scholarly journals Global land use extent and dispersion within natural land cover using Landsat data

Author(s):  
Matthew C Hansen ◽  
Peter V Potapov ◽  
Amy Pickens ◽  
Alexandra Tyukavina ◽  
Andres Hernandez Serna ◽  
...  

Abstract The conversion of natural land cover into human-dominated land use systems has significant impacts on the environment. Global mapping and monitoring of human-dominated land use extent via satellites provides an empirical basis for assessing land use pressures. Here, we present a novel 2019 global land cover, land use, and ecozone map derived from Landsat satellite imagery and topographical data using derived image feature spaces and algorithms suited per theme. From the map, we estimate the spatial extent and dispersion of land use disaggregated by climate domain and ecozone, where dispersion is the mean distance of land use to all land within a subregion. We find that percent of area under land use and distance to land use follow a power law that depicts an increasingly random spatial distribution of land use as it extends across lands of comparable development potential. For highly developed climate/ecozones, such as temperate and sub-tropical terra firma vegetation on low slopes, area under land use is contiguous and remnant natural land cover have low areal extent and high fragmentation. The tropics generally have the greatest potential for land use expansion, particularly in South America. An exception is Asian humid tropical terra firma vegetated lowland, which has land use intensities comparable to that of temperate breadbaskets such as the United States’ corn belt. Wetland extent is inversely proportional to land use extent within climate domains, indicating historical wetland loss for temperate, sub-tropical, and dry tropical biomes. Results highlight the need for planning efforts to preserve natural systems and associated ecosystem services. The demonstrated methods will be implemented operationally in quantifying global land change, enabling a monitoring framework for systematic assessments of the appropriation and restoration of natural land cover.

2021 ◽  
Vol 4 (3) ◽  
pp. 132-146
Author(s):  
Md. Lutfor Rahman ◽  
Syed Hafizur Rahman

This study aims at classifying land use land cover (LULC) patterns and detect changes in a 'secondary city' (Savar Upazila) in Bangladesh for 30 years i.e., from 1990 to 2020. Two distinct sets of Landsat satellite imagery, such as Landsat Thematic Mapper (TM) 1990 and Landsat 7 ETM+ 2020, were collected from the United States Geological Survey (USGS) website. Using ArcMap 10.3, the maximum likelihood algorithm was used to perform a supervised classification methodology. The error matrix and Kappa Kat were done to measure the mapping accuracy. Both images were classified into six separate classes: Cropland, Barren land, Built-up area, Vegetation, Waterbody, and Wetlands. From 1990 to 2020, Cropland, Barren land, Waterbody, and Wetlands have been decreased by 30.63%, 11.26%, 23.54%, and 21.89%, respectively. At the same time, the Built-up area and Vegetation have been increased by 161.16% and 5.77%, respectively. The research revealed that unplanned urbanization had been practiced in the secondary city indicated by the decreases in Cropland, Barren land, Wetland, and Waterbody, which also showed direct threats to food security and freshwater scarcity. An increase in Vegetation (mostly homestead vegetation) indicates some environment awareness programs that encourage people to maintain homestead and artificial gardens. The study argues for the sustainable planning of a secondary city for a developing country's future development.


2003 ◽  
Vol 13 (1) ◽  
pp. 63-70 ◽  
Author(s):  
Zhiqiang Gao ◽  
Jiyuan Liu ◽  
Xiangzheng Deng

Author(s):  
O. S. Olokeogun ◽  
K. Iyiola ◽  
O. F. Iyiola

Mapping of LULC and change detection using remote sensing and GIS techniques is a cost effective method of obtaining a clear understanding of the land cover alteration processes due to land use change and their consequences. This research focused on assessing landscape transformation in Shasha Forest Reserve, over an 18 year period. LANDSAT Satellite imageries (of 30 m resolution) covering the area at two epochs were characterized into five classes (Water Body, Forest Reserve, Built up Area, Vegetation, and Farmland) and classification performs with maximum likelihood algorithm, which resulted in the classes of each land use. <br><br> The result of the comparison of the two classified images showed that vegetation (degraded forest) has increased by 30.96 %, farmland cover increased by 22.82 % and built up area by 3.09 %. Forest reserve however, has decreased significantly by 46.12 % during the period. <br><br> This research highlights the increasing rate of modification of forest ecosystem by anthropogebic activities and the need to apprehend the situation to ensure sustainable forest management.


