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Geo-Information Science for Environmental Management under Climate Change

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A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 18474

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Special Issue Editors

Dr. Matteo Gentilucci

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Guest Editor

School of Science and Technology, University of Camerino, 62032 Camerino, Italy
Interests: climate; climate change; climate modelling by GIS; GIS; geostatistical analyses; agroclimatology; hydrogeological risk; remote sensing
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Dr. Marco Materazzi

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Guest Editor

School of Science and Technology, University of Camerino, 62032 Camerino, Italy
Interests: hydrogeological mapping and GIS-based mapping for water resources; soil erosion and land degradation; geomorphology
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Dr. Margherita Bufalini

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Guest Editor

School of Science and Technology, University of Camerino, 62032 Camerino, Italy
Interests: landslide; geological mapping; watershed hydrology; geomorphological hazard; flood hazard; hydrogeological hazard; soil erosion; hydrologic and hydraulic modelling; GIS analysis and mapping
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Prof. Dr. Gilberto Pambianchi

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Guest Editor

School of Science and Technology, University of Camerino, 62032 Camerino, Italy
Interests: structural geomorphology and morphotectonics; slope processes and landslide risk; geomorphological and geothematic cartography; geomorphological evolution of catchment areas and floodplains
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Special Issue Information

Dear Collegues,

Population expansion, anthropogenic changes, environmental pollution, and climate change are stressing the environment and the resources it provides to humanity as a whole. In this context, it is increasingly important to develop models that make it possible to assess the resilience of the environment in the light of external stress. Human-induced climate change causes the greatest environmental variations; however, in-depth monitoring would allow for mitigation of the harmful effects that are threatening natural biodiversity. Vegetation in general and agriculture in particular are very sensitive to these stresses, prompting us to assess their development conditions and the water needs of plant species. At the same time, the situation of water resources is increasingly worrying and requires monitoring both as a supply and as a response to extreme events from both a hydraulic and hydrogeological point of view. GIS software must play a primary role in spatial analysis aimed at monitoring and mitigating these problems, in order to make these studies not only conceptual, but also applicative. Therefore, we cordially invite authors to contribute original research articles and reviews on these fundamental issues that will inevitably determine our future.

This Issue aims to assess the risks of the environment dictated by climate change. Not only that, it would be important to create models of minor basins through GIS for a better understanding of the runoff processes. Furthermore, we would like to evaluate the stress to which vegetation and tree crops are currently subjected compared with the past. The aim of this Special Issue is to create, through GIS-type software, new automated models that allow for the conscious management of the surrounding environment, in the light of ongoing climate change.

We expect empirical or methodological contributions addressing any scientific aspect related to GIS modelling in environmental management:

GIS models to assess the overflow of minor basins based on extreme weather events.
Assessment of the influence of climate change on tree vegetation or agricultural crops.
GIS models to evaluate the activation of surface landslides due to climatic events.
Differentiated hydrogeological risk assessment on the territory, spatializing environmental variables appropriately.
Future climate change forecasts and effect on hydrogeological risk variation.
Remote sensing analysis in order to assess the change in vegetation due to climate change.

We look forward to your valuable contributions.

Dr. Matteo Gentilucci
Prof. Dr. Marco Materazzi
Dr. Margherita Bufalini
Prof. Gilberto Pambianchi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

global warming
climate change effects monitoring
environmental pollution
agricultural productivity
management of the water resources
hydrological and hydrogeological numeric models
landslides triggered by climatic extreme events
risk maps and susceptibility maps
assessment of water needs for crops and tree vegetation

Published Papers (7 papers)

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Research

26 pages, 5576 KiB

Open AccessArticle

GIS and Machine Learning for Analysing Influencing Factors of Bushfires Using 40-Year Spatio-Temporal Bushfire Data

by Wanqin He, Sara Shirowzhan and Christopher James Pettit

ISPRS Int. J. Geo-Inf. 2022, 11(6), 336; https://doi.org/10.3390/ijgi11060336 - 6 Jun 2022

