Remote Sensing Applied in Forest Management to Optimize Ecosystem Services: Advances in Research
Abstract
:1. Introduction
2. Framework
2.1. Remote Sensing
2.2. Forest Management
2.3. Ecosystem Service
3. Data and Methodology
3.1. Bibliometric Method
3.2. Data Collection
3.3. Data Processing
3.4. Method Terminology
- Determine the relationship of the publications: from a set of articles, the relationship of each pair in this set is determined, to produce hierarchical classification systems. Each article belongs to a single research area at the lowest level of a ranking system; each research area at the lowest level in turn belongs to a unique research area at the second lowest level, and so on.
- Group the articles to build the basic structure of a classification system: the articles are grouped into research areas and the research areas are organized in a hierarchical structure. The grouping technique is based on modularity. VOSviewer’s clustering algorithm allows communities to be detected in a network, which considers modularity, that is, a measure that assesses the quality of community structures. Therefore, VOSviewer’s modularity-based clustering provides networks where nodes are densely connected internally within groups, but without external connection between different groups. In this way, it unifies the mapping and grouping approaches, in addition to dividing the research carried out in documents [104].
- Labeling research areas: to complete the construction of the classification system, labels are assigned to research areas. These labels are obtained by extracting appropriate terms from the titles and summaries of the articles that belong to a research area.
4. Results and Discussion
4.1. Scientific Production and Subject Areas
4.2. Keyword Analysis
4.2.1. Clustering: Identification of Current Lines of Research
- Forest Management: during this period, mainly, the link between active forest management and sustainability has been studied since adequate sustainable forest management has made it possible to increase production as they grow. Forests, as indicated in Section 2, contribute to the reduction of carbon emissions, but in the process of logging in agriculture or other industrial activities, they emit large amounts of CO2 and other greenhouse gases into the atmosphere that negatively influence climate change [10,29,53,116].
- Ecosystem Service: the publications on these lines, during the period analyzed, the publications on these lines have been aimed at analyzing the tangible and intangible benefits that forest ecosystems provide to the natural ecosystem itself, to the rest of the ecosystems and to society, such as: maintaining the functioning of the basins; water; the conservation of the biodiversity of native flora and fauna; the provision of medicinal species and other beneficial natural products for the maintenance of health, the fight against diseases and other uses; the reduction of water, wind and biological erosion, and protection of the geomorphological structure; protection of the diversity of related natural and cultural landscapes; or the maintenance of the environmental offer of tourist and educational interest [17,25,117]. Have been aimed at analyzing the tangible and intangible benefits that forest ecosystems provide to the natural ecosystem itself, to the rest of the ecosystems and to society, such as: maintaining the functioning of the basins; water; the conservation of the biodiversity of native flora and fauna; the provision of medicinal species and other beneficial natural products for the maintenance of health, the fight against diseases and other uses; the reduction of water, wind and biological erosion, and protection of the geomorphological structure; protection of the diversity of related natural and cultural landscapes; or the maintenance of the environmental offer of tourist and educational interest [17,25,117].
- Environmental Monitoring: this school of thought has studied the study of continuous and systematic monitoring of environmental, social, economic, and institutional variables to identify and evaluate the conditions of natural resources. The development of this line has provided information on the factors that can be influenced, in addition to the state of conservation, preservation, degradation, and environmental recovery of a given region [31,34,118].
- Satellite Imagery: during this period, research in this line has sought to identify, from data and the use of aerial photographs, trends at the regional and global level and the effects of climate change on vegetation. Subsequently, satellite remote sensing has become a more versatile tool to identify trends in vegetation dynamics on a large temporal and spatial scale. The use of satellite images, as well as databases, and other environmental variables and computational statistics, has allowed us to analyze trends in forest change in different regions globally [36,47,119].
- Satellite Data: in recent years, the research has contributed to developing applications and technologies for satellite tracking, such as Google Earth, which allows anyone with an Internet connection to see aerial images of almost any place on Earth. These applications allow more effective monitoring of environmental changes, such as fluctuations in sea ice at the poles, changes in ocean plankton, and deforestation. Satellite observation data has become a business for companies. A major factor in the increased use of satellite imagery has been the Landsat Data Distribution Policy, which allows access to data captured by Landsat satellites, and has been collecting data since 1972 [9,19,120].
