cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.pphshc
title: Occurrence Download

description: A dataset containing 76 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Belize",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lysiloma"
 ]
}

 The dataset includes 76 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032105-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/2u215t
title: msXL_341r_MMSI+RTI+Arc_B14_055_F.tif
DOI: 10.25346/s6lqjm3j/bloeai
title: msXL_341r_MMSI+RTI+Arc_B12_054_F.tif
DOI: 10.25346/s6lqjm3j/jhib4t
title: msXL_341r_MMSI+RTI+Arc_B10_053_F.tif
DOI: 10.71789/rr7c-6v12
title: Climate Vulnerability Assessment Mixed Cropping Zone Grazing System Data

description: This asset is a dataset containing geospatial outputs from the mixed cropping zone grazing system model produced by the Climate Vulnerability Assessment Project. It contains the climate suitability for mixed cropping zone grazing system in NSW, both historically (1981-2010 baseline) and using future climate projections (2036-2065) for two emissions scenarios (RCP4.5 and RCP8.5), for each element of the model.
DOI: 10.25346/s6lqjm3j/pb5r8a
title: msXL_341r_MMSI+RTI+Arc_B08_052_F.tif
DOI: 10.25346/s6lqjm3j/gk2pzk
title: msXL_341r_MMSI+RTI+Arc_B06_051_F.tif
DOI: 10.25346/s6lqjm3j/2lxcur
title: msXL_341r_MMSI+RTI+Arc_B04_050_F.tif
DOI: 10.25346/s6lqjm3j/o2nx1n
title: msXL_341r_MMSI+RTI+Arc_B02_049_F.tif
DOI: 10.71789/61rm-5j63
title: Climate Vulnerability Assessment Rangeland Grazing System Data

description: This asset is a dataset containing geospatial outputs from the rangeland grazing system model produced by the Climate Vulnerability Assessment Project. It contains the climate suitability for rangeland grazing system in NSW, both historically (1981-2010 baseline) and using future climate projections (2036-2065) for two emissions scenarios (RCP4.5 and RCP8.5), for each element of the model.
DOI: 10.25346/s6lqjm3j/xp26ny
title: msXL_341r_MMSI+RTI+Arc_A15_048_F.tif
DOI: 10.25346/s6lqjm3j/fsfkpk
title: msXL_341r_MMSI+RTI+Arc_A13_047_F.tif
DOI: 10.25346/s6lqjm3j/x9botf
title: msXL_341r_MMSI+RTI+Arc_A11_046_F.tif
DOI: 10.25346/s6lqjm3j/ue7bry
title: msXL_341r_MMSI+RTI+Arc_A09_045_F.tif
DOI: 10.71789/hgr2-am58
title: Climate Vulnerability Assessment Buffalo Fly Data

description: This asset is a dataset containing geospatial outputs from the buffalo fly model produced by the Climate Vulnerability Assessment Project. It contains the climate suitability for buffalo fly in NSW, both historically (1981-2010 baseline) and using future climate projections (2036-2065) for two emissions scenarios (RCP4.5 and RCP8.5), for each element of the model.
DOI: 10.25346/s6lqjm3j/lxugzm
title: msXL_341r_MMSI+RTI+Arc_A07_044_F.tif
DOI: 10.25346/s6lqjm3j/7lmnqm
title: msXL_341r_MMSI+RTI+Arc_A05_043_F.tif
DOI: 10.25346/s6lqjm3j/fqrkzp
title: msXL_341r_MMSI+RTI+Arc_A03_042_F.tif
DOI: 10.25346/s6lqjm3j/npoeet
title: msXL_341r_MMSI+RTI+Arc_A01_041_F.tif
DOI: 10.71789/a12c-tq07
title: Climate Vulnerability Assessment Cattle Tick Data

