Land cover/land use (LULC) maps for the catchments of Kelani Ganga and Attanagalu Oya, and LULC Change comparing 1991, 2001 with the recent LCLU (2012). Classification includes two thematic levels (national 7-class scheme and 15 land cover/land use classes according to user definitions). This dataset is one of the products produced under the 2014-2016 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2016.
Sri Lanka - Land Use Land Cover LULC (Change) Mapping
Other International Organization|Private Firms|World Bank Group
Over the last two decades, Bangladesh has achieved impressive growth and poverty reduction. Its agricultural sector grew at a rate of 4.8 percent between 1990 and 2005. But poverty-related food insecurity is widespread, bolstered by the soaring prices of key staples. The country has a poverty rate of over 30% and the highest incidence of malnutrition of all countries: in 2008, Bangladesh’s food insecure population was estimated at 65.3 million. The Government of Bangladesh is pushing for increased use of technology and more intensive agricultural practices to improve food security and sustain economic growth. To that end, IAPP sponsors research to develop improved crop varieties and to promote adoption of improved varieties and production practices through the farmer field schools approach (FFS). The IAPP project is designed to improve the income and livelihoods of crop, fish, and livestock farmers in Bangladesh. It consists of four separate components: Component 1: Technology Generation and Adaptation; Component 2: Technology Adoption; Component 3: Water Management; Component 4: Project Management. The Impact Evaluation (IE) of the IAPP project will contribute to understanding the drivers of technology adoption through two lenses. First, the overall project approach will be evaluated using a randomized phase-in of project villages (referred to as the “Overall Project Evaluation”). The Overall Project Evaluation will measure the effects of Components 2 and 3 of IAPP. All sub-components will be measured, with special focus on the crops and fisheries sub-components. Second, innovations will be tested through a randomized control trial to understand what approach to demonstration plots can deliver higher results (referred to as the “Demonstration Plot Evaluation”). The Demonstration Plot Evaluation is designed to test a fundamental question about technology adoption: to what extent can “learning by doing” increase technology adoption over “learning by observing”? It will compare the relative effectiveness of single demonstration plots (the standard approach) to more distributed demonstration strategies which allow more people to experiment with new technology. The Demonstration Plot Evaluation will focus on the crops sub-component.
Florence Kondylis; DIME, Development Research Group, World Bank, Maria Jones; DIME, Development Research Group, World Bank, Daniel Stein; DIME, Development Research Group, World Bank
Bangladesh - Impact Evaluation of the Integrated Agricultural Productivity Project 2015
Water Quality Analysis for Lake Titicaca (2003-2011) measured by: a) Total suspended matter (TSM) and/or turbidity TSM is provided in the unit milligram per litre [mg/l], turbidity as Nephelometric Turbidity Unit [NTU] or (more up to date) Formazine Turbidity Unit [FTU]. b) Phytoplankton and Chlorophyll a: Chlorophyll a is one essential pigment included in phytoplankton cells and therefore a measure of phytoplankton. Common unit of chlorophyll is [µg/l]. This dataset is one of the products produced under the 2008-2012 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2013
The IAPP project is designed to improve the income and livelihoods of crop, fish, and livestock farmers in Bangladesh. It consists of four separate components: Component 1: Technology Generation and Adaptation; Component 2: Technology Adoption; Component 3: Water Management; Component 4: Project Management. The Impact Evaluation (IE) of the IAPP project will contribute to understanding the drivers of technology adoption through two lenses. First, the overall project approach will be evaluated using a randomized phase-in of project villages (referred to as the “Overall Project Evaluation”). The Overall Project Evaluation will measure the effects of Components 2 and 3 of IAPP. All sub-components will be measured, with special focus on the crops and fisheries sub-components. Second, innovations will be tested through a randomized control trial to understand what approach to demonstration plots can deliver higher results (referred to as the “Demonstration Plot Evaluation”). The Demonstration Plot Evaluation is designed to test a fundamental question about technology adoption: to what extent can “learning by doing” increase technology adoption over “learning by observing”? It will compare the relative effectiveness of single demonstration plots (the standard approach) to more distributed demonstration strategies which allow more people to experiment with new technology. The Demonstration Plot Evaluation will focus on the crops sub-component.
Bangladesh - Impact Evaluation of the Integrated Agricultural Productivity Project 2014
Florence Kondylis DIME, Development Research Group, World Bank; Maria Jones DIME, Development Research Group, World Bank; Daniel Stein DIME, Development Research Group, World Bank
Zambezi River Basin Land Use, Land Use Change and Soil Erosion
This dataset provides Land Use, Land Use Change and Soil Loss (Area: Shire sub basin) at 10m resolution. 1) Land use maps: covers land use for the years 2005 and 2010 and the resulting changes 2) Erosion map of 2010: Relative potential based on the Revised Universal Soil Loss Equation (RUSLE) erosion formula that uses information on: annual rainfall in 2010, soil type, slope, slope length, land use in 2010 and farming practices. This dataset is one of the products produced under the 2008-2012 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2013
Lake Titicaca Land Use and Land Use Changes
Lake Titicaca sub-basin land use of the years 2003 and 2010; and the land use changes between these years with thirteen Land Use classes defined. This dataset is one of the products produced under the 2008-2012 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2013
Flood extents and maximum flood maps for flood events of May 2003, Dec 2007, Nov-Dec 2008, May 2010, and Dec 2014, based on a time series of EO SAR data and optical data. The satellite imagery used, and validation and accuracy measures vary by flood event. Please consult the resources for details from respective flood events. This dataset is one of the products produced under the 2014-2016 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2016.
