Your search found 163 records
1 Geoinformatics International. 2010. Images of 25 towns, Sri Lanka. Colombo, Sri Lanka: Geoinformatics International. 54p.
(Location: IWMI HQ Call no: 912 G744 GEO Record No: H042971)
2 Geoinformatics International. 2010. Images of 25 towns, Sri Lanka. Colombo, Sri Lanka: Geoinformatics International. 54p.
(Location: IWMI HQ Call no: 912 G744 GEO c2 Record No: H042972)
3 Gumma, M. K.; Thenkabail, P. S.; Barry, Boubacar. 2010. Delineating shallow ground water irrigated areas in the Atankwidi Watershed (Northern Ghana, Burkina Faso) using Quickbird 0.61 - 2.44 meter data. African Journal of Environmental Science and Technology, 4(7):455-464.
Groundwater irrigation ; Irrigated sites ; Watersheds ; River basins ; Remote sensing ; Land use ; Land cover ; Wells ; Satellite imagery / West Africa / Ghana / Burkina Faso / Volta River Basin / Atankwidi Watershed
(Location: IWMI HQ Call no: e-copy only Record No: H043080)
http://www.academicjournals.org/AJEST/PDF/pdf%202010/Jul/Krishna%20et%20al.pdf
https://vlibrary.iwmi.org/pdf/H043080.pdf
https://vlibrary.iwmi.org/pdf/H043080.pdf
(1.38 MB)
The major goal of this research was to delineate the shallow groundwater irrigated areas (SGI) in the Atankwidi Watershed in the Volta River Basin of West Africa. Shallow ground water irrigation is carried out using very small dug-wells all along the river banks or shallow dug-outs all along the river bed. Each of these dug-wells and dug-outs are highly fragmented small water bodies that irrigate only a fraction of an acre. However, these are contiguous dug-wells and dug-outs that are hundreds or thousands in number. Very high spatial resolution (VHSR) Quickbird imagery (0.61 to 2.44 m) was used to identify: (a) dug-wells that hold small quantities of water in otherwise dry stream; and (b) dug-outs that are just a meter or two in depth but have dug-out soils that are dumped just next to each well. The Quickbird VHSR imagery was found ideal to detect numerous: (i) dug-wells through bright soils that lay next to each dug-well, and (ii) water bodies all along the dry stream bed. We used fusion of 0.61 m Quickbird panchromatic data with 2.44 Quickbird multispectral data to highlight SGI and delineate their boundaries. Once this was achieved, classification techniques using Quickbird imagery was used within the delineated areas to map SGI and other land use/land cover (LULC) areas. Results obtained showed that SGI is practiced on a land area of 387 ha (1.4%), rainfed areas is 15638 ha (54.7%) and the remaining area in other LULC. These results were verified using field-plot data which showed an accuracy of 92% with errors of omissions and commissions less than 10%.
4 Rosenqvist, A.; Shimada, M. (Eds.) 2010. Global environmental monitoring by ALOS PALSAR: science results from the ALOS Kyoto and Carbon Initiative. Tsukuba, Ibaraki, Japan: Japan Aerospace Expoloration Agency. 87p.