description: This asset is a dataset containing geospatial outputs from the cattle tick model produced by the Climate Vulnerability Assessment Project. It contains the climate suitability for cattle tick in NSW, both historically (1981-2010 baseline) and using future climate projections (2036-2065) for two emissions scenarios (RCP4.5 and RCP8.5), for each element of the model.
DOI: 10.25346/s6lqjm3j/oinyky
title: msXL_336v_MMSI+RTI+W530R72_039_F.tif
DOI: 10.25346/s6lqjm3j/t1ljqg
title: msXL_336v_MMSI+RTI+W505665_040_F.tif
DOI: 10.25346/s6lqjm3j/en5p7s
title: msXL_336v_MMSI+RTI+W450R25_030_F.tif
DOI: 10.25346/s6lqjm3j/tl65mp
title: msXL_336v_MMSI+RTI+W450G58_034_F.tif
DOI: 10.71789/qw5v-tq47
title: Climate Vulnerability Assessment Oriental Fruit Fly Data

description: This asset is a dataset containing geospatial outputs from the oriental fruit fly model produced by the Climate Vulnerability Assessment Project. It contains the climate suitability for oriental fruit fly in NSW, both historically (1981-2010 baseline) and using future climate projections (2036-2065) for two emissions scenarios (RCP4.5 and RCP8.5), for each element of the model.
DOI: 10.25346/s6lqjm3j/5srvl0
title: msXL_336v_MMSI+RTI+W450B47_038_F.tif
DOI: 10.25346/s6lqjm3j/wy6tzc
title: msXL_336v_MMSI+RTI+W400R25_029_F.tif
DOI: 10.25346/s6lqjm3j/3x0oji
title: msXL_336v_MMSI+RTI+W400G58_033_F.tif
DOI: 10.25346/s6lqjm3j/febgxh
title: msXL_336v_MMSI+RTI+W400B47_037_F.tif
DOI: 10.25346/s6lqjm3j/sb1eoa
title: msXL_336v_MMSI+RTI+W385R25_028_F.tif
DOI: 10.25346/s6lqjm3j/u6jkss
title: msXL_336v_MMSI+RTI+W385G58_032_F.tif
DOI: 10.25346/s6lqjm3j/3zcwgf
title: msXL_336v_MMSI+RTI+W385B47_036_F.tif
DOI: 10.25346/s6lqjm3j/wp8y5v
title: msXL_336v_MMSI+RTI+W365R25_027_F.tif
DOI: 10.15468/dl.wd7zj4
title: Occurrence Download

description: A dataset containing 1418 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Material sample, Material citation, Living Specimen, Occurrence evidence)",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Cratogeomys"
 ]
}

 The dataset includes 1418 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032106-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/oclmtg
title: msXL_336v_MMSI+RTI+W365G58_031_F.tif
DOI: 10.25346/s6lqjm3j/ztrhid
title: msXL_336v_MMSI+RTI+W365B47_035_F.tif
DOI: 10.25346/s6lqjm3j/bwvalg
title: msXL_336v_MMSI+RTI+TX940IR_025_F.tif
DOI: 10.71789/927c-8013
title: Climate Vulnerability Assessment Parthenium Weed Data

description: This asset is a dataset containing geospatial outputs from the parthenium weed model produced by the Climate Vulnerability Assessment Project. It contains the climate suitability for parthenium weed in NSW, both historically (1981-2010 baseline) and using future climate projections (2036-2065) for two emissions scenarios (RCP4.5 and RCP8.5), for each element of the model.
DOI: 10.25346/s6lqjm3j/j79jdy
title: msXL_336v_MMSI+RTI+TX735IR_024_F.tif
DOI: 10.15468/dl.exh2ya
title: Occurrence Download

description: A dataset listing the 9 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Momotus mexicanus"
 ]
}