The Village Law, enacted in 2014, mandated the transfer of funds to villages with the goals of reducing poverty and improving living standards in villages through village-led development and community empowerment. Village Law (VL) builds on Indonesia’s 17-year history of participatory and community-driven development (CDD) approaches such as under the Kecamatan Development Project (KDP) and Program Nasional Permberdayaan Masyarakat (PNPM). The changes consequent upon the closing down of PNPM and its replacement by Village Law transfers (Dana Desa and Alokasi Dana Desa) and implementation arrangements, form a critical backdrop to the report titled: Indonesia Village Law: Technical Evaluation of Infrastructure Built with Village Funds. The Technical Evaluation of Village Infrastructure evaluates the development process, quality, costs, and operations and maintenance (O&M) of 168 village infrastructure projects (VIPs) with budgets greater than USD 10,000, from 39 villages in six provinces. The five types of projects assessed were: A) buildings (33); B) bridges (15); C) water supply (14); D) roads and drainage (94); and E) irrigation (12). Assessors evaluated the physical structures and related files (budgets, design, approvals, etc.) implementation methods, and operations and maintenance (O&M) procedures. The technical evaluation covers VIPs in the same provinces as in 2012 under the PMPN program. This collection of data is comprised of audit results from seven field tools, plus one administrative data file. The technical evaluation team collected data on five types of infrastructure projects, with total observations at 168, as described above. The seven field tools are included in this data deposit, for reference. Data were originally collected and assembled as eight data files; one for administrative data and one for each of the seven field tools. The technical evaluation team stored data primarily in binary format, using hundreds of variables per field tool to accommodate the options available for each question within each of the field tools. These data were reorganized into five data sets, one for each infrastructure type (compare to one for each field tool). The data were also consolidated from many sets of binary variables to encoded numeric variables, where applicable, for efficiency. Responses to open-ended questions were left as string variables. Responses to simple yes/no questions were left as binary numeric variables. The public versions of the datasets included here exclude variables containing PII, including: (1) name of infrastructure project inspector; (2) name or firm of infrastructure project design consultant; (3) narrative description of infrastructure project, in Indonesian; and (4) narrative description of infrastructure project, in English. Total infrastructure variables sum to 736 across all five datasets. All variables are named logically and include descriptions in their labels.
Indonesia - Village Law: Technical Evaluation of Infrastructure Built with Village Funds 2018
Nigeria - Feed the Future Nigeria Livelihoods Project 2015
Gautam Bastian World Bank ; Sreelakshmi Papineni World Bank
Feed the Future Nigeria Livelihoods Project (FNLP) is a multi-component development project based on the graduation model pioneered by Bangladesh Rural Advancement Committee (BRAC) that intends to help 42,000 very poor households across rural communities of northern Nigeria’s Sokoto and Kebbi states, and the Federal Capital Territory (FCT). FNLP is a 5-year program implemented by Catholic Relief Services (CRS). Both the program and the impact evaluation are funded by United States Agency for International Development (USAID). This program approach is founded on an agriculture-led growth strategy that is expected to help vulnerable families diversify their income and grow assets while the community is strengthened by improving nutrition, water sanitation, and hygiene. The most vulnerable families receive cash transfers. A caseworker-led livelihood mentoring scheme also matches households with the resources they need to engage effectively in the local economy and break free from the cycle of poverty and malnutrition. The impact evaluation, led by The World Bank’s Africa Gender Innovation Lab (GIL), is being conducted in Kebbi state in North-West Nigeria and will evaluate the impact of the overall program as well as two experiments that focus on the impact of the cash transfers and the caseworker mentoring scheme. Baseline data was collected for the FNLP starting in May 2015.
The products within the water quality service provide the parameters (a) Chlorophyll concentration (CHL), (b) Total suspended matter concentration (TSM), (c) Dissolved organic matter absorption (CDOM), and (d) Signal depths (Z90). They are provided as monthly averages in raster data sets in two different resolutions: 300m and 1200m. Overview images are provided which show the monthly averages of each year. Besides the image data, times series plots are delivered showing the evolution of the respective parameters for the areas of interest (AOIs). Finally, matrix plots are provided that show the values for each month and year for interpretation of the yearly evolution of the parameters (heatmaps). This dataset is one of the products produced under the 2014-2016 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2016.
Usumacinta River Basin - Water Quality Analysis
Florence Kondylis The World Bank; Maria Jones The World Bank; Saahil Karpe The World Bank
Agriculture is a major engine of the Rwandan economy and remains a priority sector in the Government of Rwanda's goals of reducing poverty and achieving food security through commercialized agriculture. Sustainable improvements to agricultural productivity is the only way to achieve this target, calling for investments in participatory land management, water harvesting and intensified irrigation of the hillsides. The Land Husbandry, Water Harvesting and Hillside Irrigation (LWH) project has been working to meet these goals. Evaluating the overall impact of LWH is important to allow Ministry of Agriculture and Animal Resources (MINAGRIs) to effectively plan for its future activities. LWH covers a relatively small area of 30,250 ha, eventually affecting approximately 20 watersheds. From the perspective of MINAGRI, LWH can be seen as a pilot program for comprehensive agricultural overhaul. LWH includes major infrastructure investments such as hillside terracing, irrigation dams, and post-harvest storage. The project aims to operationalize MINAGRIs strategy to encourage mono cropping of cash crops, as opposed to the traditional system of inter-cropping for household consumption. LWH has been rolled out in three phases: implementation in the four Phase 1A sites began in 2010, in the three Phase 1B sites in 2012, and in the Phase 1C sites in late 2013. There have been five surveys for this project including baselines and four follow-ups. There were two sample groups: 1B and 1C. For the 1B sample group, the baseline was conducted in 2012, and follow-up surveys in 2013, 2014, and 2016. For the 1C sample, the baseline was implemented in 2014, and a follow-up in 2016. The data file documented here is from the third follow-up survey. The datasets from the baseline, the first, the second, and the fourth follow-up surveys are also published in the Microdata Library with the following study IDs: 1) The baseline, the first and the second follow-up surveys: RWA_2012-2016_LWHIE-BL-F2_v01_M 2) The fourth follow-up survey: RWA_2016_LWHIE-F4_v01_M
Rwanda - Land Husbandry, Water Harvesting and Hillside Irrigation Project Impact Evaluation 2014
Digital Elevation Model (DEM) at 20m and precise DEM at 0.5m for the catchments of Kelani Ganga and Attanagalu Oya. This dataset is one of the products produced under the 2014-2016 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2016.
Bangladesh - Poverty and Groundwater Salinity Survey 2016
The main objective of the Bangladesh Poverty and Groundwater Salinity Survey (BPGSS) 2016 is to understand the linkages between groundwater salinity and poverty in coastal areas in Bangladesh. It is also to assess the extent to which high water salinity might be associated with poor health outcomes among women and children, and identify potential coping and adaptation mechanisms, which households might be using to address high water salinity in these areas.
Small water bodies inventory and water volume, covering the full Southern Province of Zambia, and includes of 1022 small reservoirs identified with optical satellite data from the Landsat5 satellite in the years 2010 and 2011. These locations are also available in excel file with LatLong coordinates for field inspection. This dataset is one of the products produced under the 2008-2012 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2013
Lake Malawi (Zambezi River Basin) - Small Water Bodies
This dataset includes rivers, towns, lakes, basins and demographic and climate indicators.
