ISPRS International Journal of Geo-Information

Research

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14 pages, 6956 KiB

Open AccessArticle

Spatial Variability and Clustering of Quality of Life at Local Level: A Geographical Analysis in Athens, Greece

by Antigoni Faka, Kleomenis Kalogeropoulos, Thomas Maloutas and Christos Chalkias

ISPRS Int. J. Geo-Inf. 2022, 11(5), 276; https://doi.org/10.3390/ijgi11050276 - 26 Apr 2022

Cited by 8 | Viewed by 4001

Abstract

This paper presents a geographical analysis to evaluate urban quality of life in Athens, Greece, and investigate spatial heterogeneity and potential clustering. The urban environment was examined using composite criteria related to natural, built and socioeconomic environment, housing conditions, public services and infrastructures, [...] Read more.

This paper presents a geographical analysis to evaluate urban quality of life in Athens, Greece, and investigate spatial heterogeneity and potential clustering. The urban environment was examined using composite criteria related to natural, built and socioeconomic environment, housing conditions, public services and infrastructures, and cultural and recreational facilities. Each criterion constructed from a set of mappable sub-criteria/variables. Weighted cartographic overlay was implemented to assess the overall urban quality of life of each spatial unit, based on the importance the residents of the area attributed to each criterion. High levels of quality of life were revealed in the eastern neighborhoods of the municipality, whereas low levels were noticed mainly in the western neighborhoods. The results of the study were validated using the perceived quality of life of the study area’s residents, resulting in substantial agreement. Finally, after spatial autocorrelation analysis, significant clustering of urban quality of life in Athens was revealed. The quality-of-life assessment and mapping at a local scale are efficient tools, contributing to better decision making and policy making. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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29 pages, 20569 KiB

Open AccessArticle

Rapid Mapping and Annual Dynamic Evaluation of Quality of Urban Green Spaces on Google Earth Engine

by Qiang Chen, Cuiping Zhong, Changfeng Jing, Yuanyuan Li, Beilei Cao and Qianhao Cheng

ISPRS Int. J. Geo-Inf. 2021, 10(10), 670; https://doi.org/10.3390/ijgi10100670 - 2 Oct 2021

Cited by 6 | Viewed by 3137

Abstract

In order to achieve the United Nations 2030 Sustainable Development Goals (SDGs) related to green spaces, monitoring dynamic urban green spaces (UGSs) in cities around the world is crucial. Continuous dynamic UGS mapping is challenged by large computation, time consumption, and energy consumption [...] Read more.

In order to achieve the United Nations 2030 Sustainable Development Goals (SDGs) related to green spaces, monitoring dynamic urban green spaces (UGSs) in cities around the world is crucial. Continuous dynamic UGS mapping is challenged by large computation, time consumption, and energy consumption requirements. Therefore, a fast and automated workflow is needed to produce a high-precision UGS map. In this study, we proposed an automatic workflow to produce up-to-date UGS maps using Otsu’s algorithm, a Random Forest (RF) classifier, and the migrating training samples method in the Google Earth Engine (GEE) platform. We took the central urban area of Beijing, China, as the study area to validate this method, and we rapidly obtained an annual UGS map of the central urban area of Beijing from 2016 to 2020. The accuracy assessment results showed that the average overall accuracy (OA) and kappa coefficient (KC) were 96.47% and 94.25%, respectively. Additionally, we used six indicators to measure quality and temporal changes in the UGS spatial distribution between 2016 and 2020. In particular, we evaluated the quality of UGS using the urban greenness index (UGI) and Shannon’s diversity index (SHDI) at the pixel level. The experimental results indicate the following: (1) The UGSs in the center of Beijing increased by 48.62 km² from 2016 to 2020, and the increase was mainly focused in Chaoyang, Fengtai, and Shijingshan Districts. (2) The average proportion of relatively high and above levels (UGI > 0.5) in six districts increased by 2.71% in the study area from 2016 to 2020, and this proportion peaked at 36.04% in 2018. However, our result revealed that the increase was non-linear during this assessment period. (3) Although there was no significant increase or decrease in SHDI values in the study area, the distribution of the SHDI displayed a noticeable fluctuation in the northwest, southwest, and northeast regions of the study area between 2016 and 2020. Furthermore, we discussed and analyzed the influence of population on the spatial distribution of UGSs. We found that three of the five cold spots were located in the east and southeast of Haidian District. Therefore, the proposed workflow could provide rapid mapping and dynamic evaluation of the quality of UGS. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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19 pages, 3582 KiB