Cited by 6 | Viewed by 3640

Abstract

The causes of bushfires are extremely complex, and their scale of burning and probability of occurrence are influenced by the interaction of a variety of factors such as meteorological factors, topography, human activity and vegetation type. An in-depth understanding of the combined mechanisms of factors affecting the occurrence and spread of bushfires is needed to support the development of effective fire prevention plans and fire suppression measures and aid planning for geographic, ecological maintenance and urban emergency management. This study aimed to explore how bushfires, meteorological variability and other natural factors have interacted over the past 40 years in NSW Australia and how these influencing factors synergistically drive bushfires. The CSIRO’s Spark toolkit has been used to simulate bushfire burning spread over 24 h. The study uses NSW wildfire data from 1981–2020, combined with meteorological factors (temperature, precipitation, wind speed), vegetation data (NDVI data, vegetation type) and topography (slope, soil moisture) data to analyse the relationship between bushfires and influencing factors quantitatively. Machine learning-random forest regression was then used to determine the differences in the influence of bushfire factors on the incidence and burn scale of bushfires. Finally, the data on each influence factor was imported into Spark, and the results of the random forest model were used to set different influence weights in Spark to visualise the spread of bushfires burning over 24 h in four hotspot regions of bushfire in NSW. Wind speed, air temperature and soil moisture were found to have the most significant influence on the spread of bushfires, with the combined contribution of these three factors exceeding 60%, determining the spread of bushfires and the scale of burning. Precipitation and vegetation showed a greater influence on the annual frequency of bushfires. In addition, burn simulations show that wind direction influences the main direction of fire spread, whereas the shape of the flame front is mainly due to the influence of land classification. Besides, the simulation results from Spark could predict the temporal and spatial spread of fire, which is a potential decision aid for fireproofing agencies. The results of this study can inform how fire agencies can better understand fire occurrence mechanisms and use bushfire prediction and simulation techniques to support both their operational (short-term) and strategic (long-term) fire management responses and policies. Full article

(This article belongs to the Special Issue Geo-Information Science for Environmental Management under Climate Change)

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19 pages, 2142 KiB

Open AccessArticle

The Evaluation of Temporal and Spatial Trends of Global Warming and Extreme Ocean Surface Temperatures: A Case Study of Canada

by Yameng Wang, Apurbo Sarkar, Ahmed Khairul Hasan, Yingdong Tian, Qian Wu, Md. Shakhawat Hossain and Feng Wei

ISPRS Int. J. Geo-Inf. 2022, 11(1), 21; https://doi.org/10.3390/ijgi11010021 - 30 Dec 2021

Cited by 2 | Viewed by 2743

Abstract

In recent years, extreme weather has frequently occurred worldwide and caused significant disasters, including large-scale forest fires, rare heat waves, heavy rains, floods, and tornadoes. Those have caused unprecedented losses of human lives and property in some countries, affecting the livelihoods of many people. Climate change and natural disasters are the two hotspots of scientific research today, and there is a certain degree of correlation between the two. Although countries worldwide have long known about climate change and its threats to human existence and have been discussing countermeasures, they have still not been able to carry out concerted and practical actions. The study takes Canada as an example, and selects six representative provinces to evaluate the temporal change characteristics of extreme temperature at different sites. We use MATLAB software to perform multiple linear regression, linear fitting methods, and Pearson correlation analysis to analyze spatial changes and time-space trends. The method studies the relationship between the emergence of extreme weather and climate change and uses the evolutionary game theory to explore whether there is any contradiction between global warming and extreme local cold. The study found: (i) The maximum temperature of most provinces in Canada will be constantly higher, and the minimum temperature will be lower. Generally speaking, the average temperature of each year is slowly decreasing. (ii) The average temperature data of British Columbia (Eastern Pacific) and Quebec (West Atlantic) show that ocean temperature has a specific effect on land temperature in surrounding areas. (iii) Pearson correlation analysis shows that the emergence of extreme weather is closely related to climate change. (iv) The evolution path of the two-party game shows that global warming and the occurrence of extreme local cold are not contradictory. Under the conditions, there is a certain degree of synchronization between the two, interacting and influencing each other. Full article

(This article belongs to the Special Issue Geo-Information Science for Environmental Management under Climate Change)

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13 pages, 2649 KiB

Open AccessArticle

Comparison of Data from Rain Gauges and the IMERG Product to Analyse Precipitation in Mountain Areas of Central Italy

by Matteo Gentilucci, Margherita Bufalini, Fabrizio D’Aprile, Marco Materazzi and Gilberto Pambianchi

ISPRS Int. J. Geo-Inf. 2021, 10(12), 795; https://doi.org/10.3390/ijgi10120795 - 26 Nov 2021