In response to the preventable threats posed by poor sanitation and hygiene, in December 2006 the Water and Sanitation Program (WSP) launched two related large-scale projects, Global Scaling Up Handwashing1 and Global Scaling Up Rural Sanitation. Th ese hygiene and sanitation interventions are designed to improve the health and welfare outcomes for millions of poor people. Local and national governments are implementing these projects with technical support from WSP. The goal of Global Scaling Up Rural Sanitation is to reduce the risk of diarrhea and therefore increase household productivity by stimulating demand for sanitation in the lives of people in India, Indonesia, and Tanzania. Th e project approach demands involvement from communities, local government, and the private sector. It aims to trigger the desire for an open-defecation free community by raising collective awareness of the open defecation problem. Facilitators are sent to communities to initiate participatory analysis of the communities’ existing sanitation practices, and the consequences and implications of such practices for themselves. Th is process is designed to catalyze collective community desire and action to become open defecation free (ODF). Th e community must forge their own plan for making this happen with only limited follow-up support and monitoring from the program. Communities claiming to have become ODF are verifi ed by local government agencies. ODF achievement by a community brings recognition and commendation from local and provincial governments. Th e project also seeks to stimulate the supply of appropriate sanitation products and services by conducting market research and training local artisans to build the relevant facilities. To measure the magnitudes of the impacts, the project is implementing randomized-controlled trial impact evaluations (IE) study in order to establish causal linkages between the intervention (treatment) and the outcomes of interest. Th e IE uses household surveys to measure the levels of key outcomes. The overall objective of the project is to improve the health of populations at risk of diarrhea, especially in children under the age of five years, through highlighting the negative health consequences of poor sanitation. Th e impact evaluation provides a unique opportunity to learn what health and welfare impacts can be expected from sanitation improvements. If, as expected, the evaluation finds strong health and child development impacts of improved sanitation, the study will be an important promotional tool for expanding the program across the nation. But to generate the support needed for a national program, the evidence must be clear and compelling. It is therefore important that the impact evaluation use widely accepted impact evaluation protocols and that it disrupts the planned program as little as possible. The impact evaluation assesses the effects of the project on individual-level sanitation behaviors, community-level collective behaviors, and the program’s impact on the health and welfare of young children (under fi ve years of age). It examines the impact on a broad range of health indicators and intensively studies the developmental, social, and economic welfare impacts of these interventions. Health outcomes that are explicitly planned in the study include: • Diarrhea prevalence; • Stunting and wasting; • Iron defi ciency anemia (through minimally invasive fi nger-prick tests); • Parasitic infestations (from fecal samples); and • Cognitive and motor development. Some of the non-health indicators are: • School attendance, academic performance, and future earnings; • Productivity of mother’s time for household, market, and social activities; and • Female empowerment and security due to safer sanitation conditions. (The above excerpt is taken from: Scaling Up Rural Sanitation: Findings from the Impact Evaluation Baseline Survey in Indonesia by Lisa Cameron and Manisha Shah November 2010) The report is attached.
Indonesia - WSP Global Scaling Up Rural Sanitation Access (TSSM) Impact Evaluation, Baseline and Endline Surveys 2009-2011
Bangladesh - Impact Evaluation of the Integrated Agricultural Productivity Project 2012
Over the last two decades, Bangladesh has achieved impressive growth and poverty reduction. Its agricultural sector grew at a rate of 4.8 percent between 1990 and 2005. But poverty-related food insecurity is widespread, bolstered by the soaring prices of key staples. The country has a poverty rate of over 30% and the highest incidence of malnutrition of all countries: in 2008, Bangladesh’s food insecure population was estimated at 65.3 million. The Government of Bangladesh is pushing for increased use of technology and more intensive agricultural practices to improve food security and sustain economic growth. To that end, the Integrated Agricultural Productivity Project (IAPP) sponsors research to develop improved crop varieties and to promote adoption of improved varieties and production practices through the farmer field schools approach (FFS). The IAPP project is designed to improve the income and livelihoods of crop, fish, and livestock farmers in Bangladesh. It consists of four separate components: Component 1: Technology Generation and Adaptation; Component 2: Technology Adoption; Component 3: Water Management; Component 4: Project Management. The Impact Evaluation (IE) of the IAPP will contribute to understanding the drivers of technology adoption through two lenses. First, the overall project approach will be evaluated using a randomized phase-in of project villages (referred to as the “Overall Project Evaluation”). The Overall Project Evaluation will measure the effects of Components 2 and 3 of IAPP. All sub-components will be measured, with special focus on the crops and fisheries sub-components. Second, innovations will be tested through a randomized control trial to understand what approach to demonstration plots can deliver higher results (referred to as the “Demonstration Plot Evaluation”). The Demonstration Plot Evaluation is designed to test a fundamental question about technology adoption: to what extent can “learning by doing” increase technology adoption over “learning by observing”? It will compare the relative effectiveness of single demonstration plots (the standard approach) to more distributed demonstration strategies which allow more people to experiment with new technology. The Demonstration Plot Evaluation will focus on the crops sub-component.
