Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability

Topic Information

Dear Colleagues,

Environmental monitoring and modelling have accumulated advances in terms of methodologies, analytical tools, and utilisable datasets. However, continuously increasing anthropogenic and natural stressors have led to a lack of integrated sustainability worldwide. Environmental dynamism is influencing a range of human–nature interactions. The current Special Issue aims to present and discuss advances in modelling and monitoring techniques to further understand human–environmental processes at the landscape scale, including eco-geomorphic, hydro-metrologic, cultural, socio-economic, and socio-sustainability for human sustainable development that can, at the same time, conserve ecosystems for the safe prosperity of the future generations.

Subject areas include: (relating to Sustainability and the Environment)

• Environmental science (miscellaneous);
• Management, monitoring, policy and law;
• Social sciences;
• Geography, planning and development;
• Agricultural and biological sciences;
• Ecology, evolution, behaviour and systematics.

Preferred Subjects will be focusing on two main areas, including (but not limited to):

1. Environmental sustainability:
• Manuscripts that analyse pure environmental dynamism, anthropogenic
• natural interactions, environmental applications (e.g., applied
• climate, severe weathers in coastal communities, or even agricultural
• environmental interactions) as well as specific topics are invited, relating to eco-geomorphology, riverine systems, catchment, estuaries, coastal wetlands, saltmarsh, mangroves, deltaic system, fluvial, lacustrine, coastal clastic sedimentology, water demand, saltwater intrusion, and hydrometeorological changes.
2. New utilisable monitoring and modelling techniques and datasets:applied-Geoinformatics (RS, GIS, and GEE) and Earth observation system techniques for environmental issues during global climate change and anthropogenic stressors. Topics including: the environmentally applied remote sensing, GIS applications, modelling applied to hydrology, time series analysis, etc.

Prof. Dr. Brian G Jones
Dr. Ali K. M. Al-Nasrawi
Dr. Ignacio Fuentes
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Environments environments	3.7	5.7	2014	19.2 Days	CHF 1800
Sustainability sustainability	3.3	7.7	2009	19.3 Days	CHF 2400
Forests forests	2.5	4.6	2010	17.1 Days	CHF 2600

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Published Papers (11 papers)

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15 pages, 2941 KiB  

Open AccessArticle

Research on Chlorophyll-a Concentration Retrieval Based on BP Neural Network Model—Case Study of Dianshan Lake, China

by Wei-Dong Zhu, Chu-Yi Qian, Nai-Ying He, Yu-Xiang Kong, Zi-Ya Zou and Yu-Wei Li

Sustainability 2022, 14(14), 8894; https://doi.org/10.3390/su14148894 - 20 Jul 2022

Cited by 13 | Viewed by 2554

Abstract

The Chlorophyll-a (Chl-a) concentration is an important indicator of water environmental conditions; thus, the simultaneous monitoring of large-area water bodies can be realized through the remote sensing-based retrieval of the Chl-a concentrations. The back propagation (BP) neural network learning method has been widely [...] Read more.

The Chlorophyll-a (Chl-a) concentration is an important indicator of water environmental conditions; thus, the simultaneous monitoring of large-area water bodies can be realized through the remote sensing-based retrieval of the Chl-a concentrations. The back propagation (BP) neural network learning method has been widely used for the remote sensing retrieval of water quality in first and second-class water bodies. However, many Chl-a concentration measurements must be used as learning samples with this method, which is constrained by the number of samples, due to the limited time and resources available for simultaneous measurements. In this paper, we conduct correlation analysis between the Chl-a concentration data measured at Dianshan Lake in 2020 and 2021 and synchronized Landat-8 data. Through analysis and study of the radiative transfer model and the retrieval method, a BP neural network retrieval model based on multi-phase Chl-a concentration data is proposed, which allows for the realization of remote sensing-based Chl-a monitoring in third-class water bodies. An analysis of spatiotemporal distribution characteristics was performed, and the method was compared with other constructed models. The research results indicate that the retrieval performance of the proposed BP neural network model is better than that of models constructed using multiple regression analysis and curve estimation analysis approaches, with a coefficient of determination of 0.86 and an average relative error of 19.48%. The spatial and temporal Chl-a distribution over Dianshan Lake was uneven, with high concentrations close to human production and low concentrations in the open areas of the lake. During the period from 2020 to 2021, the Chl-a concentration showed a significant upward trend. These research findings provide reference for monitoring the water environment in Dianshan Lake. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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20 pages, 4313 KiB  

