Abstract
Robust remote monitoring of land cover changes is essential for a range of studies such as climate modeling, ecosystems, and environmental protection. However, since each satellite data has its own effective features, it is difficult to obtain high accuracy land cover products derived from a single satellite’s data, perhaps because of cloud cover, suboptimal acquisition schedules, and the restriction of data accessibility. In this study, we integrated Landsat 5, 7, and 8, Sentinel-2, Advanced Land Observing Satellite Advanced Visual, and Near Infrared Radiometer type 2 (ALOS/AVNIR-2), ALOS Phased Array L-band Synthetic Aperture Radar (PALSAR) Mosaic, ALOS-2/PALSAR-2 Mosaic, Shuttle Radar Topography Mission (SRTM), and ancillary data, using kernel density estimation to map and analyze land use/cover change (LUCC) over Central Vietnam from 2007 to 2017. The region was classified into nine categories, i.e., water, urban, rice paddy, upland crops, grassland, orchard, forest, mangrove, and bare land by an automatic model which was trained and tested by 98,000 reference data collected from field surveys and visual interpretations. Results were the 2007 and 2017 classified maps with the same spatial resolutions of 10 m and the overall accuracies of 90.5% and 90.6%, respectively. They indicated that Central Vietnam experienced an extensive change in land cover (33 ± 18% of the total area) during the study period. Gross gains in forests (2680 km2) and water bodies (570 km2) were primarily from conversion of orchards, paddy fields, and crops. Total losses in bare land (495 km2) and paddy (485 km2) were largely to due transformation to croplands and urban & other infrastructure lands. In addition, the results demonstrated that using global land cover products for specific applications is impaired because of uncertainties and inconsistencies. These findings are essential for the development of resource management strategy and environmental studies.
Highlights
Ttohetrroepgiciaolnseaxvapnenraienclcimesatfeosu. rThsearseogniosn: sepxrpienrgien(FceesbrfouuarrysetaosoAnps:rsilp)r,isnugmmer (May to(FJeublyru)a, rfyallto(AAupgruil)s,tstuomOmcetor b(eMra),yatnodJwulyin),tefral(lN(Aovugemusbt etor tOocJtaonbuera)r, ya)n.dThweinmteera(nNaonvnemuablerrationfall is 700–500Ja0nmuamry)[.6T1h]eamndeatnheanmnueaalnraainnnfaullailst7e0m0–p5e0r0a0tumrme i[s612]3a.9n–d2t5h.e9 m◦Cea[n28an],nwuahlitcehmspiegrnaitufirceanistl2y3.c9–ontrols the crop25s.e9a°sCon[2s8o],vwehritchhesrigengiifoicnan[3tl0y].coTnhtreodlsivtheerscerocplismeaastoen, scoomvepr ltehxe troepgioognr[a3p0h].yT, haenddivvearrsieouclsimeathten, icities lead to cdaoomcmopimnleapxnltteolxpanogdgerocagopvrhaeypr, htaynypdeasvnaodrfiloraiuncsedepstchaadnpdicyeit,iwecsriotlhpeast,dhgetroadsaoslcmaonmidnp,alwnextetlglaaennoddg,rcauoprhvbyaenra,tnfydoprleeassnt,dobsfcararipeceelawpniadtdh, adtnhyde, crops, grasslanmda,nwgreotvlea.nd, urban, forest, bare land, and mangrove
Based on the kernel density estimation, we produced land cover maps of the over Central Vietnam between 2007 and 2017 using high-resolution remotely sensed data from multiple sensors. These maps have a spatial resolution of 10 m and an overall accuracy of 90.6%
This study indicates the potential of multisensor fusion for monitoring land cover dynamics in a cloud and large area
Summary
Land use/cover change (LUCC) is increasingly impacting on the Earth’s surface biophysics, biogeochemistry, and biogeography at any rate or scale such as ecosystem services [1,2,3], water balance [4,5,6,7,8], climate [9,10,11,12,13,14], biodiversity conservation [15,16,17], and agriculture [18]. Natural disasters such as drought, floods, and typhoons are causing land cover changes [28,29]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
