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Dryland Monitoring in Turkmenistan Using Remote Sensing

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Dryland Monitoring in Turkmenistan Using Remote Sensing Dryland monitoring in Turkmenistan using remote sensing Lea Orlovsky and Dan Blumberg Shai Kaplan, Shimrit Tirosh, Eldad Eshed, Offir Matsraffi Batyr Mamedov and Elmar Mamedov Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Israel National Institute of Deserts, Flora and Fauna, Turkmenistan NEESPI/LCLUC Urumqi, China September 16-20, 2007 ResearchResearch AreaArea Research Area Background Objectives Outline Methods Results Analysis TotalTotal areaarea ofof TurkmenistanTurkmenistan --488,100 488,100 kmkm22 Conclusions KarakumKarakumDesert Desert (Black (Black Sands) Sands) occupies occupies more more than than 80% 80% •Nomadic and semi-nomadic livestock breeding is a significant income for Turkmenistan's economy and traditional occupation of local population •90% of forage comes from the natural pastures •Turkmenistan lies within the hydrological basin of the Aral and Caspian Seas Amu Darya is the region’s largest river and main source of water for drinking, agriculture, and supply to the Karakum Canal •After the fall of the Soviet regime the country experience the difficulties with the maintenance of engineering wells and water supply to distant pastures. Research Area Mean annual precipitation in the Kara-Kum desert is below 150 mm Background Objectives Outline Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 AgriculturalAgricultural potentialpotential ofof indigenousindigenous waterwater harvestingharvesting systemssystems inin thethe KarakumKarakum Desert Desert (USAID(USAID -- C21-031) C21-031) MonitoringMonitoring IndigenousIndigenous WaterWater HarvestingHarvesting SystemsSystems onon TakyrsTakyrs inin TurkmenistanTurkmenistan byby RemoteRemote Research Area SensingSensing Background Objectives Outline Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 TakyrsTakyrs (from(from TurkTurk -- barren barren land)land) These are broad and shallow clayey depressions of varying size ranging from 0.5 to tens of km2 in the Central Karakum Desert to tens and hundreds of square kilometers in western Turkmenistan Research Area Background Objectives Outline Methods Results Analysis Conclusions TakyrsTakyrs DueDue toto thethe TakyrTakyr’’ss propertiesproperties (fine(fine texture,texture, infiltrationinfiltration raterate andand lowlow slope),slope), duringduring rainfallrainfall events,events, runoffrunoff cancan bebe generatedgenerated Precipitation Research Area Sand dune Background “Takyr” Objectives Outline Runoff Methods Results Alluvial deposits Analysis Conclusions NEESPI/LCLUC Urumqi, China September“Oytak” 16-20, 2007 TakyrsTakyrs as as waterwater resourcesresources TheThe abilityability ofof aa TakyrTakyr toto collectcollect runoffrunoff Research Area ““NonNon--degradeddegraded ““DegradedDegraded TakyrsTakyrs”” Background TakyrsTakyrs”” DegreeDegree ofof Objectives degradationdegradation Outline Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 ResearchResearch ObjectivesObjectives 1.1. Determine the spectral characteristics of Takyrs and Solonchaks. 2. Determine the primary minerals of Takyr and Solonchak soils using X-Ray Diffraction. Research Area 3. Detect and assess the location and area of Background Takyrs in south Turkmenistan from the Objectives satellite images. Outline 4. Detect changes on the spatial distribution Methods of Takyrs over time.. Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 ResearchResearch OutlineOutline 11 10 Images Images QuickBird of of Images Layers LandSat LandSat 1+2 MSS 7 ETM+ 1972/5 2002/3 Pre processing Atmospheric and Geometric correction Classification Research Area Background Image Indices: NDVI, Albedo, Clay Mineral Maps processing Objectives change detection ,Supervised classification Outline Accuracy Output Methods Maps assessment Results Soil Field data Analysis XRD, spectrometer (on soil samples) measurements GPS Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 SpectralSpectral MeasurementsMeasurements FieldSpecFR (350-2500 nm) Research Area Background Objectives Outline Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 SpectrometricSpectrometric ResultsResults WeightingWeighting MethodMethod (Score:(Score: 00 -- 1)1) Spectral Spectral Binary Soil Feature Average Mineral type Angle Mapper Encoding sample Fitting Score SAM SFF BE Research Area Takyr Illite 0.918 0.954 0.881 0.917 Background Objectives Outline Solonchak Halite 0.861 0.978 0.88 0.906 Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 SpectrometricSpectrometric ResultsResults Research Area