Physical soil quality indicators for monitoring British soils

The condition or quality of soils determines its ability to deliver a range of functions that support ecosystem services, human health and wellbeing. The increasing policy imperative to implement successful soil monitoring programmes has resulted in the demand for reliable soil quality indicators (SQIs) for physical, biological and chemical soil properties. The selection of these indicators needs to ensure that they are sensitive and responsive to pressure and change e.g. they change across space and time in relation to natural perturbations and land management practices. Using a logical sieve approach based on key policy-related soil functions, this research assessed whether physical soil properties can be used to indicate the quality of British soils in terms of its capacity to deliver ecosystem goods and services. The resultant prioritised list of physical SQIs were tested for robustness, spatial and temporal variability and expected rate of change using statistical analysis and modelling. Six SQIs were prioritised; packing density, soil water retention characteristics, aggregate stability, rate of erosion, depth of soil and soil sealing. These all have direct relevance to current and likely future soil and environmental policy and are appropriate for implementation in soil monitoring programs

Landscape metrics and indices : an overview of their use in landscape research

The aim of this overview paper is to analyze the use of various landscape metrics and landscape indices for the characterization of landscape structure and various processes at both landscape and ecosystem level. We analyzed the appearance of the terms landscape metrics/indexes/indices in combination with seven main categories in the field of landscape ecology [1) use/selection and misuse of metrics, 2) biodiversity and habitat analysis; 3) water quality; 4) evaluation of the landscape pattern and its change; 5) urban landscape pattern, road network; 6) aesthetics of landscape; 7) management, planning and monitoring] in the titles, abstracts and/or key words of research papers published in international peer-reviewed scientific journals indexed by the Institute of Science Information (ISI) Web of Science (WoS) from 1994 to October 2008. Most of the landscape metrics and indices are used concerning biodiversity and habitat analysis, and also the evaluation of landscape pattern and its change (up to 25 articles per year). There are only a few articles on the relationships of landscape metrics/indices/indexes to social aspects and landscape perception

GEE-Based Ecological Environment Variation Analysis under Human Projects in Typical China Loess Plateau Region

The China Loess Plateau (CLP) is a unique geomorphological unit with abundant coal resources but a fragile ecological environment. Since the implementation of the Western Development plan in 2000, the Grain for Green Project (GGP), coal mining, and urbanization have been extensively promoted by the government in the CLP. However, research on the influence of these human projects on the ecological environment (EE) is still lacking. In this study, we investigated the spatial–temporal variation of EE in a typical CLP region using a Remote Sensing Ecological Index (RSEI) based on the Google Earth Engine (GEE). We obtained a long RSEI time series from 2002–2022, and used trend analysis and rescaled range analysis to predict changing trends in EE. Finally, we used Geodetector to verify the influence of three human projects (GGP, coal mining, and urbanization). Our results show that GGP was the major driving factor of ecological changes in the typical CLP region, while coal mining and urbanization had significant local effects on EE. Our research provides valuable support for ecological protection and sustainable social development in the relatively underdeveloped region of northwest China

Drone image-based parameters for assessing the vegetation condition the reclamation success in post-mining oil exploration

This paper examines drone-based parameters for assessing the success of reclamation activities in post-mining oil-exploration area. The applied drone-based images were multispectral images having visible light and infrared wavelength regions with 5 cm spatial resolution. The main objective of the study is to develop a mathematical model to estimate a reclamation success, through development of success indices. The model were developed by analyzing the relationship between the vegetation success and the digital number values of original and/or synthetic images of drone-based images using 70 sample plots. The mathematical models were developed using a regression analysis, where responses are biomass, volume, and basal area, while the independent variables were original digital number value of images and their derivative synthetic images. The study found that there is a close relationship between parameter biomass stock (ton/ha) and basal area (cm) with both, i.e., original digital number and vegetation indices

Quarterly literature review of the remote sensing of natural resources

The Technology Application Center reviewed abstracted literature sources, and selected document data and data gathering techniques which were performed or obtained remotely from space, aircraft or groundbased stations. All of the documentation was related to remote sensing sensors or the remote sensing of the natural resources. Sensors were primarily those operating within the 10 to the minus 8 power to 1 meter wavelength band. Included are NASA Tech Briefs, ARAC Industrial Applications Reports, U.S. Navy Technical Reports, U.S. Patent reports, and other technical articles and reports