scholarly journals Desertification in the Sahel Region: A Product of Climate Change or Human Activities? A Case of Desert Encroachment Monitoring in North-Eastern Nigeria Using Remote Sensing Techniques

2022 ◽  
Author(s):  
Esther Shupel Ibrahim ◽  
Bello Ahmed ◽  
Oludunsin Tunrayo Arodudu ◽  
Bitrus Akila Dang ◽  
Jibril Babayo Abubakar ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Land Cover ◽  
Human Activities ◽  
Sand Dune ◽  
Sand Dunes ◽  
Positive Feedbacks ◽  
Climate Records ◽  
Ground Truthing ◽  
Sahel Region

In Nigeria, desertification has become one of the most pronounced ecological disasters, with the impacts mostly affecting eleven frontline States. This has been attributed to a range of both nat-ural and man-made factors. This study applied a remote sensing-based change detection and indicator analysis to explore land use/land cover changes and detect major conversions from ecologically active land covers to sand dunes. Results indicate that areas covered by sand dunes (a major indicator of desertification) have doubled over the 25 years under consideration (1990 to 2015). Although about 0.71 km2 of dunes have been converted to vegetation, indicative of the success of various international, national, local, and individual afforestation efforts, conversely about 10.1 km2 of vegetation were converted to sand dunes, implying around 14 times more de-forestation compared to afforestation. Juxtaposing the progression of sand dune with climate records of the study area and examining the relationship between indicators of climate change and desertification suggested a mismatch between both processes as increasing rainfall and lower temperatures observed in 1994, 2005, 2012, and 2014 did not translated into positive feedbacks for desertification in the study area. On average, our results reveal that sand dune is progressing at a mean annual rate of about 15.2 km2 in the study area. Based on this study’s land cover change, trend and conversion assessment, visual reconciliation of climate records with land cover data, statistical analysis, observations from ground-truthing, as well as previous literature, it can be inferred that desertification in Nigeria is less a function of climate change, but more a product of human activities driven by poverty, population growth and failed government policies. Further projections by this study also reveal a high probability of more farmlands being converted to sand dunes by the year 2030 and 2045 if current practices prevail.

scholarly journals Vegetation Changes and Their Response to Global Change Based on NDVI in the Koshi River Basin of Central Himalayas Since 2000

2020 ◽  
Vol 12 (16) ◽  
pp. 6644
Author(s):  
Xue Wu ◽  
Xiaomin Sun ◽  
Zhaofeng Wang ◽  
Yili Zhang ◽  
Qionghuan Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Cover ◽  
River Basin ◽  
Human Activities ◽  
Vegetation Change ◽  
Precipitation Trend ◽  
Central Himalayas ◽  
Annual Minimum Temperature ◽  
Vegetation Activity ◽  
Koshi River Basin

Vegetation forms a main component of the terrestrial biosphere owing to its crucial role in land cover and climate change, which has been of wide concern for experts and scholars. In this study, we used MODIS (moderate-resolution imaging spectroradiometer) NDVI (Normalized Difference Vegetation Index) data, land cover data, meteorological data, and DEM (Digital Elevation Model) data to do vegetation change and its relationship with climate change. First, we investigated the spatio-temporal patterns and variations of vegetation activity in the Koshi River Basin (KRB) in the central Himalayas from 2000 to 2018. Then, we combined NDVI change with climate factors using the linear method to examine their relationship, after that we used the literature review method to explore the influence of human activities to vegetation change. At the regional scale, the NDVIGS (Growth season NDVI) significantly increased in the KRB in 2000–2018, with significant greening over croplands in KRB in India. Further, the croplands and forest in the KRB in Nepal were mainly influenced by human interference. For example, improvements in agricultural fertilization and irrigation facilities as well as the success of the community forestry program in the KRB in Nepal increased the NDVIGS of the local forest. Climate also had a certain impact on the increase in NDVIGS. A significant negative correlation was observed between NDVIGS trend and the annual minimum temperature trend (TMN) in the KRB in India, but an insignificant positive correlation was noted between it and the total annual precipitation trend (PRE). NDVIGS significantly decreased over a small area, mainly around Kathmandu, due to urbanization. Increases in NDVIGS in the KRB have thus been mainly affected by human activities, and climate change has helped increase it to a certain extent.

