilayer soil moisture and soil temperature from SoilNet, and fraction of vegetation cover (FVC), clumping index (CI), and leaf area index (LAI) from VegeNet, have been obtained and shared on the web. Compared with traditional single-point measurement, the “true” reference value of coarse pixel is obtained by averaging or representativeness-weighted averaging the multipoint measurements acquired using the sensor network. The preliminary applications, which validate several remote sensing products with CPP-WSN data, demonstrate that a high quality ground “truth” dataset has been available for remote sensing as well as other applications.
Highlights
With the increase of datasets from coarse-resolution remote sensing satellites, researchers have developed many quantitative products of land surface parameters and have been concerned with the need to quantify the accuracy of their application [1, 2]
We explore the establishment of the wireless sensor networks which monitor the heterogeneity of coarse spatial resolution pixel, with consideration of different categories of land surface parameters
This paper firstly presents the China validation network and Huailai remote sensing station where the CPP-Wireless sensor network (WSN) lies
Summary
With the increase of datasets from coarse-resolution remote sensing satellites, researchers have developed many quantitative products of land surface parameters and have been concerned with the need to quantify the accuracy of their application [1, 2]. The mismatch between point observation and pixel observation, in other words, the scale effect, becomes the main challenge for the validation of remote sensing products in coarse resolution. Automation, and relatively low cost to synchronously acquire data in multiple sites, the WSN is recently adopted in validation/calibration of remote sensing products [15,16,17] For this purpose, it is desirable that each node could contain multiple sensors to measure different kinds of parameters. We explore the establishment of the wireless sensor networks which monitor the heterogeneity of coarse spatial resolution pixel, with consideration of different categories of land surface parameters (hereafter referred to as CPP-WSN). The validations of a variety of remote sensing products are introduced as preliminary applications of the CPP-WSN
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