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. Th...

Full description

Saved in:
Bibliographic Details
Sonstige:
Year of Publication:2022
Language:English
Physical Description:1 electronic resource (368 p.)
Tags: Add Tag
No Tags, Be the first to tag this record!
LEADER 05720nam-a2201477z--4500
001 993544438204498
005 20231214132859.0
006 m o d
007 cr|mn|---annan
008 202206s2022 xx |||||o ||| 0|eng d
035 |a (CKB)5720000000008440 
035 |a (oapen)https://directory.doabooks.org/handle/20.500.12854/84553 
035 |a (EXLCZ)995720000000008440 
041 0 |a eng 
100 1 |a Symeonakis, Elias  |4 edt 
245 1 0 |a Land Degradation Assessment with Earth Observation 
260 |a Basel  |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2022 
300 |a 1 electronic resource (368 p.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
520 |a 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. 
546 |a English 
650 7 |a Research & information: general  |2 bicssc 
653 |a bfast 
653 |a Mann-Kendall 
653 |a Sen's slope 
653 |a East Africa 
653 |a NDVI 
653 |a breakpoint analysis 
653 |a vegetation trends 
653 |a greening 
653 |a browning 
653 |a Kenya 
653 |a Uganda 
653 |a trend analysis 
653 |a land use 
653 |a land cover 
653 |a spatial heterogeneity 
653 |a mining development 
653 |a geographically weighted regression (GWR) 
653 |a Mann-Kendall 
653 |a arid and semi-arid areas 
653 |a salinization 
653 |a irrigated systems 
653 |a Niger River basin 
653 |a salinity index 
653 |a vegetation index 
653 |a TI-NDVI 
653 |a Sentinel-2 images 
653 |a high temporal resolution 
653 |a wind erosion modeling 
653 |a RWEQ 
653 |a GEE 
653 |a central Asia 
653 |a spatial-temporal variation 
653 |a land degradation 
653 |a archetypes 
653 |a self-organizing maps 
653 |a drivers 
653 |a savannah 
653 |a Nigeria 
653 |a reference levels 
653 |a REDD+ 
653 |a greenhouse gas emissions 
653 |a Xishuangbanna 
653 |a monitoring and reporting 
653 |a Normalised Difference Vegetation Index (NDVI) 
653 |a Vegetation Condition Index (VCI) 
653 |a drought 
653 |a land use-land cover 
653 |a remote sensing 
653 |a Botswana 
653 |a developing countries 
653 |a Google Earth Engine 
653 |a Landsat time series analysis 
653 |a semi-arid areas 
653 |a sustainable land management programmes 
653 |a precipitation 
653 |a breakpoints and timeseries analysis 
653 |a ecosystem structural change 
653 |a BFAST 
653 |a land degradation neutrality 
653 |a SDG 
653 |a land productivity 
653 |a Landsat 
653 |a vegetation-precipitation relationship 
653 |a soil organic carbon 
653 |a Kobresia pygmaea community 
653 |a unmanned aerial vehicle 
653 |a Gaofen satellite 
653 |a spatial distribution 
653 |a aridity index 
653 |a satellite-based aridity index 
653 |a remote sensing index 
653 |a salinized land degradation index (SDI) 
653 |a Amu Darya delta (ADD) 
653 |a satellite imagery 
653 |a gully mapping 
653 |a machine learning 
653 |a random forest 
653 |a support vector machines 
653 |a South Africa 
653 |a semi-arid environment 
653 |a shrub encroachment 
653 |a slangbos 
653 |a Earth observation 
653 |a time series 
653 |a Sentinel-1 
653 |a Sentinel-2 
653 |a Synthetic Aperture Radar (SAR) 
653 |a Soil Adjusted Vegetation Index (SAVI) 
653 |a Kyrgyzstan 
653 |a pastures 
653 |a MODIS 
653 |a land surface phenology 
653 |a drought impacts 
653 |a drought adaptation 
653 |a drought index 
653 |a vegetation resilience 
653 |a drought vulnerability 
653 |a standardized precipitation evapotranspiration index 
653 |a AVHRR 
776 |z 3-0365-4227-2 
776 |z 3-0365-4228-0 
700 1 |a Symeonakis, Elias  |4 oth 
906 |a BOOK 
ADM |b 2023-12-15 05:35:25 Europe/Vienna  |f system  |c marc21  |a 2022-07-02 22:45:44 Europe/Vienna  |g false 
AVE |i DOAB Directory of Open Access Books  |P DOAB Directory of Open Access Books  |x https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5337644050004498&Force_direct=true  |Z 5337644050004498  |b Available  |8 5337644050004498