- Deforestation: it is key to recognize that forests represent a source of food, medicine, and fuel for the entire world population, as well as being a key tool to combat climate change and protect soil and water. In this sense, deforestation referred to the loss of forests and jungles due to the impact of human activities or natural causes has had a high impact on research in the period analyzed. Likewise, the consequences of global deforestation contribute with most of the total emission of greenhouse gases into the atmosphere, followed by the generation of energy produced by fossil fuels and industrial activities [30,121].
- Remote Sensing: this main line of research has dealt, among others [9,20,22]: (i) with the mapping of occupation and land use and the detection of changes from multispectral images of medium and high spatial resolution (Landsat Thematic Mapper (TM) and Landsat Enhanced Thematic Mapper (ETM)., Satellite Probatoire d’Observation de la Terre (SPOT) High Resolution Visible (HRV) and High Resolution Visible (HRG)) and aerial orthophotos; (ii) the remote sensing connection with the GIS; (iii) the analysis of the human risk of forest fires and the regeneration of the vegetation behind them; (iv) estimation of the moisture content of the vegetation; (v) mapping of fuel models; (vi) detection of weeds; (vii) restoration of pastures; or (viii) obtaining spectral information to estimate biophysical parameters of vegetation in the context of global change.
4.2.2. Evolution of Keywords
4.3. Future Research Directions
- Ecological Sensitivity Assessment: environmental sensitivity is the capacity of an ecosystem to withstand changes caused by anthropogenic actions, without undergoing substantial alterations that prevent it from reaching a dynamic balance that maintains an admissible level in its structure and function. Thus, the degree of environmental sensitivity will depend on the level of conservation or degradation of the ecosystem and the presence of external (anthropic) actions [122].
- Sustainable Rural Development: it refers to the process that seeks social change and economic growth of rural communities, based on the rational integration of the means of production, resources, and needs of these populations. The final objective is to improve the quality of life of these societies and conserve the environment. Among the main needs for sustainable rural development are: (i) improving the well-being of millions of people living in rural areas (approximately half of the world’s population), reducing the rural-urban gap, eradicating poverty, and avoiding poverty, migration to the city; (ii) protect and conserve natural, landscape and cultural resources; and (iii) ensure universal access to food with sustainable agricultural production. In this rural culture the role of the rural world is valued, mainly, in the conservation of nature, creating a culture of local consumption, promoting training and management resources for a sustainable economy, and transferring to urban society the importance of the world rural [123,124].
- Ecological Conservation Zone: they denote the regions that contain representative samples of ecosystems in a good state of preservation and that are intended to protect natural elements and ecological processes that promote balance and social well-being. An ecological reserve or nature reserve is a semi-protected area, of importance for wildlife, flora, or fauna, or with geological features of special interest that is protected and managed by man, for the purpose of conservation, and to provide opportunities for research and education. It is a human delimitation where activities harmful to the environment are prohibited, which is established mainly to conserve biological diversity of regional and local interest, and maintain the continuity of essential ecological processes, in addition to the provision of environmental services derived from them [5,82,122].
- Ecological Control Buffer Zone: buffer zones for conservation are strips of vegetation incorporated into the landscape to influence ecological processes and provide us with a variety of goods and services. The Intergovernmental Platform for Science and Policy on Biodiversity and Ecosystem Services (IPBES) indicates that one million species of animals and plants are in danger of extinction, a figure that reflects that three quarters of the terrestrial environment is deteriorated and approximately 66% of the oceans significantly altered [82,125].
- Air Pollution Mitigation: this line of research should provide quantitative and qualitative analyses on the mitigation of air pollution, in relation to the means of transport to make way for new energy, establish new pollution control mechanisms. Air pollution affects the environment. Growing forests absorb carbon from the atmosphere and store it in their biomass. At the time of harvesting the trees, carbon is transferred to the products and, at the end of their life cycle, part of the carbon is released into the atmosphere. Thus, good forest management, forests can mitigate the effects of climate change [77,126].
- Contemporary Political Forest: these are the result of four types of forestry intertwined chronologically: (i) colonial; (ii) national or for development; (iii) of war; and (iv) non-state. Political forests are not accurately mapped to forest cover and are different from common sense interpretations of the forest as natural formations characterized by associated trees and species, such as FAO forest classifications based on vegetation assessment. The creation of political forests implies coercion and violence, that is, wars, insurgencies, and other forms of political violence impact these areas, often forcing the displacement of resident peoples [5,127].