Open AccessArticle

How Did Built Environment Affect Urban Vitality in Urban Waterfronts? A Case Study in Nanjing Reach of Yangtze River

by Zhengxi Fan, Jin Duan, Menglin Luo, Huanran Zhan, Mengru Liu and Wangchongyu Peng

ISPRS Int. J. Geo-Inf. 2021, 10(9), 611; https://doi.org/10.3390/ijgi10090611 - 15 Sep 2021

Cited by 39 | Viewed by 4709

Abstract

The potential of urban waterfronts as vibrant urban spaces has become a focus of urban studies in recent years. However, few studies have examined the relationships between urban vitality and built environment characteristics in urban waterfronts. This study takes advantage of emerging urban [...] Read more.

The potential of urban waterfronts as vibrant urban spaces has become a focus of urban studies in recent years. However, few studies have examined the relationships between urban vitality and built environment characteristics in urban waterfronts. This study takes advantage of emerging urban big data and adopts hourly Baidu heat map (BHM) data as a proxy for portraying urban vitality along the Yangtze River in Nanjing. The impact of built environment on urban vitality in urban waterfronts is revealed with the ordinary least squares (OLS) and geographically weighted regression (GWR) models. The results show that (1) the distribution of urban vitality in urban waterfronts shows similar agglomeration characteristics on weekdays and weekends, and the identified vibrant cores tend to be the important city and town centers; (2) the building density has the strongest positive associations with urban vitality in urban waterfronts, while the normalized difference vegetation index (NDVI) is negative; (3) the effects of the built environment on urban vitality in urban waterfronts have significant spatial variations. Our findings can provide meaningful guidance and implications for vitality-oriented urban waterfronts planning and redevelopment. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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29 pages, 6359 KiB

Open AccessArticle

A GIS Assessment of the Suitability of Tilapia and Clarias Pond Farming in Tanzania

by Håkan Berg, Deogratias Mulokozi and Lars Udikas

ISPRS Int. J. Geo-Inf. 2021, 10(5), 354; https://doi.org/10.3390/ijgi10050354 - 20 May 2021

Cited by 2 | Viewed by 4046

Abstract

Aquaculture production in Tanzania has increased in recent years, responding to an increased demand for fish, but the scale and productivity of smallholder aquaculture remains below the level needed to support significant sector growth in Tanzania. This study assesses, through geospatial analyses, the [...] Read more.

Aquaculture production in Tanzania has increased in recent years, responding to an increased demand for fish, but the scale and productivity of smallholder aquaculture remains below the level needed to support significant sector growth in Tanzania. This study assesses, through geospatial analyses, the suitability for freshwater pond farming of Oreochromis niloticus and Clarias gariepinus in Tanzania, by assessing the geographical distribution of seven criteria (water availability, water temperature, soil texture, terrain slope, availability of farm inputs, potential farm-gate sales, and access to local markets) identified as important for fish pond farming. The criteria were developed and standardized from 15 sub-criteria, which were classified into a four-level suitability scale based on physical scores. The individual weights of the different criteria in the overall GIS suitability assessment were determined through a multi-criteria evaluation. The final results were validated and compared through field observations, interviews with 89 rural and 11 urban aquaculture farmers, and a questionnaire survey with 16 regional fisheries officers. Our results indicate that there is a good potential for aquaculture in Tanzania. Almost 60% of Tanzania is assessed as being suitable and 40% as moderately suitable for small-scale subsistence pond farming, which is the dominating fish farming practice currently. The corresponding figures for medium-scale commercial farming, which many regions expect to be the dominating farming method within ten-years, were 52% and 47% respectively. The availability of water was the most limiting factor for fish pond farming, which was confirmed by both farmers and regional fisheries officers, and assessed as being “suitable” in only 28% of the country. The availability of farm-gate sales and local markets were “moderate suitable” to “suitable” and were seen as a constraint for commercial farms in rural areas. The availability of farm inputs (agriculture waste and manure) was overall good (26% very suitable and 32% suitable), but high-quality fish feed was seen as a constraint to aquaculture development, both by farmers and regional fisheries officers. Soil, terrain, and water temperature conditions were assessed as good, especially at low altitudes and in regions close to the sea and south of Lake Victoria. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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18 pages, 7947 KiB

