Challenges of National Level Forest Cover Change Assessment in Myanmar

Transcription

1 International Land Cover/Land Use Changes Regional Science Team Meeting in South/Southeast Asia January 13 th - 15 th, 2016, Summit Park View Hotel, Yangon, Myanmar Challenges of National Level Forest Cover Change Assessment in Myanmar Aung Aung Myint, agagmyint@gmail.com Planning and Statistics Division, Forest Department, Ministry of Environmental Conservation and Forestry

2 Presentation Outline General Information (Country Profile) Objective of presentation Institutional Structure Background Information on Forest Management Application of RS and GIS National level Forest Cover Assessment Challenges of National level FC Change Assessment Current collaboration on FM in FD & Conclusion

3 General Information (Country Profile) Location Latitudes = 9 58 to North Longitudes = to East Area Total land area = 676,577 km 2 Length (north to south) = 2,090 km Maximum width (west to east) = 805 km Total number of districts = 68 Administrative Setup: Country->State (07)->Regions (07)- >Districts (68)->Township (318) Climatic Information Rainfall Minimum rainfall = 500 mm Maximum rainfall = 5, 000 mm Population 51.4 million (Census, 2014) Over 100 Ethnic groups Temperature 25 C to 33 C (Rainy Season) 10 C to 25 C (Cold Season) 32 C to 38 C (Hot Season) 43 C (Maximum Temperature)

4 Distribution of Vegetation Types in Myanmar. General Information-Major Forest Types Distribution of Vegetation Types in Myanmar. Source: A Checklist of the Trees, Shrubs, Herbs, and Climbers of Source: A Checklist Myanmar. of the Contributions Trees, Shrubs, from Herbs, the and United Climbers States of National Myanmar. Herbarium. Contributions Volume from 45: the United States National Herbarium. Volume 45: 1-590

5 Forest resources in Myanmar Hill and Temperate Forest Indaing Forest Mixed Deciduous Forest Dry Forest Beach & Dune Forest Tropical Evergreen Forest Swamp Forest Tidal Forest

6 Objective of Presentation To introduce application of Remote Sensing in Forest Management Practices and National Forest Monitoring activities by focusing on the followings; History, Opportunities and Current Status Challenges in RS &GIS application and forest inventory Especially Challenges of National level Forest Cover Change Assessment

7 INSTITUTIONAL STRUCTURE Ministry of Environmental Conservation and Forestry (MOECAF) Union Minister Deputy Minister ( Forest) Deputy Minister (Environment) Permanent Secretary Office (147) Forest Dept. (15429) Dry Zone Greening Dept. (3231) Myanma Timber Enterprise (46411) Survey Dept. (1485) Environmental Conservation Dept. (403) Six institutions under the MOECAF - performing their specific duties and responsibilities mainly related to forestry and environment.

8 Institutional Structure of Forest Department Forest Department

9 Institutional Structure of Planning and Statistics Division Director (Planning and Statistics Division), Forest Department Deputy Director (2) (Planning & Statistics) Deputy Director (1) (Inventory and RS&GIS) Assistant Director (3) (Planning and Statistics) Assistant Director (2) (Forest Inventory and computer) Assistant Director (3) (RS & GIS) Staff Officer (8) Staff Officer (1) (Forest Inventory) Staff Officer (3) (Data processing) Staff Officer (5) Forester + Staff (15+9) Forester + Staff (1+2) Staff (7) Forester + Staff (2+6)

10 Background Information on Forest Management National Comprehensive Development Plan ( to ) Forestry Sector Comprehensive Development Plan ( to ) National Forestry Master Plan (NFMP) ( to ) District Level Forest Management Plan (64 FMUs) ( to ), ( to ) preparing for to (68 FMUs)

11 Development of Data/Information Forest Inventory RS & GIS Application Spatial Data Non-spatial data (Tables of Data) Supporting Information for SFM

12 Major Developments towards SFM Establishment of permanent forest estate Biodiversity conservation Plantation forestry Community forestry Tree planting programs Rehabilitation programs Implementation of Timber Certification & Legality Assurance System REDD+ International cooperation

13 Permanent Forest Estate (PFE) Legal classification Area (km 2 ) % Reserved forest (RF) Protected public forest (PPF) Protected area system (PAS) Policy target RF+PPF 30% of total country's area PAS 10% of total country s area

