Land Classification and Change Intensity Analysis in a Coastal Watershed of Southeast China
The aim of this study is to improve the understanding of land changes in the Jiulong River watershed, a coastal watershed of Southeast China. We developed a stratified classification methodology for land mapping, which combines linear stretching, an Iterative Self-Organizing Data Analysis (ISODATA)...
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doaj-ae9b1820f6914906a0a98980005e53d22020-11-25T00:47:00ZengMDPI AGSensors1424-82202014-07-01147116401165810.3390/s140711640s140711640Land Classification and Change Intensity Analysis in a Coastal Watershed of Southeast ChinaPei Zhou0Jinliang Huang1Robert Gilmore Pontius2Huasheng Hong3Coastal and Ocean Management Institute, Xiamen University, Xiamen 361005, ChinaCoastal and Ocean Management Institute, Xiamen University, Xiamen 361005, ChinaGraduate School of Geography, Clark University, Worcester, MA 01610, USACoastal and Ocean Management Institute, Xiamen University, Xiamen 361005, ChinaThe aim of this study is to improve the understanding of land changes in the Jiulong River watershed, a coastal watershed of Southeast China. We developed a stratified classification methodology for land mapping, which combines linear stretching, an Iterative Self-Organizing Data Analysis (ISODATA) clustering algorithm, and spatial reclassification. The stratified classification for 2002 generated less overall error than an unstratified classification. The stratified classifications were then used to examine temporal differences at 1986, 1996, 2002, 2007 and 2010. Intensity Analysis was applied to analyze land changes at three levels: time interval, category, and transition. Results showed that land use transformation has been accelerating. Woodland’s gains and losses were dormant while the gains and losses of Agriculture, Orchard, Built-up and Bare land were active during all time intervals. Water’s losses were active and stationary. The transitions from Agriculture, Orchard, and Water to Built-up were systematically targeting and stationary, while the transition from Woodland to Built-up was systematically avoiding and stationary.http://www.mdpi.com/1424-8220/14/7/11640land-use and land-coverstratified classificationintensity analysiscoastal watershed |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pei Zhou Jinliang Huang Robert Gilmore Pontius Huasheng Hong |
spellingShingle |
Pei Zhou Jinliang Huang Robert Gilmore Pontius Huasheng Hong Land Classification and Change Intensity Analysis in a Coastal Watershed of Southeast China Sensors land-use and land-cover stratified classification intensity analysis coastal watershed |
author_facet |
Pei Zhou Jinliang Huang Robert Gilmore Pontius Huasheng Hong |
author_sort |
Pei Zhou |
title |
Land Classification and Change Intensity Analysis in a Coastal Watershed of Southeast China |
title_short |
Land Classification and Change Intensity Analysis in a Coastal Watershed of Southeast China |
title_full |
Land Classification and Change Intensity Analysis in a Coastal Watershed of Southeast China |
title_fullStr |
Land Classification and Change Intensity Analysis in a Coastal Watershed of Southeast China |
title_full_unstemmed |
Land Classification and Change Intensity Analysis in a Coastal Watershed of Southeast China |
title_sort |
land classification and change intensity analysis in a coastal watershed of southeast china |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2014-07-01 |
description |
The aim of this study is to improve the understanding of land changes in the Jiulong River watershed, a coastal watershed of Southeast China. We developed a stratified classification methodology for land mapping, which combines linear stretching, an Iterative Self-Organizing Data Analysis (ISODATA) clustering algorithm, and spatial reclassification. The stratified classification for 2002 generated less overall error than an unstratified classification. The stratified classifications were then used to examine temporal differences at 1986, 1996, 2002, 2007 and 2010. Intensity Analysis was applied to analyze land changes at three levels: time interval, category, and transition. Results showed that land use transformation has been accelerating. Woodland’s gains and losses were dormant while the gains and losses of Agriculture, Orchard, Built-up and Bare land were active during all time intervals. Water’s losses were active and stationary. The transitions from Agriculture, Orchard, and Water to Built-up were systematically targeting and stationary, while the transition from Woodland to Built-up was systematically avoiding and stationary. |
topic |
land-use and land-cover stratified classification intensity analysis coastal watershed |
url |
http://www.mdpi.com/1424-8220/14/7/11640 |
work_keys_str_mv |
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1725262572991545344 |