Dataset Information

A spatio-temporal land use and land cover reconstruction for India from 1960-2010.

ABSTRACT: In recent decades India has undergone substantial land use/land cover change as a result of population growth and economic development. Historical land use/land cover maps are necessary to quantify the impact of change at global and regional scales, improve predictions about the quantity and location of future change and support planning decisions. Here, a regional land use change model driven by district-level inventory data is used to generate an annual time series of high-resolution gridded land use/land cover maps for the Indian subcontinent between 1960-2010. The allocation procedure is based on statistical analysis of the relationship between contemporary land use/land cover and various spatially explicit covariates. A comparison of the simulated map for 1985 against remotely-sensed land use/land cover maps for 1985 and 2005 reveals considerable discrepancy between the simulated and remote sensing maps, much of which arises due to differences in the amount of land use/land cover change between the inventory data and the remote sensing maps.

SUBMITTER: Moulds S

PROVIDER: S-EPMC6091275 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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A spatio-temporal land use and land cover reconstruction for India from 1960-2010.

Moulds Simon S Buytaert Wouter W Mijic Ana A

Scientific data 20180814

In recent decades India has undergone substantial land use/land cover change as a result of population growth and economic development. Historical land use/land cover maps are necessary to quantify the impact of change at global and regional scales, improve predictions about the quantity and location of future change and support planning decisions. Here, a regional land use change model driven by district-level inventory data is used to generate an annual time series of high-resolution gridded l ...[more]

PMID: 30106391

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Project description:The Lower Mekong Basin (LMB) is biologically diverse, economically important, and home to about 65 million people. The region has undergone extensive environmental changes since the 1990s due to such factors as agricultural expansion and intensification, deforestation, more river damming, increased urbanization, growing human populations, expansion of industrial forest plantations, plus frequent natural disasters from flooding and drought. The Mekong river is also heavily used for human transportation, fishing, drinking water, and irrigation. This paper discusses use of pre-existing LULC maps from 1997 and 2010 to derive a LMB regional LULC change map for 9 classes per date using GIS overlay techniques. The change map was derived to aid SWAT hydrologic modeling applications in the LMB, given the 2010 map is currently used in multiple LMB SWAT models, whereas the 1997 map was previously used. The 2010 LULC map was constructed from Landsat and MODIS satellite data, while the 1997 map was from before the MODIS era and therefore based on available Landsat data. The 1997-2010 LULC change map showed multiple trends. Permanent agriculture had expanded in certain sub-basins into previously forested areas. Some agricultural areas were converted to industrial forest plantations. Extensive forest changes also occurred in some locations, such as areas changed to shifting cultivation or permanent crops. Also, the 1997 map under classified some urban areas, whereas the 2010 LULC map showed improved identification of such areas. LULC map accuracy were assessed for 213 randomly sampled locations. The 1997 and 2010 LULC maps showed high overall agreements with reference data exceeding 87%. The LULC change map yielded a moderately high level of overall agreement (78%) that improved to ~83% once LULC classification scheme specificity was reduced (forests and agriculture were each mapped as singular classes). The change map regionally showed a 4% decrease in agriculture and a 4 % increase in deciduous and evergreen forests combined, though deforestation hot spot areas also were evident. The project yielded LULC map data sets that are now available for aiding additional studies that assess LMB LULC change and the impacts such change may pose to water, agriculture, forestry, and disaster management efforts. More work is needed to map, quantify and assess LULC change since 2010 and to further update the 2010 LULC map currently used in the LMB SWAT models.

Project description:Land use change is the main driving force of global environmental change and is considered as most central to various debates on sustainable development. Even though a large volume of literature materials is available on land use/land cover change for many areas, very little work has been done on land use and its implications on land surface thermal characteristics over the Sokoto area of Nigeria, despite the strategic importance of the zone, including urbanization, increased population as well as the climate in the area, which is dominated by warm harmattan wind blowing Sahara dust inland. Thus, this study aimed at investigating the implications of urban growth on temporal variations of land surface temperature (LST) using remote sensing and geographic information system (GIS) techniques over Sokoto Metropolis, Nigeria between 1986 and 2016. The change detection of each land use class was carried out for each period using Landsat images obtained from the archives of the United States Geological Survey (USGS). The results revealed that the area has undergone a drastic transformation where built-up area witnessed changes at 10.77%, farmland and vegetation increased at the rate of 0.72% and 2.15%, respectively, for the period of study (1986-2016). While bare soil and water body decreased at the rate of 0.56% and 1.11%, respectively, during the study period. This shows that there exists a transformation from bare surface (desert) to vegetated surface especially between years 2009 and 2016. The LST of Sokoto Metropolis was calculated from the satellite data, and the land surface temperature of each land use class was assessed for the study period. The maximum LST of Sokoto was 30.6°C, 32.8°C and 34.6°C for 1986, 1999 and 2016, respectively. This study has revealed the existence of a positive relationship between built-up area and LST over the area. This development might be as a result of anthropogenic activities through urban growth coupled with its potential impacts on urban climate. These are intensified by constant changes of the space, causing imbalance in the interactions between surface and atmosphere which may be extensively influenced or modified by various forms of land use.

Dataset Information

A spatio-temporal land use and land cover reconstruction for India from 1960-2010.

Publications

A spatio-temporal land use and land cover reconstruction for India from 1960-2010.

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