 The dataset's 9 records were derived from 86 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032096-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/sppgvl
title: msXL_336v_MMSI+RTI+TX615RO_023_F.tif
DOI: 10.25346/s6lqjm3j/lzz8zz
title: msXL_336v_MMSI+RTI+TX1050R_026_F.tif
DOI: 10.71789/pgh3-j198
title: Climate Vulnerability Assessment Queensland Fruit Fly Data

description: This asset is a dataset containing geospatial outputs from the Queensland fruit fly model produced by the Climate Vulnerability Assessment Project. It contains the climate suitability for Queensland fruit fly in NSW, both historically (1981-2010 baseline) and using future climate projections (2036-2065) for two emissions scenarios (RCP4.5 and RCP8.5), for each element of the model.
DOI: 10.25346/s6lqjm3j/rp0fi4
title: msXL_336v_MMSI+RTI+TX1050R_022_F.tif
DOI: 10.25346/s6lqjm3j/eizlm5
title: msXL_336v_MMSI+RTI+M1050IR_021_F.tif
DOI: 10.25346/s6lqjm3j/za2jbi
title: msXL_336v_MMSI+RTI+M1050IR_020_F.tif
DOI: 10.25346/s6lqjm3j/l5bphz
title: msXL_336v_MMSI+RTI+M1050IR_019_F.tif
DOI: 10.25346/s6lqjm3j/fyynxn
title: msXL_336v_MMSI+RTI+M0940IR_018_F.tif
DOI: 10.25346/s6lqjm3j/blimi9
title: msXL_336v_MMSI+RTI+M0850IR_017_F.tif
DOI: 10.71789/n1xd-cs88
title: Climate Vulnerability Assessment Serrated Tussock Data

description: This asset is a dataset containing geospatial outputs from the serrated tussock model produced by the Climate Vulnerability Assessment Project. It contains the climate suitability for serrated tussock in NSW, both historically (1981-2010 baseline) and using future climate projections (2036-2065) for two emissions scenarios (RCP4.5 and RCP8.5), for each element of the model.
DOI: 10.25346/s6lqjm3j/kocev8
title: msXL_336v_MMSI+RTI+M0780IR_016_F.tif
DOI: 10.25346/s6lqjm3j/mdcfdo
title: msXL_336v_MMSI+RTI+M0735IR_015_F.tif
DOI: 10.25346/s6lqjm3j/k4mo29
title: msXL_336v_MMSI+RTI+M0700IR_014_F.tif
DOI: 10.25346/s6lqjm3j/i8v7hu
title: msXL_336v_MMSI+RTI+M0655DR_013_F.tif
DOI: 10.25346/s6lqjm3j/rhekmb
title: msXL_336v_MMSI+RTI+M0630RD_012_F.tif
DOI: 10.71789/7xzk-cq97
title: Climate Vulnerability Assessment Verticillium Wilt Data

description: This asset is a dataset containing geospatial outputs from the Verticillium wilt model produced by the Climate Vulnerability Assessment Project. It contains the climate suitability for Verticillium wilt in NSW, both historically (1981-2010 baseline) and using future climate projections (2036-2065) for two emissions scenarios (RCP4.5 and RCP8.5), for each element of the model.
DOI: 10.25346/s6lqjm3j/vqn4vv
title: msXL_336v_MMSI+RTI+M0615RO_011_F.tif
DOI: 10.25346/s6lqjm3j/bhkvgj
title: msXL_336v_MMSI+RTI+M0590AM_010_F.tif
DOI: 10.25346/s6lqjm3j/u9xuu6
title: msXL_336v_MMSI+RTI+M0560LI_009_F.tif
DOI: 10.25346/s6lqjm3j/hg9h5u
title: msXL_336v_MMSI+RTI+M0530GN_008_F.tif
DOI: 10.71789/2bqh-wx87
title: Climate Vulnerability Assessment Fusarium Data