Open AccessArticle

Effects of Forest Fragmentation on the Volume of Wood Resources in Managed, Pine-Dominated Forests in Poland

by Piotr Budniak and Stanisław Zięba

Forests 2022, 13(4), 590; https://doi.org/10.3390/f13040590 - 8 Apr 2022

Cited by 3 | Viewed by 2576

Abstract

Forest fragmentation is a widespread phenomenon that directly or indirectly affects the processes that take place both in forest ecosystems and in their immediate surroundings. So far, many studies confirm its negative effects, especially on biodiversity. On the other hand, there are few [...] Read more.

Forest fragmentation is a widespread phenomenon that directly or indirectly affects the processes that take place both in forest ecosystems and in their immediate surroundings. So far, many studies confirm its negative effects, especially on biodiversity. On the other hand, there are few studies that address the effects of forest fragmentation on the amount of accumulated biomass or carbon, as well as on the characteristics of wood resources in managed forests. Therefore, issues related to timber production, which are important from the point of view of multifunctional forest management, are omitted. The aim of our research was to add to the knowledge in this area. In particular, we focused on assessing the impact of forest fragmentation on wood resources based on an analysis of edge effects in forest patches (units formed by combining forest fragments characterized by structural connectivity). Vector data describing the topography of forest fragments in Poland and the results of the National Forest Inventory (NFI) from 2015–2019 were used as material for solving this problem. The results of our research showed that the effects of fragmentation on managed pine stands depend on the age of the stand and the fertility of the habitat. In young stands growing on barren or strongly barren habitats, growing stock volume turned out to be significantly higher in the edge zone. In older stands, especially on moderately fertile habitats, significantly higher resources were found in the interior zone of forest patches. Habitat quality also had a significant effect on the amount of carbon accumulated. In strongly barren habitats, higher carbon mass was found in edge zones, while in moderately fertile habitats, stands had higher carbon volume in the interior zone. Our results illustrate that forest fragmentation is a very complex process that can increase or reduce wood resources, depending on the age of the stand and the quality of the habitat. From the standpoint of measurable benefits, it was concluded that protection from the negative effects of fragmentation should focus primarily on older stands and more fertile habitats. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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17 pages, 7739 KiB  

Open AccessArticle

Analysis of Plant Water Transport Mechanism and Water Requirement for Growth Based on the Effect of Thermal Environment

by Haolin Lu, Hongfa Sun and Jibo Long

Forests 2022, 13(4), 583; https://doi.org/10.3390/f13040583 - 7 Apr 2022

Cited by 1 | Viewed by 4903

Abstract

This paper put forward a model for calculating the water requirements of plants, including a transpiration model, stem water delivery model, and root water uptake model. The results showed that the model had good accuracy. The relative error between simulated values and measured [...] Read more.

This paper put forward a model for calculating the water requirements of plants, including a transpiration model, stem water delivery model, and root water uptake model. The results showed that the model had good accuracy. The relative error between simulated values and measured values was 2.09–14.13%. The limiting effects of stem water delivery capacity and root water uptake capacity on plant–water relations were analyzed. When the transpiration rate is large, even if there is enough root water uptake capacity, the limited stem water delivery capacity may affect the plant–water relationship. In order to understand the relationship between a plant and the thermal environment, the effect of the thermal environment on a plant’s water requirements was analyzed, and the effect of air temperature was obvious. Under the simulated condition, when the air temperature increased from 0 °C to 40 °C, the water requirement of an apple tree increased from 0.0134 L/h to 33.8 L/h. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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14 pages, 4744 KiB  

Open AccessArticle

Research on Land Use Simulation of Incorporating Historical Information into the FLUS Model—Setting Songyuan City as an Example

by Jun Zhang, Zhaoshun Liu and Shujie Li

Sustainability 2022, 14(7), 3828; https://doi.org/10.3390/su14073828 - 24 Mar 2022

Cited by 5 | Viewed by 2118

Abstract

Historical information has been included in the study of land use change, but the historical information is described from the perspective of urban growth. This study selected the relevant angle between historical construction land and current construction land, and quantitatively described history information. [...] Read more.

