The manual reflects the results of a 3-year participatory learning process that comprised many meetings, workshops, village case studies, a baseline survey of 20 poor villages, two monitoring trials in another 20 villages, and a full monitoring survey of all 223 villages in Kutai Barat. The principal purpose of this manual is to provide technical guidelines and background information to poverty assessors at district, subdistrict and village level in Kutai Barat. Therefore, the manual is structured in modules according to the tasks of the assessors. It describes the poverty monitoring system step by step, from the development of local poverty indicators to the final analysis and application of monitoring data.
Tag: data collection
Remote sensing and statistical data analysis as tools to understand forest livelihood strategies
In recognition of the importance of Non-Timber Forest Products (NTFPs) in both social and forest resource management terms, one of CIFOR’s major projects is on “Sustainable Use and Development of Non-Timber Forest Products “. The project is aiming at a world level comparison of NTFPs-based forest use, and currently has field sites in seven countries, including Indonesia. This paper reports on a study on the interaction between land-use changes and forest management strategies at the household level, and how this interaction is shaped by ecological, physical, socio-economic and other exogenous factors (e.g., policies). Field sites in Indonesia are in Pasir and Mahakam in East Kalimantan, and the West of Lake Toba in North Sumatra. We are going to approach the problem by combining various data collection and data analysis tools. Data collection tools include remote sensing, household surveys, ecological surveys, market studies, gender and diversity studies. Analytical tools include GIS, statistical analysis, spatial modeling, land-use decision modeling, and gender and diversity analysis. The general framework of the study covers three scales: landscape, local and household. In the landscape level, time series of satellite images classified based on vegetation cover together with other data such as road, eleva-tion, soil type, administrative boundaries and population are used to obtain a transition probability matrix (TPM). The area with major changes is taken as local scale. Depending on the nature of the changes (e.g. road, plantation, etc.), we will apply optimization and econometric models based on data from the household studies. The overall model also allows for making scenarios to predict or outline possible future changes. We will study the impact of land-use change on biodiversity through the landscape diversity, complexity and heterogeneity. For preliminary study, we started with the simplest TPM, namely Markov TPM. A temporal Markov TPH was obtained from post-classification images of two Landsat TH images of North Sumatra taken in 1993 and 1996. Projection using this temporal Markov TPH shows the tendency of decreasing primary forest area, and increasing other types of vegetation cover over time. The spatial Markov TPM shows that it is very rare for primary forest to be directly adjacent to barren areas. More common a gradient between primary forest, secondary forest and other types of scrubs and crops is observed. Secondary forest’s role as a pivotal state, both temporally and spatially, can clearly be seen m the TPM. The preliminary analysis of the household data in two villages in North Sumatra shows that land-use changes are associated with new economic opportunities. This has reduced the time spent on the management of benzoin gardens, but it has not lead to more drastic land-use changes such as abandoning the gardens completely. Rather they are kept as a reserve for possible future utilization. This has an influence on the resilience of the forest systems of the region and contributes to explain the rates and types of change observed.
Rapid data collection using wealth ranking and other techniques
This document describes a sequence of methods recommended for the collection of data needed for ICRAF’s sustainability models. Because the data requirements and logistical problems at each site may be different, this manual outlines a set of procedural options from which researchers may choose to suit their resources, time, and interests.
Assessing the Need for Establishing Land, Soil, and Crop Information Hubs to Support Climate-Smart Agriculture in Ethiopia, Kenya, and Rwanda
The Land, Soil, and Crop Information Services (LSC-IS) project (2021–2025) aims to establish sustainable agricultural data hubs within national research organizations in Ethiopia, Kenya, and Rwanda to support climate-smart agriculture. Beginning with a comprehensive needs assessment, the project identified user data requirements, institutional capacity gaps, and staff expertise needs. These findings informed strategies for embedding, long-term maintenance, and sustainability of the hubs, alongside multi-stakeholder engagement at national, district, and local levels. Two primary use cases guided the assessments: soil fertility management and soil and water conservation. Methodology included workshops, stakeholder interviews, and surveys emphasizing data demand for advancing climate-smart agriculture. In Ethiopia, AICCRA supports the Ministry of Agriculture in developing the AgDataHub and the National Soil Information System (NSIS). In Kenya, KALRO leads the Kenya Digital Agriculture Platform and contributes through the Kenya Climate Smart Agriculture Project (KCSAP). In Rwanda, the Rwanda Soil Information System (RwaSIS) provides soil fertility advisories and links to the Smart Nkunganire System (SNS), with a national Agricultural Management Information System (AMIS) under preparation.
