244 research outputs found
Land Degradation Assessment with Earth Observation
This Special Issue (SI) on “Land Degradation Assessment with Earth Observation” comprises 17 original research papers with a focus on land degradation in arid, semiarid and dry-subhumid areas (i.e., desertification) in addition to temperate rangelands, grasslands, woodlands and the humid tropics. The studies cover different spatial, spectral and temporal scales and employ a wealth of different optical and radar sensors. Some studies incorporate time-series analysis techniques that assess the general trend of vegetation or the timing and duration of the reduction in biological productivity caused by land degradation. As anticipated from the latest trend in Earth Observation (EO) literature, some studies utilize the cloud-computing infrastructure of Google Earth Engine to cope with the unprecedented volume of data involved in current methodological approaches. This SI clearly demonstrates the ever-increasing relevance of EO technologies when it comes to assessing and monitoring land degradation. With the recently published IPCC Reports informing us of the severe impacts and risks to terrestrial and freshwater ecosystems and the ecosystem services they provide, the EO scientific community has a clear obligation to increase its efforts to address any remaining gaps—some of which have been identified in this SI—and produce highly accurate and relevant land-degradation assessment and monitoring tools
Assessing the relationship between the soil dielectric constant and electrical conductivity using 5TE sensors in the field conditions
Postprint (published version
Study of land degradation and desertification dynamics in North Africa areas using remote sensing techniques
In fragile-ecosystem arid and semi-arid land, climatic variations, water scarcity and human pressure
accelerate ongoing degradation of natural resources. In order to implement sustainable
management, the ecological state of the land must be known and diachronic studies to monitor and
assess desertification processes are indispensable in this respect. The present study is developed in
the frame of WADIS-MAR (www.wadismar.eu). This is one of the five Demonstration Projects
implemented within the Regional Programme “Sustainable Water Integrated Management (SWIM)”
(www.swim-sm.eu ), funded by the European Commission and which aims to contribute to the
effective implementation and extensive dissemination of sustainable water management policies
and practices in the Southern Mediterranean Region. The WADIS-MAR Project concerns the
realization of an integrated water harvesting and artificial aquifer recharge techniques in two
watersheds in Maghreb Region: Oued Biskra in Algeria and wadi Oum Zessar in Tunisia.
The WADIS MAR Project is coordinated by the Desertification Research Center of the University
of Sassari in partnership with the University of Barcelona (Spain), Institut des RĂ©gions Arides
(Tunisia) and Agence Nationale des Ressources Hydrauliques (Algeria) and the international
organization Observatorie du Sahara et du Sahel. The project is coordinated by Prof. Giorgio
Ghiglieri. The project aims at the promotion of an integrated, sustainable water harvesting and
agriculture management in two watersheds in Tunisia and Algeria. As agriculture and animal
husbandry are the two main economic activities in these areas, demand and pressure on natural
resources increase in order to cope with increasing population’s needs. In arid and semiarid study
areas of Algeria and Tunisia, sustainable development of agriculture and resources management
require the understanding of these dynamics as it withstands monitoring of desertification
processes.
Vegetation is the first indicator of decay in the ecosystem functions as it is sensitive to any
disturbance, as well as soil characteristics and dynamics as it is edaphically related to the former.
Satellite remote sensing of land affected by sand encroachment and salinity is a useful tool for
decision support through detection and evaluation of desertification indicating features.
Land cover, land use, soil salinization and sand encroachment are examples of such indicators that
if integrated in a diachronic assessment, can provide quantitative and qualitative information on the
ecological state of the land, particularly degradation tendencies. In recent literature, detecting and
mapping features in saline and sandy environments with remotely sensed imagery has been reported
successful through the use of both multispectral and hyperspectral imagery, yet the limitations to
both image types maintain “no agreed-on best approach to this technology for monitoring and
mapping soil salinity and sand encroachment”. Problems regarding the image classification of
features in these particular areas have been reported by several researchers, either with statistical or
neural/connectionist algorithms for both fuzzy and hard classifications methods.
In this research, salt and sand features were assessed through both visual interpretation and
automated classification approaches, employing historical and present Landsat imagery (from 1984
to 2015).