Environmental monitoring ; Satellite imagery ; Forests ; Deforestation ; Mapping ; Watersheds ; Land cover mapping ; Deserts ; Wetlands ; Wildlife ; Nature conservation ; Habitats ; Flooding ; River basins ; Mangroves ; Peatlands ; Rice ; Climate change / Africa / Malawi / South Africa / Mozambique / USA / Brazil / Sweden / Canada / Australia / Asia / South East Asia / Borneo / Indonesia / Sumatra / Vietnam / Siberia / South East Asia / Amazon / Xingu Watershed / Greater Mekong Basin / Queensland / Nile River / Lake Urema / Congo River Basin / Sahara / Alaska
(Location: IWMI HQ Call no: e-copy only Record No: H043187)
http://www.eorc.jaxa.jp/ALOS/en/kyoto/ref/KC-Booklet_2010_comp.pdf
https://vlibrary.iwmi.org/pdf/H043187.pdf
https://vlibrary.iwmi.org/pdf/H043187.pdf
(17.26 MB) (17.26 MB)
This booklet presents results obtained within the ALOS Kyoto & Carbon (K&C) Initiative. The Initiative builds on the experience gained from the JERS-1 Global Rain Forest and Boreal Forest Mapping (GRFM/GBFM) projects, in which SAR data from the JERS-1 satellite were used to generate image mosaics over the entire tropical and boreal zones of Earth. While the GRFM/GBFM projects were undertaken already in the mid 1990's, they demonstrated the utility of L-band SAR data for mapping and monitoring forest and wetland areas and the importance of providing spatially and temporally consistent satellite acquisitions for regional-scale monitoring and surveillance. The ALOS K&C Initiative is set out to suppor t data and information needs raised by international environmental Conventions, Carbon cycle science and Conservation of the environment. The project is led by JAXA EORC and supported by an international Science Team consisting of some 25 research groups from 14 countries. The objective of the ALOS K&C Initiative is to develop regional-scale applications and thematic products derived primarily from ALOS PALSAR data that can be used to meet the specific information requirements relating to Conventions, Carbon and Conservation. The Initiative is undertaken within the context of three themes which relate to three specific global biomes; Forests, Wetlands and Deserts. A fourth theme deals with the generation of continental-scale ALOS PALSAR image mosaics. Each theme has identified key products that are generated from the PALSAR data including land cover, forest cover and forest change maps, biomass and structure (Forests), wetlands inventory and change (Wetlands) and freshwater resources (Deserts). Each of these products are generated using a combination of PALSAR, in situ and ancillary datasets. The mosaic data sets and thematic products generated within the Initiative are available to the public at the K&C homepage at JAXA EORC: http://www.eorc.jaxa.jp/ALOS/en/kyoto/kyoto_index.html
5 Rebelo, Lisa-Maria. 2010. Mapping of threatened wetlands along the Nile River. In Rosenqvist, A.; Shimada, M. (Eds.). Global environmental monitoring by ALOS PALSAR: science results from the ALOS Kyoto and Carbon Initiative. Tsukuba, Ibaraki, Japan: Japan Aerospace Expoloration Agency. pp.58-59.
Wetlands ; River basins ; Mapping ; Satellite imagery / Africa / Sudan / Nile River / Jonglei Canal / Sudd Wetland
(Location: IWMI HQ Call no: e-copy only Record No: H043188)
http://www.eorc.jaxa.jp/ALOS/en/kyoto/ref/KC-Booklet_2010_comp.pdf
https://vlibrary.iwmi.org/pdf/H043188.pdf
https://vlibrary.iwmi.org/pdf/H043188.pdf
6 Rebelo, Lisa-Maria. 2010. Mapping wetlands in Africa to improve understanding of wetland-livelihood interactions Lake Urema, Mozambique. In Rosenqvist, A.; Shimada, M. (Eds.). Global environmental monitoring by ALOS PALSAR: science results from the ALOS Kyoto and Carbon Initiative. Tsukuba, Ibaraki, Japan: Japan Aerospace Expoloration Agency. pp.60-61.
Wetlands ; Lakes ; Mapping ; Satellite imagery ; Ecosystems ; Floodplains / Africa / Mozambique / Lake Urema
(Location: IWMI HQ Call no: e-copy only Record No: H043189)
http://www.eorc.jaxa.jp/ALOS/en/kyoto/ref/KC-Booklet_2010_comp.pdf
https://vlibrary.iwmi.org/pdf/H043189.pdf
https://vlibrary.iwmi.org/pdf/H043189.pdf
7 Platonov, Alexander; Kuziev, R. K.; Abdurakhmonov, N. Y. 2010. Assessment method of salinization by means of satellite snapshots: the results on the farms of Syrdarya region, Uzbekistan. In Russian. In Proceedings of the Republican Scientific Practical Conference on Efficient Agricultural Water Use and Tropical Issues in Land Reclamation, Tashkent, Uzbekistan, 10-11 November 2010. Tashkent, Uzbekistan: Ministry of Agriculture and Water Resources; Tashkent, Uzbekistan: International Water Management Institute; Tashkent, Uzbekistan: Scientific Information Center of Interstate Commission for Water Coordination (SANIIRI). pp.265-270.
(Location: IWMI HQ Call no: e-copy only Record No: H043568)
(1.69 MB)
8 Ayana, E. K. 2007. Validation of radar altimetry lake level data and it's application in water resource management. MSc thesis. Enschede, Netherlands: International Institute for Geo-information Science and Earth Observation (ITC). 76p.
