Early-warning and drought risk reduction

 

http://www.iwmi.cgiar.org/2017/01/press-release-satellite-based-early-warning-system-to-bolster-drought-risk-reduction/

Press Release: Satellite based early-warning system to bolster drought risk reduction

Experts meet in Delhi to discuss how South Asian countries could adopt the new drought monitoring system to better prepare and mitigate drought risks

(Delhi, January 30):  The South Asia Drought Monitoring System (SADMS) and its newly launched online portal was demonstrated at a regional workshop held in New Delhi today. The SADMS expected to provide near-real information of drought onset and progression helping decision makers respond in time. The interactive SADMS online portal, http://dms.iwmi.org/, would help in data sharing and viewing of all available drought and related maps for the entire region instantly.

Speaking at the event, Dr. Trilochan Mohapatra, Secretary (DARE) & Director General of ICAR, Government of India said, “South Asia routinely suffers from drought and severe impact on agriculture production and livelihoods.  Early warning and monitoring system are important but at the same time need to be robust as climatic variation is huge and location specific. If water is going to be more limited in the future and droughts more frequent, a drought monitoring system would be even more relevant going forward.”

To make geospatial tracking and mapping products more accessible

Photo credit: FAO

Forest researchers in Viet Nam use laser technologies to measure tree height and thickness.

Google and FAO partner to make remote sensing data more efficient and accessible

Partnership enhances ability to assess changing forest and to estimate greenhouse gas emissions

Google Maps and FAO have agreed to work closely together to make geospatial tracking and mapping products more accessible, providing a high-technology assist to countries tackling climate change and much greater capacity to experts developing forest and land-use policies.

Digital technology tapping into satellite imagery is revolutionizing the way countries can assess, monitor and plan the use of their natural resources, including monitoring deforestation and desertification.

“For FAO, this is not just a partnership. This is a strategic alliance,” said FAO Director-General José Graziano da Silva, noting it combines FAO’s global effort to combat climate change with Google’s commitment to help on the climate data science and awareness fronts.

The three-year partnership between Google Maps and FAO is designed to foster innovation and expertise and sharply broaden access to easy-to-use digital tools. It ushers in a major ramping up of existing collaboration between the two organizations and will boost the visibility and implementation of efforts to encourage sustainable environmental practices around the world.

“This partnership is powerful because it unites the complementary strengths of UN FAO and Google,” said Rebecca Moore, Director, Google Earth, Earth Engine & Earth Outreach. “FAO has decades of hard-won experience working on the ground in hundreds of countries on thousands of projects. Meanwhile, Google technology is at the cutting edge of big data, cloud computing, and transformatively-simple mapping tools. The FAO Collect Earth application brilliantly builds on top of Google Earth and Earth Engine to provide a simple but powerful global and national forest carbon monitoring tool, empowering countries as diverse as Chile, Panama, Namibia, Papua New Guinea, Tunisia and Bhutan. We look forward to further strengthening this partnership in support of global climate action and sustainable development.”

Concretely, Google Maps will provide 1,200 trusted tester credentials on Google Earth Engine to FAO staff and partners, while also providing training and receiving feedback on users’ needs and experiences.

Read the full article: FAO

Climate and Desertification in the Dry Land Asia

 

Future Climate Impact on the Desertification in the Dry Land Asia Using AVHRR GIMMS NDVI3g Data

by Lijuan Miao, Peilong Ye, Bin He, Lizi Chen and Xuefeng Cui

in Remote Sens. 2015, 7(4), 3863-3877

Abstract:

Dry Land Asia is the largest arid and semi-arid region in the northern hemisphere that suffers from land desertification. Over the period 1982–2011, there were both overall improvement and regional degeneration in the vegetation NDVI. We analyze future climate changes in these area using two ensemble-average methods from CMIP5 data. Bayesian Model Averaging shows a better capability to represent the future climate and less uncertainty represented by the 22-model ensemble than does the Simple Model Average. From 2006 to 2100, the average growing season temperature value will increase by 2.9 °C, from 14.4 °C to 17.3 °C under three climate scenarios (RCP 26, RCP 45 and RCP 85). We then conduct multiple regression analysis between climate changes compiled from the Climate Research Unit database and vegetation greenness from the GIMMS NDVI3g dataset. There is a general acceleration in the desertification trend under the RCP 85 scenario in middle and northern part of Middle Asia, northwestern China except Xinjiang and the Mongolian Plateau (except the middle part). The RCP 85 scenario shows a more severe desertification trend than does RCP 26. Desertification in dry land Asia, particularly in the regions highlighted in this study, calls for further investigation into climate change impacts and adaptations.

