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Manual-Cambodia M&E Dashboard
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User Guide and Manual

Cambodia M&EDashboard

Production by SERVIR Mekong

Cambodia Biophysical Monitoring and Evaluation Dashboard

User Manual

Version 1.0

© 2021, SERVIR-Mekong

DISCLAIMER

The User Manual is the property of SERVIR-Mekong. The information contained in this document is meant for the intended recipient and shall not be used, published or redistributed without the prior written consent of Asian Disaster Preparedness Center

Table of Contents

Acronyms and Abbreviations        ii

List of Figures        iii

List of Tables        iv

Executive Summary        v

1.        Introduction to Cambodia Biophysical M&E Dashboard        1

2.        Methods and data input        4

3.        Components of the Biophysical M&E Dashboard        7

3.1.        Biophysical monitoring        7

3.2.        Forest monitoring        8

3.3.        Forest alert        8

3.4.        Fire hotspot        8

4.        Steps to access the Biophysical Monitoring and Evaluation data portal.        9

4.1. Dashboard control        11

4.2. Component panel        14

4.2.1 Biophysical monitoring        14

4.2.2.  Forest monitoring        17

4.2.3. Forest Alerts        20

4.2.4. Fire hotspot        22

4.2.5. Other map layers        23

Acronyms and Abbreviations

BACI

Before and After Control Impact

CEMIS

Cambodia Environment Management Information System

EVI

Enhanced Vegetation Index

GEE

Google Earth Engine

GPL

Greening Prey Lang

M&E

Monitoring and Evaluation

MOE

Ministry of Environment

NASA

National Aeronautics and Space Agency

NFMS

National Forest Management System

PPAM

Provincial Protected Area Management

REDD+

Reducing Emissions from Deforestation and Forest Degradation

RLCMS

Regional Land Cover Monitoring System

RS

Remote Sensing

SAR

Synthetic Aperture RADAR

SFB

Supporting Forests and Biodiversity

SV-SM

SERVIR-Mekong

TCC

Tree Canopy Cover

TCH

Tree Canopy Height

UNDP

United Nation Development Program

USAID

U.S. Agency for International Development

List of Figures

Figure 1.Launching page of the Biophysical Monitoring and Evaluation Dashboard        1

Figure 2. The infrastructure for spatial application .        4

Figure 3.  Schematic overview of the BACI framework..        4

Figure 4. The tool structure and data inputs        7

Figure 5. Quick guide panel        9

Figure 6. General interface of the tool        10

Figure 7. The Dashboard control        12

Figure 8. Users can customize the Area of interest.        13

Figure 9. Biophysical monitoring component        14

Figure 10. Map and charts of Biophysical change        15

Figure 11. Map and charts of Land cover change        16

Figure 12. The forest monitoring component        17

Figure 13. Map and chart in forest monitoring panel        18

Figure 14. Exported report of forest monitoring component        19

Figure 15. The forest alert component        20

Figure 16. The exported report of forest alerts        21

Figure 17.  The Sentinel -1 forest alert examiner for REDD+        21

Figure 18. The Fire hotspot component panel        22

Figure 19. Other Map layers        23

Executive Summary

Ensuring ecological stability and biological productivity over large areas is critical for landscape management and conservation policy, USAID/Cambodia, along with other stakeholders, require insight and reports on the effectiveness of biodiversity and conservation-related project interventions. SERVIR-Mekong’s Biophysical M&E Dashboard tool was developed in response to those needs. The Cambodia Biophysical M&E Dashboard is the tool that can monitor performance of landscape-scale efforts and biophysical conditions on-the-ground. SERVIR-Mekong developed the Biophysical M&E tool to meet the request from the USAID mission in Cambodia. Development of the tool designed for project monitoring and evaluation, enabling the identification of changes in biophysical conditions on-the-ground to support USAID-funded biodiversity and conservation projects.

This manual provides information about the framework and approach that has been applied to build the Cambodia Biophysical Monitoring and Evaluation Dashboard, and the structure of components in the tool. The tool leverages the power of cloud computing and open satellite data on Google Earth Engine for data processing and monitoring the change of biophysical condition and forest cover in Cambodia due to conservation project intervention and support for sustainable landscape management. This User Manual therefore, contains all essential information for the user to make full use of the Cambodia Biophysical M&E Dashboard tool by providing stepwise information on visualizing and exploring the platform and step-by-step procedures for information access and use.