14 Application of RS & GIS

15 HISTORY OF RS & GIS in Forest Department. 1920s Using AP for assessing Ayeyarwady Delta Mangroves Cornwell University introduced AP application to Myanmar officials and FD First satellite imagery introduction under a FAO/UNEP project (Tropical Resources Assessment Project; a quick appraisal of the forest cover of the whole country using 1:1,000,000 scale Landsat imagery of the period) Aerial photography and Mapping Section was formed by UNDP; BUR/79/011 National Forest Survey and Inventory included the covering the whole of Myanmar by AP The follow up project (MYA/85/003) National Forest Management and Inventory provided a set of Landsat TM imagery and a country wide landuse map was produced by visual interpretation. The above two projects provided training for the project staff in the fields of satellite remote sensing, cartography and printing ICIMOD gave series of GIS training for Myanmar The Digital Image Processing system was installed in FD with financial assistance of the Watershed Management for Three Critical Areas Project (MYA/93/005) for its landuse mapping component. (GIS Mapping in Watershed Area) ArcInfo The Information System Development Project for the Management of Tropical Forest funded by JICA. 68% of the country was covered during 4 successive years. As the digital processing was done back in Japan, only rudimentary knowledge had been gained by the Myanmar counterparts. (Erdas Imaging) FD changed its Aerial Photography and Mapping Section to Remote Sensing and GIS

16 Remote Sensing Data Sources in FD Landsat TM and ETM+ (30 m x 30 m resolution) imageries were used for previous forest cover assessment of whole country (1990, 2000, 2005). IRS Liss 3 (23.5 m x 23.5 m resolution) are currently used Satellite Imageries, acquired during 2010 for whole country forest cover assessment. High resolution satellite imageries such as Quickbird, IKONOS, ALOS, Rapideye, Worldview, Spot and Aster imageries were also used for conservation priority areas, such as, Tanintharyi Nature Reserved, Irrawady Delta, Naypyitaw region, Wunbaik, Rakhine State and Shan State.

17 Softwares and Methodology Methodology used in image classification Ground truth collection (field survey, Google earth) Visual and Digital image classification by TNTmips (formerly) Visual image classification, automatic image segmentation by Envi and manual interpretation in ArcGIS. (Landsat8, FAO guidance) Accuracy assessment Softwares TNTmips (2 licenses) ArcGIS (2 licenses) Ecognition (1 licenses), ENVI (1 Licenses)

18 Human Resources in RS and GIS Total 32 Staff 3 Assistant Directors, 2 Staff Officers, 5 Cartographer-2, 3 Cartographer-4, 16 Range Officers, 1 Computer Operator, 1 Mechanics 1 Driver Capacities Remote Sensing 7 GIS 18 Digitizing 9 Map Layout Range Officers were recruited in March 2015 and trained for RS and RS field. 2 M.Sc. Graduated staff were Assign very recently

19 Spatial Data/Information in Forest Department Data/Information Data Status Updating Scale Contribution of Data Satellite Images Landsat TM, ETM national freely downloadable Rapideye sub-national Single User license (unable to contribute) Forest Cover Accuracy Checking 5 years interval national Yes Land use/land cover Accuracy Checking not yet finished sub-national Yes Permanent Forest Estate Accurate regular updating national Yes Boundary (reserved forests, protected public forests, protected area system) Compartment boundary Accurate sub-national Yes Beat boundary Accurate updating if needed Working Circle boundary Needed detailed 10 years demarcation on interval ground sub-national sub-national Yes Yes

20 Spatial Data/Information in Forest Department, cont. Data/Information Data Status Updating Scale Forest Concession Need to be verified not yet finished sub-national boundary (logging, forest (point data and limited plantation, mining, polygon data) ecotourism,, etc.) Inaccurate (point data Community Forestry Agroforestry and limited polygon data) not yet finished sub-national Adminstrative boundary (Country, States and Regions, Districts, updating if Townships) Need to be verified needed national Yes Road Network Need to be verified updating if needed sub-national Yes River/Stream Network Need to be verified updating if needed sub-national Yes City/Town/Village Need to be verified updating if needed national Soil types Myanmar Agriculture Atlas 2000 DEM (30 m resolution) Watershed boundary rainfall Forest fire hot spot Global Datasets NASA Datasets Contributio n Data Yes

21 Maps for Forest Management (68 Districts) Maps of Administrative Boundary Maps of Forest Beats Maps of Plantation FD/Private Forest Cover Maps Location Maps of Permanent Forest Estate Maps of Working Circles and Felling Series Topographic Maps etc..