Water management ; International waters ; Radar satellite ; Measuring instruments ; Remote sensing ; Lakes ; Data analysis ; Statistical methods ; Cartography ; Satellite imagery / Ethiopia / Lake Tana / Nile River Basin
(Location: IWMI HQ Call no: 333.91 G000 AYA Record No: H043878)
(2.20 MB) (2.198MB)
9 de Pauw, E.; Oweis, T.; Nseir, B.; Youssef, J. 2008. Spatial modeling of the biophysical potential for supplemental irrigation: a case study in Syria. Aleppo, Syria: International Center for Agricultural Research in the Dry Areas (ICARDA). 38p.
Supplemental irrigation ; Models ; Case studies ; Water conservation ; Water allocation ; Remote sensing ; Mapping ; Satellite imagery / Syria
(Location: IWMI HQ Call no: 631.7.1 G746 DEP Record No: H043879)
http://www.iwmi.cgiar.org/assessment/files_new/publications/Supplemental%20Irrigation_ICARDA.pdf
https://vlibrary.iwmi.org/pdf/H043879.pdf
https://vlibrary.iwmi.org/pdf/H043879.pdf
(2.05 MB) (2.04MB)
10 Mohammed, M. A. 2007. Hydrological responses to land cover changes: modelling case study in Blue Nile Basin, Ethiopia. MSc thesis. Enschede, Netherlands: International Institute for Geo-information Science and Earth Observation (ITC). 64p. + annexes.
Hydrological cycle ; Land cover change ; River basins ; Case studies ; Simulation models ; Rainfall-runoff relationships ; Soil moisture ; Mapping ; Satellite imagery ; Data analysis ; Evaporation / Ethiopia / Blue Nile River Basin / Chemoga Watershed
(Location: IWMI HQ Call no: 551.48 G136 MOH Record No: H043880)
(0.07 MB)
11 Gumma, M. K.; Thenkabail, P. S.; Muralikrishna. I. V.; Velpuri, M. N.; Gangadhara Rao, Parthasaradhi; Dheeravath, V.; Biradar, C. M.; Acharya, N. Sreedhar; Gaur, A. 2011. Changes in agricultural cropland areas between a water-surplus year and a water-deficit year impacting food security, determined using MODIS 250 m time-series data and spectral matching techniques, in the Krishna River basin (India). International Journal of Remote Sensing, 32(12):3495-3520. [doi: https://doi.org/10.1080/01431161003749485]
Agricultural land ; Farmland ; Water availability ; Water use ; Water deficit ; Food security ; Models ; River basins ; Rain ; Rainfed farming ; Irrigated land ; Land use ; Land cover ; Climate change ; Satellite imagery ; Mapping ; Time series analysis ; Spectral analysis / India / Krishna River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H043968)
(1.46 MB)
The objective of this study was to investigate the changes in cropland areas as a result of water availability using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data and spectral matching techniques (SMTs). The study was conducted in the Krishna River basin in India, a very large river basin with an area of 265 752 km2 (26 575 200 ha), comparing a water-surplus year (2000–2001) and a water-deficit year (2002–2003). The MODIS 250 m time-series data and SMTs were found ideal for agricultural cropland change detection over large areas and provided fuzzy classification accuracies of 61–100% for various land-use classes and 61–81% for the rain-fed and irrigated classes. The most mixing change occurred between rain-fed cropland areas and informally irrigated (e.g. groundwater and small reservoir) areas. Hence separation of these two classes was the most difficult. The MODIS 250 m-derived irrigated cropland areas for the districts were highly correlated with the Indian Bureau of Statistics data, with R2-values between 0.82 and 0.86. The change in the net area irrigated was modest, with an irrigated area of 8 669 881 ha during the water-surplus year, as compared with 7 718 900 ha during the water-deficit year. However, this is quite misleading as most of the major changes occurred in cropping intensity, such as changing from higher intensity to lower intensity (e.g. from double crop to single crop). The changes in cropping intensity of the agricultural cropland areas that took place in the water-deficit year (2002–2003) when compared with the water-surplus year (2000–2001) in the Krishna basin were: (a) 1 078 564 ha changed from double crop to single crop, (b) 1 461 177 ha changed from continuous crop to single crop, (c) 704 172 ha changed from irrigated single crop to fallow and (d) 1 314 522 ha changed from minor irrigation (e.g. tanks, small reservoirs) to rain-fed. These are highly significant changes that will have strong impact on food security. Such changes may be expected all over the world in a changing climate.