Cited by 5 | Viewed by 1617

Abstract

In central Italy, particularly in the Umbria-Marche Apennines, there are some complete, high-altitude weather stations, which are very important for assessing the climate in these areas. The mountain weather stations considered in this study were Monte Bove Sud (1917 m.a.s.l.), Monte Prata (1816 m.a.s.l.) and Pintura di Bolognola (1360 m.a.s.l.). The aim of this research was to compare the differences between the precipitation measured by the rain gauges and the data obtained by satellite using the IMERG algorithm, at the same locations. The evaluation of possible errors in the estimation of precipitation using one method or the other is fundamental for obtaining a reliable estimate of precipitation in mountain environments. The results revealed a strong underestimation of precipitation for the rain gauges at higher altitudes (Monte Bove Sud and Monte Prata) compared to the same pixel sampled by satellite. On the other hand, at lower altitudes, there was a better correlation between the rain gauge value and the IMERG product value. This research, although localised in well-defined locations, could help to assess the problems in rain detection through mountain weather stations. Full article

(This article belongs to the Special Issue Geo-Information Science for Environmental Management under Climate Change)

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20 pages, 33006 KiB

Open AccessArticle

Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa

by Alice Bernini, Alberto Bosino, Greg A. Botha and Michael Maerker

ISPRS Int. J. Geo-Inf. 2021, 10(11), 729; https://doi.org/10.3390/ijgi10110729 - 28 Oct 2021

Cited by 13 | Viewed by 2664

Abstract

Soil erosion is one of the most challenging environmental issues in the world, causing unsustainable soil loss every year. In South Africa, several episodes of gully erosion have been documented and clearly linked to the presence of Quaternary colluvial deposits on the Drakensberg Mountain footslopes. The aim of this study was to identify and assess the triggering factors of gully erosion in the upper Mkhomazi River basin in KwaZulu-Natal, South Africa. We compiled a gully inventory map and applied remote sensing techniques as well as field surveys to validate the gully inventory. The gullies were subdivided into slope gullies and fluvial gullies. We derived susceptibility maps based on the spatial distribution of gully types to assess the most important driving factors. A stochastic modeling approach (MaxEnt) was applied, and the results showed two susceptibility maps within the spatial distribution of the gully erosion probability. To validate the MaxEnt model results, a subset of the existing inventory map was used. Additionally, by using areas with high susceptibilities, we were able to delineate previously unmapped colluvial deposits in the region. This predictive mapping tool can be applied to provide a theoretical basis for highlighting erosion-sensitive substrates to reduce the risk of expanding gully erosion. Full article

(This article belongs to the Special Issue Geo-Information Science for Environmental Management under Climate Change)

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17 pages, 6637 KiB

Open AccessArticle

Soil Moisture Retrieval Using Polarimetric SAR Data and Experimental Observations in an Arid Environment

by Saeid Gharechelou, Ryutaro Tateishi, Josaphat Tetuko Sri Sumantyo and Brian Alan Johnson

ISPRS Int. J. Geo-Inf. 2021, 10(10), 711; https://doi.org/10.3390/ijgi10100711 - 19 Oct 2021

Cited by 2 | Viewed by 2787

Abstract

Soil moisture is a critical component for Earth science studies, and Synthetic Aperture Radar (SAR) data have high potential for retrieving soil moisture using backscattering models. In this study, polarimetric SAR (PALSAR: Phased Array type L-band Synthetic Aperture Radar) data and polarimetric decompositions including span, entropy/H/alpha, and anisotropy, in combination with surface properties resulting from field and laboratory measurements, are used to categorize the natural surface condition and discriminate the backscatter parameter in the test site for applying the inversion soil moisture retrieval. The work aims to introduce the better of two examined models in the research for soil moisture retrieval over the bare land and sparse vegetation in arid regions. After soil moisture retrieval using the two different models, the results of comparison and validation by field measurement of soil moisture have shown that the Oh model has a more realiable accuracy for soil moisture mapping, although it was very difficult to find the best model due to different characteristics in land cover. It seems the inversion model, with the field observation and polarimetric SAR data, has a good potential for extracting surface natural conditions such as surface roughness and soil moisture; however, over- and under-estimation are observed due to land cover variability. The estimation of accurate roughness and moisture data for each type of land cover can increase the accuracy of the results. Full article

(This article belongs to the Special Issue Geo-Information Science for Environmental Management under Climate Change)

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21 pages, 12381 KiB

Open AccessArticle

Spatio-Temporal Variation Analysis of the Biological Boundary Temperature Index Based on Accumulated Temperature: A Case Study of the Yangtze River Basin

by Guangxun Shi, Peng Ye and Xianwu Yang

ISPRS Int. J. Geo-Inf. 2021, 10(10), 675; https://doi.org/10.3390/ijgi10100675 - 5 Oct 2021