The application of remote sensing for climate change adaptation in Sahel region

2014 ◽  
Author(s):  
Taisser H. H. Deafalla ◽  
Elmar Csaplovics ◽  
Mustafa M. El-Abbas
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Climate Change Adaptation ◽  
Sahel Region

scholarly journals MULTITEMPORAL ANALYSIS OF FOREST COVER CHANGE USING REMOTE SENSING AND GIS OF KANHA TIGER RESERVE, CENTRAL INDIA

2018 ◽  
Vol XLII-5 ◽  
pp. 211-219 ◽  
Author(s):  
R. M. Devi ◽  
B. Sinha ◽  
J. Bisaria ◽  
S. Saran
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Central India ◽  
Adaptation Strategies ◽  
Land Use Land Cover ◽  
Tiger Reserve ◽  
The Impact

<p><strong>Abstract.</strong> Forest ecosystems play a key role in global ecological balance and provide a variety of tangible and intangible ecosystem services that support the livelihoods of rural poor. In addition to the anthropogenic pressure on the forest resources, climate change is also impacting vegetation productivity, biomass and phenological patterns of the forest. There are many studies reported all over the world which use change in Land Use Land Cover (LULC) to assess the impact of climate change on the forest. Land use change (LC) refers to any anthropogenic or natural changes in the terrestrial ecosystem at a variety of spatial or temporal scale. Changes in LULC induced by any causes (natural/anthropogenic) play a major role in global as well as regional scale pattern which in turn affects weather and climate. Remote sensing (RS) data along with Geographic Information System (GIS) help in inventorying, mapping and monitoring of earth resources for effective and sustainable landscape management of forest areas. Accurate information about the current and past LULC including natural forest cover along with accurate means of monitoring the changes are very necessary to design future adaptation strategies and formulation of policies in tune of climate change. Therefore, this study attempts to analyze the changes of LULC of Kanha Tiger Reserve (KTR) due to climate change. The rationale for selecting KTR is to have a largely intact forest area without any interference so that any change in LULC could be attributed to the impact of climate change. The change analysis depicted changes in land use land cover (LULC) pattern by using multi-temporal satellite data over a period of time. Further, these detected changes in different LULC class influence the livelihoods of forest-dependent communities. As the study site is a Sal dominated landscape; the findings could be applied in other Sal dominated landscape of central India in making future policies, adaptation strategies and silvicultural practices for reducing the vulnerability of forest-dependent communities.</p>

scholarly journals Land Use/Land Cover Change Detection and Urban Sprawl Analysis in the Mount Makiling Forest Reserve Watersheds and Buffer Zone, Philippines

Environments ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 9
Author(s):  
Merlyn Soriano ◽  
Noba Hilvano ◽  
Ronald Garcia ◽  
Aldrin Hao ◽  
Aldin Alegre ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Sprawl ◽  
Human Activities ◽  
Land Development ◽  
Buffer Zone ◽  
Land Conversion ◽  
Land Use Land Cover ◽  
Forest Reserve

Ecologically Valuable Areas play an important role in providing ecosystem services, however, human activities such as land conversion and urban sprawl pose pressures and threats to these areas. The study assessed the land use/land cover and urban sprawl in the Mount Makiling Forest Reserve (MMFR) Watersheds and Buffer Zone from 1992 to 2015 using remote sensing and Geographic Information System (GIS). Results showed that the land use/cover within the MMFR buffer zone has changed from 1992 to 2015 with built-up areas increasing by 117% despite Proclamation 1257, s. 1998 which regulates human activities in the zone. Based on the Shannon entropy analysis the land development in the MMFR buffer zone tends to be dispersed and sprawling. However, when the magnitude of change of urban sprawl in the buffer zone from 2002 to 2015 was calculated, a decrease in the entropy value was observed which implies a compacting pattern as the human settlement in the buffer zone increases over time. Proclamation 1257, s. 1998 needs to be strengthened to protect MMFR and its buffer zone from further encroachment and pressure. Moreover, remote sensing and GIS proved to be useful tools for assessing urban sprawl in ecologically valuable areas such as MMFR.

