Your search found 27 records
1 UN. 1999. Remote sensing for tropical ecosystem management: proceedings of the Seventh Regional Seminar on Earth Observation for Tropical Ecosystem Management, Dhaka, Bangladesh, 7-11 December 1998. New York, NY, USA: UN. 102p.
Remote sensing ; GIS ; Ecosystems ; Earth observation satellites ; Mangroves ; Ecology ; Coastal area ; Monitoring ; Land degradation ; Flooding / Asia / Bangladesh / Thailand / Cambodia / Himalaya Region / Hindu Kush / Tonle Sap Lake
(Location: IWMI HQ Call no: 621.3678 G000 UN Record No: H044218)
http://vlibrary.iwmi.org/pdf/H044218_TOC.pdf
(0.43 MB)

2 Amarnath, Giriraj; Sharma, Bharat; Smakhtin, Vladimir. 2014. Managing water resources in agriculture: opportunities from earth observation. [Abstract only]. In India Geospatial Media and Communications. India Geospatial Forum 2014 on Converging Geospatial Trade and Practices, Hyderabad, India, 5-7 February 2014. Programme guide. Noida, Uttar Pradesh, India: India Geospatial Media and Communications. pp.53.
Earth observation satellites ; Remote sensing ; Water management ; Water resources ; Agriculture ; Food production ; Climate change ; River basin / Asia / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H046368)
https://publications.iwmi.org/pdf/H046368.pdf
(0.09 MB)
Food security and economic livelihood of millions of people in Asia and Africa shall continue to depend upon the flows in the major rivers. Variability of water and other resources in time and space is the major natural impediment for sustainable agriculture, food production and development at large. The extremes of variability - floods and droughts - are the primary "agents" of destruction, severe crop damage and loss of human life. According to EM-DAT (2012), about 3 billion people in more than 110 countries are affected by catastrophic flooding. In 2011 alone they killed tens of thousands of people, primarily in developing countries, and caused over $150 billion in damage globally. Our present capacity to understand and make a reasonable forecast of the occurrence and thus management of such anomalies is rather inadequate. Earth observation (EO) satellites play a major role in the provision of information for the study and monitoring of the water resources and can support better understanding in Agricultural Water Resource Management. Their global nature also helps to address the problems of data continuity in trans-national basins where complete, consolidated, and consistent information may be difficult to obtain. In the years to come, EO technology will enter into a new era, where the increasing number of more sophisticated missions will provide scientists with an unprecedented capacity to observe and monitor the different components of climate variability on water resources from the local to the global scales. Already today, global observations of several key parameters governing the global water dynamics (e.g. precipitation, soil moisture, evaporation, transpiration, water levels, mass balance, gravity-derived groundwater measurements, etc.) are feasible. In addition, significant progress has been made in the area of data assimilation enhancing the capabilities to integrate EO-based product into suitable land surface and hydrological models; hence opening new opportunities for science and application. The presentation will illustrate examples of such information and solutions globally and from large river basins in Asia and Africa including flood risks and drought monitoring; Smart-lCT system for climate and weather information, irrigated area mapping etc.

3 Amarnath, Giriraj. 2014. Earth observation data: monitoring floods and drought. Geospatial Today, 6(June):15-19.
Earth observation satellites ; Early warning systems ; Monitoring ; Climate change ; Flooding ; Drought ; Disaster prevention ; Farmers ; Remote sensing ; Models
(Location: IWMI HQ Call no: e-copy only Record No: H046465)
https://vlibrary.iwmi.org/pdf/H046465.pdf
(0.27 MB)

4 Amarnath, Giriraj; Inada, Yoshiaki; Ghosh, Surajit; Yakob, Umer; Alahacoon, Niranga; Kota, Harada; Inoue, Ryosuke; Schlaffer, S. 2014. Earth observation technologies for flood-risk mapping, modeling and management. Training manual prepared for Capacity Building Workshop on Earth Observation Technologies for Flood-risk mapping, Modeling and Management, Peradeniya, Sri Lanka, 18-21 November 2014. Peradeniya, Sri Lanka: University of Peradeniya. Postgraduate Institute of Science. 170p.
Earth observation satellites ; Satellite imagery ; Radar satellite ; Early warning systems ; Flood control ; Risk management ; Models ; Capacity building ; Rain ; Runoff ; Climate change ; Impact assessment ; Hydraulics ; Case studies ; Training materials / Sri Lanka / Thailand / Mundeni Aru Basin
(Location: IWMI HQ Call no: IWMI Record No: H046777)
https://vlibrary.iwmi.org/pdf/H046777.pdf
(11.97 MB)