22 Monitoring by using RS & GIS Forest Cover Assessment - National level - Sub-national level - Local level Land use/cover Assessment - Sub-national level

23 National Level Forest Cover Assessment Periods FRA Reports IRS Liss III 2015 Total number of Landsat scenes = 53 Coverage area of 1 scene = 185 x 185 km Spatial resolution = 30 x 30 m Landsat Paths and Rows

24 2-5 m ha Definitions of Forest (Kyoto Protocol) 10-30% Forest Definition: (annex to decision 16/CMP.1 of Kyoto Protocol) Minimum forest area: ha Minimum tree height: 2 5 m Minimum crown cover: % Deforestation: Direct, human-induced conversion of forested land to non-forested land Degradation (from IPCC): Direct, human-induced, long-term loss [persisting for X years or more] or at least Y% of forest carbon stocks since time T [not qualifying as deforestation]

25 10-40% Definitions of Forest Forest Definition: (FAO) 5 m Minimum forest area: 0.5 ha Minimum tree height: 5 m Minimum crown cover: % 0.5 ha Deforestation: Direct, human-induced conversion of forested land to non-forested land Degradation (from IPCC): Direct, human-induced, long-term loss [persisting for X years or more] or at least Y% of forest carbon stocks since time T [not qualifying as deforestation]

26 Forest Cover Status in Myanmar (2010) Forest Cover of Myanmar derived from Landsat Images (FRA 2010) Classes Area (,000 ha) % of total country area Closed forest Open forest Total forest Other Wooded land Others Water body Total

27 Status of Major Forest Types(FRA 2010) Hill and Temperate Evergreen Forest 26.88% Scrub land 2.21% Mangrove Forest 1.47% Tropical Evergreen Forest 17.22% Deciduous Indaing (Dipterocarp) Forest 4.16% Dry Forest 9.80% Mixed Deciduous Forest 38.26%

28 Status of Major Forest Types (FRA 2015) Hill and Temperate Evergreen, 26.92% Scrub Land, 2.20% Mangrove Forest, 1.12% Tropical Evergreen Forest, 17.30% Deciduous Indaing Dipterocarp, 4.26% Dry Forest, 10.00% Mixed Deciduous Forest, 38.20%

29 2010 IRS LISS-III Images Total number of IRS scenes = 79 Coverage area of 1 scene = 140 x 140 km Spatial resolution = 23.5 x 23.5 m

30 Forest Cover Status in Myanmar Forest cover of Myanmar Derived from 2010 IRS Liss3 Images for FRA 2015 Classes Area (,000 ha) % of total country area Closed forest Open forest Total forest Other Wooded land Others Waterbody Total This is the source data for FRA2015

31 Forest Cover Status in Myanmar (2015) Projected Forest cover Data for FRA 2015 derived from 2010 IRS Liss3 Images Classes Area (,000 ha) % of total country area Closed forest 14, Open forest 14, Total forest 29, % Other Wooded land 15, Others 21, Waterbody 1, Total 67,

32 Forest Cover Status in Myanmar (2015) Projected Forest cover Data for FRA 2015 Without inland water area, FC cover % Classes Area (,000 ha) % of total country area Closed forest 14, Open forest 14, Total forest 29, % Other Wooded land 15, Others 21, Total 65, % This data can be seen in FRA2015 Desk reference book.