Impact of human intervention and climate change on the land cover change in the glacial affected area of the Tianshan Mountains

2020 ◽  
Author(s):  
Hong Wei ◽  
Liyang Xiong ◽  
Guoan Tang ◽  
Josef Strobl ◽  
Kaikai Xue
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Snow Cover ◽  
Land Cover Change ◽  
Human Activities ◽  
Tianshan Mountains ◽  
Human Intervention ◽  
Large Spatial Scale ◽  
The Impact

&lt;p&gt;&lt;strong&gt;Abstract&lt;/strong&gt;: Land use/land cover change (LULC) in glacial affected areas are driven by climate change and human activities. Monitoring and simulation of the spatial and temporal land cover changes in this special region provide scientific basis in understanding the natural environment, helping to reveal the impact of climate change and human activities on LULC. In this study, the Tianshan Mountains (TSM), located in the hinterland of Eurasia, were selected as the study area to investigate the LULC of the glacial affected areas. The relationship between LULC, human intervention and climate change on a large spatial scale were also analyzed. The LULC of the TSM in China for the past 35 years were analyzed using a dynamical change model, a landscape pattern index, a centroid transfer model, and geoinformation TUPU based on the land use data of 1980, 1990, 2000, and 2015. Results show that the areas of cultivated and built-up lands immensely increased by 45.87% and 187%, respectively. Correspondingly, the areas of bare land and ice and snow cover decreased by 27% and 38%, respectively. The land use change in the TSM was characterized by different stages, and high conversion rate and intensity were obtained from 2000 to 2015. The landscape change was mainly reflected in terms of the significant increase in the number of patches and the simplification and regularization of patch shapes. The spatial connectivity of different land use types increased. The temperature and precipitation in the region show an increasing trend, and the melting rate of ice and snow cover significantly accelerated. This study can help to achieve a dynamic LULC model to investigate the interacting influences of climate change and human activities in glacial affected areas.&lt;/p&gt;

Estimation of emission from organic soils

2021 ◽  
Author(s):  
Sergiy Stepanenko ◽  
Anatoliy Polevoy ◽  
Alexander Mykytiuk
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Land Cover ◽  
Soil Carbon ◽  
Input Data ◽  
Carbon Deposition ◽  
Organic Soils ◽  
Climate Change Scenarios ◽  
Space Images ◽  
Soil System

&lt;p&gt;Dynamic modeling of the processes of transformation of soil organic matter is part of a more complex problem - modeling the processes of soil formation and functioning of soils, and the development of the entire soil system. It is important tool for studying the functioning and predicting changes in the soil system, quantifying the role of the soil cover in the balance of greenhouse gases in the atmosphere and in the processes of climate change&lt;/p&gt;&lt;p&gt;The PEAT-GHG-Model (furthermore &amp;#8211; PEAT-GHG-MODEL), based on further development of ROTHC-model (Coleman, Jenkinson, 2008) for mineral soil and ECOSSE model (Smith, Gottschalk et al., 2010) for organic soils.&lt;/p&gt;&lt;p&gt;&amp;#160;The PEAT-GHG-MODEL evaluates of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, N&lt;sub&gt;2&lt;/sub&gt;O fluxes values at organic soils and soil carbon deposition for non-forest types of land cover. The model utilize data from existing weather stations, published soil data, and data generated by remote sensing of land cover. The model evaluates of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, N&lt;sub&gt;2&lt;/sub&gt;O fluxes values at organic soils and soil carbon deposition, including at peatlands, retrospectively for targeted period or back in time with available space images library. The model can evaluates of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, N&lt;sub&gt;2&lt;/sub&gt;O fluxes values at organic soils and soil carbon deposition for future period based on meteorological input data generated by climate change scenarios and land cover data generated by relevant habitats (land cover) change scenarios. The PEAT-GHG-MODEL estimates of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, N&lt;sub&gt;2&lt;/sub&gt;O fluxes from organic soils and soil carbon deposition for non-forest types of land cover. The model input data generates by existing weather stations, remote sensing of land cover and published soils data. The model estimates of GHG emissions from organic soils, including peatlands, retrospectively for targeted period or back in time with available space images library. The model can simulates of GHG emissions for future period based on meteorological input data generated by climate change scenarios and land cover data generated by relevant habitats change scenarios. The model generates georeferenced data. Minimum land surface area, which can be evaluates by model, equal of size of one pixel of land cover images, used for remote sensing of land cover, it can be 1 m&lt;sup&gt;2&lt;/sup&gt; or less. Due to high resolution, the model estimates highly variable in space CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, N&lt;sub&gt;2&lt;/sub&gt;O fluxes with high accuracy. Maximum land surface area is not limited. The model generates data on decade and/or annual bases. Article presents the model&amp;#8217; verification results. The model verified in 2017 by independent, from the model authors, verification team in frame of &amp;#8220;CLIMA EAST: conservation and sustainable use of peatlands&amp;#8221; project (UNDP-Ukraine). Direct field measurement data for two peatlands used for model verification, including one site drained, and another one is under natural hydrological conditions.&amp;#160; The cumulative annual of CH&lt;sub&gt;4&lt;/sub&gt; and CO&lt;sub&gt;2&lt;/sub&gt; emission presented in Table.&lt;/p&gt;&lt;p&gt;The model calculations were compared with the experimental data obtained for peat soils in the western Polesie of Belarus. The cumulative annual of CH&lt;sub&gt;4&lt;/sub&gt; and CO&lt;sub&gt;2&lt;/sub&gt; emission presented in Table.&lt;/p&gt;&lt;p&gt;Table. Cumulative annual of CH&lt;sub&gt;4&lt;/sub&gt; and CO&lt;sub&gt;2&lt;/sub&gt; emissions according to field measurements and assessment of PEAT-GHG-MODEL&lt;/p&gt;&lt;p&gt;&lt;img src=&quot;https://contentmanager.copernicus.org/fileStorageProxy.php?f=gepj.ccbf8aaeedff56227740161/sdaolpUECMynit/12UGE&amp;app=m&amp;a=0&amp;c=482eb671aeb385948d36c48791670031&amp;ct=x&amp;pn=gepj.elif&amp;d=1&quot; alt=&quot;&quot; width=&quot;906&quot; height=&quot;718&quot;&gt;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;div&gt; &lt;div&gt;&amp;#160;&lt;/div&gt; &lt;/div&gt;