5 Bastiaanssen, Wim G. M.; Karimi, Poolad; Rebelo, Lisa-Maria; Duan, Z.; Senay, G.; Muthuwatta, Lal; Smakhtin, Vladimir. 2014. Earth observation based assessment of the water production and water consumption of Nile Basin agro-ecosystems. Remote Sensing, 6(11):10306-10334. [doi: https://doi.org/10.3390/rs61110306]
Water requirements ; Water use ; Water accounting ; Water balance ; Groundwater ; Earth observation satellites ; Assessment ; Agroecosystems ; River basins ; Evapotranspiration ; Remote sensing ; Models ; Rain / Africa / Nile Basin
(Location: IWMI HQ Call no: e-copy only Record No: H046822)
http://www.mdpi.com/2072-4292/6/11/10306/pdf
https://vlibrary.iwmi.org/pdf/H046822.pdf
(2.06 MB) (2.06 MB)
The increasing competition for water resources requires a better understanding of flows, fluxes, stocks, and the services and benefits related to water consumption. This paper explains how public domain Earth Observation data based on Moderate Resolution Imaging Spectroradiometer (MODIS), Second Generation Meteosat (MSG), Tropical Rainfall Measurement Mission (TRMM) and various altimeter measurements can be used to estimate net water production (rainfall (P) > evapotranspiration (ET)) and net water consumption (ET > P) of Nile Basin agro-ecosystems. Rainfall data from TRMM and the Famine Early Warning System Network (FEWS-NET) RainFall Estimates (RFE) products were used in conjunction with actual evapotranspiration from the Operational Simplified Surface Energy Balance (SSEBop) and ETLook models. Water flows laterally between net water production and net water consumption areas as a result of runoff and withdrawals. This lateral flow between the 15 sub-basins of the Nile was estimated, and partitioned into stream flow and non-stream flow using the discharge data. A series of essential water metrics necessary for successful integrated water management are explained and computed. Net water withdrawal estimates (natural and humanly instigated) were assumed to be the difference between net rainfall (Pnet) and actual evapotranspiration (ET) and some first estimates of withdrawals—without flow meters—are provided. Groundwater-dependent ecosystems withdraw large volumes of groundwater, which exceed water withdrawals for the irrigation sector. There is a strong need for the development of more open-access Earth Observation databases, especially for information related to actual ET. The fluxes, flows and storage changes presented form the basis for a global framework to describe monthly and annual water accounts in ungauged river basins.

6 Amarnath, Giriraj; Pandey, Rajesh; Alahacoon, Niranga. 2015. Earth observation technologies for flood-risk mapping and forecast rating curve for flood recession agriculture in Nigeria. Training manual prepared for Capacity building workshop on Earth Observation Technologies for Flood-risk mapping and Forecast rating curve for Flood recession Agriculture in Nigeria, Abuja, Nigeria, 5-7 May 2015. Colombo, Sri Lanka: International Water Management Institute (IWMI). 84p.
Earth observation satellites ; Satellite imagery ; Satellite surveys ; Radar satellite ; Flood control ; Mapping ; Risk management ; Weather forecasting ; Hydrology ; Models ; Computer applications ; Remote sensing ; Water levels ; Flow discharge ; Capacity building ; Training materials ; Case studies / Nigeria / Niger River / Benue River
(Location: IWMI HQ Call no: IWMI Record No: H047076)
http://vlibrary.iwmi.org/pdf/H047076_TOC.pdf
(0.33 MB)

7 Voigt, S.; Giulio-Tonolo, F.; Lyons, J.; Kucera, J.; Jones, B.; Schneiderhan, T.; Platzeck, G.; Kaku, K,; Hazarika, M. K.; Czaran, L.; Li, S.; Pedersen, W.; James, G. K.; Proy, C.; Muthike, D. M.; Bequignon, J.; Guha-Sapir, D. 2016. Global trends in satellite-based emergency mapping. Science, 353(6296):247-252. [doi: https://doi.org/10.1126/science.aad8728]
Earth observation satellites ; Satellite imagery ; Natural disasters ; Mapping ; Disaster preparedness ; Spatial distribution ; Population density ; Technological changes ; International cooperation ; Organizations
(Location: IWMI HQ Call no: e-copy only Record No: H047649)
https://vlibrary.iwmi.org/pdf/H047649.pdf
(1.21 MB)
Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