  1. Introduction to Cambodia Biophysical M&E Dashboard

https://me-dashboard-servir.adpc.net/ 

Figure 1.Launching page of the Biophysical Monitoring and Evaluation Dashboard

Cambodia is home to around 50 protected areas and a number of biodiversity corridors, which cover an area of approximately 7.5 million hectares - equating to 41% of the country’s total land area. Cambodia’s protected area system contributes positively to the country’s economy and sustainable development through the sustainable use of its biological, natural, and cultural resources. Through implementation of USAID’s Supporting Forests and Biodiversity (USAID SFB) projects in Cambodia, there have been numerous meaningful results that have improved the conservation and governance of Cambodia’s forest landscapes.

Ensuring ecological stability and biological productivity over large areas is critical for landscape management and conservation policy, USAID/Cambodia, along with other stakeholders, require insight and reports on the effectiveness of biodiversity and conservation-related project interventions. SERVIR-Mekong’s Biophysical M&E Dashboard tool was developed in response to those needs. The Cambodia Biophysical M&E Dashboard is the tool that can monitor performance of landscape-scale efforts and biophysical conditions on-the-ground.

SERVIR-Mekong developed the Biophysical M&E tool to meet the request from the USAID mission in Cambodia. Development of the tool designed for project monitoring and evaluation, enabling the identification of changes in biophysical conditions on-the-ground to support USAID-funded biodiversity and conservation projects, according to the USAID indicators outlined below:

Therefore, the Biophysical M&E Dashboard tool builds upon SERVIR-Mekong’s existing Eco-Dash platform and consists of four key components. The default ‘biophysical monitoring’ layer evaluates changes in broad-scale biological productivity using the Enhanced Vegetation Index (EVI), a measure of relative biomass particularly suited to high-biomass areas of the globe, derived from MODIS multispectral data. The other three components are Forest monitoring (forest gain/loss, derived from Landsat); Forest alerts (threat alerts, derived from Landsat); and Fire hot spot monitoring (hotspots and burned area, derived from MODIS). The user interface leverages the power of Google Earth Engine (GEE), a cloud computing platform that links extensive data archives with substantial processing power. With the continuous time-series feature, the user is able to select a baseline and evaluation period for each of the components as well as an identified area of interest which allows for easy comparisons between ‘before’ and ‘after’ intervention timeframes (Poortinga, 2018). The results can be exported in report-style format enabling decision-makers and non-technical users alike to directly use this analysis and information. These components of the tool were selected based on the needs of USAID/Cambodia and their specific M&E indicators, with carbon and biomass estimations to be incorporated in the future.

Application Purpose

Aside from monitoring performance of landscape-scale efforts and biophysical conditions on-the-ground, the Biophysical M&E Dashboard Tool can provide valuable insights into the possible drivers of change such as climate change, urban expansion and infrastructure development.


Application Uses

The Biophysical M&E Dashboard tool is currently being used by USAID/Cambodia to track performance and report on landscape-scale efforts and biophysical conditions on-the-ground in accordance with the project performance indicators, including quantifying areas of biological improvement and improved natural resource management.

Tool Approaches and framework

The Biophysical Monitoring and Evaluation Dashboard tool was developed by applying the framework to quantify and monitor the change of biophysical condition and forest cover using two common remote-sensing data products that incorporate the Before and After Control Impact (BACI) design (Upton,2014 and Carpenters, 1989). This approach is used in ecology and environmental studies as an experimental design to evaluate the impact of an environmental change on an ecosystem (Carpenters, 1989). The framework is based on repeated measurements of several vegetation variables at various times over an observational period. Measurements were taken at a location which was known to be unaffected by vegetation change (control location) and at another location which potentially would be affected by this same change (be explicit) (treatment location) for each time step (Upton,2014). The framework is based on the Google Earth Engine cloud computing platform, which is a technology that is able to rapidly deliver information derived from remotely sensed imagery in near-real time.

Recent technological advances have greatly enhanced computational capabilities and facilitated increased access to the public. In this regard, Google Earth Engine (GEE) is an online service that applies state-of-the-art cloud computing and storage frameworks to geospatial datasets.

The framework processes as request data, perform spatial calculations, and serve the information in a browser is shown in Figure 2.

