Assessment of Rangeland Degradation in New Mexico Using Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND)

Rangelands provide significant socioeconomic and environmental benefits to humans. However, climate variability and anthropogenic drivers can negatively impact rangeland productivity. The main goal of this study was to investigate structural and productivity changes in rangeland ecosystems in New Mexico (NM), in the southwestern United States of America during the 1984-2015 period. This goal was achieved by applying the time series segmented residual trend analysis (TSS-RESTREND) method, using datasets of the normalized difference vegetation index (NDVI) from the Global Inventory Modeling and Mapping Studies and precipitation from Parameter elevation Regressions on Independent Slopes Model (PRISM), and developing an assessment framework. The results indicated that about 17.6% and 12.8% of NM experienced a decrease and an increase in productivity, respectively. More than half of the state (55.6%) had insignificant change productivity, 10.8% was classified as indeterminant, and 3.2% was considered as agriculture. A decrease in productivity was observed in 2.2%, 4.5%, and 1.7% of NM's grassland, shrubland, and ever green forest land cover classes, respectively. Significant decrease in productivity was observed in the northeastern and southeastern quadrants of NM while significant increase was observed in northwestern, southwestern, and a small portion of the southeastern quadrants. The timing of detected breakpoints coincided with some of NM's drought events as indicated by the self-calibrated Palmar Drought Severity Index as their number increased since 2000s following a similar increase in drought severity. Some breakpoints were concurrent with some fire events. The combination of these two types of disturbances can partly explain the emergence of breakpoints with degradation in productivity. Using the breakpoint assessment framework developed in this study, the observed degradation based on the TSS-RESTREND showed only 55% agreement with the Rangeland Productivity Monitoring Service (RPMS) data. There was an agreement between the TSS-RESTREND and RPMS on the occurrence of significant degradation in productivity over the grasslands and shrublands within the Arizona/NM Tablelands and in the Chihuahua Desert ecoregions, respectively. This assessment of NM's vegetation productivity is critical to support the decision-making process for rangeland management; address challenges related to the sustainability of forage supply and livestock production; conserve the biodiversity of rangelands ecosystems; and increase their resilience. Future analysis should consider the effects of rising temperatures and drought on rangeland degradation and productivity.Peer reviewe

Use of remote sensing in landscape-scale vegetation degradation assessment in the semi- arid areas of the Save catchment, Zimbabwe.

Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.The deteriorating condition of land in parts of the world is negatively affecting livelihoods, especially, in rural communities of the developing world. Zimbabwe has experienced significant vegetation cover losses, particularly, in low and varied rainfall areas of the Save catchment. The concern that Save catchment is undergoing huge vegetation losses has been largely expressed, with the causes being environmental and anthropogenic. Given the magnitude of the problem, research studies have been undertaken to assess the extent of the problem in the south eastern region of Zimbabwe, which, nevertheless, have been mainly localized. The present study seeks to identify and quantify vegetation degradation at a landscape scale in the Save catchment of Zimbabwe, using remote sensing technologies. To achieve this, two objectives were set. The first objective provided a review of the application of satellite earth observations in assessing vegetation degradation, the causes, as well as associated impacts at different geographical scales. A review of literature has revealed the effectiveness of satellite information in identifying changes in vegetation condition. A second objective sought to establish the extent of vegetation degradation in the Save catchment. Moderate Resolution Imaging Spectroradiometer- Normalised Difference Vegetation Index (MODIS NDVI) datasets were used for mapping NDVI trends over the period 2000-2015. Further analysis involved application of residual trend (RESTREND) method to separate human influences from climatic signal on vegetation degradation. RESTREND results showed an increasing trend in NDVI values in about 33.6% of the Save catchment and a decreasing trend in about 18.3% from 2000 to 2015. The results of the study revealed that about 3,609,955 hectares experienced significant human induced vegetation degradation. Approximately 38.8% of the Save Catchment was significantly degraded (p< 0.05), 3.6%, 12.8%, and 22.4% of which were classified as severely, moderately, and lightly degraded, respectively. Severe degradation was mainly found in the central districts of the Save Catchment, mainly Bikita, Chipinge and northern Chiredzi. The results of this study support earlier reports about ongoing degradation in the catchment. Vegetation changes observed across the landscape revealed different degrees of the impacts of land use activities in altering the terrestrial ecosystems. The study demonstrated the usefulness of the RESTREND method in identifying vegetation loss due to human actions in very low rainfall areas

