Determining areas affected by forest succession is one of the main tasks aimed at shaping rural areas. Effective determination of the parameters of the dynamics of forest succession in areas used for agriculture is the basis for understanding the phenomenon of land cultivation abandonment. Understanding it allows to implement a proper policy limiting the negative effects of giving up agricultural production. There are many methods to determine forested areas. The most popular group of the methods includes those that rely on the use of LiDAR data.

Phosphorus (P) and nitrogen (N) concentrations were measured at 75 points in the upper reaches of rivers draining into the agricultural watersheds south of the Ibaraki prefecture during the summer and winter of year 2009. A geographic information system (GIS) was used to combine the environmental information regarding the watersheds such as land use, topography, and soil with water quality data for a statistical analysis. As andosols have a stronger tendency to adsorb P than other soil types, watersheds were classified into areas with andosol and non-andosol soils.

This report explains TMP Systems’ statistical analysis of how geospatial data showing indicators of local environmental, social and governance (ESG) conditions correlate with tenure risk. The results indicate strong enough correlations between some of these indicators and tenure risk, to support use of the indicators by companies and investors. This work underpins something new and useful, which is Landscope’s ability to provide location-specific risk assessments across many developing countries.

This eco-type map presents land units with distinct vegetation and exposure to floods (or droughts) in three villages in the Barotseland, Zambia. The knowledge and eco-types descriptions were collected from participatory mapping and focus group discussions with 77 participants from Mapungu, Lealui, and Nalitoya. We used two Landsat 8 Enhanced Thematic Mapper (TM) images taken in March 24th and July 14th, 2014 (path 175, row 71) to calculate water level and vegetation type which are the two main criteria used by Lozi People for differentiating eco-types.

La maca (Lepidium meyenii) es una raíz andina a la cual se le atribuyen propiedades energéticas y estimulantes. En los últimos años el interés de mercados asiáticos dio lugar al “boom de la maca”, incrementando los precios y provocando la rápida conversión de pastizales altoandinos en tierras de cultivo, transformando de esta manera el paisaje, el ecosistema, la economía y la sociedad rural de la zona altoandina de Junín.

Challabamba en Cusco y Quilcas en Huancayo son dos zonas contrastantes con alta biodiversidad de variedades de papa. El presente estudio tuvo por finalidad evaluar la distribución espacial de la biodiversidad de papa mediante el mapeo participativo. Se determinaron las áreas de siembra de papa, el número de variedades de papa existente en la comunidad, el rango altitudinal de siembra por categoría varietal, la frecuencia de las variedades de papa, y la dinámica espacial-temporal de las zonas de siembra de papa en el territorio de las comunidades campesinas.

In the Gash Delta of Eastern Sudan, spate irrigation (flood-recession farming) contributes substantially to rural livelihoods by providing better yields than rainfed dryland farming. However, spate irrigation farmers are challenged by the unpredictability of flooding. In recent decades, the number of farmers practicing spate irrigation has decreased, due to varying rainfall intensity and frequency, insufficient infrastructure and farmers’ limited capacity to manage such variations.

Low adoption of sustainable intensification technologies hinders achievement of their potential impacts on increasing agricultural productivity. Proper targeting of locations to scale-out particular technologies is a key determinant of the rate of adoption. Targeting locations with similar biophysical and socio-economic characteristics significantly increases the probability of adoption. Areas with similar biophysical and socio-economic characteristics are referred to as recommendation domains (RDs).