- Cross Border Biophysical Forest Phenomena: the phenomenon of shyness of the tree canopy consists of a limited growth of the treetops, so that the leaves and branches of adjacent trees do not touch each other, producing figures and patterns with the background sky when observing the trees from the ground. The shyness of the crown has been observed in certain species of European oak and pine, and species of tropical and subtropical habitats. The mechanism that gives rise to this phenomenon is attempted to be explained by the: (i) friction hypothesis: it indicates that the friction of some branches with others when the wind hits them would limit their growth to avoid touching neighboring trees, due to damage caused by abrasion; (ii) allelopathy hypothesis: indicates that the shyness of the crown has an allelopathic origin, that is, plants and trees communicate with each other through chemical signals; and (iii) photoreceptor hypotheses: they would provoke in the tree the response to move away from the adjacent one, and would allow it to obtain a greater amount of light for photosynthesis [11,128]. This line of research should analyze whether this phenomenon: (i) allows greater light penetration into the forest to carry out photosynthesis more efficiently; (ii) prevents branches and leaves from being damaged when struck against each other in the event of a storm or gusts of wind; (iii) prevents diseases, larvae and leaf-eating insects from spreading easily from one tree to another; or (iv) follows a collaborative relationship between species for survival, rather than competition [23,129].
- Satellite Fire Mapping: this future research direction seeks to empower people based on cartographic applications to minimize the effect of forest fires and hold those responsible for burning these forest stands accountable. In this sense, it seeks to: (i) track fire activity and impacts, combining real-time satellite data, high-resolution satellite images, detailed maps of land cover and concessions for key products such as palm oil and pulp, wood, weather conditions, and air quality data; (ii) show where fires occur; (iii) help authorities determine who could be responsible; (iv) collaborate with non-governmental organizations (NGOs) and national and local governments, speeding up the response time to fire [130,131].
- Topological Acoustic Sensing: sound wave topological insulators allow sound waves to move on their surface, but inside they are acoustic insulators. The potential of these materials could be applied in ultrasound technologies, or to improve ultrasound. In this type of solids, the sound signal remains robust and insensitive to the presence of noise caused by impurities and defects in the material. In the framework of this research, previous studies have detected that this acoustic insulator could act as an extremely robust waveguide, capable of radiating sound in a very narrow beam towards the far field. The development of mobile applications, sensors, camera traps or the acoustic monitoring system, which seek to combat hunting and illegal logging, in order to conserve the planet’s biodiversity, as well as to know in what situation a certain species is or how to manage a certain natural resource. This method is used in scientific research to determine the status of a species or a geographical area in terms of conservation [132]. In this sense, various study applications have begun to be implemented, such as the AudioMoth case, with the aim of designing techniques to monitor anthropogenic disturbances, which may be linked to illegal hunting of wildlife [133].
- Unsupervised Treetop Detector: concern about the need to increase crop yields, reduce the environmental impact of plant protection products and prevent the introduction and spread of quarantine diseases, arouses interest in developing legislative, scientific, and technical tools for the early detection of diseases. Likewise, current agriculture is torn between the need to increase agricultural production and growing environmental concern. The most sustainable way to meet these challenges is to increase crop yields through a sustainable use of inputs that, in the field of crop protection, is achieved by reducing losses caused by diseases, weeds, and pests. Furthermore, the appearance of new pests and diseases derived from the intensification of commercial exchanges has caused an economic, social, and environmental alarm. In the particular context of diseases, their early detection in the field is a valuable source of information for executing adequate disease management and control strategies that prevent the development and spread of pathogens. Conventional methods for detecting diseases, based on visual inspection of symptoms and damage in the field, are costly in time and resources. An alternative to these methods is remote sensing, with the aim of detecting symptoms in early stages of the development of diseases on a cover scale. In agricultural research in the field of remote sensing based on hyperspectral and thermal sensors, the derived applications have proven to be relevant for the detection of nutritional and water deficiencies, and for the early detection of diseases [134].
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- How do the descriptors of the functioning of forest ecosystems vary in space?
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- How are forest ecosystems changing? What is the trend of change?
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- How has the ecosystem behaved in the last period analyzed with respect to the historical series?
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- What areas have had an abnormal behavior?