12 Dooley, J. F. 2005. An inventory and comparison of globally consistent geospatial databases and libraries. Rome, Italy: FAO. 177p. (FAO Environment and Natural Resources Working Paper No. 19)
GIS ; Spatial database ; Databases ; Libraries ; Surveys ; Terminology ; Statistical data ; Data analysis ; Poverty ; Food insecurity ; Mapping ; Transport ; Mathematical models ; Geology ; Geomorphology ; Hydrogeology ; Soils ; Hydrology ; Drainage ; Watersheds ; Satellite imagery ; Land cover ; Vegetation ; Climatic data ; Agroecology ; Assessment ; Agricultural production
(Location: IWMI HQ Call no: 910.285 G000 DOO Record No: H044234)
This report presents an inventory of global data sources which can be used to provide consistent geospatial baselines for core framework data layers in the support of generalized base mapping, emergency preparedness and response, food security and poverty mapping. In the report, only globally consistent data sources at the scales of 1:5 million or larger for vector data and a nominal pixel size of 5 arc minutes or higher resolution for raster data, were considered. The sources of data presented in the inventory were identified based on a review of on-line Internet resources conducted in the first quarter of 2004 and updated in January 2005.The inventory is divided into two parts: with Part One of the inventory presenting overview, terminology and summary sections of globally consistent data libraries; while Part Two contains a categorization of the data sources identified broken into topical subsections based on the individual core data layers specified by UNGIWG and FAO. The report also includes a matrix rating the suitability of the various data sources identified to each of the core data layers specified by UGIWIG and FAO, and introduces Virtual Base Maps as a potential cost-effective means for: providing spatial referencing to remote field offices, enhancing Internet map serving capabilities, and facilitating mapping via GPS handheld devices.
13 Gumma, M. K.; Thenkabail, P. S.; Hideto, F.; Nelson, A.; Dheeravath, V.; Busia, D.; Rala, A. 2011. Mapping irrigated areas of Ghana using fusion of 30 m and 250 m resolution remote-sensing data. Remote Sensing, 3(4):816-835. [doi: https://doi.org/10.3390/rs3040816]
Remote sensing ; Methodology ; Mapping ; Irrigated land ; Irrigated farming ; Land use ; Land cover ; Satellite imagery ; Statistics / Ghana
(Location: IWMI HQ Call no: e-copy only Record No: H044267)
(1.69MB)
Maps of irrigated areas are essential for Ghana’s agricultural development. The goal of this research was to map irrigated agricultural areas and explain methods and protocols using remote sensing. Landsat Enhanced Thematic Mapper (ETM+) data and time-series Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to map irrigated agricultural areas as well as other land use/land cover (LULC) classes, for Ghana. Temporal variations in the normalized difference vegetation index (NDVI) pattern obtained in the LULC class were used to identify irrigated and non-irrigated areas. First, the temporal variations in NDVI pattern were found to be more consistent in long-duration irrigated crops than with short-duration rainfed crops due to more assured water supply for irrigated areas. Second, surface water availability for irrigated areas is dependent on shallow dug-wells (on river banks) and dug-outs (in river bottoms) that affect the timing of crop sowing and growth stages, which was in turn reflected in the seasonal NDVI pattern. A decision tree approach using Landsat 30 m one time data fusion with MODIS 250 m time-series data was adopted to classify, group, and label classes. Finally, classes were tested and verified using ground truth data and national statistics. Fuzzy classification accuracy assessment for the irrigated classes varied between 67 and 93%. An irrigated area derived from remote sensing (32,421 ha) was 20–57% higher than irrigated areas reported by Ghana’s Irrigation Development Authority (GIDA). This was because of the uncertainties involved in factors such as: (a) absence of shallow irrigated area statistics in GIDA statistics, (b) non-clarity in the irrigated areas in its use, under-development, and potential for development in GIDA statistics, (c) errors of omissions and commissions in the remote sensing approach, and (d) comparison involving widely varying data types, methods, and approaches used in determining irrigated area statistics using GIDA and remote sensing. Extensive field campaigns to help in better classification and validation of irrigated areas using high (30 m ) to very high (<5 m) resolution remote sensing data that are fused with multi temporal data like MODIS are the way forward. This is especially true in accounting for small yet contiguous patches of irrigated areas from dug-wells and dug-outs.