8 Pekel, J.-F.; Cottam, A.; Gorelick, N.; Belward, A. S. 2016. High-resolution mapping of global surface water and its long-term changes. Nature, 540(7633):418-422. [doi: https://doi.org/10.1038/nature20584]
Surface water ; Mapping ; Satellite imagery ; Landsat ; Earth observation satellites ; Water distribution ; Geographical distribution ; Seasonal variation ; Expert systems ; Climate change ; Hydrology ; Models ; Drought ; Evaporation ; Human behavior ; Lakes ; Plateaus / Central Asia / USA / Australia / Aral Sea / Tibetan plateau
(Location: IWMI HQ Call no: e-copy only Record No: H047905)
https://vlibrary.iwmi.org/pdf/H047905.pdf
(8.75 MB)
The location and persistence of surface water (inland and coastal) is both affected by climate and human activity1 and affects climate2,3 , biological diversity4 and human wellbeing5,6 . Global data sets documenting surface water location and seasonality have been produced from inventories and national descriptions7 , statistical extrapolation of regional data8 and satellite imagery9–12, but measuring long-term changes at high resolution remains a challenge. Here, using three million Landsat satellite images13, we quantify changes in global surface water over the past 32 years at 30-metre resolution. We record the months and years when water was present, where occurrence changed and what form changes took in terms of seasonality and persistence. Between 1984 and 2015 permanent surface water has disappeared from an area of almost 90,000 square kilometres, roughly equivalent to that of Lake Superior, though new permanent bodies of surface water covering 184,000 square kilometres have formed elsewhere. All continental regions show a net increase in permanent water, except Oceania, which has a fractional (one per cent) net loss. Much of the increase is from reservoir filling, although climate change14 is also implicated. Loss is more geographically concentrated than gain. Over 70 per cent of global net permanent water loss occurred in the Middle East and Central Asia, linked to drought and human actions including river diversion or damming and unregulated withdrawal15,16. Losses in Australia17 and the USA18 linked to long-term droughts are also evident. This globally consistent, validated data set shows that impacts of climate change and climate oscillations on surface water occurrence can be measured and that evidence can be gathered to show how surface water is altered by human activities. We anticipate that this freely available data will improve the modelling of surface forcing, provide evidence of state and change in wetland ecotones (the transition areas between biomes), and inform water-management decision-making.

9 Dickens, Chris; Rebelo, Lisa-Maria; Nhamo, Luxon. 2017. Guidelines and indicators for Target 6.6 of the SDGs: “change in the extent of water-related ecosystems over time” Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Research Program on Water, Land and Ecosystems (WLE) 56p.
Sustainable development ; Ecosystem services ; Guidelines ; Indicators ; Monitoring ; Marshes ; Swamps ; Wetlands ; Forests ; Paddy fields ; Peatlands ; Mangroves ; Lakes ; Ponds ; Rivers ; Groundwater ; Earth observation satellites ; Remote sensing ; Water quality ; Flow discharge ; Stream flow ; Reservoirs ; Environmental health
(Location: IWMI HQ Call no: e-copy only Record No: H048340)
http://www.iwmi.cgiar.org/Publications/wle/reports/guideline_and_indicators_for_target_6-6_of_the_sdgs-5.pdf

10 Ghosh, S.; Thakur, P. K.; Sharma, R.; Nandy, S.; Garg, V.; Amarnath, Giriraj; Bhattacharyya, S. 2017. The potential applications of satellite altimetry with SARAL [Satellite with ARGOS and ALTIKA]/AltiKa for Indian inland waters. Proceedings of the National Academy of Sciences India Section A-Physical Sciences, 19p. (Online first). [doi: https://doi.org/10.1007/s40010-017-0463-5]
Earth observation satellites ; Inland waters ; Surface water ; Monitoring ; Satellite observation ; Radar ; Water levels ; River basins ; Flow discharge ; Reservoirs ; Sedimentation ; Measurement ; Hydrology ; Models ; Calibration / India
(Location: IWMI HQ Call no: e-copy only Record No: H048445)
https://vlibrary.iwmi.org/pdf/H048445.pdf
(1.39 MB)
The satellite radar altimetry datasets are now extensively used for continental water monitoring although it was primarily designed for oceanic surface and ice cap studies. Water level estimated from satellite altimetry can help to assess many hydrological parameters like river discharge and reservoir volume. These parameters can be employed for calibration and validation purposes of hydrological and hydrodynamic models, rating curve (stage-discharge relationship) generation, near real-time flood forecasting, reservoir operations and transboundary water related issues. Satellite with Argos and AltiKa (SARAL/AltiKa), a joint venture of Indian Space Research Organisation and Centre National d’Etudes Spatiales, is one of the pioneer missions in the history of satellite radar altimetry. It is first high-frequency (Ka-band, 35.75 GHz) mission with the highest sampling rate (40 Hz). The applications of radar altimetry to inland hydrology have been significantly increased in recent years in India. Major studies have been carried out in Ganga, Brahmaputra, Tapi and Godavari river basins with AltiKa data. AltiKa datasets have been successfully used for retrieving water level in reservoir and river, estimating river discharge and calculating reservoir sedimentation. Considering the stress on India’s fresh water resources and the importance of SARAL/AltiKa mission, this work was carried out. The present review paper may be helpful to understand the working principle of altimetry, altimetry waveform, waveform retracking methods, water stage, river discharge and changes in reservoir’s water storage calculation, and the status of altimetry applications to inland hydrology, specifically solicitation of SARAL/AltiKa in the Indian context.

