Remote sensing monitoring of land restoration interventions in semi-arid environments using a before-after control-impact statistical design

2017 ◽  
Author(s):  
Michele Meroni ◽  
Anne Schucknecht ◽  
Dominique Fasbender ◽  
Felix Rembold ◽  
Francesco Fava ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Statistical Design ◽  
Arid Environments ◽  
Land Restoration ◽  
Remote Sensing Monitoring ◽  
Semi Arid

Evidence for Mountain Glacier Changes in Semi-arid Environments based on Remote Sensing Data

2014 ◽  
Vol 42 (4) ◽  
pp. 801-815
Author(s):  
Neamat Karimi ◽  
Manuchehr Farajzadeh ◽  
Ali Moridnejad ◽  
Soodabeh Namdari
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Arid Environments ◽  
Mountain Glacier ◽  
Sensing Data ◽  
Glacier Changes ◽  
Semi Arid

scholarly journals Remote Sensing of Environmental Drivers Influencing the Movement Ecology of Sympatric Wild and Domestic Ungulates in Semi-Arid Savannas, a Review

2020 ◽  
Vol 12 (19) ◽  
pp. 3218
Author(s):  
Florent Rumiano ◽  
Elodie Wielgus ◽  
Eve Miguel ◽  
Simon Chamaillé-Jammes ◽  
Hugo Valls-Fox ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Southern Africa ◽  
Animal Movement ◽  
Current Knowledge ◽  
Local Development ◽  
Environmental Drivers ◽  
Arid Environments ◽  
Domestic Species ◽  
Cattle Movements ◽  
Semi Arid

Interfaces between protected areas and their peripheries in southern Africa are subject to interactions between wildlife and livestock that vary in frequency and intensity. In these areas, the juxtaposition between production and conservation land uses in a context of increasing anthropisation can create issues associated with human-wildlife coexistence and raises concerns for biodiversity conservation, local development and livelihoods. This literature review aimed at addressing the need to consolidate and gather in one article current knowledge on potential uses of satellite remote sensing (SRS) products by movement ecologists to investigate the sympatry of wildlife/domestic ungulates in savanna interface environments. A keyword querying process of peer reviewed scientific paper, thesis and books has been implemented to identify references that (1) characterize the main environmental drivers impacting buffalo (Syncerus caffer caffer) and cattle (Bos taurus & Bos indicus) movements in southern Africa environments, (2) describe the SRS contribution to discriminate and characterize these drivers. In total, 327 references have been selected and analyzed. Surface water, precipitation, landcover and fire emerged as key drivers impacting the buffalo and cattle movements. These environmental drivers can be efficiently characterized by SRS, mainly through open-access SRS products and standard image processing methods. Applying SRS to better understand buffalo and cattle movements in semi-arid environments provides an operational framework that could be replicated in other type of interface where different wild and domestic species interact. There is, however, a need for animal movement ecologists to reinforce their knowledge of remote sensing and/or to increase pluridisciplinary collaborations.

scholarly journals Remote Sensing Monitoring and Driving Force Analysis of Salinized Soil in Grassland Mining Area

2022 ◽  
Vol 14 (2) ◽  
pp. 741
Author(s):  
Zhenhua Wu ◽  
Mingliang Che ◽  
Shutao Zhang ◽  
Linghua Duo ◽  
Shaogang Lei ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Salt Content ◽  
Feature Space ◽  
Mining Area ◽  
Soil Salinization ◽  
Driving Factors ◽  
Remote Sensing Monitoring ◽  
Saline Land ◽  
Semi Arid ◽  
Salinized Soil

To deal with the problem of soil salinization that exists widely in semi-arid grassland, the Shengli Coalfield in Xilinhot City was selected as the study area. Six periods of Landsat remote sensing data in 2002, 2005, 2008, 2011, 2014, and 2017 were used to extract the salinity index (SI) and surface albedo to construct the SI-Albedo feature space. The salinization monitoring index (SMI) was used to calculate and classify the soil salinization grades in the study area. The soil salinization status and its dynamic changes were monitored and analyzed. Combined with the logistic regression model, the roles of human and natural factors in the development of soil salinization were determined. The results were as follows: (1) The SMI index constructed using the SI-Albedo feature space is simple and easy to calculate, which is conducive to remote sensing monitoring of salinized soil. R2 of the SMI and soil salt content in the 2017 data from the study area is 0.7313, which achieves good results in the quantitative analysis and monitoring of soil salinization in the Xilinhot Shengli Coalfield. (2) The study area is a grassland landscape. However, grassland landscapes are decreasing year by year, and town landscapes, mining landscapes, and road landscapes are greatly increased. The areas of soil salinization reversion in the Shengli mining area from 2002–2005, 2005–2008, 2008–2011, 2011–2014, 2014–2017, and 2002–2017 were 65.64 km2, 1.03 km2, 18.44 km2, 0.9 km2, 7.52 km2, and 62.33 km2, respectively. The overall trend of soil salinization in the study area was reversed from 2002 to 2017. (3) The driving factors of salinized land from 2002 to 2008 are as follows: the distance to the nearest town landscape > the distance to the nearest mining landscape > the distance to the nearest road landscape. The driving factors of salinized land from 2008 to 2017 are as follows: the distance to nearest mining landscape > the distance to the nearest water landscape > the distance to nearest town landscape > altitude > aspect. Coal exploitation and town expansion have occupied a large amount of saline land, and petroleum exploitation and abandoned railway test sites have intensified the development of saline land. This study provides a reference for the treatment and protection of soil salinization in semi-arid grassland mining areas.

Developing Land-surface Evapotranspiration Remote Sensing Monitoring System Using the Component Technology

2011 ◽  
Vol 13 (5) ◽  
pp. 679-686
Author(s):  
Zhiqi QIAN ◽  
Youjing ZHANG ◽  
Shizan DENG ◽  
Yingying FANG ◽  
Chen CHEN
Keyword(s):  
Remote Sensing ◽  
Monitoring System ◽  
Land Surface ◽  
Component Technology ◽  
Remote Sensing Monitoring
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