SAR and optical data in land degradation processes estimation: a case study from Southeast Bulgaria

2017 ◽  
Author(s):  
Denitsa Borisova ◽  
Daniela Avetisyan ◽  
Roumen Nedkov ◽  
Emiliya Velizarova
Keyword(s):  
Land Degradation ◽  
Optical Data ◽  
Degradation Processes

Can human-induced land degradation be distinguished from the effects of rainfall variability? A case study in South Africa

2007 ◽  
Vol 68 (2) ◽  
pp. 271-297 ◽  
Author(s):  
K.J. Wessels ◽  
S.D. Prince ◽  
J. Malherbe ◽  
J. Small ◽  
P.E. Frost ◽  
...  
Keyword(s):  
South Africa ◽  
Land Degradation ◽  
Rainfall Variability

An adapted method to assess soil organic carbon stocks in a high mountain region: A LDN case study from Kirgistan

2021 ◽  
Author(s):  
Margarete Korintenberg ◽  
Judith Walter ◽  
Katja Märten ◽  
Jutta Zeitz
Keyword(s):  
Bulk Density ◽  
Land Degradation ◽  
Carbon Stocks ◽  
Mountain Region ◽  
High Mountain ◽  
Fine Soil ◽  
Soil Organic Carbon Stocks ◽  
Global Data ◽  
Soc Stocks

<p>The Sustainable Development Goals (SDGs) adopetd by the United Nations in 2016 include the SDG 15.3 „Land Degradation Neutrality (LDN)“, which aims to reduce land degradation by national efforts of the member states. Three indicators for land degradation were gloablly identified: landcover, land productivity and soil organic carbon stocks (SOC). In particular, the assessment of SOC is challenging in countries where (a) spatial digital data is largely missing and (b) SOC mapping is difficult due to remotness typical for high mountain regions . Global data provided by the Secretariat of the United Nations Convention to Combat Desertification (UNCCD) may be used for reporting, but experience from various countries indicates inaccuracies due to generalisation. This is especially the case for SOC. Moreover, to report on changes in SOC stocks, a comprehensive baseline is mandatory. In order to approach these challenges, Kirgistan, which has signed the SDG’s but still lacks a baseline for SOC, has been chosen for a case study.</p><p>In a multinational project we developed a scientifically based method to map and assess SOC stocks enabling a nationwide upscaling of SOC data (baseline). Using globally available data on landcover, elevation, climate and national soil data, „representative SOC units“ were identified prior to sampling. We assume that mainly these factors determine the spatial variability of SOC and that similar SOC stocks can be expected at comparable site conditions. More than 90% of the surface area, that potentially store SOC, is coverd by only 20 representative units, which were sampled 3-fold in the field. Sampling location within a single unit was determined using a drone to identify a representative location. Using the drone was especially helpful as sampling sites in a high mountain region were often extremely remote. During sampling small-scale variability of SOC was considered in the field. To determine SOC stocks, bulk density of the fine soil, coarse fragments and amount of roots were measured in the laboratory. Furthermore, pH, clay, silt and sand content were analysed to identify further drivers for SOC distribution.</p><p>Results show that spatial distribution of SOC in such a high mountain region is mainly controlled by landcover (cropland, grassland, forest), elevation, bulk density and clay content. Within single landcover classes topographic indices, such as aspect, further determine SOC distribution. This is especially the case for grassland, which is the dominant landcover in Kirgistan (53%). For the assessment of SOC stocks different approaches were compared. For instance, precise assessment of stocks using the bulk density of the fine soil corrected for coarse fragments leads to significantly lower SOC stocks when compared to the global data provided by the UNCCD.</p>

The Risk of Water Erosion on the Foothills of the Middle High Atlas (Morocco): Tagueleft Basin Case Study : خطر التعرية المائية على السفوح بالأطلس الكبير الأوسط (المغرب): دراسة حالة حوض تاكلفت

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Rizki Mohamed
Keyword(s):  
Land Degradation ◽  
Local Development ◽  
Remote Sensing Data ◽  
Potential Method ◽  
Water Erosion ◽  
High Atlas ◽  
Negative Impacts ◽  
The Impact

The Tagueleft basin is geographically located in the northern edges of the Middle High Atlas, which is a geomorphological fragile area. The impact of human activity has accelerated water erosion in this mountains area. This is reflected in dynamic and unstable foothills, a decrease in forests density and degradation in the production of the land. On the other hand, land degradation due to human overexploitation of natural resources has increased land degradation in the area. The interest in the risk of erosion on the foothills in the area under study comes in the context of our contribution to clarify the role of geomatical and geomorphological approaches in explaining and identifying the mechanisms responsible for current foothills dynamism through water erosion and its negative impacts on the environment and local development. The aim of the study was to use the EPM (Erosion Potential Méthod) which is formulated by Slobodan Gavrilovic for erosion in mountainous areas and to test the reliability of its results based on fieldwork and remote sensing data. The results of the erosion assessment and its quantification by applying the coefficient (W) for the theoretical model in the area under study have shown that erosion is very important and it touches on wide areas as it appears through the domain classification of the distribution erosion in Tagueleft basin.

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