A bottom-up approach to estimating emissions from food systems: Using Biennial Transparency Reports for fine- grained, country-level estimations
Estimating greenhouse gas emissions from food systems remains a major challenge due to the lack of harmonized, sector-specific data that capture their cross-cutting nature. Food systems span all economic sectors along which national GHG inventories are usually structured: energy, industry, agriculture, land use and waste. However, national inventories are not fine-grained enough to disaggregate the share of food in those emissions, obscuring their full contribution and hindering integrated mitigation planning. Reliable, up-to-date country-level data are scarce, and global databases rely heavily on top-down estimates and outdated assumptions.
To address this gap, we introduce a model estimating food system emissions (FSE) in Common Reporting Tables (CRT). The FSE-CRT model is a straightforward, transparent and bottom-up approach that draws exclusively on official national data, as reported by countries to the United Nations Framework Convention on Climate Change (UNFCCC) through their Biennial Transparency Reports (BTRs) and CRTs. It offers a credible alternative to global datasets that is grounded in nationally generated data that countries can control and validate (data sovereignty), and aligned with their priorities for food security and self-determined reporting.
Based on the first 83 CRTs available as of mid-2025, the FSE-CRT model estimates FSE at 10.6 GtCO₂eq, matching the FAOSTAT estimate of 10.3 GtCO₂eq for the same 83 countries. When extrapolated to all countries, this corresponds to 16.8 GtCO₂eq, very close to the global estimate of 17 GtCO₂eq reported by the Intergovernmental Panel on Climate Change (IPCC: Babiker et al. 2022). The FSE-CRT model thus provides a realistic and replicable framework to validate and refine global FSE estimates, while enabling consistent, country- driven assessments for policy and planning.
Weather and climate data for Philippines rice research
The climate and weather of Los Bafios are described with particular reference to the upland lowland difference. A complete file of daily upland weather data for the period 1959-1978 has been prepared and its contents, quality control, and means of access outlined. Current surface observations at Lcs Bafios are noted with comments on quality control. Climatic data for 47 Philippine synoptic weather stations have been collected and integrated file of weekly data for periods of up to 24 years has been prepared. Access to its contents is described.
Information and dataset system on the rehabilitation of degraded tropical forest ecosystems project for international network
This information and dataset system aims to facilitate international exchange and synthesis of the scientific and technical information based on results of the CIFOR/Japan project on the rehabilitation of degraded tropical forest ecosystems. There are two main pathways. One path integrates general information at the study site from annual reports, site map, remote sensing data, aerial chart and vegetation map into plot data of each site. Their outputs are data on site condition, vegetation, soil, climate, etc. which are accessible to the public. Another path is to accumulate experimental raw data into “Download” the use of which is restricted and requires a password. Version 1 of this system is experimentally located on the website at: http://www.ffpri.affrc.go.jp/labs/fmrt/cifor/start.htm
How to know more about forests?: supply and use of information for forest policy
There are serious shortcomings in the supply and use of information needed for policy making in the forestry sectors of developing countries (and often also in developed countries). The main weakness is the failure to connect supply to demand. Much information has been gathered not because it was needed but because donors were willing to fund inventories, on traditional lines, that were vaguely thought to be potentially useful. Information is usually inadequate on topics such as actual removals of wood and other products, or the usefulness of the forests, especially to the local people. Not enough provision is made for continuous inventories to the necessarily high standards that are needed to measure change. The way in which remote sensing has been used has often been heavily influenced by the facilities that are on offer, rather than the potential usefulness of the results. It is suggested, for example, that the resources would be better used on the assessment of changes in land use and forest cover than on elaborate cartography. A key proposal is to set up national ‘Analysis Units’ that will collate and interpret available information, help users to define their needs, and make the link with suppliers, so that information gathering can be more driven by demand. Information at international level depends on what is available nationally, and therefore improvement should be sought mainly at national level.