This dataset provides five flood scenarios for Greater Dhaka Area, with estimates of location-specific depth and duration of inundation, for extreme rainfall event in 2050. Intense rainfall floods Dhaka, Bangladesh, one of the world’s fastest-growing megacities, year in and year out. Low-lying flood plains, rivers, and canals that once drained water are gradually filling up as a result of indiscriminate urbanization, and now magnify, rather than help solve the problem. The climatic outlook for South Asia in the 21st century signals heavier and more erratic rainfall during the monsoon season, according to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change and the World Meteorological Organization. Thus, climate change may further aggravate Dhaka’s flood vulnerability. Dhaka needs to better manage its flood drainage infrastructure and strengthen the city’s climate-disaster resilience and adaptive capacity. But climate-smart policies require local planners to better understand the likely damage from current flooding, potential damage from climate-related risks, measures that can be taken to cope with current and future flooding as well as adaptation costs. In an effort to enhance such understanding and to provide input to development of adaptation policies, this research estimated location-specific depth and duration of inundation from extreme rainfall events by 2050 with or without climate change, discussed structural adaptation measures to cope with current and future flooding, evaluated the reduction in inundation resulting from implementing these measures, and estimated adaptation cost. Depth and duration of inundation in Greater Dhaka Area from extreme rainfall events by 2050 with or without climate change under different scenarios at ward/ thana-level have been summarized in the Excel Workbook “Urban Flooding of Greater Dhaka in 2050” Detailed Study Area: The dataset covers Greater Dhaka Area: Eastern Dhaka, Western Dhaka-Goranchatbari, Western Dhaka-Kallyanpur, Central Dhaka, Old Dhaka, DND and Narayanganj. As flooding is a periodic problem in Dhaka, the city can be said to already have an adaptation deficit even without climate change. The analysis therefore addressed the issue from both current and future climate perspectives. **Future (2050) Rainfall Extreme Scenarios: ** Dhaka experienced 341mm rainfall in 24 hours in September 2004; and this historic extreme rainfall was taken as the current climate baseline in the underlying analysis. For the future, the underlying analysis considered a 16 percent increase in extreme rainfall in a changing climate by 2050. Assumptions about the Future: As any change in land use has implications for the percentage of built-up area, and therefore drainage of the storm water, the analysis assumed that future land cover would change according to the RAJUK’s Detailed Action Plan (DAP). For drainage, the analysis assumed that all improvements to Dhaka’s drainage infrastructure, both planned and proposed by the relevant drainage-system authority, would be implemented. Five Alternative Scenarios: Estimates of location-specific depth and duration of inundation were estimated for extreme rainfall event in 2050 for following five scenarios: Scenario1: 341mm rainfall in 24 hours As timing and magnitude of climate change is somewhat unknown, ward/thana-level inundation depth and duration for 2050 were generated for the baseline rainfall event without consideration of any climate change. The analysis accounts for expected socioeconomic changes and planned changes in the land use pattern as well as drainage infrastructure. Scenario 2: 341mm rainfall in 24 hours without adaptation deficit The estimates of inundation from scenario1 were discussed with the local experts and based on their recommendations a set of potential adaptation measures for example increase in pump capacity, sludge cleaning, laying of new drainage pipes, deepening existing water bodies was designed and incorporated in hydrological modeling. The modeling was repeated with different capacities of pumps etc. until a desirable depth and duration of inundation for each study region was attained. Scenario 3: 396mm rainfall in 24 hours Ward/thana-level estimates of inundation depth and duration were generated for the changing climate in 2050 taking into account climate change using a potential 16 percent increase in extreme rainfall as a factor as well as accounting for expected socioeconomic changes, planned changes in the land use pattern and drainage infrastructure. Scenario 4: 396mm rainfall in 24 hours without adaptation deficit Implications for flooding were estimated in a changing climate after current climate adaptation deficit is met. Scenario 5: 396mm rainfall in 24 hours without adaptation deficit and with adaptation for climate change Implications for a set of adaptation measures suggested by local experts to deal with climate change were estimated. These estimates are from the three-step hydrological modeling component of the study. The first modeling step simulated basin-level flows from the Brahmaputra River in the Ganges-Brahmaputra-Meghna River system since they strongly influence monsoon-season river flows and water levels in the Greater Dhaka area. In the second step, the effects of climate change on the regional rivers were simulated. Finally, in the third step, detailed modeling of the drainage system in and around Dhaka city was simulated. The analysis centered on the worst-case scenario in which river levels are high and all sluice gates are closed. Therefore, there is no gravity drainage out of the city and the drainage system depends primarily on the performance efficiency of drainage pumps, which is often the case during intense rainfall. For Western Dhaka-Old Dhaka, Central Dhaka, Kallyanpur, and Goranchatbari—the impacts of climate change on river flooding were not considered in the analyses as this main part of the city is protected by flood embankments on all sides. See Urban Flooding of Greater Dhaka in a Changing Climate- Building Local Resilience to Disaster Risk: chapters 2, 3 and 6 for details. These estimates were prepared by Asif Zaman, World Bank Consultant and Water Resources and DSS Specialist, Institute of Water Modeling. The study was conducted under the World Bank-supported study on Urban Flooding of Greater Dhaka in a Changing Climate: Potential Damage and Adaptation (Task team Leader: Susmita Dasgupta). The study team gratefully acknowledges the financial support provided by the Bangladesh Climate Change Resilience Fund (BCCRF) a multi-donor trust fund supported by the governments of the United Kingdom, Denmark, Sweden, Switzerland, Australia, the United States, and the European Union. Lead Researcher: Dr. Asif Zaman
Urban Flooding of Greater Dhaka in a Changing Climate - Building Local Resilience to Disaster Risk
Vietnam - WSP Global Scaling up Handwashing Behavior Impact Evaluation, Baseline and Endline Surveys 2009-2011
In December 2006, in response to the preventable threats posed by poor sanitation and hygiene, the Water and Sanitation Program (WSP) launched Global Scaling Up Handwashing and Global Scaling Up Rural Sanitation1 to improve the health and welfare outcomes for millions of poor people. Local and national governments implement these large-scale projects with technical support from WSP. Handwashing with soap at critical times-such as after contact with feces and before handling food-has been shown to substantially reduce the incidence of diarrhea. It reduces health risks even when families do not have access to basic sanitation and water supply. Despite this benefit, rates of handwashing with soap at critical times are very low throughout the developing world. Global Scaling Up Handwashing aims to test whether handwashing with soap behavior can be generated and sustained among the poor and vulnerable using innovative promotional approaches. The goal of Global Scaling Up Handwashing is to reduce the risk of diarrhea and therefore increase household productivity by stimulating and sustaining the behavior of handwashing with soap at critical times in the lives of 5.4 million people in Peru, Senegal, Tanzania, and Vietnam, where the project has been implemented to date. In an effort to induce improved handwashing behavior, the intervention borrows from both commercial and social marketing fields. This entails the design of communications campaigns and messages likely to bring about desired behavior changes and delivering them strategically so that the target audiences are “surrounded” by handwashing promotion via multiple channels. One of the handwashing project's global objectives is to learn about and document the long-term health and welfare impacts of the project intervention. To measure magnitude of these impacts, the project is implementing a randomized-controlled impact evaluation (IE) in each of the four countries to establish causal linkages between the intervention and key outcomes. The IE uses household surveys to gather data on characteristics of the population exposed to the intervention and to track changes in key outcomes that can be causally attributed to the intervention. The objective of the IE is to assess the effects of the handwashing project on individual-level handwashing behavior and practices of caregivers. By introducing exogenous variation in handwashing promotion (through randomized exposure to the project), the IE will also address important issues related to the effect of intended behavioral change on child development outcomes. In particular, it will provide information on the extent to which improved handwashing behavior contributes to child health and welfare. The primary hypothesis of the study is that improved handwashing behavior leads to reductions in disease incidence, and results in direct and indirect health, developmental, and economic benefits by breaking the fecal-oral transmission route. The IE aims to address the following research questions and associated hypotheses: 1. What is the effect of handwashing promotion on handwashing behavior? 2. What is the effect of improved handwashing behavior on health and welfare? 3. Which promotion strategies are more cost-effective in achieving desired outcomes? (The above excerpt is taken from: Scaling Up Handwashing Behavior: Findings from the Impact Evaluation Baseline Survey in Vietnam Claire Chase and Quy-Toan Do November 2010) The report is attached.