Increased human pressures on the alpine ecosystem along the Qinghai-Tibet Railway

Construction of the Qinghai-Tibet Railway (QTR) increased the links between inland China and the Qinghai-Tibet Plateau (QTP). The QTR accelerated surrounding tourism, boosted the local economy and led to rapid development of livestock raising. To assess how distance from the railway and different regions has influenced the impact of the QTR on the alpine ecosystem, human footprint maps were produced to indicate human pressures, and the normalized difference vegetation index (NDVI), an index of vegetation greenness, was used to characterize the growth of alpine vegetation. The construction and operation of the QTR have increased human pressures, while the establishment of nature reserves has effectively reduced human pressures. The QTR contributes significantly to the increased human pressures in the Tibetan region compared with the Qinghai region and exerts negative impacts on alpine vegetation. Although the warmer and wetter climate trend has proven beneficial in enhancing alpine vegetation greenness, the declining trend of alpine vegetation has been stronger in regions with more intensive human pressures, especially in the grazing areas and the tourist areas around Lhasa. These results suggest that the impact of the QTR on alpine vegetation in Tibet is greater than that in Qinghai and that the spatial extent of the indirect impact of the QTR in Tibet is confined to approximately 30 km from the railway. These results will provide guidance and a theoretical basis for the protection of the alpine environment on the QTP under intensified anthropogenic influence

Land Degradation Assessment with Earth Observation

This Special Issue (SI) on “Land Degradation Assessment with Earth Observation” comprises 17 original research papers with a focus on land degradation in arid, semiarid and dry-subhumid areas (i.e., desertification) in addition to temperate rangelands, grasslands, woodlands and the humid tropics. The studies cover different spatial, spectral and temporal scales and employ a wealth of different optical and radar sensors. Some studies incorporate time-series analysis techniques that assess the general trend of vegetation or the timing and duration of the reduction in biological productivity caused by land degradation. As anticipated from the latest trend in Earth Observation (EO) literature, some studies utilize the cloud-computing infrastructure of Google Earth Engine to cope with the unprecedented volume of data involved in current methodological approaches. This SI clearly demonstrates the ever-increasing relevance of EO technologies when it comes to assessing and monitoring land degradation. With the recently published IPCC Reports informing us of the severe impacts and risks to terrestrial and freshwater ecosystems and the ecosystem services they provide, the EO scientific community has a clear obligation to increase its efforts to address any remaining gaps—some of which have been identified in this SI—and produce highly accurate and relevant land-degradation assessment and monitoring tools

Desertification

IPCC SPECIAL REPORT ON CLIMATE CHANGE AND LAND (SRCCL) Chapter 3: Climate Change and Land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystem

The assessment of degradation state in Ecological Infrastructure and prioritisation for rehabilitation and drought mitigation in the Tsitsa River Catchment

