Cradle to grave Life Cycle Assessment of Lebanese biomass briquettes

Land degradation is a gradual, negative environmental process that is accelerated by human activities. Its gradual nature allows degradation to proceed unnoticed, thus reducing the likelihood of appropriate and timely control action. Presently, there are few practical frameworks to help countries design national strategies and policies for its control. The study presented here developed a framework for the national assessment of land degradation. This framework is envisaged to support governments in formulating policies on land degradation. It uses time-series remote sensing data to identify the rate and extent of land degradation, local experts to identify prevalent degradation types and drivers of the degradation and field observations to validate the overall assessment. Its simplicity, use of freely downloadable input data and self-triangulation of the assessment methods make it suitable for rapid assessment of land degradation on a national scale. It was tested in Somalia, where it exhibited accuracy greater than 60 per cent when assessing land degradation. This framework is relevant for designing national strategies and policies that address land degradation and provides an opportunity for accurate identification of areas to target with comprehensive local assessment. Testing of the framework in Somalia showed that about one-third of the country was degraded because of loss of vegetation cover, topsoil loss and to the decline of soil moisture. Overgrazing, excessive tree cutting and poor agronomic practices in agricultural areas were identified as the primary drivers of the country's land degradation. These drivers are encouraged by the prevailing communal land tenure practices, poor governance and civil war. Copyright © 2011 John Wiley & Sons, Ltd.

A framework for national assessment of land degradation in the drylands

. The induction of biocrusts through inoculation-based techniques has gained increasing scientific attention in the last 2 decades due to its potential to address issues related to soil degradation and desertification. The technology has shown the most rapid advances in the use of biocrust organisms, particularly cyanobacteria and mosses, as inoculants and biocrust initiators. Cyanobacteria and mosses are
poikilohydric organisms – i.e., desiccation-tolerant organisms capable of
reactivating their metabolism upon rehydration – that can settle on bare soils in abiotically stressing habitats, provided that selected species are used and an appropriate and customized protocol is applied. The success of inoculation of cyanobacteria and mosses depends on the inoculant's physiology, but also on the ability of the practitioner to
identify and control, with appropriate technical approaches in each case
study, those environmental factors that most influence the inoculant
settlement and its ability to develop biocrusts. This review illustrates the current knowledge and results of biocrust
induction biotechnologies that use cyanobacteria or mosses as inoculants. At the same time, this review's purpose is to highlight the current
technological gaps that hinder an efficient application of the technology in the field.

/pdf/drought-tolerant-cyanobacteria-and-mosses-as-bieu2pndx9.pdf

Drought-tolerant cyanobacteria and mosses as biotechnological tools to attain land degradation neutrality

Land degradation neutrality: A review of progress and perspectives

Comprehensive forest cover mapping is essential for making policy and management decisions. However, creating a forest cover map from raw remote sensing data is a barrier for many users. Here, we investigated the effects of different tree cover thresholds on the accuracy of forest cover maps derived from the Global Forest Change Dataset (GFCD) across different ecological zones in a country-scale evaluation of Myanmar. To understand the effect of different thresholds on map accuracy, nine forest cover maps having thresholds ranging from 10% to 90% were created from the GFCD. The accuracy of the forest cover maps within each ecological zone and at the national scale was assessed. The overall accuracies of ecological zones other than tropical rainforest were highest when the threshold for tree cover was less than 50%. The appropriate threshold for tropical rainforests was 80%. Therefore, different optimal tree cover thresholds were required to achieve the highest overall accuracy depending on ecological zones. However, in the unique case of Myanmar, we were able to determine the threshold across the whole country. We concluded that the threshold for tree cover for creating a forest cover map should be determined according to the areal ratio of ecological zones determined from large-scale monitoring. Our results are applicable to tropical regions having similar ecological zones.

https://www.mdpi.com/1999-4907/10/12/1062/pdf

Assessing the Importance of Tree Cover Threshold for Forest Cover Mapping Derived from Global Forest Cover in Myanmar

