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Editorial for Special Issue “Digital Mapping in Dynamic Environments”

Agriculture and Food Commonwealth Scientific and Industrial Research Organisation, Bruce E Butler Laboratory, Clunies Ross Street, Black Mountain, ACT 2601, Australia
School of Life & Environmental Sciences, Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(20), 3384;
Received: 25 September 2020 / Accepted: 13 October 2020 / Published: 16 October 2020
(This article belongs to the Special Issue Digital Mapping in Dynamic Environments)
It is widely acknowledged that the global stock of soil and environmental resources are diminishing and under threat. This issue stems from current and historical unsustainable management practices, leading to degraded landscapes, which is further compounded by increased pressures upon them from ever-increasing anthropogenic activities. To curb the trajectory toward a collapse of our ecosystems, systematic ways are needed to assess the condition of our natural resources, how much they might have changed, and to what extent this might impact on the life sustaining functions we derive from our environment and the extent of our food producing systems. Some solutions to these issues come in the form of measurement, mapping and monitoring technology, which facilitates powerful ways in which to be informed about and to understand and assess the condition of our landscapes so that they can be managed strategically or simply improved. This Special Issue showcases from several locations across the globe, detailed examples of what is achievable at the convergence of big data brought about by remote and proximal sensing platforms, advanced statistical modelling and computing infrastructure to understand and monitor our ecosystems better. These utilities not only provide high-resolution abilities to map the extent and changes to our food producing systems, they also have yielded new ways to determine land-use and climate effects on the fate of soil carbon across living generations and to identify hydrological risk strategies in otherwise data-poor urban environments. Leveraging the availability of remote sensing data is telling, but the papers in this Special Issue also highlight the sophistication of modelling capabilities to deliver not only highly detailed maps of temporal dynamic soil phenomena but ways to draw new inferences from sparse and disparate model input data. The challenges of restoring our ecosystems are immense and sobering. However, we are well equipped and capable of confronting these pervasive issues in objective and data-informed ways that have previously never been possible. View Full-Text
MDPI and ACS Style

Malone, B.; Minasny, B. Editorial for Special Issue “Digital Mapping in Dynamic Environments”. Remote Sens. 2020, 12, 3384.

AMA Style

Malone B, Minasny B. Editorial for Special Issue “Digital Mapping in Dynamic Environments”. Remote Sensing. 2020; 12(20):3384.

Chicago/Turabian Style

Malone, Brendan, and Budiman Minasny. 2020. "Editorial for Special Issue “Digital Mapping in Dynamic Environments”" Remote Sensing 12, no. 20: 3384.

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