Ecosystem degradation is a serious concern globally, including in South Africa, because of the potential adverse impacts on food security, livelihoods, climate change, biodiversity, and ecosystem services. Ecosystem degradation can result in flow alteration in the landscape through changes in the hydrological regime. The study adopts the South African National Biodiversity Institute (SANBI) Framework of Investing in Ecological Infrastructure (EI) to prioritise the restoration of degraded ecosystems and maintain ecosystem structures and functions. This study aims to assess how EI (specifically wetlands, grassland, abandoned cultivated fields, and riparian zone) can facilitate drought mitigation: to assess land degradation status and identify priority EI areas that can be restored to improve the drought mitigation capacity. Two assessment methods were used in this study. Firstly, the Trends.Earth tool was used to assess degradation and land cover change from the year 2000-2015 in Tsitsa catchment, through assessment of Sustainable Development Goal degradation indicator (SDG15.3.1) at a resolution of 300 m. The degradation indicator uses information from three sub-indicators: Productivity, Landcover and Soil Organic Carbon to compute degraded areas. The degraded areas need to be restored and rehabilitated to maintain the flow of essential ecosystems services provided by EI. The second assessment used the Analytical Hierarchy Process (AHP), which integrates stakeholder inputs into a multi-criteria decision analysis (MCDA). The AHP is a useful decision support system that considers a range of quantitative and qualitative alternatives in making a final decision to solve complex problems. As part of the AHP analysis, participatory mapping using Participatory Geographic Information System was conducted to obtain stakeholder inputs for prioritising restoration of the key EI categories (wetlands, grassland, abandoned cultivated fields, and riparian zone) in the catchment. During the participatory mapping, communities prioritised the key EI based on three criteria: (1) ecosystem health, (2) water provisioning and (3) social benefits. The AHP method was used in ArcGIS to prioritise suitable key EI restoration areas with high potential to increase water recharge and storage, contribute to drought mitigation and ecosystem services for the catchment. The prioritisation of EI for community livelihoods in the AHP analysis included all three main criteria. In comparison, the prioritisation of suitable key EI restoration areas for flow regulations was based on two criteria: ecosystem health and water provisioning. The land degradation indicator showed that approximately 54% of the catchment is stable, 41% is degraded land, and 5% of the area has improved over the assessment period (15 years). The degradation status in the EI suggests that more than half (>50%) of each EI category is stable, but there are areas showing signs of degradation, including 43% of grasslands degraded and 39% of wetlands, cultivated lands, and riparian zones also degraded. Degradation is dominant in the upper (T35B and T3C) and lower (T35K, T35L and T35M) parts of the catchments. The three criteria used by the stakeholders in the prioritisation process of the key EI were assigned 12 spatial attributes (the catchment characteristics about the study area in relation to the criteria) to indicate relevant information needed for selecting suitable restoration areas to enhance flow regulation. The AHP analysis results identified approximately 63% (17,703 ha) of wetlands, 88% (235,829 ha) of grasslands, 78% (13,608 ha) of abandoned cultivated fields and 93% (3,791 ha) of the riparian zones as suitable areas for restoration to mitigate drought impact through flow regulation. Also, the suitability results showed 63% (17,703 ha) of wetlands, 58% (2,203 ha) of riparian zones, 68% (11,745 ha) of abandoned cultivated fields and 46% (122,285 ha) of grasslands as suitable restoration areas for improving ecosystem services for community livelihoods. The AHP analysis identified more than 39-43% (of the degraded EI indicated by the Trends.Earth analysis) areas that are suitable for restoration, because key EI plays a significant role in flow regulation and people’s livelihoods, especially when they are managed, maintained, and restored to good health conditions. Therefore, the prioritized EI areas should be either maintained, managed, rehabilitated or restored. The major distinct causes of land degradation are woody encroachment in grasslands, invasion of alien plants on abandoned cultivated fields and soil erosion in the catchment. The most suitable EI areas recommended for restoration are those natural resources near local communities, which provide essential ecosystem services to sustain their livelihood. Therefore, degraded EI in the T35 catchments should be restored and maintained to improve livelihood and mitigate drought impacts. The study pointed out how the key selected ecological infrastructure can help mitigate the impacts of droughts and improve human livelihood. The study contributes towards the important concept of investing in ecological infrastructure to improve the social, environmental, and economic benefits.Thesis (MSc) -- Faculty of Science, Institute for Water Research, 202

Land Degradation and Its Impacts on Ecosystem Services in the Nigerian Guinea Savannah: Implications for Sustainable Land Management