Bibliography

Quantitative Assessment of Desertification Using Landsat Data on a Regional Scale – A Case Study in the Ordos Plateau, China

Duanyang Xu et al. – Sensors, 2009

On the Current and Future Dry Spell Characteristics over Africa

Bessam Bouagila et al. – Atmosphere, 2013

Satellite data to measure and monitor land degradation

 

UNCCD CST S-4 Side Event Discusses Use of Satellite Data

A side event organized by the Scientific and Technical Advisory Panel of the Global Environment Facility (GEF/STAP) during the fourth special session of the Committee on Science and Technology (CST S-4) of the UN Convention to Combat Desertification (UNCCD) considered ‘The use of satellite data to measure and monitor land degradation over time at multiple scales.’

Participants at the side event were informed of a new GEF project that will seek to provide guidance, methods and tools to monitor and assess land degradation using remote sensing, and they were encouraged to address the needs of users of remote sensing. Speakers noted challenges in harmonizing and interpreting data from different remote sensing products and how the data could be used to develop policy advice, among other topics.

Read the full text: IISD

Desertification and remote sensing

Photo credit: Google

Jilin City (red) in Jilin province (orange)

Study on Remote Sensing of the Degree of Land Desertification in the West of Ji Lin Province

Posted by Basic Science

See: Basic Science Paper

Land desertification that is an important content in the global change research is the one of most serious ecological problems all over the world. It is not only the threat to the survival of the human environment, but also the important factor to restrict the development of the global economy and affect Social stability. If we don’t take fundamental measures, the process of land desertificationwill not stop automatically, but will intensify to develop.We should start from the inherent attributes of the land desertification for learning to its type and extent. The comprehensive application and research of the Remote Sensing Data and Multiple Geo-information can be show attributes and inherent feature of the objects with a variety of ways and different scales. It’s very advantaged for Remote Sensing information to distinguish the object with their differentia of electromagnetic radiation features, but also it have some limitations. Practice has proved that we must relate Remote Sensing data to Multiple Geo-information that contain Geological data and Geochemical data with addition of the difficulty of geological work, and then we truly understand the nature of the objects and relation each other, also to be satisfied with the application of geological effects.

Heavenly Lake, Changbai Mountains in Jilin Province, China. September, 2003 – http://www.uoguelph.ca/~thsiang/visit/tianchi.jpg

This article use the west of Ji Lin Province as study area. It make an estimate to desert land in working area as a whole with Remote Sensing Data (2007 ETM) and Geochemical Data (the results of 1:200000 soil geochemical survey in the west of Ji Lin Province).

Major work is as follows:(1) The classification of desert land.We obtain the information of land desertification in the west of Ji Lin Province by the ways of unsupervised classification and supervised classification, and then compare the results of both so that to separate accurately desert land and undesert land. The result indicates that the method of supervised classification is more accurate.(2) Enhance the information of Clay minerals among Remote Sensing Data. The special configuration of the objects fix on their Physical and Chemical character. We can analyse the inherent attributes after studying their spectrum character. Clay minerals which play an important role in extent of Land Desertification is an important part of soil composing. But vegetation and clay minerals have similar characteristic absorbable spectrum because the west of Ji Lin Province locate moist area. We should make use of Band Ratio and Principal Components to avoid vegetation information that would disturb clay minerals information in Remote Sensing Data as a whole hog so that we can analyse accurately the negative correlation between the extent of desertification and content of clay minerals.(3) Research methods of combination and classification of elements about Geochemical Data.We make use of Genealogy Cluster Analysis to combine and classify various elements among Geochemical data. The establishment of equal deep image of minerals content such as Quartz, Clay Minerals, Carbonate and so on could reflect directly the distribution of various minerals about Geochemical Data. It validates the seasonable of classification through contrasting Remote Sensing Image.(4) Complete the classification evaluation of desert land and find the variety rule between Remote Sensing spectrum and mineral content.The substance composing of different degrees of desert land is different. There is a close relationship between mineral content and spectral characteristics. We can found the association of both after establishing relevant model of Remote Sensing Spectral Profile image and equal deep image of minerals content.This article first study on Remote Sensing of the degree of land desertification to study area by the ways of combining geochemical data. It’s also the innovation point. It not only has done the evaluation of distribution and degree of desertification land, but also has realized semi-quantitative analysis of clay minerals to desertification land of different degrees. Reached the conclusions as follows:(1) It’s a negative correlation between the extent of desertification and content of clay minerals. The more serious desertification, the less content of clay minerals. There is may be a potential desertification to crops and grassland that contain less clay minerals.(2) The contain of Quartz is more than 42.115077% and the contain of clay minerals is less than 6.410923% to desert land which degree is serious; The contain of Quartz is 39.673305～42.115077% and the contain of clay minerals is 6.410923～8.557119% to desert land which degree is moderate; The contain of Quartz is 34.789760～39.673305% and the contain of clay minerals is 8.557119～10.414073% to desert land which degree is mild.