Historical information has been included in the study of land use change, but the historical information is described from the perspective of urban growth. This study selected the relevant angle between historical construction land and current construction land, and quantitatively described history information. This research put forward the STLEI index and STEWMEI index, which quantitatively describes the historical information scores, and draw the following conclusions: the closer the construction land generation period is to the current, the greater the driving effect, and this difference is particularly obvious in the past 5 years. We incorporated historical information into the FLUS model; the FoM index increased by 1.93% compared with the previous inclusion, and the Kappa index increased by 2.45% compared with the previous inclusion, verifying the driving role of historical information in land use change. Historical information has an obvious driving effect in land use change. After that, we used the FLUS model, combined with the Markov chain model, anti–planning concepts, and incorporated historical information to simulate the land use change in 2025. These experiments show that historically generated construction land plays a driving role in current and future land use changes and provides a new perspective for the study of land use simulation. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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16 pages, 4198 KiB  

Open AccessArticle

Spatio-Temporal Extraction of Surface Waterbody and Its Response of Extreme Climate along the Upper Huaihe River

by Hang Wang, Zhenzhen Liu, Jun Zhu, Danjie Chen and Fen Qin

Sustainability 2022, 14(6), 3223; https://doi.org/10.3390/su14063223 - 9 Mar 2022

Cited by 5 | Viewed by 2311

Abstract

The upper Huaihe River is the water-producing area of the Huaihe River Basin and the major grain and oil-producing area in China. The changing global climate over the recent years has increased the frequency of extreme weather in the upper reaches of the [...] Read more.

The upper Huaihe River is the water-producing area of the Huaihe River Basin and the major grain and oil-producing area in China. The changing global climate over the recent years has increased the frequency of extreme weather in the upper reaches of the Huaihe River. Research on the responses of surface water bodies to extreme climates has become increasingly important. Based on all utilizable Landsat 4–8 T1–SR data and frequency mapping, the spatio-temporal extraction of surface water and its response to extreme climate were studied. We generated high-precision frequency maps of surface water, and a comparison of cartographic accuracy evaluation indices and spatial consistency was also carried out. The high-precision interpretation of small waterbodies constructs a surface water distribution with better continuity and integrity. Furthermore, we investigated the effect of El Niño/La Niña events on precipitation, temperature, and surface water along the upper Huaihe River, using the Mann–Kendall mutation tests. The results show: in 1987–2018, periods of abrupt changes in precipitation coincide with EI Niño/La Niña events, indicating that the precipitation was sensitive to EI Niño/La Niña events, which also strongly correlated with surface water area during wet and dry years. The effect of extreme events on seasonal water was smaller than permanent water. Surface water area showed an insignificant declining trend after 1999 and a significant drop in 2012. The phenomenon of topographic enhancement of precipitation controlled the spatial distribution of permanent water, with human activities having a substantial effect on the landscape pattern of seasonal water. Finally, discussions and applications related to the Markov Chain probability calculation theory in the paper contributed to enriching the theories on frequency mapping. The relevant results provide a theoretical basis and case support for the formulation of long-term water resources utilization and allocation policies. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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18 pages, 4881 KiB  

Open AccessArticle

Multidimensional Spatial Match of Hierarchical Healthcare Facilities Considering Floating Population: A Case of Beijing, China

by Xingfei Cai, Hao Wang, Xiaogang Ning, Qiyong Du and Peng Jia

Sustainability 2022, 14(3), 1092; https://doi.org/10.3390/su14031092 - 18 Jan 2022

Cited by 4 | Viewed by 2833

Abstract

Good health and well-being are key to achieving the main goals of the UN Sustainable Development Goals (SDGs), especially after the outbreak of the COVID-19 epidemic. What is a concern for both government and society is how to understand the spatial match of [...] Read more.