Christian Borja-Vega World Bank; Bertha Briceno Inter-American Development Bank; Vicente Garcia Columbia University; Water and Sanitation Program World Bank
Senegal - WSP Global Scaling up Handwashing Behavior Impact Evaluation 2009-2011
Hygiene information and practices play a critical role in preventing diseases, particularly among children. Hygiene behaviors practiced in the household have been linked to development outcomes such as socio-emotional skills. The WSP Global Scaling up Handwashing Behavior Impact Evaluation (WSPIE) 2009-2011 was conducted in Senegal, where the randomized design suffered from contamination between comparison groups. The variations in exposure and intensity to hygiene information campaigns captured in the surveys were used to understand contamination biases. Such variations were interacted with the presence of household communication assets to explore potential effects on children’s socio-emotional scores. In the presence of contamination biases, the study exploited the longitudinal sample of children in the surveys to reduce time-dependent biases. For robustness, statistical matching was applied between the impact evaluation surveys and Demographic and Health Surveys conducted in 2008 and 2011. Socio-emotional outcomes were the imputed into Demographic and Health surveys to expand sample sizes. By applying matching techniques and imputing outcomes into a larger sample, impacts were non-negligible. Double-difference estimates showed that children’s socio-emotional scores were higher when intervention status was interacted with the presence of communication assets within households. Without the presence of communication assets in the households the impacts were close to zero. Evaluating the effect of hygiene campaigns on children’s socio-emotional skills is challenging because of the biases from contamination that exist when information flows between comparison groups. Targeted hygiene information to the poorest households is relevant for reducing risks of recurrent infections and enables better conditions for socio-emotional development of children.
Carol Newan Trinity College of Dublin; Tara Mitchell Trinity College of Dublin; Marcus Holmlund DECIE, World Bank
The Senegal Stormwater Management and Climate Change Adaptation Impact Evaluation, Baseline Survey (SMCCAIE-BL) 2014 was collected for DIME’s impact evaluation on community engagement mechanisms in the preservation of public spaces and drainage infrastructures. It is carried out in the context of the World Bank-assisted Stormwater Management and Climate Change Adaptation Project (PROGEP), which is implemented by the Dakar Municipal Development Agency (ADM) in Senegal. It will inform strategies through which PROGEP and similar projects can achieve their community engagement objectives, which are vital to the sustainability and return on these investments. Furthermore, it will contribute to our understanding of community directed development (CDD) interventions in urban settings. Data collected through the IE, including at baseline, will improve our understanding of populations living in PROGEP areas and inform the better targeting of project activities and other investments in these and similar settings.
Senegal - Stormwater Management and Climate Change Adaptation Impact Evaluation 2014
Caribbean Islands - Land Use Land Cover (LULC)
Land Use/Land Cover Mapping including water bodies, rivers and streams, for St. Lucia, Grenada, and St. Vincent and the Grenadines. This dataset is one of the products produced under the 2014-2016 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2016.
This dataset provides coral reef habitat mapping (detailed geomorphological zonation) and change detection maps spanning 2000-2011. First data output is: Oil spills monitored twice a week during 6 months (from July 1st to January 3rd 2011) leading to a total of 324 products (in netcdf/cdf formats along with png snapshots), including: Chlorophyll concentration, Low-Res Sea Surface Temperature, Hi-Res Sea Surface Temperature, Total Suspended Matter, Water Transparency and Significant Wave Height. Second data output is: Assessment of coral reef health and evolution focusing on four sites of interest (Aldabra, Tulear, Mayotte, Rodrigues). This dataset is one of the products produced under the 2008-2012 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2013.
Mozambique Channel - Coral Reef and Oil Spill Mapping
The association between hygiene, sanitation and health is well documented, yet thousands of children die each year from exposure to contaminated fecal matter. At the same time, evidence on the effectiveness of at-scale behavior change interventions to improve sanitation and hygiene practices is limited. In response to the preventable threats posed by poor sanitation and hygiene, the World Bank's Water and Sanitation Program (WSP) has launched two large projects, Global Scaling Up Handwashing and Global Scaling Up Rural Sanitation, to improve the health and welfare outcomes for millions of people in developing nations. These projects have been implemented by local and national governments with technical support from WSP. Researchers from the World Bank and Inter-American Development Bank studied these two projects impemented in rural Tanzania, with the objective of tracing the causal chain from hygiene and sanitation promotion to changes in child health outcomes. The research team specifically tested for potential interaction effects of combining handwashing and sanitation interventions. The study was designed as an effectiveness trial to provide evidence for policymakers and government implementing agencies planning at-scale campaigns. From mid-2009 to early 2011, two interventions were rolled out in ten districts of Tanzania following a factorial experimental design. 181 rural wards included in the study were divided into four groups to receive the handwashing intervention alone, the sanitation intervention alone, both the handwashing and sanitation, or neither intervention (control group). A baseline was planned for early 2009 but was aborted due to logistical field challenges. Since random assignment of implementation was adhered to, the study continued and researchers conducted an endline survey in 2012, approximately one year after the conclusion of the program. The survey included 3,619 households and 5,768 children under five years old.