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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R | Year | Article Title | Author(s) | Journal | Term Associated |
---|---|---|---|---|---|
[17] | 2020 | Earth observation-based ecosystem services indicators for national and subnational reporting of the sustainable development goals | Cochran, F.; Daniel, J.; Jackson, L.; Neale, A. | Remote Sensing of Environment | RS—ES |
[18] | 2020 | Integrating Remote Sensing and Street View Images to Quantify Urban Forest Ecosystem Services | Barbierato, E.; Bernetti, I.; Capecchi, I.; Saragosa, C. | Remote Sensing | RS—FM—ES |
[19] | 2020 | Estimation of Forest Biomass in Beijing (China) Using Multisource Remote Sensing and Forest Inventory Data | Zhu, Y.; Feng, Z.; Lu, J.; Liu, J. | Forests | RS—FM |
[20] | 2018 | Remote Sensing of Landslides—A Review | Zhao, C.; Lu, Z. | Remote Sensing | RS—ES |
[21] | 2018 | Remote sensing of ecosystem trajectories as a proxy indicator for watershed water balance | Chasmer, L.E.; Devito, K.J.; Hopkinson, C.D.; Petrone, R.M. | Ecohydrology | RS—ES |
[22] | 2018 | Analysis of remote sensing time-series data to foster ecosystem sustainability: use of temporal information entropy | Wang, C.; Zhao, H. | International Journal of Remote Sensing | RS—FM—ES |
[23] | 2018 | Do Silviculture and Forest Management Affect the Genetic Diversity and Structure of Long-Impacted Forest Tree Populations? | Aravanopoulos, F. | Forests | FM—ES |
[24] | 2017 | Remote Sensing of Above-Ground Biomass | Kumar, L.; Mutanga | Remote Sensing | RS—FM |
[25] | 2016 | Remote sensing of species dominance and the value for quantifying ecosystem services | Pau, S.; Dee, L.E. | Remote Sensing in Ecology and Conservation | RS—ES |
[26] | 2009 | Habitat assessment for forest dwelling species using LiDAR remote sensing: capercaillie in the Alps | Graf, R.F.; Mathys, L.; Bollmann, K. | Forest Ecology and Management | RS—FM |
[27] | 2006 | Surveying mountain pine beetle damage of forests: A review of remote sensing opportunities | Wulder, M.A.; Dymond, C.C.; White, J.C.; Leckie, D.G.; Carroll, A.L. | Forest Ecology and Management | FM—ES |
[28] | 2005 | Remote Sensing of Forest Regeneration in Highland Tropical Forests | Aguilar, A. | GIScience & Remote Sensing | RS—FM |
[29] | 2004 | Remote sensing of selective logging impact for tropical forest management | De Wasseige, C.; Defourny, P. | Forest Ecology and Management | RS—FM |
[30] | 1998 | Tropical deforestation and remote sensing | Myers, N. | Forest Ecology and Management | RS—FM |
[31] | 1995 | The use and limits of remote sensing for analyzing environmental and social change in the Himalayan Middle Mountains of Nepal | Millette, T.L.; Tuladhar, A.R.; Kasperson, R.E.; Turner, B. | Global Environmental Change | RS—FM—ES |
R | Keyword | N | C | L | TLS | R | Keyword | N | C | L | TLS |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | Remote Sensing | 1695 | 7 | 998 | 25,638 | 16 | Satellite Data | 191 | 5 | 782 | 3438 |
2 | Forest Management | 802 | 1 | 963 | 12,971 | 17 | Forest Inventory | 186 | 1 | 672 | 3211 |
3 | Forestry | 670 | 1 | 981 | 12,484 | 18 | Environmental Monitoring | 185 | 3 | 797 | 4303 |
4 | Ecosystem Service | 526 | 2 | 880 | 8400 | 19 | Environmental Protection | 177 | 2 | 710 | 3948 |
5 | Ecosystems | 436 | 2 | 943 | 8272 | 20 | LiDAR (Laser Imaging Detection and Ranging) | 167 | 1 | 630 | 2900 |
6 | Satellite Imagery | 327 | 4 | 883 | 5952 | 21 | Mapping | 165 | 1 | 677 | 2822 |
7 | Land Use | 316 | 2 | 837 | 6219 | 22 | Climate Change | 165 | 5 | 740 | 3243 |
8 | GIS (Geographical Information Systems) | 306 | 2 | 829 | 4830 | 23 | Forest Cover | 143 | 4 | 654 | 2585 |
9 | Biodiversity | 255 | 4 | 835 | 4452 | 24 | Biomass | 136 | 1 | 676 | 2468 |
10 | Land Use Change | 237 | 2 | 736 | 4276 | 25 | Conservation | 134 | 4 | 683 | 2655 |