Good health and well-being are key to achieving the main goals of the UN Sustainable Development Goals (SDGs), especially after the outbreak of the COVID-19 epidemic. What is a concern for both government and society is how to understand the spatial match of hierarchical healthcare facilities and residential areas in terms of quantity and capacity, to meet the challenges of various diseases and build a healthy life. Using hierarchical healthcare data and cellphone signaling data in Beijing, China, we used the kernel density estimation, a bivariate spatial autocorrelation model, and a coupling index to explore the spatial relationships between hierarchical healthcare facilities and residential areas. We found large numbers of both healthcare facilities and residential areas in the urban center, and small numbers of both at the urban edge. The hospitals and designated retail pharmacies in the densely populated areas do not have enough capacity to meet the need of the population. In addition, the capacity of primary healthcare institutions can meet people’s needs. Our findings would serve as a reference for urban planning, optimization of hierarchical healthcare facilities, and research on similar themes. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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27 pages, 34719 KiB  

Open AccessArticle

The Stability and Suitability of the Bhasan Char Island as an Accommodation for the Forcibly Displaced Myanmar Nationals (FDMN)

by Md. Yousuf Gazi, A. S. M. Maksud Kamal, Md. Nazim Uddin, Md. Anwar Hossain Bhuiyan and Md. Zillur Rahman

Sustainability 2022, 14(2), 747; https://doi.org/10.3390/su14020747 - 11 Jan 2022

Cited by 12 | Viewed by 5504

Abstract

Assessing the dynamics of Bhasan Char is very crucial, as the Government of Bangladesh (GoB) has recently selected the island as the accommodation of the FDMN. This article critically evaluates the spatiotemporal morphological variations due to erosion, accretion, and subsurface deformation of the [...] Read more.

Assessing the dynamics of Bhasan Char is very crucial, as the Government of Bangladesh (GoB) has recently selected the island as the accommodation of the FDMN. This article critically evaluates the spatiotemporal morphological variations due to erosion, accretion, and subsurface deformation of the island through multi-temporal geospatial and geophysical data analysis, groundwater quality-quantity, and also determines the nature and rate of changes from 2003 to 2020. This is the first study in this island on which multi-temporal Landsat Satellite Imagery and seismic data have been used with geospatial techniques with Digital Shoreline Analysis System (DSAS) and petrel platform, respectively. The analysis of satellite images suggests that the island first appeared in 2003 in the Bay of Bengal, then progressively evolved to the present stable condition. Significant changes have taken place in the morphological and geographical conditions of the island since its inception. Since 2012, the island has been constantly accreted by insignificant erosion. It receives tidally influenced fluvial sediments from the Ganges-Brahmaputra-Meghna (GBM) river system and the sedimentary accretion, in this case, is higher than the erosion due to relatively weaker wave action and longshore currents. It has gained approximately 68 km² area, mostly in the northern part and because of erosion in the south. Although the migration of the Bhasan Char was ubiquitous during 2003–2012, it has been concentrated in a small area to the east since 2018. The net shoreline movements (NSM) suggest that the length of the shoreline enlarged significantly by around 39 km in 2020 from its first appearance. Seismic and GPS data clearly indicate that the island is located on the crest of a slowly uplifting low-amplitude anticline, which may result in a stable landform around the island. Based on the analysis of historical data, it has been assessed that the current configuration of Bhasan Char would not be severely affected by 10–15-foot-high cyclone. Therefore, FDMN rehabilitation here might be safer that would be a good example for future geo-environmental assessment for any areas around the world for rehabilitation of human in remote and vulnerable island. The findings of this research will facilitate the government’s decision to rehabilitate FDMN refugees to the island and also contribute to future research in this area. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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23 pages, 3928 KiB  

Open AccessArticle

Multi-Objective Spatial Suitability Evaluation and Conflict Optimization Considering Productivity, Sustainability, and Livability in Southwestern Mountainous Areas of China

by Yishu Fang, Dong Ai, Yuting Yang, Weijian Sun and Jian Zu

Sustainability 2022, 14(1), 371; https://doi.org/10.3390/su14010371 - 30 Dec 2021

Cited by 7 | Viewed by 2732

Abstract

Space is the fundamental carrier for production, living, and ecological activities, and optimizing the spatial pattern is of vital importance to promote regional sustainable development. To achieve this goal, the core issues are to identify the risks of resource and environmental constraints of [...] Read more.

