scholarly journals Environmental Armed Conflict Assessment Using Satellite Imagery

2020 ◽  
Vol 13 (3-4) ◽  
pp. 1-14
Author(s):  
Fernando Arturo Mendez Garzón ◽  
István Valánszki

Abstract Armed conflicts not only affect human populations but can also cause considerable damage to the environment. Its consequences are as diverse as its causes, including; water pollution from oil spills, land degradation due to the destruction of infrastructure, poisoning of soils and fields, destruction of crops and forests, over-exploitation of natural resources and paradoxically and occasionally reforestation. In this way, the environment in the war can be approached as beneficiary, stage, victim or/and spoil of war. Although there are few papers that assess the use of remote sensing methods in areas affected by warfare, we found a gap in these studies, being both outdated and lacking the correlation of remote sensing analysis with the causes-consequences, biome features and scale. Thus, this paper presents a methodical approach focused on the assessment of the existing datasets and the analysis of the connection between geographical conditions (biomes), drivers and the assessment using remote sensing methods in areas affected by armed conflicts. We aimed to find; weaknesses, tendencies, patterns, points of convergence and divergence. Then we consider variables such as biome, forest cover affectation, scale, and satellite imagery sensors to determine the relationship between warfare drivers with geographical location assessed by remote sensing methods. We collected data from 44 studies from international peer-reviewed journals from 1998 to 2019 that are indexed using scientific search engines. We found that 62% of the studies were focused on the analysis of torrid biomes as; Tropical Rainforest, Monsoon Forest / Dry Forest, Tree Savanna and Grass Savanna, using the 64% Moderate-resolution satellite imagery sensors as; Landsat 4-5 TM and Landsat 7 ETM+. Quantitative analysis of the trends identified within these areas contributes to an understanding of the reasons behind these conflicts.

Author(s):  
Dmytro Liashenko ◽  
◽  
Dmytro Pavliuk ◽  
Vadym Belenok ◽  
Vitalii Babii ◽  
...  

The article studies the issues of using remote sensing data for the tasks of ensuring sustainable nature management in the territories within the influence of transport infrastructure objects. Peculiarities of remote monitoring for tasks of transport networks design and in the process of their operation are determined. The paper analyzes the development of modern remote sensing methods (satellite imagery, the use of mobile sensors installed on cars or aircraft). A brief overview of spatial data collecting methods for the tasks of managing the development of territories within the influence of transport infrastructure (roads, railways, etc.) has made. The article considers the experience of using remote sensing technologies to monitor changes in the parameters of forest cover in the Transcarpathian region (Ukraine) in areas near to highways, by use Landsat imagery.


2020 ◽  
Vol 62 (4) ◽  
pp. 288-305
Author(s):  
Addo Koranteng ◽  
Isaac Adu-Poku ◽  
Emmanuel Donkor ◽  
Tomasz Zawiła-Niedźwiecki

AbstractLand use and land cover (LULC) terrain in Ghana has undergone profound changes over the past years emanating mainly from anthropogenic activities, which have impacted countrywide and sub-regional environment. This study is a comprehensive analysis via integrated approach of geospatial procedures such as Remote Sensing (RS) and Geographic Information System (GIS) of past, present and future LULC from satellite imagery covering Ghana’s Ashanti regional capital (Kumasi) and surrounding districts. Multi-temporal satellite imagery data sets of four different years, 1990 (Landsat TM), 2000 (Landsat ETM+), 2010 (Alos and Disaster Monitoring Constellation-DMC) and 2020 (SENTINEL), spanning over a 30-year period were mapped. Five major LULC categories – Closed Forest, Open Forest, Agriculture, Built-up and Water – were delineated premised on the prevailing geographical settings, field study and remote sensing data. Markov Cellular Automata modelling was applied to predict the probable LULC change consequence for the next 20 years (2040). The study revealed that both Open Forest and Agriculture class categories decreased 51.98 to 38.82 and 27.48 to 20.11, respectively. Meanwhile, Built-up class increased from 4.8% to 24.8% (over 500% increment from 1990 to 2020). Rapid urbanization caused the depletion of forest cover and conversion of farmlands into human settlements. The 2040 forecast map showed an upward increment in the Built-up area up to 35.2% at the expense of other LULC class categories. This trend from the past to the forecasted future would demand that judicious LULC resolutions have to be made to keep Ghana’s forest cover, provide arable land for farming activities and alleviate the effects of climate change.