How to keep track of the world’s carbon stocks ?

Photo credit: Pixabay

Victoria Falls rain forest (Zimbabwe)

Mapping forests’ carbon with lasers

VIDEO : http://youtu.be/ATBFfJFDOwU

EXCERPT

Measuring carbon emissions is crucial for planning a response to climate change. But scientists have so far struggled to keep track of the world’s carbon stocks and how they vary.

At the Carnegie Airborne Observatory, he has developed a lidar (light detection and ranging) system based on laser technology that is flown over the tropics to measure how much carbon is trapped in the forests, and where deforestation, illegal logging and mining activities are releasing it.

This video shows what pilots can see from above the forest, and how the system turns aerial imagery into colourful, animated carbon maps.

– See more at: http://www.scidev.net/global/forestry/multimedia/mapping-forests-carbon-lasers.html#sthash.V8e8qZff.dpuf

 

Water scarcity impacts and drought early warning system in Iran

Photo credit: GFCS

Zayandehrood-river, Iran

Implementation of Drought Early-warning System over IRAN (DESIR)

Iran’s precipitation is approximately one third of global average and distribution of the monthly rainfall has been changed in recent years. Water scarcity has many environmental and socio-economical impacts over Iran. Unlike to the floods that have limited coverage areas, water scarcity impacts cover vast regions. By increasing global mean temperature, drought and population, water and its consumption has become important. This may even become more significant in those countries where the volume of rainfall is limited. Occurrence of drought is one of the main reasons of the water crisis. Implementation of a drought early warning system is the most important priority for I. R. of Iran Meteorological Organization (IRIMO).

Read the full article: Global Framework Climate Services

Earth Observation (EO) data for desertification indicators

Photo credit: CERENA

Development of EO indicators for the Dynamic of Desertification in Southern Africa

This is a one year project involving a partnership with ISEGI, Mondelane U. and U. DELFT.

The aim of this project is the analysis of new dynamics of desertification in the region Southern Africa ( Mozambique , Zimbabwe and Northern part of South Africa ) by using and implementing the main achievements of the DW –E, a methodology developed by CERENA and a standard processing chain over Earth Observation data, in order to produce desertification indicators, allowing the monitoring of areas subject or in risk of desertification.

A second objective is to propose new methods for integration of EO data with different spatial and spectral resolutions, namely the new ESA Proba- V mission with products ranging in spatial resolution from 100m to 1km , and new field data in particular the survey and risk map of natural disasters made between 2010 and 2011 for Mozambique.

Read the full article: CERENA

The partial greening of the Sahel and climate change

Photo credit: Marc Pille

Reforestation project with Jatropha curcas in Mali 2009-10

A climate model-based review of drought in the Sahel: Desertification, the re-greening and climate change

by Alessandra Giannini , Michela Biasutti

and Michel M. Verstraete

Abstract

We review the evidence that connects drought and desertification in the Sahel with climate change past, present and future.  Advances in climate modeling point to the oceans, not land, as the cause of the recent persistence of drought in the Sahel.

The current generation of global climate models reproduces the spatial extent, continental in scale, and the timing and duration of the shift to dry conditions that occurred in the late 1960’s given knowledge of observed surface oceanic conditions only.

The pattern statistically and dynamically associated with drought is one of warming of the tropical oceans, especially the Pacific and Indian Oceans, superimposed on an enhanced warming of the southern compared to the northern hemisphere most evident in the Atlantic.