33 % of total land area Forest Cover Trend as per respective Year % % 49.25% 46.96% 42.92% Closed forest Open forest Total Forest Year Source: Forest Department, Myanmar (FRA 2015)

34 Forest cover of Myanmar 2005 for GMS+ Proj. Forest Cover Class Area (,000 ha) % of total country area Closed forest (NL) Closed forest (Mix) Closed forest (BL) Open forest (NL) Open forest (Mix) Open forest (BL) Total forest % Other Wooded land Others Waterbody Total

35 Forest cover of Myanmar 2010 for GMS+ Proj. Forest Cover Class Area (,000 ha) % of total country area Closed forest (NL) Closed forest (Mix) Closed forest (BL) Open forest (NL) Open forest (Mix) Open forest (BL) Total forest % Other Wooded land Others Waterbody Total

36 Harmonizing Land use, Land Cover and Forest Cover Categories No Land use categories IPCC FRA APFnet 1 Broadleaved forest closed Broadleaf closed 2 Needleaf closed Needleaf closed 3 Mixed forest closed Closed forest Mixed forest closed 4 Evergreen forest closed Broadleaf closed 5 Mangrove Wetland (mangrove forest) 6 Broadleaved forest open Broadleaf open 7 Needleaf open Needleaf open 8 Degraded Forest Forest land Mixed forest open Open forest 9 Evergreen forest open Broadleaf open 10 Bamboo Bamboo 11 Forest open Dry forest 12 Scrubland Scrub 13 Fallow Taungya/Active Taungya Other wooded land Shifting cultivation 14 Forest Plantation Broadleaf 15 Grassland / Grazing Land Grassland Grass 16 Crop land floating Crop land floating 17 Crop land (agri) Paddy/Commercial Agriculture/Tree Cropland Crops/Permanent dryland ag. 18 Alluvial land Alluvial land 19 Unclassified Cloud/cloud shadows 20 Snow Snow 21 Permanent Bare Land/Sandbars Others Otherlands Sand 22 Fish Pond Urban & built-up 23 Shrimp Pond Urban & built-up 24 Salt pan Urban & built-up 25 Settlements/Buildings/ Urban & built-up Settlement 26 Roads Road 27 Swamp / Wetland Wetlands Wetland (fresh water swamp) forest 28 Water - Rivers/Water - Lakes Water Water

37 Forest Cover & Carbon Mapping in the GMS and Malaysia Project, Forest Cover Changes between 2005 and 2010 together with CAF under APFNet Program (2005) (2010)

38 Forest Cover Change map between 2005 and 2010 period. No 2005 _ 2010 Change Data Hectare Km 2 Area Acre 1 Forest to Forest Forest to Others Others to Forest Others to Others Total

39 Deforestation Rate within and Outside of PFE between 2005 and 2010 period derived original source data. Land Categories Forest to Non (Ha) PFE (RF+PPF+PAS) % Outside PFE % Total % Deforestation Rate It is obvious that deforestation rate of outside PFE is more than twice inside PFE.

40 Deforestation Condition within and Outside of PFE between 2005 and 2010 period as per FRA2015 Deforestation rate data. Land Categories Forest to Non (Ha) PFE (RF+PPF+PAS) % Outside PFE % Total % Deforestation Rate It is obvious that deforestation rate of outside PFE is more than twice inside PFE. That is why deforestation rate inside PFE is less than 1/3 of total rate.

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42 Deforestation as per Regions and States between 2005 and 2010 period Region&State Forest - Forest Forest- Non Non - Forest Non - Non Total (ha) Kachin State Kayah State Kayin State Chin State Sagaing Region Taninthryi Bago Magwe Mandalay Mon Rakhine Yangon Shan Ayeyarwady Total

43 Deforestation as per Regions and States between 2005 and 2010 period Thousand hectare Deforestation amount between 2005 to 2010 period Forest- Non Regions and States According to the above figure, Highest deforestation in Shan State, second highest is Kachin State and the lowest is Yangon Division.

44 Biomass Estimation and Carbon Stock (Country Level) Forest Carbon Storage Mapping in Myanmar (300 m spatial resolution) derived from MODIS data. In Second Phase GMS+ project LiDAR imageries will be used for Carbon Mapping.