Land degradation is a major environmental concern. Globally, land degradation directly impacts about 1.5 to 3.2 billion people by affecting water and nutrient cycles, reducing food and biomass production, and adversely affecting livelihoods that are dependent on land and natural resources. Land degradation, its drivers, and its impacts manifest differently depending on the social and ecological contexts. Thus, attention to the context in analysing land degradation and its proximate and underlying causes will yield insights to foster sustainable land management (SLM). Although land degradation has been implicated in various environmental and development challenges in Africa, knowledge about land degradation in some regions remains inadequate to support the identification of SLM practices. The Guinea savannah zone in Nigeria is one such region, facing widespread and severe land degradation. The region has lost much of its native vegetation due to the combined effects of land degradation, deforestation, and land use changes. Land degradation has been associated with farmer–herder conflicts, communal clashes, out-migration, and food insecurity. These impacts are likely to worsen as climate change progresses and in the absence of SLM. Thus, the overarching aim of this study is to improve understanding of the spatial distribution of land degradation in the Nigerian Guinea Savannah (NGS) and its drivers and thus derive insights into the sustainable management of its land resources. The insights will also help inform pathways to achieving land degradation neutrality (LDN), a global environmental goal. Its objectives are to (1) assess human-induced biomass loss as a proxy for land degradation in the NGS; (2) identify characteristic patterns of social and ecological factors associated with land degradation in the region and analyse their implications for land governance and SLM; (3) examine land users’ perceptions of land degradation and its implications for SLM, using Niger state as a case study; and (4) examine the potentials for operationalizing LDN in Nigeria. These four objectives were addressed in four studies. The research questions were investigated with a mixed-methods approach combining satellite remote sensing data and analysis and geographic information systems (GIS) with field surveys, focus group discussions, key informant interviews, and a review of environmental policies in Nigeria. Results from assessing human-induced biomass loss, as a proxy for land degradation (Study 1) showed a declining trend in annual mean normalized difference vegetation index (NDVI) and annual NDVI anomalies observed in the NGS between 2003 and 2018. The indices were from the Moderate Resolution Imaging Spectroradiometer (MODIS). Overall, the study revealed that 38% (251K km2) of the NGS experienced degradation, 14% (91K km2) experienced improvement, and the remaining 48% (320K km2) was stable. Land degradation is mostly evident in states bordering the northwest to the central and northeast of the NGS, such as Niger state. These results show that land degradation affects a substantial part of the study area. Thus, identifying characteristic patterns of social and ecological factors associated with land degradation in the region and analysing their implications for land governance and SLM (Study 2) provided further insights. The archetype analysis identified nine archetypes dominated by (1) protected areas; (2) very high-density population; (3) moderately high information and knowledge access; (4) low literacy levels and moderately high poverty levels; (5) rural remoteness; (6) remoteness from a major road; (7) very high livestock density; (8) moderate poverty level and nearly level terrain; and (9) very rugged terrain remote from a major road. Among these archetypes, four archetypes characterized by very high-density population, moderately high information and knowledge access, and moderately high poverty level, as well as remoteness from a major town, were associated with 61.3% large-area degradation. The other five archetypes, covering 38.7% of the area, were associated with small-area degradation. Although the MODIS satellite analysis (Study 1) and the archetype analysis of spatial data on land degradation drivers, hint at the different types of land use and management including the ecological aspects of land degradation (Study 2), Study 3 examines the perspectives of land users on land degradation. A questionnaire survey was used to capture local land users’ perceptions of land degradation. The assessment of local land users’ perceptions of land degradation in predominantly rural remote farming communities was necessary to provide insights to further guide land governance and management. Thus, focused on the rural remote archetypes and its analysed communities far from major towns but with a moderately low prevalence of land degradation drivers such as population density, protected areas, and flat terrain. Using a case study on Niger state, an administrative unit in the NGS and a Principal Component Analysis, Study 3 identified key