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02-08: Frontier of Sustainable Land Management Research
10:30am - 12:00pm
Session Chair: Paola Agostini, The World Bank, United States of America
ID: 1147 / 02-08: 1 Invited Paper
Geospatial Impact Evaluation and Valuation of Land Degradation Projects
Juha Ilari Uitto1, Geeta Batra1, Anupam Anand1, Dan Runfola2, Ariel BenYishay2, Jyoteshwar Nagol3
1Global Environment Facility Independent Evaluation Office, Washington DC; 2College of William and Mary, USA; 3University of Maryland, USA
We will present the impact assessment and valuation of GEF Land degradation projects using geospatial and econometric methods. The use of machine learning algorithms for assessing the factors influencing the environmental outcomes of the land degradation projects will be discussed. We will also present the use of Value Transfer Approach to estimate the amount of carbon sequestered highlighting the additional benefits generated from these projects. Our work demonstrates the utility of satellite-derived land degradation indicators and geospatial methods for impact assessment and valuation of sequestered carbon using the indicators proposed by the UNCCD's Land Degradation Neutrality(LDN) framework recommended for the SDG target 15.3. Lastly, we will share our experiences in using these methods, lessons learned and future work.
ID: 928 / 02-08: 2 Individual Papers Oral Presentation Topics: Academic research on land governance / rigorous impact evaluations Keywords: Global Environment Benefit, Land Degradation, Sustainable Land Management, Tracking Tool, Production Landscape
Quantifying The Multiple Environmental Benefits Of Sustainable Land Management Projects: An Analysis Of The Land Degradation Portfolio Of the Global Environment Facility (GEF)
World Bank, Global Environment Facility, United States of America
The Global Environment Facility (GEF) is the financing mechanism of several Multilateral Agreements for the Environment. The Land Degradation (LD) Focal Area is the GEF mechanism under the United Nations Convention to Combat Desertification (UNCCD) for investing in Sustainable Land Management to improve or restore ecosystem services in production systems. This paper presents the first analysis of LD Focal Area Tracking Tools available from a cohort of 1117 GEF projects submitted between July 1st 2010 and June 30, 2016, equivalent of 504 million of US dollars of GEF grants. These projects include direct interventions on 50.5 million ha of production landscapes, benefiting to 40 million rural people (half of them being women). The multiple global environment benefits are related to the maintenance, enhancement, or restoration of ecosystem services, including biodiversity, water, carbon, and forests resources. This analysis uses the tracking tools and other relevant data to quantitatively discuss the global environment benefits, local socio-economic benefits, and contextual information on the extent and drivers of land degradation at the GEF portfolio level. Recent findings will help to complement the analysis and the discussion (Value for Money study from the Independent Evaluation Office, Land Degradation Neutrality and SDG 15.3).
ID: 986 / 02-08: 3 Individual Papers Oral Presentation Topics: Harnessing geospatial data, cloud platforms and other data technologies Keywords: SLM, Ethiopia, watershed management, Google Earth Engine
SLM Intervention Impact Assessment Using Remotely Sensed Data
Daniel Monchuk, Daniel Ali, Klaus Deininger, Marguerite Duponchel
The World Bank, United States of America
The purpose of this paper is to examine the benefits of watershed conservation and management practices on introduced in the Abbay River-Basin of the Amhara and Benishangul Gumuz Regions in Ethiopia from 2009-15 as part of the Tana Beles Integrated Water Resources Development Project (TBIWRD). Specifically, this paper examines the impact of project interventions on vegetative intensity as measured by the Normalized Difference Vegetation Index (NDVI). The Google Earth Engine developer platform is used to compute seasonal average NDVI values at the pixel level (30m resolution) in project areas as well as proximate, non-intervention(control) areas. A panel dataset is constructed combining pixel-level NDVI with micro-watershed-level M+E activity data. Controlling for pixel characteristics by way of a fixed-effects regression model, we find TBIWRD has had a positive impact on vegetation outcomes as measured by NDVI. These results are found to be robust to various specifications.
ID: 1128 / 02-08: 4 Invited Paper
Building Local Capacity to Monitor Land Use Change and Intervention Impacts
Amadou Moctar Dieye
Centre de Suivi Ecologique (CSE), Senegal
To be compeleted
ID: 1166 / 02-08: 5 Invited Paper
The World Bank, United States of America
To be completed
ID: 1235 / 02-08: 6 Individual Papers Oral Presentation Topics: Harnessing geospatial data, cloud platforms and other data technologies