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Information on the spatialtemporal distribution and trends in SOC stocks is limited, especially in drylands of Kenya. Understanding the spatial and temporal changes in SOC stocks in relation to Land use and land cover (LULC), and climate change is essential in advising on sustainable land use management (SLM) practices. This study assessed the spatial and temporal changes in SOC stocks from four LULC types (cropland, forested land, grassland and shrubland) in Kibwezi West, Kenya. A completely randomized design (CRD) was used, with the different LULC types as treatments, each having three sampling points with five replicates. Baseline SOC stocks were analyzed from soil samples collected from the topsoil (0–30 cm) of the four LULC types. Rothamsted carbon model (RothC) was used in simulating SOC under three land management scenarios (BAU – business-as-usual scenario/current land use, LSLM – low SLM (5% increase in carbon inputs) and HSLM – high SLM (20% increase in carbon inputs)) and two climate change scenarios (Representative Concentration Pathways (RCP) 4.5 and 8.5). The SOC stocks significantly (p < 0.05) varied across the LULC types, recording Mg C ha−1 of 20.21 in cropland, 62.13 in forested land, 53.80 in grassland and 30.80 in shrubland. Projections under different land management scenarios showed a higher SOC sequestration potential (Mg C ha−1 yr−1) under HSLM (0.71–1.63) than in LSLM (0.16–1.24) and BAU (0.13–1.12). A reduction in SOC sequestration potential was strongly (p < 0.05) influenced by warmer climate (RCP 8.5) and absence of SLM. The study has shown that HSLM practices, once adopted, could be a measure towards enhancing SOC sequestration and hence climate change mitigation. This study contributes to the body of knowledge on spatial and temporal distribution of SOC in drylands of Kenya. The results will be instrumental in guiding SLM practices and policies in Kibwezi West and other similar landscapes.

Urbanization processes are some of the key drivers of spatial changes which shape and influence land use and land cover. The aim of sustainable land use policies is to preserve and manage existing resources for present and future generations. Increasing access to information about land use and land cover has led to the emergence of new sources of data and various classification systems for evaluating land use and spatial changes. A single globally recognized land use classification system has not been developed to date, and various sources of land-use/land-cover data exist around the world. As a result, data from different systems may be difficult to interpret and evaluate in comparative analyses. The aims of this study were to compare land-use/land-cover data and selected land use classification systems, and to determine the influence of selected classification systems and spatial datasets on analyses of land-use structure in the examined area. The results of the study provide information about the existing land-use/land-cover databases, revealing that spatial databases and land use and land cover classification systems contain many equivalent land-use types, but also differ in various respects, such as the level of detail, data validity, availability, number of land-use types, and the applied nomenclature.

In this study we examine the effect of land use land cover (LULC) types on MODIS land surface temperature (LST) in Ghana. The purpose of the research is to explore the relationship between air temperature ( T air ) and LST over LULC types and to identify their association with elevations. Datasets consist of MODIS land cover type-product (MCD12Q1), Shuttle Radar Topography Mission (SRTM) DEM, and composite dataset of 1 km terra MODIS and aqua MODIS 8-day LSTs (MOD11A2 and MYD11A2). The study time period ranged from February 2003 to January 2019. Two categorical steps were employed: (i) Assessment of LST over LULC types based on all pixels. (ii) Assessment of LST over LULC types based on meteorological station locations. Validation of LSTs was done using the air temperature of station records. Seventy station sites across Ghana were selected. The results confirm an estimation of the average T air consisting of T max , T min , and T mean . RMSE, MBE, and MAE were also computed. There was a direct positive correlation between T air and LST over LULC types. ANOVA test method was applied to verify the accuracy of LSTs over LULC types. Croplands have the highest day LST of 39.6 °C whereas evergreen broadleaf forest has the lowest (27.0 °C). The lowest night LST was observed in savannas, grasslands, and croplands with each having 18.6 °C while the highest was water body (23.6 °C). The study revealed that an increase in elevations results in a decrease in LSTs. Also, climatic conditions and specific heat capacities of LULC types had an influence on LST estimates. This study is aims to analyze the effects of LULC types on land surface temperature in Ghana. It was revealed that LULC types had a noticeable influence on the LST estimates. This study provides practical information for urban planners, natural resources managers, environmental experts, extension officers, and farmers to manage natural landscapes to be sustainable and healthy.