Author(s):  
I. C. Onuigbo ◽  
J. Y. Jwat

The study was on change detection using Surveying and Geoinformatics techniques. For effective research study, Landsat satellite images and Quickbird imagery of Minna were acquired for three periods, 2000, 2005 and 2012. The research work demonstrated the possibility of using Surveying and Geoinformatics in capturing spatial-temporal data. The result of the research work shows a rapid growth in built-up land between 2000 and 2005, while the periods between 2005 and 2012 witnessed a reduction in this class. It was also observed that change by 2020 may likely follow the trend in 2005 – 2012 all things being equal. Built up area may increase to 11026.456 hectares, which represent 11% change. The study has shown clearly the extent to which MSS imagery and Landsat images together with extensive ground- truthing can provide information necessary for land use and land cover mapping. Attempt was made to capture as accurate as possible four land use and land cover classes as they change through time.


Author(s):  
E. Ramadan ◽  
T. Al-Awadhi ◽  
Y. Charabi

The study of land cover/land use dynamics under climate change conditions is of great significance for improving sustainable ecological management. Understanding the relationships between land cover and land use changes and climate change is thus very important. Understanding the interactive and cumulative effects of climate and land-use changes are a priority for urban planners and policy makers. The present investigation is based on Landsat satellite imagery to explore changes in vegetation spatial distribution between the years from 2000 to2018 The methodology is focused on vegetation indexes tracking and algebraic overlay calculation to analyzed vegetation and their spatial differentiation, land cover change pattern, and the relationships between vegetation dynamics and land cover change in Dhofar Governorate. The study results have revealed that the vegetation vigor is lower in all years compared to 2000. The scene of 2010 shows the minimum vegetation vigor, overall. Besides, the investigation shows a statistical relationship between rainfall and the status of the health of vegetation. Monsoon rainfall has an impact of the growth of vegetation. Between 2012 and 2013, the vegetation activity shows a decreasing trend. The analysis diagnoses an area affected by the worst degree of aridity situated in the southeastern of Dhofar Mountains. Climate change is the main driving factor resulted from both human activities and rainfall fluctuation.


<i>Abstract.</i>—Surrounding land use and cover can have profound effects on the physical, chemical, and biological properties of stream ecosystems. For this reason, changes in land use and cover throughout catchments often have strong effects on stream ecosystems that are particularly interesting to researchers. Additionally, natural physical and climatic, or physiographic, characteristics are important for determining natural land cover and constraining human land use and are also strongly related to stream habitat and biota. Because the physiographic template differs among catchments and is an important mediator of catchment processes, it is important to account for natural physiographic differences among catchments to understand the relationship between land use/cover and stream biota. In this paper, we develop and assess the usefulness of a regional framework, land use/cover distinguished physiographic regions (LDPRs), which is designed for understanding relationships between land use/cover and stream biota while accounting for the physiographic template. We classified hydrologic units into LDPRs based on physiographic predictors of land use and cover for the eastern and western United States through the use of multivariate regression tree analysis. Next, we used case study data to assess the usefulness of LDPRs by determining if the relationships between fish assemblage function and land use/cover varied among classes using hierarchical logistic regression models. Eight physiographic characteristics determined land cover patterns for both the eastern and western United States and were used to classify hydrologic units into LDPR classes. Five commonly used biotic metrics describing trophic, reproductive, and taxonomic groupings of fish species responded in varying ways to agriculture and urban land use across LDPRs in the upper Mississippi River basin. Our findings suggest that physiographic differences among hydrologic units result in different pathways by which land use and cover affects stream fish assemblages and that LDPRs are useful for stratifying hydrologic units to investigate those different processes. Unlike other commonly used regional frameworks, the rationale and methods used to develop LDPRs properly account for the often-confounded relationship between physiography and land use/cover when relating land cover to stream biota. Therefore, we recommend the use and refinement of LDPRs or similarly developed regional frameworks so that the varying processes by which human land use results in stream degradation can be better understood.


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