The decision tree analysis was chosen because of its high flexibility of input data range and type,
the easiness of class extraction through non-parametric, multi-stage classification. It makes no a
priori assumption on class distribution, unlike traditional statistical classifiers. The visual
interpretation mapping of land cover and land use was undergone according to acknowledged
standard nomenclature and methodology, such as CORINE land cover or AFRICOVER 2000,
Global Land Cove 2000 etc. The automated one implies a decision tree (DT) classifier and an
unsupervised classification applied to the principal components (PC) extracted from Knepper ratios
composite in order to assess their validity for the change detection analysis. In the Tunisian study
area, it was possible to conduct a thorough ground truth survey resulting in a record of 400 ground
truth points containing several information layers (ground survey sheet information on various land
components, photographs, reports in various file formats) stored within the a shareable standalone
geodatabase. Spectral data were also acquired in situ using the handheld ASD FieldSpec 3 Jr. Full
Range (350 – 2500 nm) spectroradiometer and samples were taken for X-ray diffraction analysis.
The sampling sites were chosen on the basis of a geomorphological analysis, ancillary data and the
previously interpreted land cover/land use map, specifically generated for this study employing
Landsat 7 and 8 imagery. The spectral campaign has enabled the acquisition of spectral reflectance
measurements of 34 points, of which 14 points for saline surfaces (9 samples); 10 points for sand
encroachment areas (10 samples); 3 points for typical vegetation (halophyte and psammophyte) and
7 points for mixed surfaces.
Five of the eleven indices employed in the Decision Tree construction were constructed throughout
the current study, among which we propose also a salinity index (SMI) for the extraction of highly
saline areas. Their application have resulted in an accuracy of more than 80%. For the error
estimation phase, the interpreted land cover/use map (both areas) and ground truth data (Oum
Zessar area only) supported the results of the 1984 to 2014 salt – affected areas diachronic analysis
obtained through both automatic methods. Although IsoDATA classification maps applied to
Knepper ratios Principal Component Analysis has proven its good potential as an approach of fast
automated, user-independent classifier, accuracy assessment has shown that decision tree outstood
it and was proven to have a substantial advantage over the former. The employment of the Decision
Tree classifier has proven to be more flexible and adequate for the extraction of highly and
moderately saline areas and major land cover types, as it allows multi-source information and
higher user control, with an accuracy of more than 80%.
Integrating results with ancillary spatial data, we could argue driving forces, anthropic vs natural, as
well as source areas, and understand and estimate the metrics of desertification processes. In the
Biskra area (Algeria), results indicate that the expansion of irrigated farmland in the past three
decades contributes to an ongoing secondary salinization of soils, with an increase of over 75%. In
the Oum Zessar area (Tunisia), there was substantial change in several landscape components in the
last decades, related to increased anthropic pressure and settlement, agricultural policies and
national development strategies. One of the most concerning aspects is the expansion of sand
encroached areas over the last three decades of around 27%
Satellite and UAV Platforms, Remote Sensing for Geographic Information Systems
The present book contains ten articles illustrating the different possible uses of UAVs and satellite remotely sensed data integration in Geographical Information Systems to model and predict changes in both the natural and the human environment. It illustrates the powerful instruments given by modern geo-statistical methods, modeling, and visualization techniques. These methods are applied to Arctic, tropical and mid-latitude environments, agriculture, forest, wetlands, and aquatic environments, as well as further engineering-related problems. The present Special Issue gives a balanced view of the present state of the field of geoinformatics
Impact of agricultural land use in Central Asia: a review
International audienceAbstractAgriculture is major sector in the economy of Central Asia. The sustainable use of agricultural land is therefore essential to economic growth, human well-being, social equity, and ecosystem services. However, salinization, erosion, and desertification cause severe land degradation which, in turn, degrade human health and ecosystem services. Here, we review the impact of agricultural land use in the five countries of Central Asia, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, during 2008–2013 in 362 articles. We use the Land Use Functions framework to analyze the type and relative shares of environmental, economic, and social topics related to agricultural land use. Our major findings are (1) research on land use in Central Asia received high levels of international attention and the trend in the number of publications exceeded the global average. (2) The impacts of land use on abiotic environmental resources were the most explored. (3) Little research is available about how agricultural land use affects biotic resources. (4) Relationships between land degradation, e.g., salinization and dust storms, and human health were the least explored. (5) The literature is dominated by indirect methods of data analysis, such as remote sensing and mathematical modeling, and in situ data collection makes up only a small proportion
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