Sebastian Martinez Inter-American Development Bank; Aidan Coville World Bank; Bertha Briceno Inter-American Development Bank
Tanzania - Impact Evaluation of Scaling-up Handwashing and Rural Sanitation Behavior Projects in Tanzania 2012
Zambezi River Basin Water Quality and Temperature
Water quality and temperature for Lake Malawi, Lake Malombe and Lake Chilwa, derived from MERIS FR images for 2010-2011 using the proprietary WISP algorithm. These parameters are: - Chlorophyll-a (Chl-a) - Total Suspended Matter (TSM) - Colored Dissolved Organic Matter (CDOM) - Kd averaged over the spectrum (KDP) The results were resampled to a spatial resolution of 300m. Selected Water Surface Temperature (SST) data is also included here as an additional product. This dataset is one of the products produced under the 2008-2012 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2013
Rwanda - Land Husbandry, Water Harvesting and Hillside Irrigation Project Impact Evaluation 2016
Agriculture is a major engine of the Rwandan economy and remains a priority sector in the Government of Rwanda's goals of reducing poverty and achieving food security through commercialized agriculture. Sustainable improvements to agricultural productivity is the only way to achieve this target, calling for investments in participatory land management, water harvesting and intensified irrigation of the hillsides. The Land Husbandry, Water Harvesting and Hillside Irrigation (LWH) project has been working to meet these goals. Evaluating the overall impact of LWH is important to allow Ministry of Agriculture and Animal Resources (MINAGRIs) to effectively plan for its future activities. LWH covers a relatively small area of 30,250 ha, eventually affecting approximately 20 watersheds. From the perspective of MINAGRI, LWH can be seen as a pilot program for comprehensive agricultural overhaul. LWH includes major infrastructure investments such as hillside terracing, irrigation dams, and post-harvest storage. The project aims to operationalize MINAGRIs strategy to encourage mono cropping of cash crops, as opposed to the traditional system of inter-cropping for household consumption. LWH has been rolled out in three phases: implementation in the four Phase 1A sites began in 2010, in the three Phase 1B sites in 2012, and in the Phase 1C sites in late 2013. There have been five surveys for this project including baselines and four follow-ups. There were two sample groups: 1B and 1C. For the 1B sample group, the baseline was conducted in 2012, and follow-up surveys in 2013, 2014, and 2016. For the 1C sample, the baseline was implemented in 2014, and a follow-up in 2016. The data file documented here is from the fourth follow-up survey. The datasets from the baseline, the first, the second, and the third follow-up surveys are also published in the Microdata Library with the following study IDs: 1) The baseline, the first and the second follow-up surveys: RWA_2012-2016_LWHIE-BL-F2_v01_M 2) The third follow-up survey: RWA_2014_LWHIE-F3_v01_M
This study provides Microdata for household and school surveys collected to support the 2017 Poverty Diagnostic of the Drinking Water, Sanitation and Hygiene (WASH) Sector. The diagnostic aimed to assess and visualize drinking water, sanitation, and hygiene service conditions of communities and households in the bottom 40 percent of the income distribution. The primary survey data comes from two nationally representative surveys that were carried out for this study. The Household WASH Survey and the School WASH Survey covered about 3,000 households and 300 primary/secondary schools, respectively, and were conducted in the same primary sampling units following a household listing exercise. The school survey covers basic WASH conditions in schools, whereas the household survey contains information on the availability and quality of WASH services, costs incurred for meeting WASH needs, the health and other impacts on household wellbeing, and willingness to pay for improved services.
Tajikistan - Survey of Water, Sanitation, and Hygiene for Households and Schools 2017
Tuvalu - Meteorologic and Oceanographic Conditions
This dataset is for an area from Vanuatu to Samoa between 2007 and 2012, mapping meteorologic and oceaonographic conditions. Meteorologic parameters include: Hurricanes, wave heights, air temperature, and wind fields. Oceanographic parameters include: Chlorophyll-a concentration of case 1 and 2 waters (CHL), total suspended matter (TSM), water transparency, sea surface temperature. Yearly averages and seasonal averages are considered. Wet season is considered from November to April, dry season is considered from May to October. Maps highlight the possible link between Funafuti conditions and the wider meteorological and oceanographic environment. Meteorological information is delivered in PNG format. This dataset is one of the products produced under the 2014-2016 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2016.
Agriculture is a major engine of the Rwandan economy and remains a priority sector in the Government of Rwanda's goals of reducing poverty and achieving food security through commercialized agriculture. Sustainable improvements to agricultural productivity is the only way to achieve this target, calling for investments in participatory land management, water harvesting and intensified irrigation of the hillsides. The Land Husbandry, Water Harvesting and Hillside Irrigation (LWH) project has been working to meet these goals. Evaluating the overall impact of LWH is important to allow Ministry of Agriculture and Animal Resources (MINAGRIs) to effectively plan for its future activities. LWH covers a relatively small area of 30,250 ha, eventually affecting approximately 20 watersheds. From the perspective of MINAGRI, LWH can be seen as a pilot program for comprehensive agricultural overhaul. LWH includes major infrastructure investments such as hillside terracing, irrigation dams, and post-harvest storage. The project aims to operationalize MINAGRIs strategy to encourage mono cropping of cash crops, as opposed to the traditional system of inter-cropping for household consumption. LWH has been rolled out in three phases: implementation in the four Phase 1A sites began in 2010, in the three Phase 1B sites in 2012, and in the Phase 1C sites in late 2013. There have been five surveys for this project including baselines and four follow-ups. There were two sample groups: 1B and 1C. For the 1B sample group, the baseline was conducted in 2012, and follow-up surveys in 2013, 2014, and 2016. For the 1C sample, the baseline was implemented in 2014, and a follow-up in 2016. The data files documented here are from the baseline, the first follow-up, and the second follow-up surveys. The datasets from the third and the fourth follow-up surveys are also published in the Microdata Library with the following study IDs: 1) The third follow-up: RWA_2014_LWHIE-F3_v01_M 2) The fourth follow-up: RWA_2016_LWHIE-F4_v01_M
Rwanda - Land Husbandry, Water Harvesting and Hillside Irrigation Project Impact Evaluation 2012-2016
Private Participation in Infrastructure (PPI) Project Database - Water Sector
The Private Participation in Infrastructure (PPI) Project Database has data on over 6,400 infrastructure projects in 137 low- and middle-income countries. The database is the leading source of PPI trends in the developing world, covering projects in the energy, transport, water and sewerage, ICT backbone, and Municipal Solid Waste (MSW) sectors (MSW data includes projects since 2008) Projects include management or lease contracts, concessions, greenfield projects, and divestitures.