The front-end relies on Google App engine technology. Code developed from either the JavaScript or Python APIs are interpreted by the relevant client library (JavaScript or Python, respectively) and sent to Google as JSON request objects. Results are sent to either the Python command line or the web browser for display and/or further analysis. Spatial information is displayed with the Google Maps API and other information is sent to a console or the Google Visualization API.

Figure 2. The infrastructure for spatial application development provided by Google. The Google Earth Engine consists of a cloud-based data catalogue and computing platform. The Django web server framework is used to host the Earth Engine application.

  1. Methods and data input

  1. Method

A common method for evaluating the impact of environmental and ecological interventions that applied in this tool development is the BACI (Before-After, Control-Impact) method (Smith, 1993). Figure 3 provides a schematic overview of the BACI framework. For the intervention area, the before and after variables of interest are measured. These are compared with the before and after measures of the same variables at a control site. The differences between the intervention and control sites determine the impact generated by the interventions (Conquest, 2000 and Underwood, 1992).

 

Figure 3.  Schematic overview of the BACI (Before-After, Control-Impact) framework. For both the control and impact sites the before and after situations are evaluated. The difference between the two after situations defines the impact of the measures.

Together with recent advances in cloud-based remote sensing and geo-computational platforms, these technologies have led to greater open scientific data for use by policy makers and practitioners outside of academia. The hybridization and simplification of these technologies also allow scientists to provide policy-makers, international donors, NGOs, and other development partners with tailor-made products to monitor and value their ecosystems in near real-time, and requiring less advanced technical expertise than in the past.

In this tool development, we applied a near real-time method for quantifying vegetation using cloud computing technology and remote-sensing data. We developed a novel custom indicator to monitor vegetation on a planetary scale, and then combined this with remote-sensing data for near real-time customized quantification of vegetation change. We demonstrate how new cloud-based geo-computational technology can be used to temporally, geographically and adaptively filter data collections.

  1. Input data

All data input for the Biophysical Monitoring and Evaluation Dashboard are opened and available data on the Google Earth Engine (GEE) that listed below,

  1. Components of the Biophysical M&E Dashboard

The Biophysical Monitoring and Evaluation (M&E) Dashboard tools has four components which provides information related to change of biophysical condition and the change of forest cover on the ground, that indicated the area of improved or degraded biophysical condition in the project area; and Annual area of deforestation (ha) and/or reforestation (ha) as the M&E indicator of USAID project requirements. Four components of the tool included: Biophysical monitoring; Forest monitoring, Forest alerts, and Fire monitoring as in the Figure 4 below.

Figure 4. The tool structure and data inputs

  1. Biophysical monitoring

The Biophysical monitoring component provide information about the change of biophysical productivity of the landscape – scale, uses the Enhanced Vegetation Index (EVI), which was calculated using MODIS multispectral data (MOD13Q1) with a pixel resolution of 250 x 250m. The algorithm chooses the best available pixel value from all the acquisitions from the 16-day period. EVI is a measure of relative biomass and is particularly well-suited for high-biomass areas of the globe

The map result was obtained by calculating the difference between vegetation growth (positive trend) and vegetation decline (negative trend) over any given area according to the baseline and evaluation period. Negative numbers indicate a net negative trend whereas positive numbers indicate net greening. By tracking changes of the Enhanced Vegetation Index (EVI) user can track the performance of landscape-scale efforts to maintain biological productivity.

A time series of Cambodia national land cover map from 2000 – 2020 is included in this component, that helps users to track the change of vegetation productivity with the land cover change during the evaluation period quantitatively.

  1. Forest monitoring

The forest monitoring component provides information about the annual forest cover and forest cover change during the evaluation period. The map of annual forest cover and map of forest gain and loss during the evaluation period was created using the annual layers of Tree Canopy Cover (TCC) and Tree Canopy Height (TCH) from GLAD lab of University of Maryland (UMD) for Mekong region, using Landsat data with the forest definition of FAO (10% of TCC and TCH above 5m). In this component, users can access a time series data set of annual forest cover and forest cover change, with total area of forest gain and loss comparison between baseline and evaluation period. These data can help users to track the result of the landscape enhancement activities, and provide quantitative information about the area of forest change.