Using farmers’ local knowledge of tree provision of ecosystem services to strengthen the emergence of coffee-agroforestry landscapes in southwest China
Intensive monoculture coffee farms quickly expanded in Yunnan Province in the 1990’s and 2000’s. In 2012, local authorities in Pu’er and Xishuangbanna Prefectures, the main coffee producing centre in the province, initiated a large-scale conversion program of these farms towards coffee-agroforestry systems to promote “ecologically-friendly coffee”. Shade tree inventories and household interviews were conducted in these two prefectures to characterize coffee farms and the Local Ecological Knowledge (LEK) of farmers on the provision of ecosystem services by associated tree species. This study on newly emerging coffee farming systems revealed a high level of tree species diversity at both farm and landscape levels despite the previous dominance of intensive coffee monoculture and the large-scale distribution of a limited number of shade tree species by the government. 162 tree species were encountered during farm inventories, out of which the community of coffee farmers was able to rank 30 against 9 ecosystem services and disservices. This study reveals that this LEK is a type of hybrid knowledge that still relies mostly on traditional knowledge of tree species combined with experience acquired from newly-implemented coffee-agroforestry practices. This study also pointed out knowledge gaps regarding the impact of mature trees on coffee yield, coffee quality and pest control. The participatory approach resulted in the identification of non-promoted species with a high potential to provide locally relevant ecosystem services in coffee-agroforestry systems. These results lead to the upgrade of an online tool (www.shadetreeadvice.org) which allows extension services generating lists of recommended shade tree species tailored to the local ecological context and individual farmers’ needs. This tool will benefit farmers’ livelihood, support landscape health and contribute to the sustainability of the emerging Yunnan coffee agriculture sector.
Strengths and limitations of computer assisted telephone interviews (CATI) for nutrition data collection in rural Kenya
Despite progress in fighting undernutrition, Africa has the highest rates of undernutrition globally, exacerbated by drought and conflict. Mobile phones are emerging as a tool for rapid, cost effective data collection at scale in Africa, as mobile phone subscriptions and phone ownership increase at the highest rates globally. To assess the feasibility and biases of collecting nutrition data via computer assisted telephone interviews (CATI) to mobile phones, we measured Minimum Dietary Diversity for Women (MDD-W) and Minimum Acceptable Diet for Infants and Young Children (MAD) using a one-week test-retest study on 1,821 households in Kenya. Accuracy and bias were assessed by comparing individual scores and population prevalence of undernutrition collected via CATI with data collected via traditional face-to-face (F2F) surveys. We were able to reach 75% (n = 1366) of study participants via CATI. Women’s reported nutrition scores did not change with mode for MDD-W, but children’s nutrition scores were significantly higher when measured via CATI for both the dietary diversity (mean increase of 0.45 food groups, 95% confidence interval 0.34–0.56) and meal frequency (mean increase of 0.75 meals per day, 95% confidence interval 0.53–0.96) components of MAD. This resulted in a 17% higher inferred prevalence of adequate diets for infants and young children via CATI. Women without mobile-phone access were younger and had fewer assets than women with access, but only marginally lower dietary diversity, resulting in a small non-coverage bias of 1–7% due to exclusion of participants without mobile phones. Thus, collecting nutrition data from rural women in Africa with mobile phones may result in 0% (no change) to as much as 25% higher nutrition estimates than collecting that information in face-to-face interviews.