description: This asset is a dataset containing geospatial outputs from the Fusarium model produced by the Climate Vulnerability Assessment Project. It contains the climate suitability for Fusarium in NSW, both historically (1981-2010 baseline) and using future climate projections (2036-2065) for two emissions scenarios (RCP4.5 and RCP8.5), for each element of the model.
DOI: 10.25346/s6lqjm3j/rswzkc
title: msXL_336v_MMSI+RTI+M0505CN_007_F.tif
DOI: 10.25346/s6lqjm3j/5cuywt
title: msXL_336v_MMSI+RTI+M0470LB_006_F.tif
DOI: 10.25346/s6lqjm3j/kmwnbx
title: msXL_336v_MMSI+RTI+M0450RB_005_F.tif
DOI: 10.25346/s6lqjm3j/7l7qjm
title: msXL_336v_MMSI+RTI+M0420VI_004_F.tif
DOI: 10.25346/s6lqjm3j/lf8ctw
title: msXL_336v_MMSI+RTI+M0400UV_003_F.tif
DOI: 10.25346/s6lqjm3j/dnubaw
title: msXL_336v_MMSI+RTI+M0385UV_002_F.tif
DOI: 10.25346/s6lqjm3j/g0lmmk
title: msXL_336v_MMSI+RTI+M0365UV_001_F.tif
DOI: 10.25346/s6lqjm3j/42rwqt
title: msXL_336v_MMSI+RTI+Arc_G15_096_F.tif
DOI: 10.25346/s6lqjm3j/t0uuqo
title: msXL_336v_MMSI+RTI+Arc_G13_095_F.tif
DOI: 10.25346/s6lqjm3j/uxyzfk
title: msXL_336v_MMSI+RTI+Arc_G11_094_F.tif
DOI: 10.25346/s6lqjm3j/vhwnml
title: msXL_336v_MMSI+RTI+Arc_G09_093_F.tif
DOI: 10.25346/s6lqjm3j/8rbtir
title: msXL_336v_MMSI+RTI+Arc_G07_092_F.tif
DOI: 10.25346/s6lqjm3j/eoid9d
title: msXL_336v_MMSI+RTI+Arc_G05_091_F.tif
DOI: 10.25346/s6lqjm3j/h8nrwm
title: msXL_336v_MMSI+RTI+Arc_G03_090_F.tif
DOI: 10.25346/s6lqjm3j/qp2k8t
title: msXL_336v_MMSI+RTI+Arc_G01_089_F.tif
DOI: 10.25346/s6lqjm3j/3zeaab
title: msXL_336v_MMSI+RTI+Arc_F16_088_F.tif
DOI: 10.25346/s6lqjm3j/qelhyi
title: msXL_336v_MMSI+RTI+Arc_F14_087_F.tif
DOI: 10.25346/s6lqjm3j/p8bv4m
title: msXL_336v_MMSI+RTI+Arc_F12_086_F.tif
DOI: 10.25346/s6lqjm3j/3ynfkl
title: msXL_336v_MMSI+RTI+Arc_F10_085_F.tif
DOI: 10.25346/s6lqjm3j/2tuq4a
title: msXL_336v_MMSI+RTI+Arc_F08_084_F.tif
DOI: 10.25346/s6lqjm3j/ckuscw
title: msXL_336v_MMSI+RTI+Arc_F06_083_F.tif
DOI: 10.25346/s6lqjm3j/8joycq
title: msXL_336v_MMSI+RTI+Arc_F04_082_F.tif
DOI: 10.25346/s6lqjm3j/fa2wg2
title: msXL_336v_MMSI+RTI+Arc_F02_081_F.tif
DOI: 10.25346/s6lqjm3j/q4fasm
title: msXL_336v_MMSI+RTI+Arc_E15_080_F.tif
DOI: 10.25346/s6lqjm3j/2c1cje