11 Bunting, P.; Rosenqvist, A.; Lucas, R. M.; Rebelo, Lisa-Maria; Thomas, N.; Hardy, A.; Itoh, T.; Shimada, M.; Finlayson, C. M. 2018. The global mangrove watch - a New 2010 global baseline of mangrove extent. Remote Sensing, 10(10):1-19. [doi: https://doi.org/10.3390/rs10101669]
Mangroves ; Wetlands ; Mapping ; Landsat ; Satellite imagery ; Satellite observation ; Earth observation satellites ; Human behaviour ; Coastal area ; Deltas ; Environmental monitoring
(Location: IWMI HQ Call no: e-copy only Record No: H049127)
https://www.mdpi.com/2072-4292/10/10/1669/pdf
https://vlibrary.iwmi.org/pdf/H049127.pdf
(18 MB)
This study presents a new global baseline of mangrove extent for 2010 and has been released as the first output of the Global Mangrove Watch (GMW) initiative. This is the first study to apply a globally consistent and automated method for mapping mangroves, identifying a global extent of 137,600 km 2 . The overall accuracy for mangrove extent was 94.0% with a 99% likelihood that the true value is between 93.6–94.5%, using 53,878 accuracy points across 20 sites distributed globally. Using the geographic regions of the Ramsar Convention on Wetlands, Asia has the highest proportion of mangroves with 38.7% of the global total, while Latin America and the Caribbean have 20.3%, Africa has 20.0%, Oceania has 11.9%, North America has 8.4% and the European Overseas Territories have 0.7%. The methodology developed is primarily based on the classification of ALOS PALSAR and Landsat sensor data, where a habitat mask was first generated, within which the classification of mangrove was undertaken using the Extremely Randomized Trees classifier. This new globally consistent baseline will also form the basis of a mangrove monitoring system using JAXA JERS-1 SAR, ALOS PALSAR and ALOS-2 PALSAR-2 radar data to assess mangrove change from 1996 to the present. However, when using the product, users should note that a minimum mapping unit of 1 ha is recommended and that the error increases in regions of disturbance and where narrow strips or smaller fragmented areas of mangroves are present. Artefacts due to cloud cover and the Landsat-7 SLC-off error are also present in some areas, particularly regions of West Africa due to the lack of Landsat-5 data and persistence cloud cover. In the future, consideration will be given to the production of a new global baseline based on 10 m Sentinel-2 composites.

12 Rebelo, Lisa-Maria; Finlayson, C. M.; Strauch, A.; Rosenqvist, A.; Perennou, C.; Totrup, C.; Hilarides, L.; Paganini, M.; Wielaard, N.; Siegert, F.; Ballhorn, U.; Navratil, P.; Franke, J.; Davidson, N. 2018. The use of earth observation for wetland inventory, assessment and monitoring: an information source for the Ramsar Convention on wetlands. Gland, Switzerland: Ramsar Convention Secretariat. 31p.
Earth observation satellites ; Wetlands ; Environmental impact assessment ; Environmental monitoring ; Surveys ; Land cover ; Land use ; Sustainable Development Goals ; Water quality ; Surface water ; Ecology ; Lakes ; Mediterranean region ; Coastal area ; Mangroves ; Mapping ; Case studies / Egypt / West Africa / Ghana / Southern Europe / Lake Burullus / Lake Volta / Lake Victoria
(Location: IWMI HQ Call no: e-copy only Record No: H049128)
https://www.ramsar.org/sites/default/files/documents/library/rtr10_earth_observation_e.pdf
https://vlibrary.iwmi.org/pdf/H049128.pdf
(2.79 MB)