Identifying and quantifying the impact of non-climatic effects on the water cycle in a semi-arid environment 

2021 ◽  
Author(s):  
Julie Collignan ◽  
Jan Polcher ◽  
Pere Quintana Seguí
Keyword(s):  
Climate Change ◽  
Land Cover ◽  
Water Balance ◽  
Human Activities ◽  
River Discharge ◽  
Water Cycle ◽  
Land Cover Changes ◽  
Anthropogenic Changes ◽  
The Impact ◽  
Semi Arid

&lt;p&gt;In a context of climate change, the stakes surrounding water availability and use are getting higher,&amp;#160;especially in semi-arid climates. Human activities such as irrigation and land cover changes impact the water cycle, raising questions around the effects it could have on regional atmospheric circulation and how to separate the impact of climate change from the impact of anthropogenic activities to better understand their role in the historical records. The ORCHIDEE Land Surface Model from Institut Pierre Simon Laplace (IPSL) simulates global carbon cycle and aims at quantifying terrestrial water and energy balance. It is being developed at regional scale but does not include satisfying hypothesis to account for human activities such as irrigation at such scale so far.&lt;/p&gt;&lt;p&gt;We &lt;span&gt;propose&lt;/span&gt; a methodology to semi-empirically separate the effect of climate from the impact of the changing catchment characteristics on river discharge. &lt;span&gt;It is based on&lt;/span&gt; the Budyko framework and &lt;span&gt;allows to characterise the&lt;/span&gt; annual river discharge of over 363 river monitoring stations in Spain. The Budyko parameter is estimated for each basin and &lt;span&gt;represents&lt;/span&gt; its hydrological characteristics. Precipitations and potential evapotranspiration are derived from the forcing dataset GSWP3 (Global Soil Wetness Project Phase 3) &amp;#8211; from 1901 to 2010 &amp;#8211;. Two methods are used to estimate evapotranspiration : the first uses evapotranspiration from the ORCHIDEE LSM outputs while the second deduced evapotranspiration from river discharge observations and the water balance equation.&amp;#160;The first method only accounts for the effects of atmospheric forcing while the other combines, through the observations, &lt;span&gt;climatic and non-climatic processes&lt;/span&gt; over the watersheds.&amp;#160;We then study the evolution over the &lt;span&gt;Budyko&lt;/span&gt; parameter fitted with these two &lt;span&gt;estimates of evaporation&lt;/span&gt;. Studying the watershed parameter allows us to free ourselves from some of the climate interannual variability compared to directly looking at changes in the river discharge and better separate anthropogenic changes from the effect of climatic forcing.&lt;/p&gt;&lt;p&gt;Our results show that for most basins tested over Spain, there is an increasing trend in the &lt;span&gt;Budyko parameter representing increasing evaporation efficiency&lt;/span&gt; of the watershed which &lt;span&gt;can not be&lt;/span&gt; explained by the climate forcing. This trend is consistent with changes in irrigation equipment and land cover changes over the studied period. However changes of the basin characteristics can not be fully quantified by this variables. Other factors as glaciers melting which derails the water balance over our time of study.&lt;/p&gt;&lt;p&gt;The methodology needs to be extended to other areas such as Northern Europe to see if the differences in response of the catchments to anthropogenic changes quantified by our methodology corresponds to known contrasts. Balance between climatic and anthropogenic changes of basin characteristics are different in semi-arid climate than in northern more humid regions.&lt;/p&gt;