Open AccessArticle

Urban Quality of Life: Spatial Modeling and Indexing in Athens Metropolitan Area, Greece

by Antigoni Faka, Kleomenis Kalogeropoulos, Thomas Maloutas and Christos Chalkias

ISPRS Int. J. Geo-Inf. 2021, 10(5), 347; https://doi.org/10.3390/ijgi10050347 - 18 May 2021

Cited by 14 | Viewed by 4627

Abstract

The purpose of this study is to assess and visualize the Quality of Life provided by urban space as a place of residence. The proposed methodology, after its theoretical documentation, is implemented in Athens Metropolitan Area, Greece. For the evaluation of Urban Quality [...] Read more.

The purpose of this study is to assess and visualize the Quality of Life provided by urban space as a place of residence. The proposed methodology, after its theoretical documentation, is implemented in Athens Metropolitan Area, Greece. For the evaluation of Urban Quality of Life, a complex index is constructed by using multicriteria analysis. For this purpose, Quality of Life controlling factors such as built space, natural, socioeconomic, and cultural environment, infrastructure and services, and the quality of housing were analyzed within a GIS environment. The mapping of this index led to the identification of areas with different levels of Quality of Life. The results of the research can lead to more effective decision making regarding the planning of targeted actions and the distribution of financial resources to improve the Quality of Life of the residents in urban areas. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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18 pages, 4096 KiB

Open AccessArticle

Spatial Distribution Characteristics of Heavy Metals in Surface Soil of Xilinguole Coal Mining Area Based on Semivariogram

by Guoqing Chen, Yong Yang, Xinyao Liu and Mingjiu Wang

ISPRS Int. J. Geo-Inf. 2021, 10(5), 290; https://doi.org/10.3390/ijgi10050290 - 2 May 2021

Cited by 10 | Viewed by 3449

Abstract

Heavy metal pollution is a major environmental problem facing humankind. Locating the source and distribution of heavy metal pollutants around mines can provide a scientific basis for environmental control. The structure effect and random effect of a semivariogram can be used to determine [...] Read more.

Heavy metal pollution is a major environmental problem facing humankind. Locating the source and distribution of heavy metal pollutants around mines can provide a scientific basis for environmental control. The structure effect and random effect of a semivariogram can be used to determine the reason for spatial differences in the heavy metal content in surface soil, and the coefficient of variation and regression analysis can be used to confirm that the verification accuracy meets the geostatistical requirements. According to the maximum difference method, the content of heavy metals in the surface soil of the mining area is higher than that of the surroundings, and Cu and Zn levels are higher than the background values for Inner Mongolia. In the present case, Zn, Mn, Pb, Cr, Ni, and Cu levels exceeded the background values for the surroundings of the study area by 65.10%, 53.72%, 52.17%, 46.24%, 33.08%, and 29.49%, respectively. The results show that human activities play a decisive role in the spatial distribution of heavy metals, leading to their spatial distribution in the form of “core periphery”. This distribution pattern was significantly affected by the slope, NDVI value, and the distance from the mining area, but the spatial distribution of Pb was significantly related to high-grade roads. The research methods and conclusions have reference significance for the sources and spatial distribution characteristics of heavy metal pollution in similar mining areas and provide a target for the prevention and control of environmental pollution in the study area. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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19 pages, 5103 KiB

Open AccessEditor’s ChoiceArticle

Assessing Quality of Life Inequalities. A Geographical Approach

by Antigoni Faka

ISPRS Int. J. Geo-Inf. 2020, 9(10), 600; https://doi.org/10.3390/ijgi9100600 - 12 Oct 2020

Cited by 23 | Viewed by 5365

Abstract

This study proposes an integrated methodology for evaluating and mapping quality of life (QoL) and the quality of a place as residence area, at local level. The QoL assessment was based on the development of composite criteria, using geographical variables that evaluate QoL, [...] Read more.