13 Pocas, I.; Calera, A.; Campos, I.; Cunha, M. 2020. Remote sensing for estimating and mapping single and basal crop coefficientes: a review on spectral vegetation indices approaches. Agricultural Water Management, 233:106081. [doi: https://doi.org/10.1016/j.agwat.2020.106081]
Remote sensing ; Crops ; Water requirements ; Evapotranspiration ; Vegetation index ; Irrigation management ; Soil water balance ; Soil moisture ; Earth observation satellites ; Landsat ; Geographical information systems ; Monitoring ; Water stress ; Mapping ; Models
(Location: IWMI HQ Call no: e-copy only Record No: H049654)
https://vlibrary.iwmi.org/pdf/H049654.pdf
(0.77 MB)
The advances achieved during the last 30 years demonstrate the aptitude of the remote sensing-based vegetation indices (VI) for the assessment of crop evapotranspiration (ETc) and irrigation requirements in a simple, robust and operative manner. The foundation of these methodologies is the well-established relationship between the VIs and the basal crop coefficient (Kcb), resulting from the ability of VIs to measure the radiation absorbed by the vegetation, as the main driver of the evapotranspiration process. In addition, VIs have been related with single crop coefficient (Kc), assuming constant rates of soil evaporation. The direct relationship between VIs and ET is conceptually incorrect due to the effect of the atmospheric demand on this relationship. The rising number of Earth Observation Satellites potentiates a data increase to feed the VI-based methodologies for estimating and mapping either the Kc or Kcb, with improved temporal coverage and spatial resolution. The development of operative platforms, including satellite constellations like Sentinels and drones, usable for the assessment of Kcb through VIs, opens new possibilities and challenges. This work analyzes some of the questions that remain inconclusive at scientific and operational level, including: (i) the diversity of the Kcb-VI relationships defined for different crops, (ii) the integration of Kcb-VI relationships in more complex models such as soil water balance, and (iii) the operational application of Kcb-VI relationships using virtual constellations of space and aerial platforms that allow combining data from two or more sensors.

14 del Rio-Mena, T.; Willemen, L.; Tesfamariam, G. T.; Beukes, O.; Nelson, A. 2020. Remote sensing for mapping ecosystem services to support evaluation of ecological restoration interventions in an arid landscape. Ecological Indicators, 113:106182. (Online first) [doi: https://doi.org/10.1016/j.ecolind.2020.106182]
Ecosystem services ; Ecological control ; Remote sensing ; Arid zones ; Normalized difference vegetation index ; Revegetation ; Earth observation satellites ; Geographical information systems ; Essential oils ; Biomass ; Thicket ; Forage ; Land degradation ; Erosion control ; Water flow ; Regulations ; Livestock ; Indicators ; Models / South Africa / Baviaanskloof Hartland Bawarea Conservancy
(Location: IWMI HQ Call no: e-copy only Record No: H049672)
https://vlibrary.iwmi.org/pdf/H049672.pdf
(1.27 MB)
Considerable efforts and resources are being invested in integrated conservation and restoration interventions in rural arid areas. Empirical research for quantifying ecosystem services – nature’s benefits to people – is essential for evaluating the range of benefits of ecological restoration and to support its use in natural resource management. Satellite remote sensing (RS) can be used to monitor interventions, especially in large and remote areas. In this study we used field measurements, RS-based information from Sentinel-2 imagery together with soil and terrain data, to estimate ecosystem service supply and evaluate integrated ecological restoration interventions. We based our research on the arid, rural landscape of the Baviaanskloof Hartland Bawarea Conservancy, South Africa, where several integrated interventions have been implemented in areas where decades of small livestock farming has led to extensive land degradation. Interventions included i) long term livestock exclusion, ii) revegetating of degraded areas, iii) a combination of these two, and iv) essential oil production as alternatives to goat and sheep farming. We assessed six ecosystem services linked to the objectives of the interventions: erosion prevention, climate regulation, regulation of water flows, provision of forage, biomass for essential oil production, and the sense of place through presence of native species. We first estimated the ecosystem service supply based on field measurements. Secondly, we explored the relationships between ecosystem services quantities derived from the field measurements with 13 Sentinel-2 indices and four soil and terrain variables. We then selected the best fitting model for each ecosystem service. Finally, we compared the supply of ecosystem services between intervened and non-intervened sites. Results showed that models based on Sentinel-2 indices, combined with slope information, can estimate ecosystem services supply in the study area even when the levels of field-based ecosystem services supplies are low. The RS-based models can assess ecosystem services more accurately when their indicators mainly depend on green vegetation, such as for erosion prevention and provision of forage. The agricultural fields presented high variability between plots on the provision of ecosystem services. The use of Sentinel-2 vegetation indices and terrain data to quantify ecosystem services is a first step towards improving the monitoring and assessment of restoration interventions. Our results showed that in the study area, livestock exclusion lead to a consistent increase in most ecosystem services.