title: msXL_336v_MMSI+RTI+Arc_E13_079_F.tif
DOI: 10.25346/s6lqjm3j/q3h1rf
title: msXL_336v_MMSI+RTI+Arc_E11_078_F.tif
DOI: 10.25346/s6lqjm3j/fkupjl
title: msXL_336v_MMSI+RTI+Arc_E09_077_F.tif
DOI: 10.25346/s6lqjm3j/ijohyx
title: msXL_336v_MMSI+RTI+Arc_E07_076_F.tif
DOI: 10.25346/s6lqjm3j/0nnxlc
title: msXL_336v_MMSI+RTI+Arc_E05_075_F.tif
DOI: 10.25346/s6lqjm3j/ihpuh3
title: msXL_336v_MMSI+RTI+Arc_E03_074_F.tif
DOI: 10.25346/s6lqjm3j/pvejw1
title: msXL_336v_MMSI+RTI+Arc_E01_073_F.tif
DOI: 10.25346/s6lqjm3j/rox3wp
title: msXL_336v_MMSI+RTI+Arc_D16_072_F.tif
DOI: 10.25346/s6lqjm3j/lvuhfk
title: msXL_336v_MMSI+RTI+Arc_D14_071_F.tif
DOI: 10.25346/s6lqjm3j/juto2i
title: msXL_336v_MMSI+RTI+Arc_D12_070_F.tif
DOI: 10.25346/s6lqjm3j/ztgemz
title: msXL_336v_MMSI+RTI+Arc_D10_069_F.tif
DOI: 10.25346/s6lqjm3j/j6jh0p
title: msXL_336v_MMSI+RTI+Arc_D08_068_F.tif
DOI: 10.25346/s6lqjm3j/3ibiri
title: msXL_336v_MMSI+RTI+Arc_D06_067_F.tif
DOI: 10.25346/s6lqjm3j/hfoge2
title: msXL_336v_MMSI+RTI+Arc_D04_066_F.tif
DOI: 10.25346/s6lqjm3j/0zo4qo
title: msXL_336v_MMSI+RTI+Arc_D02_065_F.tif
DOI: 10.25346/s6lqjm3j/rvz8q0
title: msXL_336v_MMSI+RTI+Arc_C15_064_F.tif
DOI: 10.25346/s6lqjm3j/bsgfy8
title: msXL_336v_MMSI+RTI+Arc_C13_063_F.tif
DOI: 10.25346/s6lqjm3j/i2ii8v
title: msXL_336v_MMSI+RTI+Arc_C11_062_F.tif
DOI: 10.25346/s6lqjm3j/a3bc2g
title: msXL_336v_MMSI+RTI+Arc_C09_061_F.tif
DOI: 10.25346/s6lqjm3j/gjrfwb
title: msXL_336v_MMSI+RTI+Arc_C07_060_F.tif
DOI: 10.25346/s6lqjm3j/daaw3g
title: msXL_336v_MMSI+RTI+Arc_C05_059_F.tif
DOI: 10.25346/s6lqjm3j/duk6lh
title: msXL_336v_MMSI+RTI+Arc_C03_058_F.tif
DOI: 10.25346/s6lqjm3j/3ozgff
title: msXL_336v_MMSI+RTI+Arc_C01_057_F.tif
DOI: 10.25346/s6lqjm3j/6b0lzx
title: msXL_336v_MMSI+RTI+Arc_B16_056_F.tif
DOI: 10.25346/s6lqjm3j/l8cdiv
title: msXL_336v_MMSI+RTI+Arc_B14_055_F.tif
DOI: 10.25346/s6lqjm3j/6fwdhi
title: msXL_336v_MMSI+RTI+Arc_B12_054_F.tif
DOI: 10.25346/s6lqjm3j/wimlx1
title: msXL_336v_MMSI+RTI+Arc_B10_053_F.tif
DOI: 10.25346/s6lqjm3j/mxrd0o
title: msXL_336v_MMSI+RTI+Arc_B08_052_F.tif
DOI: 10.25346/s6lqjm3j/drl8ls
title: msXL_336v_MMSI+RTI+Arc_B06_051_F.tif
DOI: 10.25346/s6lqjm3j/gdedhc
title: msXL_336v_MMSI+RTI+Arc_B04_050_F.tif