This study proposes an integrated methodology for evaluating and mapping quality of life (QoL) and the quality of a place as residence area, at local level. The QoL assessment was based on the development of composite criteria, using geographical variables that evaluate QoL, and geographic information systems. The composite criteria are related to the natural and the socioeconomic environment, the housing conditions, the infrastructure and services, and the cultural and recreational facilities. Each criterion was evaluated by a set of variables and each variable was weighted based on the residents’ preferences and the analytical hierarchy process. The criteria were also weighted and combined to assess overall QoL. The methodology was implemented in the Municipality of Katerini, Greece, and QoL mapping led to the zoning of the study area and the identification of areas with low and high QoL. The results revealed the highest level of overall QoL in three out of twenty-nine communities, which provide better housing conditions and access to public services and infrastructures, combining also qualitative natural environment, whereas five mountainous and remote communities scored the lowest level. Mapping QoL may support decision making strategies that target to improve human well-being, increase QoL levels and upgrade living conditions. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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21 pages, 6944 KiB

Open AccessArticle

Assessment and Mapping of Spatio-Temporal Variations in Human Mortality-Related Parameters at European Scale

by Panagiotis Andreopoulos, Christos Polykretis and Alexandra Tragaki

ISPRS Int. J. Geo-Inf. 2020, 9(9), 547; https://doi.org/10.3390/ijgi9090547 - 15 Sep 2020

Cited by 3 | Viewed by 2313

Abstract

Research efforts focusing on better understanding and capture of mortality progression over the time are considered to be of significant interest in the field of demography. On a demographic basis, mortality can be expressed by different physical parameters. The main objective of this [...] Read more.

Research efforts focusing on better understanding and capture of mortality progression over the time are considered to be of significant interest in the field of demography. On a demographic basis, mortality can be expressed by different physical parameters. The main objective of this study is the assessment and mapping of four such parameters at the European scale, during the time period 1993–2013. Infant mortality (parameter θ), population aging (parameter ξ), and individual and population mortality due to unexpected exogenous factors/events (parameter κ and λ, respectively) are represented from these parameters. Given that their estimation is based on demographics by age and cause of death, and in order to be examined and visualized by gender, time-specific mortality and population demographic data with respect to gender, age, and cause of death was used. The resulting maps present the spatial patterns of the estimated parameters as well as their variations over the examined period for both male and female populations of 22 European countries in all. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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20 pages, 4799 KiB

Open AccessArticle

An Integrated Spatiotemporal Pattern Analysis Model to Assess and Predict the Degradation of Protected Forest Areas

by Ramandeep Kaur M. Malhi, Akash Anand, Prashant K. Srivastava, G. Sandhya Kiran, George P. Petropoulos and Christos Chalkias

ISPRS Int. J. Geo-Inf. 2020, 9(9), 530; https://doi.org/10.3390/ijgi9090530 - 2 Sep 2020

Cited by 12 | Viewed by 3997

Abstract

Forest degradation is considered to be one of the major threats to forests over the globe, which has considerably increased in recent decades. Forests are gradually getting fragmented and facing biodiversity losses because of climate change and anthropogenic activities. Future prediction of forest [...] Read more.

Forest degradation is considered to be one of the major threats to forests over the globe, which has considerably increased in recent decades. Forests are gradually getting fragmented and facing biodiversity losses because of climate change and anthropogenic activities. Future prediction of forest degradation spatiotemporal dynamics and fragmentation is imperative for generating a framework that can aid in prioritizing forest conservation and sustainable management practices. In this study, a random forest algorithm was developed and applied to a series of Landsat images of 1998, 2008, and 2018, to delineate spatiotemporal forest cover status in the sanctuary, along with the predictive model viz. the Cellular Automata Markov Chain for simulating a 2028 forest cover scenario in Shoolpaneshwar Wildlife Sanctuary (SWS), Gujarat, India. The model’s predicting ability was assessed using a series of accuracy indices. Moreover, spatial pattern analysis—with the use of FRAGSTATS 4.2 software—was applied to the generated and predicted forest cover classes, to determine forest fragmentation in SWS. Change detection analysis showed an overall decrease in dense forest and a subsequent increase in the open and degraded forests. Several fragmentation metrics were quantified at patch, class, and landscape level, which showed trends reflecting a decrease in fragmentation in forest areas of SWS for the period 1998 to 2028. The improvement in SWS can be attributed to the enhanced forest management activities led by the government, for the protection and conservation of the sanctuary. To our knowledge, the present study is one of the few focusing on exploring and demonstrating the added value of the synergistic use of the Cellular Automata Markov Chain Model Coupled with Fragmentation Statistics in forest degradation analysis and prediction. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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21 pages, 5753 KiB