15 Steinbach, S.; Cornish, N.; Franke, J.; Hentze, K.; Strauch, A.; Thonfeld, F.; Zwart, Sander J.; Nelson, A. 2021. A new conceptual framework for integrating earth observation in large-scale wetland management in East Africa. Wetlands, 41(7):93. [doi: https://doi.org/10.1007/s13157-021-01468-9]
Wetlands ; Environmental management ; Earth observation satellites ; Sustainable use ; Food security ; Environmental protection ; Surface water ; Land use ; Land cover ; Ecosystems ; Large scale systems ; Decision making ; Spatial data / East Africa / Rwanda
(Location: IWMI HQ Call no: e-copy only Record No: H050718)
https://link.springer.com/content/pdf/10.1007/s13157-021-01468-9.pdf
https://vlibrary.iwmi.org/pdf/H050718.pdf
(5.27 MB) (5.27 MB)
Wetlands are abundant across the African continent and provide a range of ecosystem services on different scales but are threatened by overuse and degradation. It is essential that national governments enable and ensure the sustainable use of wetland resources to maintain these services in the long run. As informed management decisions require reliable, up-to-date, and large coverage spatial data, we propose a modular Earth observation-based framework for the geo-localisation and characterization of wetlands in East Africa. In this study, we identify four major challenges in spatial data supported wetland management and present a framework to address them. We then apply the framework comprising Wetland Delineation, Surface Water Occurrence, Land Use/Land Cover classification and Wetland Use Intensity for the whole of Rwanda and evaluate the ability of these layers to meet the identified challenges. The layers’ spatial and temporal characteristics make them combinable and the information content, of each layer alone as well as in combination, renders them useful for different wetland management contexts.

16 Masenyama, A.; Mutanga, O.; Dube, T.; Bangira, T.; Sibanda, M.; Mabhaudhi, T. 2022. A systematic review on the use of remote sensing technologies in quantifying grasslands ecosystem services. GIScience and Remote Sensing, 59(1):1000-1025. [doi: https://doi.org/10.1080/15481603.2022.2088652]
Grasslands ; Ecosystem services ; Remote sensing ; Technology ; Earth observation satellites ; Hydrological modelling ; Systematic reviews ; Biomass ; Leaf area index ; Canopy ; Vegetation index ; Sensors ; Water management ; Monitoring ; Machine learning ; Forecasting
(Location: IWMI HQ Call no: e-copy only Record No: H051246)
https://www.tandfonline.com/doi/pdf/10.1080/15481603.2022.2088652
https://vlibrary.iwmi.org/pdf/H051246.pdf
(3.82 MB) (3.82 MB)
The last decade has seen considerable progress in scientific research on vegetation ecosystem services. While much research has focused on forests and wetlands, grasslands also provide a variety of different provisioning, supporting, cultural, and regulating services. With recent advances in remote sensing technology, there is a possibility that Earth observation data could contribute extensively to research on grassland ecosystem services. This study conducted a systematic review on progress, emerging gaps, and opportunities on the application of remote sensing technologies in quantifying all grassland ecosystem services including those that are related to water. The contribution of biomass, Leaf Area Index (LAI), and Canopy Storage Capacity (CSC) as water-related ecosystem services derived from grasslands was explored. Two hundred and twenty-two peer-reviewed articles from Web of Science, Scopus, and Institute of Electrical and Electronics Engineers were analyzed. About 39% of the studies were conducted in Asia with most of the contributions coming from China while a few studies were from the global south regions such as Southern Africa. Overall, forage provision, climate regulation, and primary production were the most researched grassland ecosystem services in the context of Earth observation data applications. About 39 Earth observation sensors were used in the literature to map grassland ecosystem services and MODIS had the highest utilization frequency. The most widely used vegetation indices for mapping general grassland ecosystem services in literature included the red and near-infrared sections of the electromagnetic spectrum. Remote sensing algorithms used within the retrieved literature include process-based models, machine learning algorithms, and multivariate techniques. For water-related grassland ecosystem services, biomass, CSC, and LAI were the most prominent proxies characterized by remotely sensed data for understanding evapotranspiration, infiltration, run-off, soil water availability, groundwater restoration and surface water balance. An understanding of such hydrological processes is crucial in providing insights on water redistribution and balance within grassland ecosystems which is important for water management.