Space is the fundamental carrier for production, living, and ecological activities, and optimizing the spatial pattern is of vital importance to promote regional sustainable development. To achieve this goal, the core issues are to identify the risks of resource and environmental constraints of development and to realize the rational distribution of human living space. Based on the integration of multisource heterogeneous data, taking Yunnan Province, a typical mountainous area in China, as an example, this research proposes a multi-object suitability evaluation method based on 50 × 50 m grid data at the provincial scale. We build a spatial conflict analysis model to identify production–living–ecological space (PLES) and propose governance suggestions for different functional areas. The results show that (1) areas suitable for ecology make up the greatest proportion of Yunnan Province, but areas with living and ecological functions show obvious spatial complementarity; (2) areas suitable for production are restricted by steep slope, geological hazards and fragmented pattern; (3) areas suitable for living is rare, and they are mainly concentrated in the plains of central Yunnan; and (4) twenty-seven percent of area has potential spatial conflicts, among which 4.38% of the area is all suitable for production–living–ecological. The production–living advantage areas are concentrated in the central Yunnan UA (Urban agglomeration), which has a high spatial overlap. These results are expected to provide valuable insights to support comprehensive multifunctional spatial utilization and sustainable development in mountainous areas. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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21 pages, 5174 KiB  

Open AccessArticle

Flood Hazard Zonation Using an Artificial Neural Network Model: A Case Study of Kabul River Basin, Pakistan

by Muhammad Saeed, Huan Li, Sami Ullah, Atta-ur Rahman, Amjad Ali, Rehan Khan, Waqas Hassan, Iqra Munir and Shuaib Alam

Sustainability 2021, 13(24), 13953; https://doi.org/10.3390/su132413953 - 17 Dec 2021

Cited by 15 | Viewed by 4273

Abstract

Floods are the most frequent and destructive natural disasters causing damages to human lives and their properties every year around the world. Pakistan in general and the Peshawar Vale, in particular, is vulnerable to recurrent floods due to its unique physiography. Peshawar Vale [...] Read more.

Floods are the most frequent and destructive natural disasters causing damages to human lives and their properties every year around the world. Pakistan in general and the Peshawar Vale, in particular, is vulnerable to recurrent floods due to its unique physiography. Peshawar Vale is drained by River Kabul and its major tributaries namely, River Swat, River Jindi, River Kalpani, River Budhni and River Bara. Kabul River has a length of approximately 700 km, out of which 560 km is in Afghanistan and the rest falls in Pakistan. Looking at the physiography and prevailing flood characteristics, the development of a flood hazard model is required to provide feedback to decision-makers for the sustainability of the livelihoods of the inhabitants. Peshawar Vale is a flood-prone area, where recurrent flood events have caused damages to standing crops, agricultural land, sources of livelihood earnings and infrastructure. The objective of this study was to determine the effectiveness of the ANN algorithm in the determination of flood inundated areas. The ANN algorithm was implemented in C# for the prediction of inundated areas using nine flood causative factors, that is, drainage network, river discharge, rainfall, slope, flow accumulation, soil, surface geology, flood depth and land use. For the preparation of spatial geodatabases, thematic layers of the drainage network, river discharge, rainfall, slope, flow accumulation, soil, surface geology, flood depth and land use were generated in the GIS environment. A Neural Network of nine, six and one neurons for the first, second and output layers, respectively, were designed and subsequently developed. The output and the resultant product of the Neural Network approach include flood hazard mapping and zonation of the study area. Parallel to this, the performance of the model was evaluated using Root Mean Square Error (RMSE) and Correlation coefficient (R2). This study has further highlighted the applicability and capability of the ANN in flood hazard mapping and zonation. The analysis revealed that the proposed model is an effective and viable approach for flood hazard analysis and zonation. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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20 pages, 910 KiB  

Open AccessArticle

Optimal Politics of Conflict over Physical-Industrial Development Using a Technique of Cooperative Game Theory in Iran

by Samaneh Zahedi, Amir Hedayati Aghmashhadi and Christine Fürst

Sustainability 2021, 13(22), 12716; https://doi.org/10.3390/su132212716 - 17 Nov 2021

Cited by 6 | Viewed by 2429

Abstract

One of the most important parameters for economic growth is industrial development in many developing regions like Iran. The Markazi province in the center of Iran is one of the most important industrial areas in the country, where unplanned economic development in recent [...] Read more.