14 Joshi, P. K.; Singh, T. P. 2011. Geoinformatics for climate change studies. New Delhi, India: The Energy and Resources Institute (TERI). 470p.
Remote sensing ; GIS ; Climate change ; Environmental temperature ; Global warming ; Models ; Mountains ; Glaciers ; Forests ; Ecosystems ; Phenology ; Mapping ; Sea level ; Water management ; Evapotranspiration ; Land degradation ; Satellite imagery ; Natural disasters ; Landslides ; Flooding ; Wildfires ; Risk reduction ; Research ; Greenhouse gases ; Vegetation ; Invasive species ; River basins ; Health hazards ; Waterborne diseases ; Diarrhoea ; Malaria ; Land degradation ; Data analysis / South Africa / Nigeria / Bangladesh / Morocco / Germany / Thailand / Malaysia / Australia / Eastern Cape Province / Mooi River Basin / Weida River Basin / Murray Darling River Basin / Thuringia / Chang Mai / Kanchanaburi
(Location: IWMI HQ Call no: 621.3678 G000 JOS Record No: H044290)
(0.33 MB)
15 Bossio, Deborah; van der Zaag, P.; Jewitt, G.; Mahoo, H. (Eds.) 2011. Smallholder system innovation for integrated watershed management in Sub-Saharan Africa. Agricultural Water Management, 98(11):1683-1773. (Special issue on "Smallholder systems innovations for integrated watershed management in Sub-Saharan Africa" with contributions by IWMI authors).
Watershed management ; Smallholders ; Farmers ; Yields ; Tillage ; Farming systems ; Dry farming ; Rainfed farming ; Case studies ; Water productivity ; Water allocation ; Water use ; Simulation models ; Grasslands ; Sloping land ; Land degradation ; Spate irrigation ; Satellite imagery ; River basins / Africa South of Sahara / South Africa / Tanzania / KwaZulu-Natal / Makanya catchment / Thukela River Basin / Pangani River Basin / South Pare Mountains
(Location: IWMI HQ Call no: PER Record No: H044307)
16 Vrba, J.; Verhagen, B. T. (Eds.) 2011. Groundwater for emergency situations: a methodological guide. Paris, France: UNESCO. International Hydrological Programme (IHP). 316p. (UNESCO IHP-VII Series on Groundwater No. 3)
Water resources ; Groundwater recharge ; Disaster preparedness ; Drinking water ; Water supply ; Geology ; Hydrogeology ; Hydrology ; Remote sensing ; GIS ; Mathematical models ; Risk assessment ; Risk management ; Water governance ; Policy ; Early warning systems ; Natural disasters ; Flooding ; Drought ; Earthquakes ; Landslides ; Tsunamis ; Storms ; Cyclones ; Volcanoes ; Water flow ; Aquifers ; Isotopes ; Case studies ; Sewage ; Drainage ; Rehabilitation ; Chemical composition ; Analytical methods ; Satellite surveys ; Satellite imagery ; Capacity building / South Africa / South Germany / Czech Republic / India / China / Peru / Maldives / Sri Lanka / Japan / Molasses Basin / Labe River / Elbe River / Orissa / Shenthen Xikeng Reservoir
(Location: IWMI HQ Call no: e-copy only Record No: H044405)
(17.39 MB) (17.4MB)
The aim of the UNESCO IHP project ‘Groundwater for Emergency Situations’ (GWES) is to consider natural catastrophic events that could adversely influence human health and life and to identify in advance emergency groundwater resources resistant to natural disasters that could replace damaged public and domestic drinking water supplies. The GWES project was approved during the 15th session of the Intergovernmental Council of the International Hydrological Programme (IHP). It was included in the Implementation Plan of the Sixth Phase of the IHP (2002–2007), Theme 2: ‘Integrated watershed and aquifer dynamics’, under the title ‘Identification and management of strategic groundwater bodies to be used for emergency situations as a result of extreme events or in case of conflicts’. The Second phase of the GWES project is implemented within IHP VII (2008–2013) by an International Working Group composed of UNESCO, and IAH representatives and experts from different regions of the world.
17 Thenkabail, P. S.; Lyon, J. G.; Huete, A. (Eds.) 2012. Hyperspectral remote sensing of vegetation. Boca Raton, FL, USA: CRC Press. 705p.