17 Strauch, A.; Bunting, P.; Campbell, J.; Cornish, N.; Eberle, J.; Fatoyinbo, T.; Franke, J.; Hentze, K.; Lagomasino, D.; Lucas, R.; Paganini, M.; Rebelo, Lisa-Maria; Riffler, M.; Rosenqvist, A.; Steinbach, S.; Thonfeld, F.; Tottrup, C. 2022. The fate of wetlands: can the view from space help us to stop and reverse their global decline?. In Kavvada, A.; Cripe, D.; Friedl, L. (Eds.). Earth observation applications and global policy frameworks. Washington, DC, USA: American Geophysical Union (AGU); Hoboken, NJ, USA: John Wiley. pp.85-104. (Geophysical Monograph Series 274) [doi: https://doi.org/10.1002/9781119536789.ch5]
Wetlands ; Monitoring ; Collaboration ; Frameworks ; Earth observation satellites ; Landsat ; Datasets ; Mapping ; Sustainable Development Goals ; Stakeholders ; Ecosystem services ; Water resources ; Surface water ; Water quality ; Mangroves ; Land use ; Land cover ; Normalized difference vegetation index ; Case studies / Europe / Africa / Rwanda / Senegal
(Location: IWMI HQ Call no: e-copy only Record No: H051369)
https://vlibrary.iwmi.org/pdf/H051369.pdf
(23.00 MB)
Wetlands are among the most vulnerable, threatened, valuable, diverse, and heterogeneous ecosystems existing on our planet. While they provide invaluable ecosystem services to our society, they have been declining globally for many centuries. Monitoring of these changes is necessary for implementing efficient conservation policies and sustainable management schemes. Earth observation techniques can support the effort of monitoring, assessing, and inventorying wetlands at different scales with ever growing capabilities and toolsets. While the GEO-Wetlands initiative provides a framework for collaboratively increasing and utilizing these capabilities, global stakeholders like the Ramsar Convention on Wetlands and U.N. Environment are starting to adopt EO-based methods in their guidelines and technical reports. Many challenges still remain, although different projects and case studies successfully demonstrate the opportunities provided by the growing data archives, analysis algorithms, and processing capabilities. Many of these demonstrations focus on local wetland sites. The mapping and inventorying, specifically of vegetated wetlands, on national or even global scales remains a challenge for the wetlands and EO communities for years to come. Collaboration and partnership between different stakeholders of both communities are key for success. Initiatives like GEO-Wetlands, in cooperation with global stakeholders, need to provide the framework for this collaborative effort.

18 Ghosh, Surajit; Mukherjee, J. 2023. Earth observation data to strengthen flood resilience: a recent experience from the Irrawaddy River. Natural Hazards, 115(3):2749-2754. [doi: https://doi.org/10.1007/s11069-022-05644-w]
Earth observation satellites ; Floods ; Resilience ; Rivers ; Rain / Myanmar / Irrawaddy River
(Location: IWMI HQ Call no: e-copy only Record No: H051500)
https://vlibrary.iwmi.org/pdf/H051500.pdf
(3.22 MB)
The improvement of Earth Observation (EO) sensors and modern computational efficiency in the form of cloud analytics platform has made monitoring and interpretation of floods much more efficient. In this study, we present the recently occurred floods in the north-central section of the Irrawaddy River, inundating the adjoining farmlands on the active floodplains along a stretch of 228 km. The amount of rainfall was observed to have gradually risen from early June 2022 captured through GPM data. Similarly, the water levels in the study stretch were observed to have increased from 98.08 m to 104.08 m (from Sentinel-3 altimetry) due to torrential rains on the northern hilly tracts of Myanmar. High-resolution Sentinel-1 SAR datasets have been used to estimate flood progression in the GEE platform. The total inundated area had risen from 196 to 989 sq. km. throughout June till the first week of July. Thus, EO data associated with accessible computing on cloud platforms help monitor flood progression, warn the community well in advance and support the development of crop insurance strategies, anticipatory actions and many more to strengthen evidence-based flood policy.

