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Remote Sensing and Geospatial Approaches for Landscape Ecology

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ecological Remote Sensing".

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 14264

Special Issue Editor


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Guest Editor
Biology Program, Faculty of Natural Sciences and Mathematics, Universidad del Rosario, Kr 26 No 63B-48, Bogotá D.C., Colombia
Interests: landscape ecology; remote sensing, ecosystem services mapping; ecological disturbances; land use change impacts

Special Issue Information

Dear Colleagues,

Landscape ecology focuses on the analysis of spatial patterns to investigate how altered landscapes affect ecological processes. Remote sensing technologies provide fundamental tools and data to this scientific discipline, largely due to the strong spatial component of its analyses. Optical and radar remote sensing imagery supply key information to map spatially explicit variables that can be processed and analyzed using different geospatial approaches. This strong link is gaining importance in applied ecological research, due to expanding global environmental change processes, such as biodiversity loss and land use change.

This open access Special Issue invites research papers describing cutting-edge research on the application of remote sensing technologies from any platform (satellite, aircraft, drones, etc.) to the study of landscape ecology problems. Possible topics include, but are not restricted to: mapping of landscape processes under change dynamics, methods for monitoring ecosystem processes, effects of scale on monitoring landscape properties, novel remote sensing data, and approaches for socio-ecological landscape assessment. Research that integrates active with passive remote sensing approaches is also relevant.

Prof. Nicola Clerici
Guest Editor

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Keywords

  • Landscape structure
  • Land-Cover/Land-Use Change
  • Landscape assessment
  • Fragmentation
  • Connectivity
  • Environmental Monitoring
  • Deforestation
  • Biodiversity mapping
  • Environmental Change
  • Land degradation
  • Scale
  • Geospatial approaches

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Published Papers (3 papers)