DOI: 10.25346/s6lqjm3j/5lp9fl
title: msXL_336v_MMSI+RTI+Arc_B02_049_F.tif
DOI: 10.25346/s6lqjm3j/p2rja4
title: msXL_336v_MMSI+RTI+Arc_A15_048_F.tif
DOI: 10.25346/s6lqjm3j/xwis6x
title: msXL_336v_MMSI+RTI+Arc_A13_047_F.tif
DOI: 10.25346/s6lqjm3j/ve2nuo
title: msXL_336v_MMSI+RTI+Arc_A11_046_F.tif
DOI: 10.25346/s6lqjm3j/ryr5xl
title: msXL_336v_MMSI+RTI+Arc_A09_045_F.tif
DOI: 10.25346/s6lqjm3j/8eh0u7
title: msXL_336v_MMSI+RTI+Arc_A07_044_F.tif
DOI: 10.25346/s6lqjm3j/6g1iu8
title: msXL_336v_MMSI+RTI+Arc_A05_043_F.tif
DOI: 10.25346/s6lqjm3j/gsbmfd
title: msXL_336v_MMSI+RTI+Arc_A03_042_F.tif
DOI: 10.25346/s6lqjm3j/nilopq
title: msXL_336v_MMSI+RTI+Arc_A01_041_F.tif
DOI: 10.25346/s6lqjm3j/ndlnvu
title: msXL_336r_MMSI+RTI+W530R72_039_F.tif
DOI: 10.25346/s6lqjm3j/5fp8sz
title: msXL_336r_MMSI+RTI+W505665_040_F.tif
DOI: 10.25346/s6lqjm3j/xyvzik
title: msXL_336r_MMSI+RTI+W450R25_030_F.tif
DOI: 10.25346/s6lqjm3j/9bujza
title: msXL_336r_MMSI+RTI+W450G58_034_F.tif
DOI: 10.25346/s6lqjm3j/6iee4i
title: msXL_336r_MMSI+RTI+W450B47_038_F.tif
DOI: 10.25346/s6lqjm3j/t4fdos
title: msXL_336r_MMSI+RTI+W400R25_029_F.tif
DOI: 10.25346/s6lqjm3j/xvwtsc
title: msXL_336r_MMSI+RTI+W400G58_033_F.tif
DOI: 10.25346/s6lqjm3j/swcovd
title: msXL_336r_MMSI+RTI+W400B47_037_F.tif
DOI: 10.25346/s6lqjm3j/jxuhyn
title: msXL_336r_MMSI+RTI+W385R25_028_F.tif
DOI: 10.25346/s6lqjm3j/6g5gg1
title: msXL_336r_MMSI+RTI+W385G58_032_F.tif
DOI: 10.25346/s6lqjm3j/wyjhwj
title: msXL_336r_MMSI+RTI+W385B47_036_F.tif
DOI: 10.25346/s6lqjm3j/9c2ttf
title: msXL_336r_MMSI+RTI+W365R25_027_F.tif
DOI: 10.25346/s6lqjm3j/hiepez
title: msXL_336r_MMSI+RTI+W365G58_031_F.tif
DOI: 10.25346/s6lqjm3j/20nwx4
title: msXL_336r_MMSI+RTI+W365B47_035_F.tif
DOI: 10.25346/s6lqjm3j/gmx8ho
title: msXL_336r_MMSI+RTI+TX940IR_025_F.tif
DOI: 10.25346/s6lqjm3j/ppgazb
title: msXL_336r_MMSI+RTI+TX735IR_024_F.tif
DOI: 10.25346/s6lqjm3j/akx2vj
title: msXL_336r_MMSI+RTI+TX615RO_023_F.tif
DOI: 10.25346/s6lqjm3j/egosqq
title: msXL_336r_MMSI+RTI+TX1050R_026_F.tif
DOI: 10.25346/s6lqjm3j/rnlfpd
title: msXL_336r_MMSI+RTI+TX1050R_022_F.tif
DOI: 10.5281/zenodo.17604957
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS251114a Initial

