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Analyzed about 2 hours ago. based on code collected 1 day ago.
Nov 05, 2025 — Nov 05, 2026
Commit Message Contributor Files Modified Lines Added Lines Removed Code Location Date
Section 1451 updated
K.Srinivasan
More... almost 2 years ago
Section 1488 updated
K.Srinivasan
More... almost 2 years ago
Section 1488 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Updated BestPractices.txt
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1556 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1313 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
1560. (JIRA,THEORY and FEATURE) GIS Urban Sprawl Analytics - Contour segment and Voronoi-Delaunay triangulation analysis of Chennai Metropolitan Area Global Human Settlement Layer Urban Center Database (UCDB) R2024A imagery - 9 November 2024 - related to 823,1163,1164,1174,1175,1177,1179,1194,1211,1226,1234,1290,1291,1292,1295,1296,1297,1301,1302,1304,1312,1313,1320,1323,1326,1328,1342,1343,1349,1350,1351,1362,1363,1377,1386,1387,1395,1397,1398,1412,1414,1423,1448,1449,1462,1471,1472,1533,1559 and all sections on GIS Urban Sprawl Analytics, Merit of Large Scale Visuals, Gridded Population Estimators (SEDAC GPW4 and GHSL convex hull estimators), DBSCAN and Neural Network Urban Extent Learners, Computational Geometry, Intrinsic Merit Rankings, Verlhulste-R Ricker Population Estimation, Community detection, Social Network Analytics, Space filling by Curves, Unequal Circle and Polynomial packing, Computational Geometry and Polygonal packing by Voronoi Tessellation, Four color theorem, Economic Merit, Computational Economics - GDP estimation from Urban sprawl demographics, electricity consumption, Poverty alleviation, Preferential Attachment, Automatic Delineation of Urban Sprawls, Cellular Automata-SLEUTH-Polya Urn-Dynamic Facegraph Urban Growth Models,Expander Graphs,Timeseries analysis,Graph Edit Distance and Earth mover distance, Face recognition,Graph Isomorphism (Exact, Approximate and Subgraph),Graph matching,Graph similarity,Image Search,Quadrilateral Mesh Deformation and Isomorphism,Maximum Common Subgraph Problem and Approximate Topological Matching
Srinivasan Kannan
More... almost 2 years ago
-------------------------------------------------------------------------------------------------------------------------------------------- 1560. (JIRA,THEORY and FEATURE) GIS Urban Sprawl Analytics - Contour segment and Voronoi-Delaunay triangulation analysis of Chennai Metropolitan Area Global Human Settlement Layer Urban Center Database (UCDB) R2024A imagery - 9 November 2024 - related to 823,1163,1164,1174,1175,1177,1179,1194,1211,1226,1234,1290,1291,1292,1295,1296,1297,1301,1302,1304,1312,1313,1320,1323,1326,1328,1342,1343,1349,1350,1351,1362,1363,1377,1386,1387,1395,1397,1398,1412,1414,1423,1448,1449,1462,1471,1472,1533,1559 and all sections on GIS Urban Sprawl Analytics, Merit of Large Scale Visuals, Gridded Population Estimators (SEDAC GPW4 and GHSL convex hull estimators), DBSCAN and Neural Network Urban Extent Learners, Computational Geometry, Intrinsic Merit Rankings, Verlhulste-R Ricker Population Estimation, Community detection, Social Network Analytics, Space filling by Curves, Unequal Circle and Polynomial packing, Computational Geometry and Polygonal packing by Voronoi Tessellation, Four color theorem, Economic Merit, Computational Economics - GDP estimation from Urban sprawl demographics, electricity consumption, Poverty alleviation, Preferential Attachment, Automatic Delineation of Urban Sprawls, Cellular Automata-SLEUTH-Polya Urn-Dynamic Facegraph Urban Growth Models,Expander Graphs,Timeseries analysis,Graph Edit Distance and Earth mover distance, Face recognition,Graph Isomorphism (Exact, Approximate and Subgraph),Graph matching,Graph similarity,Image Search,Quadrilateral Mesh Deformation and Isomorphism,Maximum Common Subgraph Problem and Approximate Topological Matching -------------------------------------------------------------------------------------------------------------------------------------------- 