Cited by 3 | Viewed by 1736 | Correction

Abstract

Active accumulated temperature is an important index of agricultural heat resources in a region. Based on the temperature data of the Yangtze River Basin from 1970 to 2014, this paper analyzed the characteristics of the temporal and spatial variations of the biological boundary temperature in the Yangtze River Basin. The main conclusions were drawn as follows: (1) since 1970, the accumulated temperature of ≥0 °C in the northern subtropical zone, mid-subtropical zone, and plateau climate zone showed overall increasing trends, and the trends were 122 (p < 0.001), 87.7 (p < 0.001), and 75.3 °C/10a (p < 0.001), respectively. The accumulated temperature of ≥5 °C showed an upward trend, and the change tendency rates were 122.6 (p < 0.001), 90.5 (p < 0.001), and 81.4 °C/10a (p < 0.001), respectively. The accumulated temperature of ≥10 °C showed overall increasing trends and the trends were 115.7 (p < 0.001), 92.5 (p < 0.001), and 78.9 °C/10a (p < 0.001). Accumulated temperatures of ≥0 °C, ≥5 °C, and ≥10 °C in the northern subtropical zone increased significantly higher than that in the mid-subtropical zone and plateau climate zone. (2) The accumulated temperatures of ≥0 °C, ≥5 °C, and ≥10 °C in the northern subtropical zone showed an abrupt change in 1997. In the mid-subtropical zone and plateau climate zone, there was an abrupt change in the accumulated temperatures of ≥0 °C and ≥5 °C in 1994, and in the northern subtropical zone, the abrupt change of the accumulated temperature ≥10 °C occurred in 1998. (3) There are obvious differences in the biological boundary temperature within the Yangtze River Basin, and the stations with large increases are mainly distributed in the middle and lower reaches, such as the Hanshui Basin, the Poyang Lake Basin, the Taihu Lake Basin, and the middle and lower reaches of the mainstream area. The initial day, final day, and continuous days showed a trend of advancement, postponement, and extension, respectively. Besides, the heat resources showed significant increasing trends, which is of guiding significance for the future production and development of agriculture in the region. With the increase of heat resources in the Yangtze River Basin, appropriate late-maturing varieties should be selected in variety breeding, to make full use of heat resources and improve the quality of agricultural products. Secondly, the planting system should be adjusted and the multiple cropping index improved to steadily increase agricultural output. This brings new opportunities to adjust the structure of the agricultural industry and increase farmers’ income, in the Yangtze River basin. Full article

(This article belongs to the Special Issue Geo-Information Science for Environmental Management under Climate Change)

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25 pages, 6523 KiB

Open AccessArticle

Quantifying the Contributions of Environmental Factors to Wind Characteristics over 2000–2019 in China

by Yuming Lu, Bingfang Wu, Nana Yan, Weiwei Zhu, Hongwei Zeng, Zonghan Ma, Jiaming Xu, Xinghua Wu and Bo Pang

ISPRS Int. J. Geo-Inf. 2021, 10(8), 515; https://doi.org/10.3390/ijgi10080515 - 30 Jul 2021

Cited by 6 | Viewed by 2047

Abstract

Global climate change and human activities have resulted in immense changes in the Earth’s ecosystem, and the interaction between the land surface and the atmosphere is one of the most important processes. Wind is a reference for studying atmospheric dynamics and climate change, analyzing the wind speed change characteristics in historical periods, and studying the influence of wind on the Earth-atmosphere interaction; additionally, studying the wind, contributes to analyzing and alleviating a series of problems, such as the energy crisis, environmental pollution, and ecological deterioration facing human beings. In this study, data from 697 meteorological stations in China from 2000 to 2019 were used to study the distribution and trend of wind speed over the past two decades. The relationships between wind speed and climate factors were explored using statistical methods; furthermore, combined with terrain, climate change, and human activities, we quantified the contribution of environmental factors to wind speed. The results show that a downward trend was recorded before 2011, but overall, there was an increasing trend that was not significant; moreover, the wind speed changes showed obvious seasonality and were more complicated on the monthly scale. The wind speed trend mainly increased in the western region, decreased in the eastern region, was higher in the northeastern, northwestern, and coastal areas, and was lower in the central area. Temperature, bright sunshine duration, evaporation, and precipitation had a strong influence, in which wind speed showed a significant negative correlation with temperature and precipitation and vice versa for sunshine and evapotranspiration. The influence of environmental factors is diverse, and these results could help to develop environmental management strategies across ecologically fragile areas and improve the design of wind power plants to make better use of wind energy. Full article

(This article belongs to the Special Issue Geo-Information Science for Environmental Management under Climate Change)

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