Quantification of Microtopography in Natural Ecosystems Using Close-Range Remote Sensing

Abstract

Microtopography plays an important role in various ecological, hydrologic, and biogeochemical processes. However, quantifying the characteristics of microtopography represents a data-intensive challenge. Over the last decade, high-resolution or close-range remote sensing data and techniques have emerged as powerful tools to quantify microtopography. Traditional field surveys were mostly limited to transects or small plots, using limited sets of observations but with the decrease in the cost of close-range remote sensing technologies and the increase in computing performance, the microtopography even in forested environments can be assessed. The main objective of this article is to provide a systematic framework for microtopographic studies using close-range remote sensing technologies. This is achieved by reviewing the application of close-range remote sensing to capture microtopography and develop microtopographic models in natural ecosystems. Specifically, to achieve the main objectives, we focus on addressing the following questions: (1) What terrain attributes represent microtopography in natural ecosystems? (2) What spatial resolution of terrain attributes is needed to represent the microtopography? (3) What methodologies have been adopted to collect data at selected resolutions? (4) How to assess microtopography? Current research, challenges, and applicability of close-range remote sensing techniques in different terrains are analyzed with an eye to enhancing the use of these new technologies. We highlight the importance of using a high-resolution DEM (less than 1 m2 spatial resolution) to delineate microtopography. Such a high-resolution DEM can be generated using close-range remote sensing techniques. We also illustrate the need to move beyond elevation and include terrain attributes, such as slope, aspect, terrain wetness index, ruggedness, flow accumulation, and flow path, and assess their role in influencing biogeochemical processes such as greenhouse gas emissions, species distribution, and biodiversity. To assess microtopography in terms of physical characteristics, several methods can be adopted, such as threshold-based classification, mechanistically-based delineation, and machine learning-based delineation of microtopography. The microtopographic features can be analyzed based on physical characteristics such as area, volume, depth, and perimeter, or by using landscape metrics to compare the classified microtopographic features. Remote sensing techniques, when used in conjunction with field experiments/data, provide new avenues for researchers in understanding ecological functions such as biodiversity and species distribution, hydrological processes, greenhouse gas emissions, and the environmental factors that influence those parameters. To our knowledge, this article provides a comprehensive and detailed review of microtopography data acquisition and quantification for natural ecosystem studies.