Background Objectives Outline Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 X-RayX-Ray DiffractionDiffraction ResultsResults Research Area Analysis of the Takyr spectra indicates the presence of: Background Quartz, Calcite, Illite, Albite or Orthoclase, Kaolinite and Halite. Objectives Outline Methods Results Analysis Conclusions Solonchak spectra analysis indicates that the main minerals composing this sample are: Quartz, Halite, Anorthite, Illite and Bassanite. ImageImage ClassificationClassification 11 LanduseLanduse/cover/cover Research Area classificationclassification Background 22 Objectives Outline Methods Results Analysis 33 RecodeRecode Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 ClassificationClassification ResultsResults Research Area Background Objectives Outline Methods Results Analysis Clean takyr Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 ChangeChange DetectionDetection Research Area Background Objectives Outline Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 AccuracyAccuracy assessmentassessment Research Area Background Objectives Outline Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 AccuracyAccuracy assessmentassessment Research Area Background Objectives Outline Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 AccuracyAccuracy assessmentassessment Research Area Background Objectives Outline Methods Results Analysis Conclusions AccuracyAccuracy assessmentassessment Research Area Background Objectives Outline Methods Results Analysis Conclusions GPSGPS Research Area Background Objectives Outline Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 ConclusionConclusion The main mineral components of the Takyr soil and of the Solonchak as derived from the spectrometer are Illite and Halite, respectively. The XRD supports our spectrometric results. An area of ~8000 km2 that were previously occupied by Research Area Takyrs has been degraded mainly due to anthropogenic Background pressure, leaving an area of ~17,000 km2 of non Objectives degraded Takyrs that is suitable for water harvesting. Outline Methods Results Analysis Conclusions NEESPI/LCLUC Urumqi, China September 16-20, 2007 ConclusionConclusion The difference of ~5000 km2 detected in the ETM+ imagery is mainly due to spectral and spatial resolutions between the two sensors relative to the size of the Takyr patches. Research Area According to this research, the available potential Background area suitable for water harvesting is strongly Objectives overestimated by local scientists and authorities . Outline Methods Results Analysis Conclusions Acknowledgements The research is supported by the United States Agency for International Development Thank you! Monitoring Vegetation Dynamics in Mongolia Using Remote Sensing Indices E. Eshed, L.Orlovsky, E. Adar - BGU F. Kogan – NOAA C.& E. Dugarjav, S. Tsooj, L. Jargalsaikhan, Sanjit, et al. – Institute of Botany, Mongolia מ ו נגול יה NEESPI/LCLUC Urumqi, China September 16-20, 2007 Research Aims •Develop and implement a remote sensing system for monitoring seasonal vegetation dynamics in four different ecosystems in Mongolia •Monitor grazing effects and trends in ecosystems מ ו נגול יה NEESPI/LCLUC Urumqi, China September 16-20, 2007 Bulgan Desert Steppe Height, 1442 m` NEESPI/LCLUC Urumqi, China September 16-20, 2007 Bayanunjuul Dry Steppe Height 1369 m` NEESPI/LCLUC Urumqi, China September 16-20, 2007 Tumensogt Typical Steppe Height 1000 m` NEESPI/LCLUC Urumqi, China September 16-20, 2007 Partizan Forest Steppe Height 1320 m` NEESPI/LCLUC Urumqi, China September 16-20, 2007 Normalized Indices Based on Historical Data Vegetation Condition Index (VCI) Month 1998 1999 2000 2001 2002 2003 MAX MIN July 0.2 0.124 0.3 0.344 0.268 0.316 0.34 0.12 Aug 0.272 0.182 0.268 0.344 0.3 0.256 0.344 0.182 Sep 0.268 0.204 0.3 0.384 0.384 0.412 0.412 0.204 VCINDV=(NDVIi in−Im ) NDV /( Im− axIm )× NDV 100 in VCI (July 1998)=(0.2-0.124)/(0.344-0.124)*100 VCI=34 The VCI expresses the relationship between physiological status of vegetation and moisture. China qi,NEESPI/LCLUC Urum September 16-20, 2007 Temperature Condition Index (TCI) Month 1998 1999 2000 2001 2002 2003 MAX MIN July 306 317 296 305 307 298 317 296 Aug 318 317 313 307 307 312 318 307 Sep 311 314 318 309 315 308 318 308 (TCI= max BTBTi− ) /( BT − min)BT max × 100 TCI (July 1998)=(317-306)/(317-280)*100 TCI=30 The TCI is received through NOAA-AVHRR channel 4, which measures the ground temperature China qi,NEESPI/LCLUC Urum September 16-20, 2007 Vegetation Health Index (VHI) VHI a= × VCI(+ 1− × ) a TCI Combines the two indices into one equation which assumes vegetation productivity is a result of
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