Assessing land degradation is essentially needed for decision-makers to monitor and mitigate degradation and implement sustainable land management practices. More specifically, monitoring land degradation on a regular basis enables decision-makers to analyze impact of degradation and effects of sustainable land management practices. This requires adopting a precise methodology for assessing land degradation. With information form assessments, decision-makers can establish achievable management goals to attain land degradation neutrality as addressed by the Sustainable Development Goal 15 (i.e., SDG 15). Accordingly, this work aimed at developing a systematic approach for assessing land degradation at the subnational level with the combined use of geo-spatial information and field data. The specific objectives were to (1) assess trends in land degradation and the impact of historical land uses on the current landscape characters, (2) investigate and characterize principal criteria of land degradation, and (3) identify sustainable land management practices. Multi-source and multi-resolution spatial data were employed for assessing the three indicators of land degradation neutrality (i.e., changes in vegetation cover, land productivity, and soil organic carbon). Prioritizing lands prone to degradation was investigated using a set of spatial attributes of different weights. Field data collection involved the use of pre-defined set of questions for assessing the principal criteria of land degradation including type, extent, rate, degree, and causes of land degradation. Sustainable land management practices were identified and categorized accordingly. This assessment provided a means for prioritization of interventions (i.e., prevention, mitigation, and/or rehabilitation) in an area characterized by a climate varying from semi-arid to moist subhumid.

Assessing land degradation and identifying potential sustainable land management practices at the subnational level in Lebanon

Regular detection and timely monitoring of shoreline evolution are essentially needed in order to identify areas that require further investigation and protection. Possibilities for regular monitoring of shoreline changes are better facilitated now with high-frequency revisit times of Landsat-Sentinel-2 virtual constellation. Accordingly, this study aimed at investigating the performance of Landsat 8 and Sentinel-2A satellite imagery in mapping shoreline changes. The specific objectives were to 1) create reference data of shoreline erosion, accretion and seafilling using very high spatial resolution data, 2) compare the results of shoreline changes by using Landsat 8 and Sentinel-2A imagery respectively, and 3) complete the inventory of shoreline changes between 1962 and 2016. A Quickbird panchromatic imagery (0.6 m) of 2010 was employed in combination with aerial photography (0.5 m) from 1962 for the generation of reference data using a traditional photo-interpretation method. Then, geographic object-based image analysis (GEOBIA) was employed to map changes in the shoreline between 1962 (i.e., reference shoreline) and 2016 using Sentinel-2A (10 m) and Landsat 8 panchromatic band (15 m) imagery, consecutively. The use of Sentinel-2A image provided slightly better accuracy results when compared with those from the Landsat 8 image. Accordingly, an inventory of Lebanese shoreline evolution between 1962 and 2016 was completed using the Sentinel-2A classification results. The combined use of Landsat-Sentinel-2 imagery is expected to generate reliable data records for continuous monitoring of shoreline changes.

Investigating the performance of sentinel-2A and Landsat 8 imagery in mapping shoreline changes

Assessment of potential risk of land degradation, especially after fire events, is essential for identifying and prioritizing sites for post-fire management. This study aimed to model potential post-fire land degradation risk in Lebanon in order to plan and prioritize post-fire management actions. The specific objectives were to 1) map “burn severity” of the year 2019 using Landsat 8 and Sentinel 2-A imagery and 2) model post-fire land degradation risk using a Geographic ObjectBased Image Analysis (GEOBIA) approach. Initially, mapping burned areas of the 2019 fire season involved the use of a differenced Normalized Burn Ratio (dNBR) of Sentinel 2-A imagery. Another dNBR image was produced with the use of Landsat 8 imagery. Mapping overall burn severity was conducted based on cross-mapping between the two dNBR images which involved data sources of different spatial and spectral characteristics. Potential post-fire degradation risk was modelled in GEOBIA with the combined use of burn severity and topographic data (i.e., slope gradients). In addition, field data was collected to produce a Composite Burn Index (CBI) of fire-affected sites. The correlation between field data (i.e., CBI scores) and imagery analysis (i.e., dNBR data from Sentinel 2-A and Landsat 8) was assessed using a Spearman correlation test. The combined use of satellite remote sensing images (i.e., polygons of postfire degradation risk) and their corresponding ancillary data (i.e., CBI and soil texture) allowed the prioritization of fire affected sites for implementing post-fire restoration measures.

Assessment of post-fire land degradation risk in Lebanon's 2019 fire affected areas using remote sensing and GIS

http://manuscript.elsevier.com/S1309104222000617/pdf/S1309104222000617.pdf

Karen Gebrael

Papers

Assessing land degradation and identifying potential sustainable land management practices at the subnational level in Lebanon

Investigating the performance of sentinel-2A and Landsat 8 imagery in mapping shoreline changes

Assessment of post-fire land degradation risk in Lebanon's 2019 fire affected areas using remote sensing and GIS

Quantifying indoor PM2.5 levels and its sources in schools: What role does location, chalk use, and socioeconomic equity play ?

Assessment of socio-economic factors affecting energy consumption for residential heating in the Caza of Koura, Lebanon.