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Research

21 pages, 4044 KiB  
Article
Using Unmanned Aerial Vehicle and LiDAR-Derived DEMs to Estimate Channels of Small Tributary Streams
by Joan Grau, Kang Liang, Jae Ogilvie, Paul Arp, Sheng Li, Bonnie Robertson and Fan-Rui Meng
Remote Sens. 2021, 13(17), 3380; https://doi.org/10.3390/rs13173380 - 26 Aug 2021
Cited by 6 | Viewed by 2942
Abstract
Defining stream channels in a watershed is important for assessing freshwater habitat availability, complexity, and quality. However, mapping channels of small tributary streams becomes challenging due to frequent channel change and dense vegetation coverage. In this study, we used an Unmanned Aerial Vehicle [...] Read more.
Defining stream channels in a watershed is important for assessing freshwater habitat availability, complexity, and quality. However, mapping channels of small tributary streams becomes challenging due to frequent channel change and dense vegetation coverage. In this study, we used an Unmanned Aerial Vehicle (UAV) and photogrammetry method to obtain a 3D Digital Surface Model (DSM) to estimate the total in-stream channel and channel width within grazed riparian pastures. We used two methods to predict the stream channel boundary: the Slope Gradient (SG) and Vertical Slope Position (VSP). As a comparison, the same methods were also applied using low-resolution DEM, obtained with traditional photogrammetry (coarse resolution) and two more LiDAR-derived DEMs with different resolution. When using the SG method, the higher-resolution, UAV-derived DEM provided the best agreement with the field-validated area followed by the high-resolution LiDAR DEM, with Mean Squared Errors (MSE) of 1.81 m and 1.91 m, respectively. The LiDAR DEM collected at low resolution was able to predict the stream channel with a MSE of 3.33 m. Finally, the coarse DEM did not perform accurately and the MSE obtained was 26.76 m. On the other hand, when the VSP method was used we found that low-resolution LiDAR DEM performed the best followed by high-resolution LiDAR, with MSE values of 9.70 and 11.45 m, respectively. The MSE for the UAV-derived DEM was 15.12 m and for the coarse DEM was 20.78 m. We found that the UAV-derived DEM could be used to identify steep bank which could be used for mapping the hydrogeomorphology of lower order streams. Therefore, UAVs could be applied to efficiently map small stream channels in order to monitor the dynamic changes occurring in these ecosystems at a local scale. However, the VSP method should be used to map stream channels in small watersheds when high resolution DEM data is not available. Full article
(This article belongs to the Special Issue Remote Sensing and Geospatial Approaches for Landscape Ecology)
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16 pages, 33012 KiB  
Article
Land Cover Trends in South Texas (1987–2050): Potential Implications for Wild Felids
by Jason V. Lombardi, Humberto L. Perotto-Baldivieso and Michael E. Tewes
Remote Sens. 2020, 12(4), 659; https://doi.org/10.3390/rs12040659 - 17 Feb 2020
Cited by 23 | Viewed by 5013
Abstract
The Rio Grande Delta and surrounding rangelands in Texas has become one of the fastest urbanizing regions in the United States over the last 35 years. We assessed how land cover trends contributed to the large-scale processes that have driven land cover change [...] Read more.
The Rio Grande Delta and surrounding rangelands in Texas has become one of the fastest urbanizing regions in the United States over the last 35 years. We assessed how land cover trends contributed to the large-scale processes that have driven land cover change since 1987. We classified LANDSAT imagery from 1987 to 2016 to quantify different rates of land cover change and used housing density scenarios to project changes in the amount and spatial distribution of woody cover until 2050 and its potential impact on wild felid habitat. Since 1987, woody cover increased from 3.9% along with patch and edge density, whereas mean patch area and Euclidean nearest neighbor decreased. Closer inspection revealed that woody encroachment of small patches (<1 ha) was the leading cause of woody cover increase by a magnitude of 4, with an observed significant skewness and kurtosis in the frequency distribution of patch size across years. By 2050, urbanization will be the dominant landscape type and at least 200 km2 of woody cover may be lost, thereby affecting felid populations in South Texas. These results provide important information for predicting future woody cover fragmentation and its potential impact on the connectivity of wild felid populations. Full article
(This article belongs to the Special Issue Remote Sensing and Geospatial Approaches for Landscape Ecology)
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22 pages, 2873 KiB  
Article
The Socio-Economic and Environmental Variables Associated with Hotspots of Infrastructure Expansion in South America
by María José Andrade-Núñez and T. Mitchell Aide
Remote Sens. 2020, 12(1), 116; https://doi.org/10.3390/rs12010116 - 1 Jan 2020
Cited by 6 | Viewed by 4171
Abstract
The built environment, defined as all human-made infrastructure, is increasing to fulfill the demand for human settlements, productive systems, mining, and industries. Due to the profound direct and indirect impacts that the built environment produces on natural ecosystems, it is considered a major [...] Read more.
The built environment, defined as all human-made infrastructure, is increasing to fulfill the demand for human settlements, productive systems, mining, and industries. Due to the profound direct and indirect impacts that the built environment produces on natural ecosystems, it is considered a major driver of land change and biodiversity loss, and a major component of global environmental change. In South America, a global producer of minerals and agricultural commodities, and a region with many biodiversity hotspots, infrastructure expanded considerably between 2001 and 2011. This expansion occurred mainly in rural areas, towns, and sprawling suburban areas that were not previously developed. Herein, we characterized the areas of major infrastructure expansion between 2001 and 2011 in South America. We used nighttime light data, land use maps, and socio-economic and environmental variables to answer the following questions: (1) Where are the hotspots of infrastructure expansion located? and (2) What combination of socio-economic and environmental variables are associated with infrastructure expansion? Hotspots of infrastructure expansion encompass 70% (337,310 km2) of the total infrastructure expansion occurring between 2001 and 2011 across South America. Urban population and economic growth, mean elevation, and mean road density were the main variables associated with the hotspots, grouping them into eight clusters. Furthermore, within the hotspots, woody vegetation increased around various urban centers, and several areas showed a large increase in agriculture. Investments in large scale infrastructure projects, and the expansion and intensification of productive systems (e.g., agriculture and meat production) play a dominant role in the increase of infrastructure across South America. We expect that under the current trends of globalization and land changes, infrastructure will continue increasing and expanding into no-development areas and remote places. Therefore, to fully understand the direct and indirect impacts of land use change in natural ecosystems studies of infrastructure need to expand to areas beyond cities. This will provide better land management alternatives for the conservation of biodiversity as well as peri-urban areas across South America. Full article
(This article belongs to the Special Issue Remote Sensing and Geospatial Approaches for Landscape Ecology)
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