  1. Forest alert

The forest alert component provides information about map of forest disturbance alerts with both SAR alert and GLAD alert data by year. SAR Alert system is developed using Sentinel-1 data applied deep learning method in TensorFlow. The system is operated as part of the Cambodia Protected Area Monitoring Platform (PAMP) which can monitor near real-time forest changes and external threats including deforestation, forest fires and floods within the extended Prey Lang Wildlife Sanctuary. Which integrates ground-based and remotely sensed data to improve the efficiency and effectiveness of law enforcement and conservation activities.

  1. Fire hotspot

The Fire hotspot component provides information and a map of fire hotspots of the defined area or landscape by year.  The information shows the active fire / hotspot of the Fire Information for Resource Management System (FIRMS) data. This system was developed to provide near real-time active fire locations to natural resource managers that faced challenges obtaining timely satellite-derived fire information.  

Data displayed in this tool is the Earth Engine version of the Fire Information for Resource Management System (FIRMS) dataset containing the LANCE fire detection product in rasterized form.

  1. Steps to access the Biophysical Monitoring and Evaluation data portal

This section will give instructions that users can follow all steps to interact with the tool to display the data and export information as reports for M&E purposes.

To start using the tool, users will first see the Quick guide window popup with a summary of four main steps to work with the Biophysical M&E Dashboard tool, and a link to the video demonstration on how to use the tool.

Figure 5. Quick guide panel

1. Select Baseline and Evaluation period (Baseline period: period before project intervention and Evaluation period: The period of project intervention)

2. Define area of interest 

3. Update map

4. Select information of interest

5. Watch a demo video

Overall interface and front end design of the tool is displayed in the figure below.

Figure 6. General interface of the tool

4.1. Dashboard control

The tool allows users to monitor and evaluate the change of the biophysical condition using the vegetation monitoring framework which is applicable at a regional and landscape scale, and is based on the BACI (Before-After, Control-Impact) design.

Users use the Dashboard control to set up the period and area to get information for monitoring. On the Dashboard control panel, users can define:

  1. The baseline period is the period before project intervention, the number of years should be similar to the number of evaluation periods, which is the evaluation period below.
  2. The evaluation period is the period of project intervention, which is the number of years of project implementation and operation.
  3. Define area of interest. The Area of Interest (AOI) will identify areas for data calculations in all components of the tool. Users can identify areas of interest by selecting administrative boundaries (province or district), by selecting protected areas or customize their own area of interest by drawing polygons or uploading the boundaries from their computer.

Figures bellows will guide you step by step to setup and interact with the Dashboard control

       

Figure 7. The Dashboard control

To customize the area of interest, users can choose options to draw polygon, rectangle or uploading the existing boundaries from their computer in the format of KML or GEOJSON

Figure 8. Users can customize the Area of interest

4.2. Component panel

4.2.1 Biophysical monitoring

The Biophysical monitoring component, provides information about the change of the biophysical value between the baseline period and the evaluation period by showing the change of cumulative anomaly value of Enhanced Vegetation Index (EVI) in the area of interest.

Beside the change of EVI, users can also see and access the annual Cambodia national land cover map by years which was indicated in the evaluation period. User can turn on and off the layers to see the land cover change which was associated with the change of EVI value in that period.

Figure below explain about available functions of each component, follow the number to interact with the tool.

Figure 9. Biophysical monitoring component

Figure 10. Map and charts of Biophysical change

 These data and chart can be downloaded for report in the CSV format and pie chart in picture format (PNG)

Figure 11. Map and charts of Land cover change

Click to CSV to download the table of change area of each land cover types in the GPL boundary and PNG to download the graphic of the chart

4.2.2.  Forest monitoring

The forest monitoring component provides information about forest change at the selected area of interest by the evaluation period. Figure 12 below explains the available information that users can explore and extract from the tool.

 

Figure 12. The forest monitoring component

  1. Turn on and off the button to display layers of forest gain and forest loss during the evaluation period for selected areas.
  2. Map area showing the layers which was selected to be displayed on the information panel (area of forest gain and loss over the evaluation period and forest cover by year)
  3. Turn on and off the button to display the forest cover by year of the evaluation period.
  4. Download data: Click the button to download the data of forest cover and forest gain and loss available in the information panel. download data is in image format (TIF file). Users will be asked to save the Metadata.csv file, and the Data file in Zip format. Data received has a resolution of 100m.
  5. The column chart showing area (in million hectare) of forest cover by year during the evaluation period by the selected area of interest.