1560.1 python-src/image_pattern_mining/ImageNet/GISUrbanSprawlAnalytics.py has been updated to typecast Delaunay triangle vertices from float to int due to OpenCV exception and cv.waitKey() invocation has been commented due to OpenCV incompatibility in GISUrbanSprawlAnalytics.py and ImageGraph_Keras_Theano.py - This resolves JIRA issue https://krishnairesearch.atlassian.net/browse/NEUR-52 1560.2 GHSL R2024A UCDB imagery for Chennai Metropolitan Area obtained from GHSL Urban Data Platform Plus (1559.5) - testlogs/GHSL_R2024A_UCDB_ChennaiMetropolitanArea2.jpeg - has been contour segmented, Voronoi-Delaunay triangulated and k-means clustered. 1560.3 Following are the logs,facegraph DOT file and images for segmentation,cannyedge,triangulation and clustering: testlogs/GHSL_R2024A_UCDB_ChennaiMetropolitanArea2-cannyedgedetection.jpg (Canny Edge Detection) testlogs/GHSL_R2024A_UCDB_ChennaiMetropolitanArea2-contourkmeansclustered.jpg (KMeans clustering) testlogs/GHSL_R2024A_UCDB_ChennaiMetropolitanArea2-contourlabelled.jpg (Voronoi-Delaunay Triangulation) testlogs/GHSL_R2024A_UCDB_ChennaiMetropolitanArea2-contoursegmented.jpg (Contours) testlogs/GISUrbanSprawlAnalytics.log.9November2024 testlogs/RemoteSensingGIS/GHSL_R2024A_UCDB_ChennaiMetropolitanArea2_ImageNet_Keras_Theano_Segmentation_FaceGraph.dot testlogs/RemoteSensingGIS/GHSL_R2024A_UCDB_ChennaiMetropolitanArea2_segmented.jpg (Watershed segmentation)
Srinivasan Kannan
More... almost 2 years ago
GHSL R2024A UCDB imagery for Chennai Metropolitan Area - urban centers and periurban clusters
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Section 1558 updated
K.Srinivasan
More... almost 2 years ago
Updated Requirements.txt and Section 1559
Srinivasan Kannan
More... almost 2 years ago
1559. (THEORY and FEATURE) GIS Urban Sprawl Analytics - Global Human Settlement Layer Urban Center Database R2024A - Excel file parser - 7 November 2024 - related to 823,1163,1164,1174,1175,1177,1179,1194,1211,1226,1234,1290,1291,1292,1295,1296,1297,1301,1302,1304,1312,1313,1320,1323,1326,1328,1342,1343,1349,1350,1351,1362,1363,1377,1386,1387,1395,1397,1398,1412,1414,1423,1448,1449,1462,1471,1472,1533 and all sections on GIS Urban Sprawl Analytics, Merit of Large Scale Visuals, Gridded Population Estimators (SEDAC GPW4 and GHSL convex hull estimators), DBSCAN and Neural Network Urban Extent Learners, Computational Geometry, Intrinsic Merit Rankings, Verlhulste-R Ricker Population Estimation, Community detection, Social Network Analytics, Space filling by Curves, Unequal Circle and Polynomial packing, Computational Geometry and Polygonal packing by Voronoi Tessellation, Four color theorem, Economic Merit, Computational Economics - GDP estimation from Urban sprawl demographics, electricity consumption, Poverty alleviation, Preferential Attachment, Automatic Delineation of Urban Sprawls, Cellular Automata-SLEUTH-Polya Urn-Dynamic Facegraph Urban Growth Models,Expander Graphs,Timeseries analysis,Graph Edit Distance and Earth mover distance, Face recognition,Graph Isomorphism (Exact, Approximate and Subgraph),Graph matching,Graph similarity,Image Search,Quadrilateral Mesh Deformation and Isomorphism,Maximum Common Subgraph Problem and Approximate Topological Matching
Srinivasan Kannan
More... almost 2 years ago
-------------------------------------------------------------------------------------------------------------------------------------------- 1559. (THEORY and FEATURE) GIS Urban Sprawl Analytics - Global Human Settlement Layer Urban Center Database R2024A - Excel file parser - 7 November 2024 - related to 823,1163,1164,1174,1175,1177,1179,1194,1211,1226,1234,1290,1291,1292,1295,1296,1297,1301,1302,1304,1312,1313,1320,1323,1326,1328,1342,1343,1349,1350,1351,1362,1363,1377,1386,1387,1395,1397,1398,1412,1414,1423,1448,1449,1462,1471,1472,1533 and all sections on GIS Urban Sprawl Analytics, Merit of Large Scale Visuals, Gridded Population Estimators (SEDAC GPW4 and GHSL convex hull estimators), DBSCAN and Neural Network Urban Extent Learners, Computational