Open AccessEditor’s ChoiceArticle

High Resolution Viewscape Modeling Evaluated Through Immersive Virtual Environments

by Payam Tabrizian, Anna Petrasova, Perver K. Baran, Jelena Vukomanovic, Helena Mitasova and Ross K. Meentemeyer

ISPRS Int. J. Geo-Inf. 2020, 9(7), 445; https://doi.org/10.3390/ijgi9070445 - 17 Jul 2020

Cited by 8 | Viewed by 4010

Abstract

Visual characteristics of urban environments influence human perception and behavior, including choices for living, recreation and modes of transportation. Although geospatial visualizations hold great potential to better inform urban planning and design, computational methods are lacking to realistically measure and model urban and [...] Read more.

Visual characteristics of urban environments influence human perception and behavior, including choices for living, recreation and modes of transportation. Although geospatial visualizations hold great potential to better inform urban planning and design, computational methods are lacking to realistically measure and model urban and parkland viewscapes at sufficiently fine-scale resolution. In this study, we develop and evaluate an integrative approach to measuring and modeling fine-scale viewscape characteristics of a mixed-use urban environment, a city park. Our viewscape approach improves the integration of geospatial and perception elicitation techniques by combining high-resolution lidar-based digital surface models, visual obstruction, and photorealistic immersive virtual environments (IVEs). We assessed the realism of our viewscape models by comparing metrics of viewscape composition and configuration to human subject evaluations of IVEs across multiple landscape settings. We found strongly significant correlations between viewscape metrics and participants’ perceptions of viewscape openness and naturalness, and moderately strong correlations with landscape complexity. These results suggest that lidar-enhanced viewscape models can adequately represent visual characteristics of fine-scale urban environments. Findings also indicate the existence of relationships between human perception and landscape pattern. Our approach allows urban planners and designers to model and virtually evaluate high-resolution viewscapes of urban parks and natural landscapes with fine-scale details never before demonstrated. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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19 pages, 5909 KiB

Open AccessArticle

A GIS-Based Multi-Criteria Decision Analysis Model for Determining Glacier Vulnerability

by Mustafa Yalcin

ISPRS Int. J. Geo-Inf. 2020, 9(3), 180; https://doi.org/10.3390/ijgi9030180 - 23 Mar 2020

Cited by 8 | Viewed by 5059

Abstract

Investigating the causes of the spatial heterogeneity of glacial changes offers vital information about glacial behavior and provides forecasting ability to define where glacier retreat may occur in the future. This study was designed to determine the spatial distribution of Ağrı Mountain glacier [...] Read more.

Investigating the causes of the spatial heterogeneity of glacial changes offers vital information about glacial behavior and provides forecasting ability to define where glacier retreat may occur in the future. This study was designed to determine the spatial distribution of Ağrı Mountain glacier vulnerability. The main goal of the current study was to assess the forecasting capabilities of Geographical Information System (GIS)-based Multi-Criteria Decision Analysis (MCDA) for determining the location of the mountain glacier retreat. To estimate the glacier retreat, the following criteria were selected: elevation, aspect, slope, direction, and glacier surface temperature anomaly (GSTA). The entropy method was used for weighting the criteria for the evaluation of the vulnerable areas of the glacier. The results of this method clearly indicate a strong relationship between GSTA, direction, and elevation criteria and glacier retreat. The glacier vulnerability map was created by synthesizing criteria layers with their weights. The vulnerability map provided a consistency of 77.8% in the short term and 92.1% in the long term. In the study, the priority melting zones were determined and glacial retreat locations were forecasted in 10-year periods. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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19 pages, 7136 KiB

Open AccessArticle

Analyzing the Spatiotemporal Patterns in Green Spaces for Urban Studies Using Location-Based Social Media Data

by Hidayat Ullah, Wanggen Wan, Saqib Ali Haidery, Naimat Ullah Khan, Zeinab Ebrahimpour and Tianhang Luo

ISPRS Int. J. Geo-Inf. 2019, 8(11), 506; https://doi.org/10.3390/ijgi8110506 - 10 Nov 2019

Cited by 36 | Viewed by 5774

Abstract

Green parks are vital public spaces and play a major role in urban living and well-being. Research on the attractiveness of green parks often relies on traditional techniques, such as questionnaires and in-situ surveys, but these methods are typically insignificant in scale, time-consuming, [...] Read more.