components in land users’ perceptions of land degradation characteristics and drivers and SLM. They include (1) four perception dimensions of land degradation characteristics: (2) two perception dimensions of land degradation drivers, and (3) six perception dimensions of sustainable land management. The four major dimensions of perceptions of land degradation in the study context include vegetation-condition-dominated characteristics, soil-condition-dominated characteristics, and vegetation with Sudano-Sahelian characteristics as well as land use land cover (LULC) with the prevalence of drier conditions. The two categories of land degradation drivers are human-activity-dominated drivers at a smaller scale and nature-dominated drivers at a larger scale. The two categories of land degradation drivers are human activities dominated drivers at a smaller scale and larger-scale drivers (nature-driven). The dimensions of SLM identified include institutional actors’ effect; natural resources management and environmentally friendly agricultural practices as well as tree-based initiatives; conservation initiatives and policy initiatives. The study showed that land degradation in Niger State is due to land use pressure from within the state and from migrant resource users with limited cultural attachments to local land management approaches. A spatial differentiation in dependence on natural resources showed that of the three geopolitical zones in Niger State, the zone with more diversified livelihood alternatives from agriculture, B, has less degradation than the other two zones, A and C. The archetypes approach (Study 2) identified policies and practices addressing increasing population in combination with other socio-economic factors such as poverty reduction as important. Other strategies include creating awareness about land degradation, the promotion of sustainable practices, and various forms of land restoration, such as tree planting, as ways of progressing towards LDN. In addition, Study 3 on key dimensions based on land users’ perceptions identified environmentally friendly agriculture initiatives such as farmer-managed natural regeneration and a bottom-up approach involving traditional village heads to tackle land degradation. Ranking of SLM using the relative importance index (RII) (Study 3) showed that land users perceive institutional actors (70.0%), technological practices (67.6%), conservation practices (66.8%), and policy initiatives (66.5%) as effective SLM. Connecting the insights from the three previous studies on land degradation in the NGS, Study 4 examined ways to operationalize LDN in Nigeria. Study 4 reviewed literature, assessed spatial datasets, and analysed national policies to examine the need to contextualize LDN according to the main agro-ecological zones in Nigeria, which include the NGS. The study also identified two promising entry points for operationalizing LDN; these are incentivizing and promoting SLM practices among local resource users and mainstreaming SLM initiatives in sectors such as agriculture and the environment. To support SLM measures, reform of national land use policy is needed to address the current limitations of land tenure in Nigeria. In conclusion, this study has identified large areas of the NGS affected by land degradation and identified the typologies of degradation extent, thus making it easier to target SLM measures. Because land degradation depends on land users’ perceptions and contexts, knowledge gained can inform approaches to motivate the land users themselves to address land degradation. Insights gained from the focus on the NGS have informed contributions to examine how changes in land use affect biodiversity and ecosystem services in the Río de la Plata grasslands (RPG), one of the most modified savannah biomes in the world, managed by Argentina, Brazil, and Uruguay. Results showed that a strict regulation of LULC change in the RGP is required to address land degradation. Studies in both contexts thus show the importance of appropriate policies to support SLM. These studies also highlight further research questions, such as what the key socio and economic determinants shaping land users’ perceptions of land degradation are and how land users prioritize ecosystem services, as additional pathways to align SLM practices to the social and ecological context

Satellite and UAV Platforms, Remote Sensing for Geographic Information Systems

The present book contains ten articles illustrating the different possible uses of UAVs and satellite remotely sensed data integration in Geographical Information Systems to model and predict changes in both the natural and the human environment. It illustrates the powerful instruments given by modern geo-statistical methods, modeling, and visualization techniques. These methods are applied to Arctic, tropical and mid-latitude environments, agriculture, forest, wetlands, and aquatic environments, as well as further engineering-related problems. The present Special Issue gives a balanced view of the present state of the field of geoinformatics