One of the most important parameters for economic growth is industrial development in many developing regions like Iran. The Markazi province in the center of Iran is one of the most important industrial areas in the country, where unplanned economic development in recent decades has led to many social and environmental problems. Accordingly, the main organizations involved in industrial development in this region are facing difficulties in the future development of industrial areas, which has become a complex problem. Therefore, the main purpose of this paper is to study the industrial development dispute in the Markazi province through a cooperative model of game theory in order to achieve conflict resolution through a comprehensive approach. In this research, the conflict has been analyzed through strategic analysis of stakeholders. For this purpose, a model of cooperative game theory and its bargaining analysis methods, including social choice rules (SCRs) and fallback bargaining (FB), and six available options were used. According to the six SCRs, the most likely option that can exist between the Department of the Environment (DOE) and the Industrial and Mining Organization (IMO) is compromise coordination (C). In addition, the results of the Fallback Bargaining (FB) rule in three different forms show that the most appropriate options for agreement between the IMO and DOE are the moderate version of construction through arbitration (TCa) and compromise coordination (C). In fact, the results indicate that if the actors involved in this conflict do not cooperate to resolve it, it can lead to more complex problems and the involvement of other groups who may not even have a proper perception of the conflict. In addition, the findings show that cooperation between the parties and understanding of their positions and views along with the policy coherence are necessary to strive for sustainable development and maintain economic growth and development. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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18 pages, 1979 KiB  

Open AccessArticle

Development and Assessment of a Web-Based National Spatial Data Infrastructure for Nature-Based Solutions and Their Social, Hydrological, Ecological, and Environmental Co-Benefits

by Cyndi V. Castro and Hanadi S. Rifai

Sustainability 2021, 13(19), 11018; https://doi.org/10.3390/su131911018 - 4 Oct 2021

Cited by 13 | Viewed by 4150

Abstract

Comprehensive datasets for nature-based solutions (NBS), and their diverse relationships have not yet been accumulated into a deployable format. This research describes the development of a novel National Spatial Data Infrastructure (NSDI) system for NBS co-benefits throughout the contiguous United States. Here, we [...] Read more.

Comprehensive datasets for nature-based solutions (NBS), and their diverse relationships have not yet been accumulated into a deployable format. This research describes the development of a novel National Spatial Data Infrastructure (NSDI) system for NBS co-benefits throughout the contiguous United States. Here, we gather and integrate robust geospatial datasets from the social, ecological, environmental, and hydrologic domains using seamless, cloud-based data services to facilitate the trans-disciplinary assessment of NBSs as a function of society and Earth. This research enhances practical decision making and research by assimilating web-based datasets and describing the missing links between national policy and robust adoption of NBSs as a sustainability solution. This NSDI serves to foster participatory planning capabilities and integrate local sustainability goals into decision–support frameworks. Such a platform strengthens the knowledge base necessary for addressing multiple, co-evolving issues of societal relevance, an essential component of fully espousing NBSs within the realm of socio-technological systems and improving policies and implementation regarding sustainable solutions. The efficacy of the proposed platform to serve as a holistic data information system is assessed by exploring important characteristics associated with geospatial NSDI tools, namely, openness, spatial functionality, scalability, and standardization. By placing GIS strengths and weaknesses in the context of transdisciplinary NBSs, we reveal strategic directions toward further co-production of such NSDIs. We conclude with recommendations for facilitating a shared vision of transdisciplinary technologies to strengthen the amalgamation of broad co-benefits and multi-disciplinary influences in sustainability planning. Full article

(This article belongs to the Topic Geoinformatics Evaluations of Environmental Dynamism and Future Sustainability)

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