Quantitative Remote Sensing of Land Surface Variables: Progress and Perspective

Abstract

The land is of particular importance to the human being, not only because it is our, as well as terrestrial biomes’, habitat, but the land surface also plays a unique role in the Earth system. For example, it regulates the climate through exchange of matter, energy, and momentum with the atmosphere [1]. Data on the status and dynamics of the land surface variables are essential for understanding the land surface processes and entangling interactions between the land and other Earth system components. Since the emergence of remote sensing, the land surface is among its key study domains. The quantitative remote sensing system does not directly measure land surface parameters of interest. Instead, the signature remote sensors receive is electromagnetic radiation reflected, scattered, and emitted from both the surface and the atmosphere. The inversion algorithm is needed to obtain land surface parameters from remotely sensed data. It is not a trivia task to reliably retrieve land surface parameters since the remote sensing signature is a function of not only the variable of interest but also many other atmosphere and surface characteristics. Multifaceted aspects of the remote sensing data, such as the temporal, spectral, spatial, polarized information, as well as ancillary and prior knowledge, are typically used in a synthetic way to improve the quality of land parameter retrievals [2]. Numerous parameters regarding the land surface properties can now be estimated with the help of remote sensing, to name a few, surface cover type, snow cover and amount, surface altitude, surface radiative fluxes, biophysical parameters, biochemical variables, vegetation structure, and many other variables. With the maturity of the retrieval algorithms, many products of land surface variables have been generated from remotely sensed data by various agencies. For example, the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) land team produces 16 different products of land parameters [3]. The Global Land Surface Satellite (GLASS) Product suite includes 12 land variables [4]. The Satellite Application Facility on Climate Monitoring (CM SAF) develops dozens of real-time operational products and long-term climate data records of surface radiation, energy, and water fluxes [5]. The increased availability and improved quality of remote sensing land products have promoted their applications in various modeling and analytical studies and advanced our knowledge on global environmental changes as a unique source of observational evidence from the space-based perspective. With the availability of more advanced remote sensing data from various types of instruments with different spectral characteristics and temporal and spatial resolutions, the field of quantitative land remote sensing is advancing at an unprecedented rate. Considerable effort has been devoted to the study of land remote sensing theory and methodology; development of retrieval algorithms to estimate land surface variables from remote sensing data; assessment of land remote sensing data and products by comparing them with in situ measurements, modeling results or other remote sensing products; and application of remote sensing data and products in answering various scientific problems. This special issue collected 11 papers on several areas of quantitative land remote sensing, which will be briefly summarized in the following section.