19 Steinbach, S.; Hentschel, E.; Hentze, K.; Rienow, A.; Umulisa, V.; Zwart, Sander J.; Nelson, A. 2023. Automatization and evaluation of a remote sensing-based indicator for wetland health assessment in East Africa on national and local scales. Ecological Informatics, 75:102032. [doi: https://doi.org/10.1016/j.ecoinf.2023.102032]
Wetlands ; Ecosystems ; Environmental health ; Assessment ; Remote sensing ; Indicators ; Earth observation satellites ; Datasets ; Land use ; Surface water ; Water quality ; Vegetation ; Gomorphology ; Satellite imagery / East Africa / Rwanda
(Location: IWMI HQ Call no: e-copy only Record No: H051812)
https://www.sciencedirect.com/science/article/pii/S1574954123000614/pdfft?md5=37e51464f7fbd9d1321d786007b58ce3&pid=1-s2.0-S1574954123000614-main.pdf
https://vlibrary.iwmi.org/pdf/H051812.pdf
(8.71 MB) (8.71 MB)
To avoid wetland degradation and promote sustainable wetlands use, decision-makers and managing institutions need quantified and spatially explicit information on wetland ecosystem condition for policy development and wetland management. Remote sensing holds a significant potential for wetland mapping, inventorying, and monitoring. The Wetland Use Intensity (WUI) indicator, which is not specific to a particular crop and which requires little ancillary data, is based on the Mean Absolute Spectral Dynamics (MASD), which is a cumulative measure of reflectance change across a time series of optical satellite images. It is sensitive to the compound effects of land cover changes caused by different agricultural practices, flooding or burning. The more frequent and intrusive management practices are on the land cover, the stronger the WUI signal. WUI thus serves as a surrogate indicator to measure pressure on wetland ecosystems.
We developed a new and automated approach for WUI calculation that is implemented in the Google Earth Engine (GEE) cloud computing environment. Its automatic calculation, use of regular Sentinel-2 derived time series, and automatic cloud and cloud shadow masking renders WUI applicable for wetland management and produces high quality results with minimal user requirements, even under cloudy conditions. For the first time, we quantitatively tested the capacity of WUI to contribute to wetland health assessment in Rwanda on the national and local scale. On the national scale, we analyzed the discriminative power of WUI between different wetland management categories. On the local scale, we evaluated the possible contribution of WUI to a wetland ecosystem health scoring system. The results suggest that the adapted WUI indicator is informative, does not overlap with existing indicators, and is applicable for wetland management. The possibility to measure use intensity reliably and consistently over time with satellite data is useful to stakeholders in wetland management and wetland health monitoring, and can complement established field-based wetland health assessment frameworks.

20 Mukherjee, J.; Ghosh, Surajit. 2023. Decoding the vitality of earth observation for flood monitoring in the Lower Godavari River Basin, India. Journal of the Geological Society of India, 99(6):802-808. [doi: https://doi.org/10.1007/s12594-023-2387-9]
Floods ; Monitoring ; Earth observation satellites ; River basins ; Datasets ; Stream flow ; Forecasting ; Rainfall ; Monsoons ; Climate change ; Satellite imagery / India / Lower Godavari River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H052095)
https://vlibrary.iwmi.org/pdf/H052095.pdf
(2.44 MB)
The entire Indian subcontinent experienced devastating floods in the year 2022. The central section of the Godavari river basin (GRB) received torrential rainfall from the southwest monsoon during the second week of July 2022. This study exhibits how Earth observation (EO) datasets and cloud platforms like Google Earth Engine (GEE) can be used for swift, lucid and accurate decoding of the flood inundation signatures. Geospatial analysts can estimate concurrent floods using high-resolution C-band SAR/Sentinel-1 images, gridded precipitation and streamflow forecast datasets. The GPM (IMERG) precipitation data showed an incremental trend with prime hotspots, rainfall dissemination and retrieval from 01–20 July 2022 in the mid-GRB. The flood inundation layers were derived based on Otsu’s method with selective topographic conditions from Sentinel-1 in GEE. Five significant flood affected case sites were identified in the lower GRB from Kothapalli to Yanam town, where the Godavari river meets the Bay of Bengal. Large stretches of agricultural lands were found to be inundated, resulting in extensive economic losses. Such flooded farmlands surrounding Kothapalli, Bhadrachalam, Kunavaram, Polavaram and Yanam towns were estimated as 60, 91, 86, 170 and 142 km2 on 16 and 21 July 2022, respectively. The results were validated and cross-verified using bulletins and maps issued by various national agencies. Hence, EO, GEE and cloud analytical techniques are modern untapped potential e-assets vital for incorporation in policy frameworks helping disaster managers with comprehensive flood condition analysis.

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