2009 ◽  
Vol 26 (4) ◽  
pp. 148-155
Author(s):  
Nathan A. Briggs ◽  
Steven A. Sader

Abstract Conversion of forestland to other uses is occurring in Maine as growing human populations and desire for second homes are exerting development pressures on privately owned forestland. This study was performed to assess forest cover change and conversion to developed uses in a 636,000-hastudy area in Maine. A three-date time series (2000, 2002, and 2006) of Landsat Thematic Mapper data was analyzed to detect forest cover losses, and overall mapping accuracy was determined to be 91%. Forest cover losses (percentage per year) were aggregated for 81 townships and reported foreach time sequence. Rates of forest cover loss differ among townships and for the same township in different time periods. Visual interpretation of forestland conversion using high-resolution images for a subsample of 24 townships showed that 305 of 4,716 harvested forest hectares (6.47%)was converted to developed uses. The study demonstrates the practical use of low-cost remote-sensing imagery and routine interpretation methods for accurate tracking of forest change and quantification of land use conversion. The methods are adaptable to other states to assist decisionmakersin assessing regional and local land use and planning forest conservation measures.


2020 ◽  
Author(s):  
Ian McCallum ◽  
Stefan Velev ◽  
Finn Laurien ◽  
Reinhard Mechler ◽  
Adriana Keating ◽  
...  

<p>The purpose of the “Flood Resilience Dashboard” is to put geo-spatial flood resilience data into the hands of practitioners. The idea is to provide an intuitive platform that combines as much open, peer-reviewed flood resilience related spatial data as possible with available related spatial data from the Flood Resilience Alliance, which in turn can be used to inform decisions. This data will include among others the Zurich Flood Resilience Measurement for Communities (FRMC) data, Vulnerability Capacity Assessment (VCA) maps, remote sensing derived information on flooding and other biophysical datasets (e.g. forest cover, water extent), modelled risk information, satellite imagery (e.g. night-time lights), crowdsourced data and more. </p><p>The Dashboard will, as much as possible, lower the entry barrier for non-technical users, providing a simple login experience for the users. Users should be able to explore the Dashboard using standard web map navigation tools. The various charts and tables on the Dashboard dynamically refresh as features on the map are selected or the map extent is changed. No previous experience or understanding of geo-spatial data is required, beyond basic web-map navigation.</p>


2011 ◽  
Vol 33 (3) ◽  
pp. 229 ◽  
Author(s):  
Roderick J. Fensham ◽  
Owen Powell ◽  
James Horne

There is a prevailing paradigm that woody vegetation is expanding at the expense of grassland with reduced burning under pastoralism in the Mulga Lands biogeographic region in eastern Australia. This raises the possibility that the region is acting as a carbon sink. Vegetation boundaries were precisely positioned from rail survey plans dating from 1895 to 1900. This baseline was compared with the position of boundaries on 1952 aerial photography and 2010 Google Earth imagery. The conversion of forest to non-forest by mechanical clearing was also mapped from satellite imagery. There was no consistent trend in the direction of boundary movement for mulga (Acacia aneura F.Muell. ex Benth.), gidgee (Acacia cambagei R.T. Baker) forest or miscellaneous other forest types. The stability of the boundaries, despite the transition from aboriginal management to rangeland pastoralism, contrasts with dramatic declines in tree cover resulting from mechanical clearing. Mapping of forest cover from satellite imagery reveals that conversion of forest to non-forest has reduced mulga forest to 74%, gidgee forest to 30% and miscellaneous forest types to 82% of their original area. Annual clearing rates for the period between 1997 and 2005 were 0.83, 0.95 and 0.43% for those forest types, respectively. Clearing has declined substantially in the period 2005–09 since the advent of recent regulations in Queensland. The area remains a source of carbon emissions but this situation may reverse if restoration of mulga dry forest becomes an attractive land use with an emerging carbon market.


2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Jan Piekarczyk

AbstractWith increasing intensity of agricultural crop production increases the need to obtain information about environmental conditions in which this production takes place. Remote sensing methods, including satellite images, airborne photographs and ground-based spectral measurements can greatly simplify the monitoring of crop development and decision-making to optimize inputs on agricultural production and reduce its harmful effects on the environment. One of the earliest uses of remote sensing in agriculture is crop identification and their acreage estimation. Satellite data acquired for this purpose are necessary to ensure food security and the proper functioning of agricultural markets at national and global scales. Due to strong relationship between plant bio-physical parameters and the amount of electromagnetic radiation reflected (in certain ranges of the spectrum) from plants and then registered by sensors it is possible to predict crop yields. Other applications of remote sensing are intensively developed in the framework of so-called precision agriculture, in small spatial scales including individual fields. Data from ground-based measurements as well as from airborne or satellite images are used to develop yield and soil maps which can be used to determine the doses of irrigation and fertilization and to take decisions on the use of pesticides.


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