1. Roadless areas on United States Department of Agriculture (USDA) Forest Service lands hold significant potential for the conservation of native biodiversity and ecosystem processes, primarily because of their size and location. We examined the potential increase in land-cover types, elevation representation and landscape connectivity that inventoried roadless areas would provide in a northern Rockies (USA) conservation reserve strategy, if these roadless areas received full protection. 2. For the northern Rocky Mountain states of Montana, Wyoming and Idaho, USA, we obtained GIS data on land-cover types and a digital elevation model. We calculated the percentage of land-cover types and elevation ranges of current protected areas (wilderness, national parks and national wildlife refuges) and compared these with the percentages calculated for roadless and protected areas combined. Using five landscape metrics and corresponding statistics, we quantified how roadless areas, when assessed with current protected areas, affect three elements of landscape connectivity: area, isolation and aggregation. 3. Roadless areas, when added to existing federal-protected areas in the northern Rockies, increase the representation of virtually all land-cover types, some by more than 100%, and increase the protection of relatively undisturbed lower elevation lands, which are exceedingly rare in the northern Rockies. In fact, roadless areas protect more rare and declining land-cover types, such as aspen, whitebark pine, sagebrush and grassland communities, than existing protected areas. 4. Synthesis and applications. Landscape metric results for the three elements of landscape connectivity (area, isolation and aggregation) demonstrate how roadless areas adjacent to protected areas increase connectivity by creating larger and more cohesive protected area 'patches.' Roadless areas enhance overall landscape connectivity by reducing isolation among protected areas and creating a more dispersed conservation reserve network, important for maintaining wide-ranging species movements. We advocate that the USDA Forest Service should retain the Roadless Area Conservation Rule and manage roadless areas as an integral part of the conservation reserve network for the northern Rockies.

Biophysical and economic values of ecosystem services (ESs) are commonly used to define areas for land use and management planning. To date, there has been limited research conducted in Ethiopia regarding farmers’ evaluations of ESs. This article addresses farmers’ evaluations and perceptions of 16 ESs that are provided by five major land uses within two catchments, using a combined method of data generation and synthesis. Most farmers perceived the majority of land use/land cover (LUC) types as multifunctional; however, they showed distinctly diverse opinions of the benefits and services that the land uses provide. The farmers also distinguished pristine ESs as different importantance depending on their location in up- or downstream regions. Accordingly, shade and shelter values in the upstream region and fodder sources in the downstream regions were among the services perceived as the most important, followed by erosion control. Conversely, water treatment and tenure security were attributed poor value. Farmers’ also identified various threats to the studied ESs that were believed to be the consequences of overpopulation coupled with climate change. Routine anthropogenic activities, woodlots extraction, agribusiness investment, and drought and rainfall variability appeared to be the main drivers of these threats. The farmers’ perceptions recorded in this study generally parallel empirical research, wherein anthropogenic and environmental challenges affect the ecosystems. This general consensus represents an important basis for the establishment of collaborative land management activities.

Question: In frequently disturbed habitats such as savannas, survival of seedlings and saplings depends on the species-specific ability to persist for a long time and to re-sprout following disturbances that are damaging to individuals. This physiological ability increases with increasing stem diameter, as re-sprouting requires sufficient nutrient reserves. Are survival and growth of seedlings and saplings of woody savanna species related to habitat conditions and land-cover type? Location: Semi-arid savannas representing different site conditions and land-use practices in North Benin, West Africa. Methods: For individuals of 18 common woody species <1-m tall, basal diameter and height were repeatedly measured in five censuses from 2008 to 2010 in the land-cover types non-arable sites, fallows and protected areas. We used multistate capture—recapture models to estimate survival and transition probabilities between diameter classes. Results: We detected six groups of species with similar survival and transition probabilities. For one of these groups we found no correlation to land use, whereas the other groups comprise species with distinct preferences for different land-cover types. Most species developed better in the communal area compared to the protected area. For five species (one shrub and four trees), we detected an extremely low transition probability for the latter land-cover type. Conclusion: For some species groups, differences in plant performance were explained by a human-caused opening of the canopy that is beneficial for germination of seeds and enhances survival of juveniles by reducing the competition for light, water and nutrients. Other species showed their best demographic performance in the communal area on non-arable sites with unfavourable environmental conditions and resulting small-scale heterogeneity (mosaic of bare ground and areas with low herbaceous cover), whereas five species are likely to decline in the protected area.