Geometry, Intrinsic Merit Rankings, Verlhulste-R Ricker Population Estimation, Community detection, Social Network Analytics, Space filling by Curves, Unequal Circle and Polynomial packing, Computational Geometry and Polygonal packing by Voronoi Tessellation, Four color theorem, Economic Merit, Computational Economics - GDP estimation from Urban sprawl demographics, electricity consumption, Poverty alleviation, Preferential Attachment, Automatic Delineation of Urban Sprawls, Cellular Automata-SLEUTH-Polya Urn-Dynamic Facegraph Urban Growth Models,Expander Graphs,Timeseries analysis,Graph Edit Distance and Earth mover distance, Face recognition,Graph Isomorphism (Exact, Approximate and Subgraph),Graph matching,Graph similarity,Image Search,Quadrilateral Mesh Deformation and Isomorphism,Maximum Common Subgraph Problem and Approximate Topological Matching -------------------------------------------------------------------------------------------------------------------------------------------- 1559.1 python-src/image_pattern_mining/ImageNet/GISUrbanSprawlAnalytics.py has been updated to import openpyxl for parsing GHSL UCDB R2024A Excel dataset GHS_UCDB_REGION_CENTRAL_AND_SOUTHERN_ASIA_R2024A.xlsx (downloaded from https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_UCDB_GLOBE_R2024A/GHS_UCDB_REGION_GLOBE_R2024A/GHS_UCDB_REGION_CENTRAL_AND_SOUTHERN_ASIA_R2024A/V1-0/GHS_UCDB_REGION_CENTRAL_AND_SOUTHERN_ASIA_R2024A_V1_0.zip) 1559.2 New python function def urban_sprawl_from_ucdb_excel(ghsl_ucdb_excel,urban_center="All",sheetname="GENERAL_CHARACTERISTICS",fromrow=2185,torow=2200) loads GHSL UCDB excel dataset by openpyxl load_workbook(), sets active worksheet to sheetname and iterates through every row and column between fromrow to torow arguments in active worksheet. (*) If argument urban_center is set to an urban center name, cell data are searched for urban_center and matching cells are printed (*) If argument urban_center is set to "All" entire data in excel sheet is printed. 1559.3 Data parsed from R2024A UCDB excel dataset for few urban center rows is captured in following logs : python-src/image_pattern_mining/ImageNet/testlogs/GISUrbanSprawlAnalytics.log.7November2024 python-src/image_pattern_mining/ImageNet/testlogs/GISUrbanSprawlAnalytics.log2.7November2024 python-src/image_pattern_mining/ImageNet/testlogs/GISUrbanSprawlAnalytics.log3.7November2024 1559.4 Following are Column labels for UCDB R2024A dataset - from python-src/image_pattern_mining/ImageNet/testlogs/GISUrbanSprawlAnalytics.log2.7November2024) - Columns 6 and 7 contain area and population of urban center in Column 2: ------------------Column 1 ----------- urban_sprawl_from_ucdb_excel(): cell A1 : ID_UC_G0 ------------------Column 2 ----------- urban_sprawl_from_ucdb_excel(): cell B1 : GC_UCN_MAI_2025 ------------------Column 3 ----------- urban_sprawl_from_ucdb_excel(): cell C1 : GC_UCN_LIS_2025 ------------------Column 4 ----------- urban_sprawl_from_ucdb_excel(): cell D1 : GC_CNT_GAD_2025 ------------------Column 5 ----------- urban_sprawl_from_ucdb_excel(): cell E1 : GC_CNT_UNN_2025 ------------------Column 6 ----------- urban_sprawl_from_ucdb_excel(): cell F1 : GC_UCA_KM2_2025 ------------------Column 7 ----------- urban_sprawl_from_ucdb_excel(): cell G1 : GC_POP_TOT_2025 ------------------Column 8 ----------- urban_sprawl_from_ucdb_excel(): cell H1 : GC_DEV_WIG_2025 ------------------Column 9 ----------- urban_sprawl_from_ucdb_excel(): cell I1 : GC_DEV_USR_2025 ------------------Column 10 ----------- urban_sprawl_from_ucdb_excel(): cell J1 : GC_PLS_SCR_2025 ------------------Column 11 ----------- urban_sprawl_from_ucdb_excel(): cell K1 : GC_UCB_YOB_2025 ------------------Column 12 ----------- urban_sprawl_from_ucdb_excel(): cell L1 : GC_UCB_YOD_2025 ------------------Column 13 ----------- urban_sprawl_from_ucdb_excel(): cell M1 : GC_UCM_CAP
Srinivasan Kannan
More... almost 2 years ago
Section 1558 updated
Srinivasan Kannan
More... almost 2 years ago
Updated BestPractices.txt
Srinivasan Kannan
More... about 2 years ago