 

Figure 13. Map and chart in forest monitoring panel

All information and map that displayed on the screen can be exported to a template report by click to “Export a Report”

Figure 14. Exported report of forest monitoring component

4.2.3. Forest Alerts

The Forest alert component shows the location and total area of forest disturbance or deforestation area by year. The component included forest alerts from two systems which included GLAD Alert (alert derived by Landsat image) and SAR Alert (forest alert derived by SAR Sentinel 1 image). Figure 15 below explains the available information and data and interaction with the forest alert component.

Figure 15. The forest alert component

Figure 16. The exported report of forest alerts

The SAR alert system allows users to access the App Engine platform to export the near real time forest disturbance and deforestation by identifying dates and areas that could be used for the validation process.

Figure 17.  The Sentinel -1 forest alert examiner for REDD+

4.2.4. Fire hotspot

The fire hotspot component provides information and a map of fire hotspots of the defined area or landscape by year. Figure below explains the available information on the component and interact with the tool

 

Figure 18. The Fire hotspot component panel

4.2.5. Other map layers

In this tool, users can also display other GIS layers such as infrastructures, road networks, and community forest management to help better understand the change of biophysical condition on the ground for better visualization and interpretation of information provided by the Biophysical M&E Dashboard tool. Figure 19 below explains about the available GIS layers in this component.

Figure 19. Other Map layers

 

This part of the tool consists of 2 main content

Annex 1. Information about data uses in the tool

Biophysical Monitoring layer

Forest Monitoring layer

Forest Alert

Included in this system, the SAR Alert System (SARAS) is a near real time forest alert system using Synthetic Aperture Radar (SAR). The system is developed by SERVIR-Mekong in partnership with the USAID Greening Prey Lang Project and the Applied Science Team from Oregon State University. The system relies on the newest technologies in the field of cloud computing and artificial intelligence.

Fires Hotspot 

Data displayed in this tool is the Earth Engine version of the Fire Information for Resource Management System (FIRMS) dataset containing the LANCE fire detection product in rasterized form. The near real-time (NRT) active fire locations are processed by LANCE using the standard MODIS MOD14/MYD14 Fire and Thermal Anomalies product. Pixel displayed as a fire hotspot in this tool achieves 90% confidence of the LANCE fire detection model.

Land Cover 


Additional GIS Layers.

Cambodia Protected Area

Cambodia Airports 

 

Community protected areas in Cambodia (2006-2019)

Published by: Open Development Cambodia

Hydropower dams in Cambodia (1993-2014)

Road and railway networks in Cambodia (2012- 2020)

References

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  2. Conner, M.M.; Saunders, W.C.; Bouwes, N.; Jordan, C. Evaluating impacts using a BACI design, ratios, and a Bayesian approach with a focus on restoration. Environ. Monit. Assess. 2016, 188, 555.
  3. Conquest, L.L. Analysis and interpretation of ecological field data using BACI designs: Discussion. J. Agric. Biol. Environ. Stat. 2000, 5, 293–296.
  4. Didan, K.; Huete, A. MODIS Vegetation Index Product Series Collection 5 Change Summary; TBRS Lab, The University of Arizona: Tucson, AZ, USA, 2006
  5. Gorelick, N.; Hancher, M.; Dixon, M.; Ilyushchenko, S.; Thau, D.; Moore, R. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 2017, 202, 18–2
  6. Poortinga, A.; Clinton, N.; Saah, D.; Cutter, P.; Chishtie, F.; Markert, K.N.; Anderson, E.R.; Troy, A.; Fenn, M.; Tran, L.H.; et al. An Operational Before-After-Control-Impact (BACI) Designed Platform for Vegetation Monitoring at Planetary Scale. Remote Sens. 2018, 10, 760.
  7. Smith, E.P.; Orvos, D.R.; Cairns, J., Jr. Impact assessment using the before-after-control-impact (BACI) model: Concerns and comments. Can. J. Fish. Aquat. Sci. 1993, 50, 627–637.
  8. Underwood, A. Beyond BACI: The detection of environmental impacts on populations in the real, but variable, world. J. Exp. Mar. Biol. Ecol. 1992, 161, 145–178.
  9. Upton, G.; Cook, I. A Dictionary of Statistics 3e; Oxford University Press: Oxford, UK, 2014.