Coastal wetland ecosystems, one of the most important ecosystems in the world, play an important role in regulating climate, sequestering blue carbon, and maintaining sustainable development of coastal zones. Wetland landscapes are notoriously difficult to map with satellite data, particularly in highly complex, dynamic coastal regions. The Liao River Estuary (LRE) wetland in Liaoning Province, China, has attracted major attention due to its status as Asia’s largest coastal wetland, with extensive Phragmites australis (reeds), Suaeda heteroptera (seepweed, red beach), and other natural resources that have been continuously encroached upon by anthropogenic land-use activities. Using the Continuous Change Detection and Classification (CCDC) algorithm and all available Landsat images, we mapped the spatial–temporal changes of LRE coastal wetlands (e.g., seepweed, reed, tidal flats, and shallow marine water) annually from 1986 to 2018 and analyzed the changes and driving forces. Results showed that the total area of coastal wetlands in the LRE shrank by 14.8% during the study period. The tidal flats were the most seriously affected type, with 45.7% of its total area lost. One of the main characteristics of wetland change was the concurrent disappearance and emergence of wetlands in different parts of the LRE, creating drastically different mixtures of wetland quality (e.g., wetland age composition) in addition to area change. The reduction and replacement/translocation of coastal wetlands were mainly caused by human activities related to urbanization, tourism, land reclamation, and expansion of aquaculture ponds. Our efforts in mapping annual changes of wetlands provide direct, specific, and spatially explicit information on rates, patterns, and causes of coastal wetland change, both in coverage and quality, so as to contribute to the effective plans and policies for coastal management, preservation, and restoration of coastal ecosystem services.

Vegetation is the main component of the terrestrial ecosystem and plays a key role in global climate change. Remotely sensed vegetation indices are widely used to detect vegetation trends at large scales. To understand the trends of vegetation cover, this research examined the spatial-temporal trends of global vegetation by employing the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) time series (1982–2015). Ten samples were selected to test the temporal trend of NDVI, and the results show that in arid and semi-arid regions, NDVI showed a deceasing trend, while it showed a growing trend in other regions. Mann-Kendal (MK) trend test results indicate that 83.37% of NDVI pixels exhibited positive trends and that only 16.63% showed negative trends ( P < 0.05) during the period from 1982 to 2015. The increasing NDVI trends primarily occurred in tree-covered regions because of forest growth and re-growth and also because of vegetation succession after a forest disturbance. The increasing trend of the NDVI in cropland regions was primarily because of the increasing cropland area and the improvement in planting techniques. This research describes the spatial vegetation trends at a global scale over the past 30+ years, especially for different land cover types.

Airborne light detection and ranging (LiDAR) and unmanned aerial vehicle structure from motion (UAV-SfM) are two major methods used to produce digital surface models (DSMs) for geomorphological studies. Previous studies have used both types of DSM datasets interchangeably and ignored their differences, whereas others have attempted to locally compare these differences. However, few studies have quantified these differences for different land cover types. Therefore, we simultaneously compared the two DSMs using airborne LiDAR and UAV-SfM for three land cover types (i.e. forest, wasteland, and bare land) in northeast China. Our results showed that the differences between the DSMs were the greatest for forest areas. Further, the average elevation of the UAV-SfM DSM was 0.4 m lower than that of the LiDAR DSM, with a 95th percentile difference of 3.62 m for the forest areas. Additionally, the average elevations of the SfM DSM for wasteland and bare land were 0.16 and 0.43 m lower, respectively, than those of the airborne LiDAR DSM; the 95th percentile differences were 0.67 and 0.64 m, respectively. The differences between the two DSMs were generally minor over areas with sparse vegetation and more significant for areas covered by tall dense trees. The findings of this research can guide the joint use of different types of DSMs in certain applications, such as land management and soil erosion studies. A comparison of the DSM types in complex terrains should be explored in the future.

Land surface microwave emissivity is crucial to the accurate retrieval of surface and atmospheric parameters and the assimilation of microwave data into numerical models over land. The microwave radiation imager (MWRI) sensors aboard on Chinese FengYun-3 (FY-3) series satellites provide valuable measurements for the derivation of global microwave physical parameters. In this study, an approximated microwave radiation transfer equation was used to estimate land surface emissivity from MWRI by using brightness temperature observations along with corresponding land and atmospheric properties obtained from ERA-Interim reanalysis data. Surface microwave emissivity at the 10.65, 18.7, 23.8, 36.5, and 89 GHz vertical and horizontal polarizations was derived. Then, the global spatial distribution and spectrum characteristics of emissivity over different land cover types were investigated. The seasonal variations of emissivity for different surface properties were presented. Furthermore, the error source was also discussed in our emissivity derivation. The results showed that the estimated emissivity was able to capture the major large-scale features and contains a wealth of information regarding soil moisture and vegetation density. The emissivity increased with the increase in frequency. The smaller surface roughness and increased scattering effect may result in low emissivity. Desert regions showed high emissivity microwave polarization difference index (MPDI) values, which suggested the high contrast between vertical and horizontal microwave signals in this region. The emissivity of the deciduous needleleaf forest in summer was almost the greatest among different land cover types. There was a sharp decrease in the emissivity at 89 GHz in the winter, possibly due to the influence of deciduous leaves and snowfall. The land surface temperature, the radio-frequency interference, and the high-frequency channel under cloudy conditions may be the main error sources in this retrieval. This work showed the potential capabilities of providing continuous and comprehensive global surface microwave emissivity from FY-3 series satellites for a better understanding of its spatiotemporal variability and underlying processes.