This paper provides insight into innovation energy, its five working mechanisms, and innovative work behaviour (IWB). Although human energy is often mentioned as an important factor in theories about motivation, it is still an unexplored theme in literature. The management of organisations often focuses on the innovation content and neglects the process aspects. Strategic and operational HRM involvement is needed to realising the essential conditions for the innovation energy of innovative employees. An abductive case study on innovation energy took place in five educational departments of one academy at Saxion University of Applied Sciences in the Netherlands. We interviewed 21 innovating lecturers and their five team leaders individually and organised five focus groups with a total of 17 team members. Innovation energy converts individual innovation properties (creativity, psychological empowerment, and optimism) into IWB. Organisations must pay attention to these properties and four other working mechanisms (autonomy, teamwork, leadership, and external contacts) that influence this conversion process. HRM professionals should be involved with innovation processes to realise the right conditions for innovation energy, together with line management. The construct of innovation energy with five working mechanisms gives more insight into the IWB process from the perspective of the engaged employee with IWB. This research contributes to the body of knowledge on IWB, (human) innovation energy, and engagement in relation to HRM.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

 Landscape architects, who guide planning and design decisions by understanding the socio-cultural expectations, functional needs, and social behaviors of the community, create ideal spaces for people by integrating natural, social, cultural, and aesthetic factors with a holistic design approach in urban public areas. Public open green spaces are important urban areas that have a positive impact on people’s physical, mental, and emotional health. In this context, the concept of personal space, its impact on individuals, and related perception studies have been examined. In landscape design, criteria that affect individuals’ personal space distances and personal space perceptions have been identified, providing a basis for sustainable landscape design projects in public open and green spaces.

The Sipongi System is essential in dealing with forest and land fires because this system provides real-time data that empowers stakeholders and communities to proactively overcome fire dangers. Its advantages are seen in its ability to provide detailed information regarding weather conditions, wind patterns, water levels in peatlands, air quality, and responsible work units. This data facilitates efficient decision-making and resource allocation for fire prevention and control. As an embodiment of Collaborative Governance, the Sipongi System actively involves various stakeholders, including government institutions, local communities, environmental organizations and the private sector. This cooperative approach fosters collective responsibility and accountability, improving fire management efforts. The Sipongi approach is critical in reducing forest and land fires in Indonesia by providing real-time data and a collaborative governance model. This results in faster response times, more effective fire prevention and better resource allocation. Although initially designed for Indonesia, the adaptable nature of the system makes it a blueprint for addressing similar challenges in other countries and regions, tailored to specific needs and environmental conditions. Qualitative research methods underlie this study, including interviews with key stakeholders and analysis of credible sources. Government officials, community leaders, environmental experts and organizational representatives were interviewed to comprehensively examine the mechanisms of the Sipongi System and its impact on forest and land fire management in Indonesia. Future research should explore the application of Sipongi Systems and collaborative governance in various contexts by conducting comparative studies across countries and ecosystems. Additionally, assessing the long-term impact and sustainability of the Sipongi System is critical to evaluating its effectiveness over time.

The Guacimal River catchment has an area of 181 km² and is located in the NW of Costa Rica, between the coordinates 84.745° W-10.016° N and 84.909° W-10.325° N. In this territory, as in most of the country, detailed geomorphological studies are scarce; therefore, the objective of this paper is to present the geomorphological mapping at a scale of 1:25,000 of the Guacimal River, which allows us to explain the dynamics of the agents involved in the modeling of the catchment. The work methodology consisted of three stages: pre-mapping, field activity and post-mapping, which resulted in a map in which ten relief forms are represented, ordered according to their morphogenesis in endogenous modeled and exogenous (fluvial, gravitational and littoral). This document will be the base line for land use planning, both continental and coastal, and for local risk management.