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS251114a Initial. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.5281/zenodo.17604958
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS251114a Initial

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS251114a Initial. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.25346/s6lqjm3j/ar7e1h
title: msXL_336r_MMSI+RTI+M1050IR_021_F.tif
DOI: 10.25346/s6lqjm3j/oabbdb
title: msXL_336r_MMSI+RTI+M1050IR_020_F.tif
DOI: 10.25346/s6lqjm3j/xyt8rh
title: msXL_336r_MMSI+RTI+M1050IR_019_F.tif
DOI: 10.25346/s6lqjm3j/1gjwmd
title: msXL_336r_MMSI+RTI+M0940IR_018_F.tif
DOI: 10.25346/s6lqjm3j/wctyh2
title: msXL_336r_MMSI+RTI+M0850IR_017_F.tif
DOI: 10.5281/zenodo.17604956
title: emburden: Processed Energy Burden Datasets (North Carolina)

description: PROCESSED, analysis-ready household energy burden datasets from the DOE Low-Income Energy Affordability Data (LEAD) Tool, formatted for the emburden R package.

Scope: North Carolina (proof-of-concept demonstration)

IMPORTANT: These are PRE-PROCESSED datasets, not raw OpenEI data. They have been:



Aggregated by census tract + income bracket

Enriched with computed energy burden metrics (EROI, NER, DEAR)

Standardized for immediate analysis

Quality-checked and validated


This repository provides census tract-level data on household energy burden for North Carolina, covering ~1,600 census tracts. Data includes both Area Median Income (AMI) and Federal Poverty Line (FPL) cohort analyses for 2018 and 2022 vintages.


Files Included:



lead_ami_cohorts_2022_us.csv.gz: 2022 AMI cohort data (15K records, NC)

lead_fpl_cohorts_2022_us.csv.gz: 2022 FPL cohort data (588K records, NC)

lead_ami_cohorts_2018_us.csv.gz: 2018 AMI cohort data (531K records, NC)

lead_fpl_cohorts_2018_us.csv.gz: 2018 FPL cohort data (515K records, NC)

checksums.txt: MD5 checksums for verification



Data Processing



Source: Raw LEAD Tool data from OpenEI

Processing: emburden R package v0.4.7 data pipeline

Format: CSV (aggregated tract-level cohorts with computed metrics)

Ready for: Immediate analysis, no additional processing required



Future Expansion
This proof-of-concept can be expanded to nationwide data (all 51 states, ~72,000 census tracts) in future versions.


Data Sources
Original raw data from:



DOE LEAD Tool 2022: https://data.openei.org/submissions/6219

DOE LEAD Tool 2018: https://data.openei.org/submissions/573


Processed using: emburden R package v0.4.7 (https://github.com/ScheierVentures/emburden)


Citation
When using this data, please cite:



This Zenodo repository (DOI provided)

The emburden R package v0.4.7

The original DOE LEAD Tool publications



License
CC-BY-4.0 (same as source data)
DOI: 10.25346/s6lqjm3j/4rm4g9
title: msXL_336r_MMSI+RTI+M0780IR_016_F.tif
DOI: 10.5281/zenodo.17604955
title: emburden: Processed Energy Burden Datasets (North Carolina)

description: PROCESSED, analysis-ready household energy burden datasets from the DOE Low-Income Energy Affordability Data (LEAD) Tool, formatted for the emburden R package.

Scope: North Carolina (proof-of-concept demonstration)

IMPORTANT: These are PRE-PROCESSED datasets, not raw OpenEI data. They have been:



Aggregated by census tract + income bracket

Enriched with computed energy burden metrics (EROI, NER, DEAR)

Standardized for immediate analysis

Quality-checked and validated


This repository provides census tract-level data on household energy burden for North Carolina, covering ~1,600 census tracts. Data includes both Area Median Income (AMI) and Federal Poverty Line (FPL) cohort analyses for 2018 and 2022 vintages.