45 Some sample GPS photos of field verification

46 Thandwe District, Gwa T.S. Gwa Chaung PPF (Bamboo)

47 Mangroves, Pathein District, Ngaputaw T.s.

48 On going activities, Image Interpretation for Finished in 11 th Jan nd order classification 1 st order classification Landsat8 Images Three Districts already Finished Rapideye Images

49 Forest cover of Myanmar 2015 Forest cover of Myanmar Derived from Landsat8 of Nov, 2014 to March, 2015 Classes Area (,000 ha) % of total country area Closed forest Open forest Total forest Other Wooded land Others Waterbody Total Real-Time Classified Data

50 Image Classification (ENVI) Methodological Flow Chart of Image Classification ROI(region of interest) of each Category Referencing Google Earth Landsat OLI8 Images (Acquired between 2014,Novemb er and 2015,March) Band Selection (654)mostly Supervised Classification (Maximum Likelihood) Majority Minority Analysis (3*3) Radiometric calibration Atmospheric correction (FLAASH module) Reprojection-46 Two outputs form ENVI 1.Export Classification Image 2.Export Classification Vectors(used for further processes e.g EDITING) Image Classification (Vector) Ground Truth Checking(not yet) Accuracy Checking(On going with Google Earth) Image Mosaicing for each district Preprocessing (ENVI) 1. Closed Forest 2. Open Forest 3. OtherwoodedLand 4. Grassland 5. Cropland 6. Otherlands 7. Settlement 8. Wetlands 9. Water FAO and IPCC Guideli ne Editing(manually) (ArcGIS for Desktop) 2015 National Forest Cover Map

51 FRA & IPCC Closed forest Open forest Other wooded land Grassland Cropland Otherlands Settlement Wetlands Water LAND USE Broadleaved forest closed Needleaf closed Mixed forest closed Evergreen forest closed Mangrove Broadleaved forest open Needleaf open Degraded Forest Evergreen forest open Bamboo Forest open Scrubland Fallow Taungya/Active Taungya Forest Plantation Grassland / Grazing Land Crop land floating Paddy/Commercial Agriculture/Tree Crops/Permanent dryland ag. Alluvial land Unclassified Snow Permanent Bare Land/Sandbars Fish Pond Shrimp Pond Salt pan Settlements/Buildings/ Roads Swamp / Wetland Water - Rivers/Water - Lakes

52 Challenges of National level FC Change Assessment It is difficult to get cloud free imageries for the whole country especially more difficult to get historical data (i.e. earlier than 2013) (Landsat, 53 scenes & IRS Liss3 79 scenes are needed to cover the country). Every respective data should be real-time and accurate as much as possible. Due to the variety of forest types and forest disturbance levels, as well as the variable images acquisition conditions, it is unlikely deforestation and forest degradation monitoring can be conducted throughout the country using a single automated approach with currently available remote sensing data.(stibig et al., 2014)

53 Challenges of National level FC Change Assessment, cont. The application of automated methods to large area assessments remains a major challenge and included a strong visual interpretation component.(stibig et al.) Forest Definition should be standardized, land cover categories should be harmonized due to different definitions and categories can lead to different results, e.g., IPCC, FAO and so forth. To improve capacity building within forest department for wide area forest assessment is also challenge. Because it is important for countries to maintain their forest monitoring system and update their inventories on a regular basis.

54 Challenges of National level FC Change Assessment, cont. This will improve accuracy and reliability of data and information on forest resources and will provide the country with the necessary input to refine policies and decision and to further improve forest management. Transparent information should be provided to justify adjustments. Country with lower capacities in the past had the tendency to overestimate the net area of forest loss and that use of low quality data and expert judgments resulted in biases in forest loss estimation in large area assessment.(romijn, E., 2015)

55 Challenges of National level FC Change Assessment, cont. The engagement in REDD+ capacity development initiatives had a positive impact on country forest monitoring capacity. This clearly shows the importance of capacity building programs and the need for further capacity development. Collaboration with other organizations can develop capacities, methodologies. Working together is cost effective, reduce time span and success.

56 Some current challenges to develop NFMS in FD Application of Technical capacity (Hard ware, software etc..) Weakness in Institutional systems (RS and GIS facilities only in FD HQ, no facilities in District Forest Office) Limited Funding for ground truthing Limited Human resources (needed to improve capacity) Data Sources (i.e. Satellite Images for Regular assessment, no Lidar images etc.) Still need to develop updated forest type level maps

57 Current collaboration on Forest Monitoring in FD & Conclusion UN-REDD FAO UNDP UNEP ITTO Forest Department Line Departments Regional Biomass Mapping National Land Inventory Researches (Institutes and Universities) With NGOs and various international organization (EUIMG, USAID, SDC, ICIMOD, AAS, KFS, JICA, AIT, etc..

58 Thank you very much for your kind attention!