Green parks are vital public spaces and play a major role in urban living and well-being. Research on the attractiveness of green parks often relies on traditional techniques, such as questionnaires and in-situ surveys, but these methods are typically insignificant in scale, time-consuming, and expensive, with less transferable results and only site-specific outcomes. This article presents an investigative study that uses location-based social network (LBSN) data to collect spatial and temporal patterns of park visits in Shanghai metropolitan city. During the period from July 2016 to June 2017 in Shanghai, China, we analyzed the spatiotemporal behavior of park visitors for 157 green parks and conducted empirical research on the impacts of green spaces on the public’s behavior in Shanghai. Our main findings show (i) the check-in distribution of users in different green spaces; (ii) the seasonal effects on the public’s behavior toward green spaces; (iii) changes in the number of users based on the hour of the day, the intervals of the day (morning, afternoon, evening), and the day of the week; (iv) interesting user behavior variations that depend on temperature effects; and (v) gender-based differences in the number of green park visitors. These results can be used for the purpose of urban city planning for green spaces by accounting for the preferences of visitors. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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Review

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33 pages, 4090 KiB

Open AccessFeature PaperEditor’s ChoiceReview

Geoinformation Technologies in Support of Environmental Hazards Monitoring under Climate Change: An Extensive Review

by Andreas Tsatsaris, Kleomenis Kalogeropoulos, Nikolaos Stathopoulos, Panagiota Louka, Konstantinos Tsanakas, Demetrios E. Tsesmelis, Vassilios Krassanakis, George P. Petropoulos, Vasilis Pappas and Christos Chalkias

ISPRS Int. J. Geo-Inf. 2021, 10(2), 94; https://doi.org/10.3390/ijgi10020094 - 21 Feb 2021

Cited by 51 | Viewed by 7417

Abstract

Human activities and climate change constitute the contemporary catalyst for natural processes and their impacts, i.e., geo-environmental hazards. Globally, natural catastrophic phenomena and hazards, such as drought, soil erosion, quantitative and qualitative degradation of groundwater, frost, flooding, sea level rise, etc., are intensified [...] Read more.

Human activities and climate change constitute the contemporary catalyst for natural processes and their impacts, i.e., geo-environmental hazards. Globally, natural catastrophic phenomena and hazards, such as drought, soil erosion, quantitative and qualitative degradation of groundwater, frost, flooding, sea level rise, etc., are intensified by anthropogenic factors. Thus, they present rapid increase in intensity, frequency of occurrence, spatial density, and significant spread of the areas of occurrence. The impact of these phenomena is devastating to human life and to global economies, private holdings, infrastructure, etc., while in a wider context it has a very negative effect on the social, environmental, and economic status of the affected region. Geospatial technologies including Geographic Information Systems, Remote Sensing—Earth Observation as well as related spatial data analysis tools, models, databases, contribute nowadays significantly in predicting, preventing, researching, addressing, rehabilitating, and managing these phenomena and their effects. This review attempts to mark the most devastating geo-hazards from the view of environmental monitoring, covering the state of the art in the use of geospatial technologies in that respect. It also defines the main challenge of this new era which is nothing more than the fictitious exploitation of the information produced by the environmental monitoring so that the necessary policies are taken in the direction of a sustainable future. The review highlights the potential and increasing added value of geographic information as a means to support environmental monitoring in the face of climate change. The growth in geographic information seems to be rapidly accelerated due to the technological and scientific developments that will continue with exponential progress in the years to come. Nonetheless, as it is also highlighted in this review continuous monitoring of the environment is subject to an interdisciplinary approach and contains an amount of actions that cover both the development of natural phenomena and their catastrophic effects mostly due to climate change. Full article

(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)

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