Remote sensing ; Vegetation ; Indicators ; Multispectral imagery ; Satellite observation ; Satellite imagery ; Image analysis ; Data processing ; Data analysis ; Algorithms ; Models ; Sensors ; Water use ; Agriculture ; Crop management ; Cereal crops ; Cotton ; Botany ; Tissue analysis ; Nitrogen content ; Moisture content ; Plant diseases ; Pastures ; Indicator plants ; Species ; Canopy ; Forest management ; Tropical forests ; Wetlands ; Ecosystems ; Soil properties ; Land cover ; Reflectance
(Location: IWMI HQ Call no: 621.3678 G000 THE Record No: H044548)
(0.54 MB)
18 Kam, S. P.; Teoh, Shwu J.; Hoanh, Chu Thai; Reis, J.; McCartney, Matthew; Lacombe, Guillaume. 2011. Identifying land and water resources for improving livelihoods of people living around reservoirs in the Mekong Basin. [Abstract only]. Paper presented at the 3rd International Forum on Water and Food, Tshwane, South Africa, 14-17 November 2011. 2p.
Water resources ; Land resources ; Reservoirs ; River basins ; GIS ; Satellite imagery ; Research project / South East Asia / Laos / Cambodia / Mekong River Basin / Nam Gnouang Reservoir
(Location: IWMI HQ Call no: e-copy only Record No: H044554)
http://cgspace.cgiar.org/bitstream/handle/10568/10549/MSSe001_Final_RD_1710.pdf?sequence=3
https://vlibrary.iwmi.org/pdf/H044554.pdf
https://vlibrary.iwmi.org/pdf/H044554.pdf
(0.28 MB) (288.68KB)
19 Yilmaz, K. K.; Yucel, I.; Gupta, H.V.; Wagener, T.; Yang, D.; Savenjie, H.; Neale, C.; Kunstmann, H.; Pomeroy, J. (Eds.) 2009. New approaches to hydrological prediction in data-sparse regions: proceedings of symposium HS.2 at the Joint Convention of the International Association of Hydrological Sciences (IAHS) and the International Association of Hydrogeologists (IAH), Hyderabad, India, 6-12 September 2009. Wallingford, UK: International Association of Hydrological Sciences (IAHS). 342p. (IAHS Publication 333)
Hydrological factors ; Simulation models ; River basins ; Calibration ; Remote sensing ; Hydrometeorology ; Climate change ; Forecasting ; Rainfall-runoff relationships ; Flooding ; Drought ; Water balance ; Precipitation ; Case studies ; Evapotranspiration ; Satellite surveys ; Satellite imagery ; Catchment areas ; Groundwater ; Data ; Monitoring ; Macropores ; Vegetation ; Downstream ; Watersheds ; Analytical methods / Iran / West Africa / South Africa / China / India / Peru / USA / Brazil / Botswana / Karkheh River Basin / River Bani / Yellow River / Hanjiang Basin / Sahel / Kaidu River Basin / Laohahe River Basin / Peruvian Amazon-Andes Basin / Arizona / San Francisco River Basin / Brahmaputra River Basin / Limpopo River Basin
(Location: IWMI HQ Call no: 551.48 G000 YIL Record No: H044653)
(0.44 MB)
20 Chemin, Yann. (Ed.) 2012. Remote sensing of planet earth. Rijeka, Croatia: InTech. 240p.
Remote sensing ; GIS ; Vegetation ; Water resources ; Surface Water ; Mapping ; Monitoring ; Wetlands ; Lakes ; Satellite surveys ; Satellite imagery ; Image analysis ; Image processing ; Data ; Analytical methods ; Time series analysis ; Land cover ; Land classification ; Land use ; Tsunamis ; Snow cover ; Models ; Environmental effects ; Water vapour / Brazil / China / Italy / Indonesia / Thailand / Chile / Japan / Solomon Islands / Samoa Islands / Indonesia / Peruacu watershed / Tibet Plateau / Umbria / Subasio Mountain Regional Park / Banda Aceh / Phang Nga / Phuket / Tohoku / Okushiri Island / Banda Aceh
(Location: IWMI HQ Call no: IWMI Record No: H044692)
http://www.intechopen.com/books/show/title/remote-sensing-of-planet-earth
https://vlibrary.iwmi.org/pdf/H044692.pdf
https://vlibrary.iwmi.org/pdf/H044692.pdf
(28.13 MB) (28.13MB)
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