Covid-19 Response Haiti - mWater Data Console
The purpose of this page is to follow the state and offers washes hands of identified and installed in response to the epidemic Covid 19. L'objectif de cette page est de suivre l'état et l'offre des stations de lavage des mains identifiées et installées en réponse à l'épidémie de COVID 19.
In Peru, the handwashing project targets mothers/caregivers of children under five years old, and it is aimed at improving handwashing with soap practices. Children under five represent the age group most susceptible to diarrheal disease and acute respiratory infections, which are two major causes of childhood morbidity and mortality in less developed countries. These infections, usually transferred from dirty hands to food or water sources, or by direct contact with the mouth, can be prevented if mothers/caregivers wash their hands with soap at critical times (such as before feeding a child, cooking, eating, and after using a toilet or changing a child’s diapers). In an effort to improve handwashing behavior, the intervention borrows from both commercial and social marketing fields. This entails the design of communications campaigns and messages likely to bring about the desired behavior changes, and delivering them strategically so that the target audiences are “surrounded” by handwashing promotion. Some key elements of the intervention include: • Key behavioral concepts or triggers for each target audience • Persuasive arguments stating why and how a given concept or trigger will lead to behavior change, and • Communication ideas to convey the concepts through many integrated activities and communication channels. The objective of the IE is to assess the effects of the project on individual-level handwashing behavior and practices of caregivers and children. By introducing exogenous variation in handwashing promotion (through randomized exposure to the project), the IE also addresses important issues related to the effect of intended behavioral change on child health and development outcomes. In particular, it provides information on the extent to which improved handwashing behavior impacts infant health and welfare.
Peru - WSP Global Scaling up Handwashing Behavior Impact Evaluation, Baseline and Endline Surveys 2009-2011
Water and Sanitation Program World Bank; Network for Engineering and Economics Research and Management NEERMAN
In India, WSP's Global Scaling Up Rural Sanitation Program is supporting the Government of India's Total Sanitation Campaign (TSC) in two states: Himachal Pradesh and Madhya Pradesh. TSC is an ambitious countrywide, scaled-up rural sanitation program launched in 1999, which seeks to attain an Open-Defecation Free (ODF) India by 2012. In contrast to earlier, hardware-centric supply approaches to rural sanitation, TSC aims to generate demand for and adoption of improved sanitation at the community level. This impact evaluation aimed at better understanding what health and welfare impacts can be expected from rural sanitation improvements. Researchers hypothesized that promotion of rural sanitation through community-led total sanitation (CLTS) and social marketing campaigns will improve the health of the population especially children under five years old, a population that is vulnerable to unsafe disposal of feces in the environment and fecal-oral contamination. This impact evaluation consisted of baseline and endline surveys. In collaboration with the government of Madhya Pradesh, two districts Dhar and Khargone were selected. In each district, 80 Gram Panchayats were chosen and randomized into two groups: 1) treatment group (to participate in Total Sanitation Campaign immediately following the baseline survey) and 2) control group (to receive TSC after follow-up data collection). The baseline survey collected information from a representative sample of the population targeted by the intervention. This baseline survey was administered to approximately 2,000 households between June and July 2009. The survey provided information on the characteristics of household members, access to sanitation facilities, self-reported open defecation, prevalence of child diseases such as diarrhea and respiratory infection, and child growth and development. The endline survey was carried out in February-March 2011. It followed the same households sampled in baseline, as well as additional children to increase statistical power.
India - WSP Global Scaling Up Rural Sanitation Access (TSSM) Impact Evaluation, Madhya Pradesh State, Baseline and Endline Surveys 2009-2011
This dataset also consists of data on other non-grid connected solar installations/applications such as standalone solar solutions, lanterns, solar pumps, and solar water heaters. The capacities of the solar pumps and the water heaters in terms of their flow rates and volumes respectively are reported. This dataset was last updated in June 2014. NB: The number of solar lanterns distributed by the Ministry of Energy And Petroleum(MOEP) is not given but a total capacity of those lantern distributed was 42kW. Citation: Ghana Energy Commission & Negawatt challenge. A curated list of datasets for the World Bank Negawatt Challenge competition in Accra and Nairobi cities: https://datahub.io/organization/negawatt-challenge
Ghana - Off-grid Solar Installations Capacity & Quantity
Bangladesh - Impact Evaluation of the Integrated Agricultural Productivity Project 2013
This dataset provides Land Cover Land Use (LCLU) in Usumacinta river basin (Mexico). This dataset is one of the products produced under the 2014-2016 World Bank (WBG) European Space Agency (ESA) partnership, and is published in the partnership report: Earth Observation for Sustainable Development, June 2016.
Usumacinta River Basin - Land Cover Land Use Mapping (LCLU)
Related materials (Questionnaires, reports, tables, technical documents, and data files)
2B. GeoTIFF: Lake Titicaca Sub-basin - Land Use 2010
2A. Total Suspended Matter (TSM) Maps (PNG)
Maps (.png) of Monthly Means and Single Day TSM Levels
Ready Maps for Printing: Small Reservoirs Basemap, Timeseries and ASAR-Automated Classification
These are PDF-maps produced using the attached datasets. It is recommended to review these maps in order to navigate better your raw data needs from the underlying datasets.
Ready Maps for Printing: Land Use (2005-2010), Soil Loss and Soil Erosion
Includes output map, metadata and satellite specifications, validation procedures and accuracy measures.
3A. Lake Titicaca Sub-basin - Land Use Change 2003-2010
1B. ArcGIS Total Suspended Matter Map Editor
Please refer to the readme file to review the folder structure behind this dataset
Land Use Map Data include: DEM (Digital Elevation Model), Land Use 2005, Land Use 2010, and Soil Loss. Underlying data also include Shire sub basin AOI, POI (Places of Interest), and related administrative boundaries.
1E. GeoTIFF: Lake Titicaca Sub-basin - Mosaic Landsat 2003
Satellite Images (GeoTIFF) of Monthly Means and Single Day TSM Levels
Shapefile: Land Cover Classification 2012
Dissolved organic matter absorption (CDOM) 2003-2011 at 300m (.KMZ)
Shapefile: Historical Flood Map - May 2003
Data includes floot extent, maximum flood, and xml metadata
Volume Timeseries data monitor the evolution of identified small reservoirs from the basemap, volume and extent (processed shapefiles and raw ASAR imagery).
Small Reservoirs Volume Timeseries (Change Over Time 5/2010-5/2011)
Four sites were mapped (Aldabra, Tulear, Mayotte, Rodrigues) and change detection was performed over the last decade.