These models, which include a prognostic description of land surface and/or vegetation, albeit crude, indicate that positive feedbacks between precipitation and land surface/cover may act to amplify the ocean-forced component of continental climate.

Despite the advances made in understanding the recent past, uncertainty dominates as we move forward in time, to the present, partial greening of the Sahel, and to the future of climate change projections.

Read the full article: Science Direct

 

Appropriate indicators of land-cover modifications

Photo credit: Pixabay

Monitoring land-cover changes in semi-arid regions: remote sensing data and field observations in the Ferlo, Senegal

by A. Diouf and E.F. Lambin

Abstract

Dryland degradation rarely translates into linear, declining trends in vegetation cover due to interannual climatic variability. Appropriate indicators of land-cover modifications need to be defined for semi-arid regions.

Our hypothesis is that degradation can be measured by:

• (1) a decrease in the resilience of vegetation to droughts;
• (2) a decrease in rain-use efficiency; and
• (3) a modification of floristic composition.

The objective of this paper is to test the relationships between a remotely sensed indicator of vegetation, rainfall data and field measurements of biomass and floristic composition.

The study was based on field measurements of vegetation conditions covering a period of 10 years, in the semi-arid region of the Ferlo in Senegal.

Our results indicate that land-cover modifications in the Ferlo are best measured by changes in rain-use efficiency. No consistent trend in the relative abundance of grass species was visible at the scale of the decade, even on the two sites affected by degradation. Just after a drought, a given increase in rainfall results in less biomass production than is the case for normal years.

Read the full article: Science Direct

Alarming increase in the spread of sand dunes in India (Google / Directions Magazine India)

Read at : Google Alerts – desertification

http://www.directionsmag.in/articles/remote-sensing-reveals-desertification/429293

Andhra Pradesh State Remote Sensing Applications Centre study reveals desertification and land degradation

By Aditi Pandey

---

Andhra Pradesh State Remote Sensing Applications Centre has revealed an alarming increase in the spread of sand dunes, as 0.32 sq. km of land is being covered by sand dunes every year since the last 10 years.

The study revealed different signs of desertification and land degradation in the study area as judged by change in patterns of land use and land cover types. These changes indicated an increase of degrading land, vegetation cover, sandy soil and sandy clay in the study area. Desertification is one of the main problems threatening the agricultural production The study aimed at monitoring and assessing desertification in area, in addition to investigating the potential use of remote sensing and GIS) in assessing and monitoring sand encroachment and vegetation degradation as desertification indicators in the semi-arid environment.

(continued)

GIS techniques to assess desertification with IMDPA model in IRAN ( ijabr)

Read at :

http://www.ijabbr.com/article_9989_1344.html

Assessment of Land Degradation and Desertification with Use of IMDPA Model (Case Study; Chah-hashm Plain, Iran)

Article 4, Volume 2, Issue 10, October 2014, Page 2644-2650  PDF (480 K)

Document Type: Original Article

Authors

1 Nasrollah Aslinezhad ; 2 Ahmad Pahlavanravi; 2 Nasrollah Basirani; 3 Mahdiye Ebrahimi; 4 Rasoul Kharazmi

1M.sc graduated of combating desertification, University of Zabol, Zabol, Iran

2Associate Professor, Department of Rang and watershed management, University of Zabol, Zabol, Iran

3Assistant Professor, Department of Rang and watershed management, University of Zabol, Zabol ,Iran

4M.sc graduated of Information System and Technology, Moscow State University of Geodesy and Kartographi, Russian

Abstract

Objective: More than 75 percent of Iran is located in arid and semi-arid then land degradation and desertification are one of the crises ecological. We require a proper understanding of causes and processes of desertification to control the huge phenomenon on the global and regional situation. Because southeast of Iran located in arid land then assessment of desertification is very importance for planning of project. Methods: In this study, using GIS techniques to assess desertification with IMDPA model in 27.020 Ha of Chah-hashm Plain. Results: Result show vegetation criteria (2.97) is more effective than climate criteria (2.68) and other hand aridity index (3.92) is most effective index and continuing drought (1.6) index is less effective index in this area. Result indicated intensity of desertification is in high class with 2.82 numerical value. In this area some limitations such as lack of rainfall, high temperatures, high evaporation, the instability and sensitivity to soil erosion is a natural limits of the area and cannot be control but with improved irrigation methods, education and extension service for the optimization use of agricultural land can be move to improve the situation and to assist in slowing desertification