Files Included:



lead_ami_cohorts_2022_us.csv.gz: 2022 AMI cohort data (15K records, NC)

lead_fpl_cohorts_2022_us.csv.gz: 2022 FPL cohort data (588K records, NC)

lead_ami_cohorts_2018_us.csv.gz: 2018 AMI cohort data (531K records, NC)

lead_fpl_cohorts_2018_us.csv.gz: 2018 FPL cohort data (515K records, NC)

checksums.txt: MD5 checksums for verification



Data Processing



Source: Raw LEAD Tool data from OpenEI

Processing: emburden R package v0.4.7 data pipeline

Format: CSV (aggregated tract-level cohorts with computed metrics)

Ready for: Immediate analysis, no additional processing required



Future Expansion
This proof-of-concept can be expanded to nationwide data (all 51 states, ~72,000 census tracts) in future versions.


Data Sources
Original raw data from:



DOE LEAD Tool 2022: https://data.openei.org/submissions/6219

DOE LEAD Tool 2018: https://data.openei.org/submissions/573


Processed using: emburden R package v0.4.7 (https://github.com/ScheierVentures/emburden)


Citation
When using this data, please cite:



This Zenodo repository (DOI provided)

The emburden R package v0.4.7

The original DOE LEAD Tool publications



License
CC-BY-4.0 (same as source data)
DOI: 10.25346/s6lqjm3j/jlznzr
title: msXL_336r_MMSI+RTI+M0735IR_015_F.tif
DOI: 10.25346/s6lqjm3j/5tqbnr
title: msXL_336r_MMSI+RTI+M0700IR_014_F.tif
DOI: 10.25346/s6lqjm3j/fag6ww
title: msXL_336r_MMSI+RTI+M0655DR_013_F.tif
DOI: 10.25346/s6lqjm3j/oittut
title: msXL_336r_MMSI+RTI+M0630RD_012_F.tif
DOI: 10.25346/s6lqjm3j/lmxhi1
title: msXL_336r_MMSI+RTI+M0615RO_011_F.tif
DOI: 10.25346/s6lqjm3j/75qtmg
title: msXL_336r_MMSI+RTI+M0590AM_010_F.tif
DOI: 10.25346/s6lqjm3j/baj0lh
title: msXL_336r_MMSI+RTI+M0560LI_009_F.tif
DOI: 10.25346/s6lqjm3j/staxai
title: msXL_336r_MMSI+RTI+M0530GN_008_F.tif
DOI: 10.25346/s6lqjm3j/y092ij
title: msXL_336r_MMSI+RTI+M0505CN_007_F.tif
DOI: 10.25346/s6lqjm3j/6byakf
title: msXL_336r_MMSI+RTI+M0470LB_006_F.tif
DOI: 10.15468/dl.ds8738
title: Occurrence Download

description: A dataset containing 5769415 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Colombia",
 "GadmGid is COL.2_2",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 5769415 records from 882 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032089-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.utmryg
title: Occurrence Download

description: A dataset containing 69008 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((11.35704 41.92703,74.01769 41.92703,74.01769 66.98056,11.35704 66.98056,11.35704 41.92703))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Carex flacca Schreb."
 ]
}

 The dataset includes 69008 records from 171 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013781-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15487739
title: Fine scale location data for Blantyre district, Malawi
title: Communities location in Blantyre district, Malawi
title: Residential areas in Blantyre district, Malawi
title: Villages in Blantyre district, Malawi

description: This dataset contains geospatial data for residential areas in Blantyre district, Malawi. It uses WGS84 coordinate reference system (EPSG:4326) for seamless compatibility with standard GIS software and web mapping applications.