Product Sheet: Land Use Land Cover Change 1991-2001-2012
Includes output map, statistics, metadata and satellite specifications, validation procedures and accuracy measures.
Basemap data include small reservoir centroid, volume and extent (processed shapefiles and raw Landsat imagery). Underlying data also include dam inventory, administrative boundaries, and Landsat imagery AOI. The base map provides a good overview of the development of small reservoirs in the Southern Province of Zambia. All small reservoirs within the extent of the province are mapped with the use of the latest cloud free Landsat-5 imagery – outside the local rain season.
1D. Chlorophyll-a Timeseries (PNG Charts)
Timeseries Charts showing Chlorophyll Concentration for the three lakes: Malawi, Chilwa and Malombe.
Data delivered twice a week during 6 months (from July 1st to January 3rd) leading to a total of 324 products (in netcdf/cdf formats along with png snapshots). This corresponds to 54 dates times 6 products (Chlorophyll concentration, Low-Res Sea Surface Temperature, Hi-Res Sea Surface Temperature, Total Suspended Matter, Water Transparency and Significant Wave Height).
Shapefile: Historical Flood Map - May 2007
Ready Map for Printing: Land Use Land Cover - Grenada
Product Sheet: Historical Flood Map - May 2003
Descriptions of the output maps, timeseriescharts, metadata, and file formats and storage.
3B. Colored Dissolved Organic Matter (CDOM) Satellite Images (GeoTIFF)
Satellite Images (GeoTIFF) of Monthly Means and Single Day CDOM Levels
2D. Lake Titicaca Sub-basin - Mosaic RapidEye Map 2010
Ready Map for Printing: Historical Flood Map - Dec 2007 (BMP)
Ready Map for Printing: Historical Flood Map - Dec 2007 (PDF)
Raw satellite imagery used in this project.
Raw Satellite Imagery (Landsat and SPOT)
Maps (.png) of Monthly Means and Single Day Chlorophyll Levels
Land Cover Land Use (LCLU) Raw Imagery (GeoTIFF)
Timeseries Charts showing KdP for the three lakes: Malawi, Chilwa and Malombe.
Shapefile: Historical Flood Map - Dec 2014
Shapefile: Land Cover Classification 1991
Sri Lanka - Historical Flood Mapping(Feature Service)
Product Sheet: Historical Flood Map - Nov/Dec 2008
Timeseries Charts showing SST for the two lakes: Malawi and Malombe.
Shapefile: Land Cover Classification 2001
1A. Lake Titicaca Sub-basin - Land Use Map 2003
3B. GeoTIFF: Lake Titicaca Sub-basin - Land Use Change 2003-2010
Shapefile: Historical Flood Map - May 2010
2B. GeoTIFF Images: Total Suspended Matter
1B. GeoTIFF: Lake Titicaca Sub-basin - Land Use 2003
Mozambique Channel - Coral Reef and Oil Spill Mapping(Feature Service)
Maps (.png) of Monthly Means and Single Day KdP Diffuse Attenuation Coefficient
4A. KdP Diffuse Attenuation Coefficient Maps (PNG)
solar installation capacity quantity 2014 csv
Satellite Images (GeoTIFF) of Monthly Means and Single Day SST Levels
Total suspended matter (TSM) 2003-2011 Timeseries (.PNG)
Chlorophyll (CHL) 2003-2011 Timeseries (.PNG)
Ready Map for Printing: Land Use Land Cover - St. Lucia
Land Cover Land Use (LCLU) Data (GeoTIFF)
Satellite Images (GeoTIFF) of Monthly Means and Single Day KdP Diffuse Attenuation Coefficient
4B. KdP Diffuse Attenuation Coefficient Satellite Images (GeoTIFF)
1B. Chlorophyll-a Satellite Images (GeoTIFF)
Satellite Images (GeoTIFF) of Monthly Means and Single Day Chlorophyll Levels
Ready Map for Printing: Land Cover Classification 2012 (JPG)
Small Reservoirs Automated Classification using SAR
PLEASE NOTE: Object oriented classification was used to automatically classify water bodies. For this classification the minimal mapping unit of 0.5 ha was not used, because of the possibility of encountering smaller ones, due to the fact that reservoirs become smaller in the dry season. For this demonstration a subset was taken with 55 reservoirs that could be manually digitised that are validated against the base map. 51 reservoirs were automatically extracted with the developed classification method. This has detection rate of 93%.
Dissolved organic matter absorption (CDOM) 2003-2011 Timeseries (.PNG)
Shapefiles include rivers, roads, and water bodies. GeoTIFFs include land cover classifications.
Land Use Land Cover Data (GeoTIFF, Shapefiles)
KMZ files of Chlorophyll Monthly Mean Values
2E. GeoTIFF: Lake Titicaca Sub-basin - Mosaic RapidEye 2010
Maps (.png) of Monthly Means and Single Day SST Levels
5A. Selected Water Surface Temperature (SST) Maps (PNG)
4AB. Overview Map Products: Water Quality Timeseries Analysis by Chlorophyll and TSM
1D. Lake Titicaca Sub-basin - Mosaic Landsat 5TM Map 2003
Shapefile: Historical Flood Map - Dec 2008
Timeseries Charts showing TSM levels for the three lakes: Malawi, Chilwa and Malombe.
Product Sheet: Historical Flood Map - Dec 2007
Final Report and Documentation: Mozambique Channel Coral Reef Habitat Mapping
Includes methodology, bibliography, results of analysis, and metadata of the satellite imagery used. This report can be referred as: Andréfouët S, 2012, Mozambique Channel Coral Reef Habitat Mapping. Report to Collecte Localisation Satellites, IRD, Nouméa, January 2012. 56 pages.
ESRI Small Reservoirs Work Project (ArcMAP file: .mxd)
2A. Lake Titicaca Sub-basin - Land Use Map 2010
3A. Print Satellite Imagery: Chlorophyll
Descriptions of the folders and file structure.
Ready Map for Printing: Land Use Land Cover - Grenadines
Ready Map for Printing: Land Use Land Cover - St. Vincent
3B. Print Satellite Imagery: Total Suspended Matter
Product Sheet: Rapid Flood Map - Dec 2014
Sri Lanka - Land Use Land Cover LULC (Change) Mapping(Feature Service)
Lake Titicaca Water Quality(Feature Service)