Application of Remote Sensing and GIS to Detect Land Use and Land Cover Changes in Jos East Local Government Area, Plateau State, Nigeria.

2021 ◽  
Vol 1 (1) ◽  
pp. 1-8
Author(s):  
Solomon Wuyep zitta
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Digital Camera ◽  
Land Cover Changes ◽  
Remotely Sensed Data ◽  
Plateau State ◽  
Ground Truthing ◽  
Land Management System

This study examines the potentials of Remote Sensing techniques and GIS in land resources management with particular reference to detect land use and land cover changes in Jos East L.G.A, between 1995 to 2015. In this study, administrative maps, remotely sensed data (Landsat and Nigeriasat-1 satellite imageries) and GIS techniques were used in the image analysis. All these were done using Ilwis 3.3 Academic, ERDAS 9.3, IDIRISI 17.0 and ArcGIS 10.1. Digital camera was also used for ground truthing. The results were presented using classified imageries. Between the years 1995 to 2015, there was consistent change in the land use land cover of Jos east with different LULC categories. Throughout the study years, vegetation was observed to have the highest percentage of the total land coverage with 57544.28 ha (63%) in 1995, decreasing to 50322.96 ha (50%) in 2005, and 34969.95 (39%) in the year 2015. While agricultural/farm land was gradually increasing throughout the study period with 21271.05 ha (23%) in 1995, 27017.37 ha (27%) in 2005 and 25406.19 ha (28%) in 2015. Findings also showed that build-up-areas/settlement development increased consistently from 1451.97ha (2%) in 1995, 3290.49 ha (3%) in 2005 to 5817.96 (6%) in 2015. It was concluded that agriculture in the study area is increasing while large areas of vegetation is drastically reducing and being converted to farmlands and settlements. It is recommended that government should put up a reliable land management system in form of restrictions on premature conversion of agricultural land, there should be policies that control threat to the vegetation cover. Government should take cognizance of the land use and land cover at a regular interval to ascertain the changes that are taking place in the study area.

scholarly journals Lake Watershed Dynamics and Bathymetry Modeling of Rara and Begnas Lakes in Nepal

Earth ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 272-286
Author(s):  
Sudeep Thakuri ◽  
Furbe Lama ◽  
Rabin Malla ◽  
Nitesh Khadka ◽  
Narayan Prasad Ghimire ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Cover ◽  
Human Activities ◽  
Scientific Evidence ◽  
Primary Source ◽  
Climate Change Impacts ◽  
Maximum Depth ◽  
Water Volume ◽  
Lake Area ◽  
Watershed Dynamics

Lake evolution and its changes over time are an evident and easily measurable signal of human activities and climate change impacts in mountain regions. This study presents bathymetric modeling of permanent lakes (Begnas and Rara Lakes) located in two different geographic settings of Nepal. Moreover, temporal changes in land cover and soil erosion of the lake watersheds, as well as climatic trends around these lakes, are assessed. This study supports establishing reference sites for exploring scientific evidence on the impacts of anthropogenic and climate change on lake hydrological systems. Second-order polynomial models best represent the relationship between lake depth and volume. Rara Lake had a maximum depth of 169 m with an area of 10.52 km2 and a volume of 1013.305 million cubic meters (Mm3), whereas Begnas Lake had a maximum depth of 12.5 m with an area of 2.98 ± 0.10 km2 and a water volume of 13.539 Mm3 in the year 2019. Both lake regions are experiencing changes in temperature and rainfall. The area and volume of Rara Lake and its watershed have been relatively stable even with minimal land-cover change during the recent decades. Begnas Lake and its watershed have experienced significant changes in the last few decades. This study concludes that human activities in the Begnas Lake watersheds are the primary source of lake area variation rather than climate change.

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