11 | Landsat | 232 | 5 | 773 | 4026 | 26 | Sustainable Development | 133 | 2 | 618 | 2388 |
12 | Land Cover | 218 | 2 | 743 | 3815 | 27 | Image Analysis | 132 | 1 | 676 | 2462 |
13 | Vegetation | 209 | 3 | 838 | 4234 | 28 | Forest Ecosystem | 129 | 6 | 668 | 2287 |
14 | Deforestation | 200 | 6 | 714 | 3574 | 29 | Conservation of Natural Resources | 123 | 3 | 641 | 3267 |
15 | Ecology | 194 | 2 | 811 | 3724 | 30 | NDVI (Normalized Difference Vegetation Index) | 121 | 5 | 580 | 1924 |
R | Cluster Name | Color (Figure 4) | % | O | L | TLS | Top 10 Keywords |
---|---|---|---|---|---|---|---|
1 | Forest Management | Pink | 31.63 | 963 | 12,971 | 802 | Forestry, Forest Inventory, LiDAR, Mapping, Biomass, Image Analysis, Optical Radar, Satellites, Spatial Resolution, Forest Canopy |
2 | Ecosystem Service | Green | 23.92 | 880 | 8400 | 526 | Ecosystems, Land Use, GIS (Geographic Information Systems), Land Use Change, Land Cover, Ecology, Environmental Protection, Sustainable Development, Agriculture, Landscape |
3 | Environmental Monitoring | Red | 14.01 | 797 | 4303 | 185 | Vegetation, Conservation of Natural Resources, Tree, Forest Fire, Vegetation Index, Leaf Area Index, Carbon Cycle, Land Management, Topography, Deciduous Forest |
4 | Satellite Imagery | Yellow | 12.71 | 883 | 5952 | 327 | Biodiversity, Forest Cover, Conservation, Reforestation, Conservation Management, Landscape Change, Forest Dynamics, Protected Area, Habitat Fragmentation, Species Diversity |
5 | Satellite Data | Violet | 8.81 | 782 | 3438 | 191 | Landsat, Climate Change, NDVI (Normalized Difference Vegetation Index), MODIS (Moderate Resolution Imaging Spectroradiometer), Vegetation Cover, Radiometers, Vegetation Dynamics, Evapotranspiration, Soil Moisture, Moderate Resolution Imaging Spectroradiometer |
6 | Deforestation | Blue | 7.31 | 714 | 3574 | 200 | Forest Ecosystem, Carbon Sequestration, Tropical Forest, Sustainable Forest Management, Environmental Degradation, Rhizophoraceae, Coastal Zone, Forest Degradation, Greenhouse Gas, Carbon Emission |
7 | Remote Sensing | Orange | 1.40 | 998 | 25,638 | 1695 | Wildfire, Mountain Region, Montane Forest, Mediterranean Environment, Himalayas, Topographic Mapping, Landsat Thematic Mapper, Change Detection, National Forest Planning, Topographic Effect |
Rank | Term | Relevance Score |
---|---|---|
1 | Ecological Sensitivity Assessment | 69.061 |
2 | Sustainable Rural Development | 47.721 |
3 | Ecological Conservation Zone | 47.376 |
4 | Ecological Control Buffer Zone | 47.376 |
5 | Air Pollution Mitigation | 38.412 |
6 | Contemporary Political Forest | 37.773 |
7 | Cross Border Biophysical Forest Phenomena | 37.773 |
8 | Satellite Fire Mapping | 37.773 |
9 | Topological Acoustic Sensing | 37.773 |
10 | Unsupervised Treetop Detector | 26.409 |
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Abad-Segura, E.; González-Zamar, M.-D.; Vázquez-Cano, E.; López-Meneses, E. Remote Sensing Applied in Forest Management to Optimize Ecosystem Services: Advances in Research. Forests 2020, 11, 969. https://doi.org/10.3390/f11090969
Abad-Segura E, González-Zamar M-D, Vázquez-Cano E, López-Meneses E. Remote Sensing Applied in Forest Management to Optimize Ecosystem Services: Advances in Research. Forests. 2020; 11(9):969. https://doi.org/10.3390/f11090969
Chicago/Turabian StyleAbad-Segura, Emilio, Mariana-Daniela González-Zamar, Esteban Vázquez-Cano, and Eloy López-Meneses. 2020. "Remote Sensing Applied in Forest Management to Optimize Ecosystem Services: Advances in Research" Forests 11, no. 9: 969. https://doi.org/10.3390/f11090969
APA StyleAbad-Segura, E., González-Zamar, M.-D., Vázquez-Cano, E., & López-Meneses, E. (2020). Remote Sensing Applied in Forest Management to Optimize Ecosystem Services: Advances in Research. Forests, 11(9), 969. https://doi.org/10.3390/f11090969